Sample records for supervised locally linear
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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-SC2), 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. PMID:29666661
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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.
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Active learning for semi-supervised clustering based on locally linear propagation reconstruction.
Chang, Chin-Chun; Lin, Po-Yi
2015-03-01
The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.
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L1-norm locally linear representation regularization multi-source adaptation learning.
Tao, Jianwen; Wen, Shiting; Hu, Wenjun
2015-09-01
In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.
Gilra, Aditya; Gerstner, Wulfram
2017-11-27
The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.
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Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network
Gerstner, Wulfram
2017-01-01
The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically. PMID:29173280
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A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.
Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe
2012-04-01
We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.
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Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.
Li, Xin; Bai, Yanqin; Peng, Yaxin; Du, Shaoyi; Ying, Shihui
2018-03-01
Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation. By this approach, we project the data into a high dimensional space, where the data can be well represented by linear ML. Then, we reformulate the linear ML by a minimization problem on the positive definite matrix group. Finally, we develop a two-step algorithm for solving this model and design an intrinsic steepest descent algorithm to learn the positive definite metric matrix. Experimental results validate that our proposed method is effective and outperforms several state-of-the-art ML methods.
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NASA Technical Reports Server (NTRS)
Cole, M. M.; Wen-Jones, S. (Principal Investigator)
1976-01-01
The author has identified the following significant results. Series of linears were identified on the March imagery of Lady Annie-Mt. Gordon fault zone area. The series with a WSW-ENE orientation which is normal to the major structural units and also several linears with NNW-SSE orientation appears to be particularly important. Copper mineralization is known at several localities where these linears are intersected by faults. Automated outputs using supervised methods involving the selection of training sets selected by visual recognition of spectral signatures on the color composites obtained from combinations of MSS bands 4, 5 and 7 projected through appropriate filters, were generated.
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Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.
Wu, Panpan; Xia, Kewen; Yu, Hengyong
2016-11-01
Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Gönen, Mehmet
2014-01-01
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 F1, and micro F1 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. PMID:24532862
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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.
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Towards Stability Analysis of Jump Linear Systems with State-Dependent and Stochastic Switching
NASA Technical Reports Server (NTRS)
Tejada, Arturo; Gonzalez, Oscar R.; Gray, W. Steven
2004-01-01
This paper analyzes the stability of hierarchical jump linear systems where the supervisor is driven by a Markovian stochastic process and by the values of the supervised jump linear system s states. The stability framework for this class of systems is developed over infinite and finite time horizons. The framework is then used to derive sufficient stability conditions for a specific class of hybrid jump linear systems with performance supervision. New sufficient stochastic stability conditions for discrete-time jump linear systems are also presented.
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Image interpolation via regularized local linear regression.
Liu, Xianming; Zhao, Debin; Xiong, Ruiqin; Ma, Siwei; Gao, Wen; Sun, Huifang
2011-12-01
The linear regression model is a very attractive tool to design effective image interpolation schemes. Some regression-based image interpolation algorithms have been proposed in the literature, in which the objective functions are optimized by ordinary least squares (OLS). However, it is shown that interpolation with OLS may have some undesirable properties from a robustness point of view: even small amounts of outliers can dramatically affect the estimates. To address these issues, in this paper we propose a novel image interpolation algorithm based on regularized local linear regression (RLLR). Starting with the linear regression model where we replace the OLS error norm with the moving least squares (MLS) error norm leads to a robust estimator of local image structure. To keep the solution stable and avoid overfitting, we incorporate the l(2)-norm as the estimator complexity penalty. Moreover, motivated by recent progress on manifold-based semi-supervised learning, we explicitly consider the intrinsic manifold structure by making use of both measured and unmeasured data points. Specifically, our framework incorporates the geometric structure of the marginal probability distribution induced by unmeasured samples as an additional local smoothness preserving constraint. The optimal model parameters can be obtained with a closed-form solution by solving a convex optimization problem. Experimental results on benchmark test images demonstrate that the proposed method achieves very competitive performance with the state-of-the-art interpolation algorithms, especially in image edge structure preservation. © 2011 IEEE
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Source localization in an ocean waveguide using supervised machine learning.
Niu, Haiqiang; Reeves, Emma; Gerstoft, Peter
2017-09-01
Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data. The pressure received by a vertical linear array is preprocessed by constructing a normalized sample covariance matrix and used as the input for three machine learning methods: feed-forward neural networks (FNN), support vector machines (SVM), and random forests (RF). The range estimation problem is solved both as a classification problem and as a regression problem by these three machine learning algorithms. The results of range estimation for the Noise09 experiment are compared for FNN, SVM, RF, and conventional matched-field processing and demonstrate the potential of machine learning for underwater source localization.
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Supervised orthogonal discriminant subspace projects learning for face recognition.
Chen, Yu; Xu, Xiao-Hong
2014-02-01
In this paper, a new linear dimension reduction method called supervised orthogonal discriminant subspace projection (SODSP) is proposed, which addresses high-dimensionality of data and the small sample size problem. More specifically, given a set of data points in the ambient space, a novel weight matrix that describes the relationship between the data points is first built. And in order to model the manifold structure, the class information is incorporated into the weight matrix. Based on the novel weight matrix, the local scatter matrix as well as non-local scatter matrix is defined such that the neighborhood structure can be preserved. In order to enhance the recognition ability, we impose an orthogonal constraint into a graph-based maximum margin analysis, seeking to find a projection that maximizes the difference, rather than the ratio between the non-local scatter and the local scatter. In this way, SODSP naturally avoids the singularity problem. Further, we develop an efficient and stable algorithm for implementing SODSP, especially, on high-dimensional data set. Moreover, the theoretical analysis shows that LPP is a special instance of SODSP by imposing some constraints. Experiments on the ORL, Yale, Extended Yale face database B and FERET face database are performed to test and evaluate the proposed algorithm. The results demonstrate the effectiveness of SODSP. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Supervised linear dimensionality reduction with robust margins for object recognition
NASA Astrophysics Data System (ADS)
Dornaika, F.; Assoum, A.
2013-01-01
Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.
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Label Information Guided Graph Construction for Semi-Supervised Learning.
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.
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A blended supervision model in Australian general practice training.
Ingham, Gerard; Fry, Jennifer
2016-05-01
The Royal Australian College of General Practitioners' Standards for general practice training allow different models of registrar supervision, provided these models achieve the outcomes of facilitating registrars' learning and ensuring patient safety. In this article, we describe a model of supervision called 'blended supervision', and its initial implementation and evaluation. The blended supervision model integrates offsite supervision with available local supervision resources. It is a pragmatic alternative to traditional supervision. Further evaluation of the cost-effectiveness, safety and effectiveness of this model is required, as is the recruitment and training of remote supervisors. A framework of questions was developed to outline the training practice's supervision methods and explain how blended supervision is achieving supervision and teaching outcomes. The supervision and teaching framework can be used to understand the supervision methods of all practices, not just practices using blended supervision.
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Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M
2017-05-01
Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.
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Supervised Learning for Dynamical System Learning.
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.
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Automated selection of brain regions for real-time fMRI brain-computer interfaces
NASA Astrophysics Data System (ADS)
Lührs, Michael; Sorger, Bettina; Goebel, Rainer; Esposito, Fabrizio
2017-02-01
Objective. Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI. Approach. 3 T fMRI data of six volunteers were re-analyzed in simulated real-time. During a localizer run, participants performed three mental tasks following visual cues. During two communication runs, a letter-spelling display guided the subjects to freely encode letters by performing one of the mental tasks with a specific timing. GLM- and ICA-based procedures were used to decode each letter, respectively using compact ROIs and whole-brain distributed spatio-temporal patterns of fMRI activity, automatically defined from subject-specific or group-level maps. Main results. Letter-decoding performances were comparable to supervised methods. In combination with a similarity-based criterion, GLM- and ICA-based approaches successfully decoded more than 80% (average) of the letters. Subject-specific maps yielded optimal performances. Significance. Automated solutions for ROI selection may help accelerating the translation of rt-fMRI BCIs from research to clinical applications.
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Clinical supervision: an important part of every nurse's practice.
Bifarin, Oladayo; Stonehouse, David
2017-03-23
Clinical supervision involves a supportive relationship between supervisor and supervisee that facilitates reflective learning and is part of professional socialisation. Clinical supervision can take many different forms and may be adapted to suit local circumstances. A working agreement is required between the parties to the supervision and issues surrounding confidentiality must be understood. High-quality clinical supervision leads to greater job satisfaction and less stress. When it is absent or inadequate, however, the results can be serious and it is particularly important that student nurses are well supported in this way. Further research in this area is necessary.
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Linear time relational prototype based learning.
Gisbrecht, Andrej; Mokbel, Bassam; Schleif, Frank-Michael; Zhu, Xibin; Hammer, Barbara
2012-10-01
Prototype based learning offers an intuitive interface to inspect large quantities of electronic data in supervised or unsupervised settings. Recently, many techniques have been extended to data described by general dissimilarities rather than Euclidean vectors, so-called relational data settings. Unlike the Euclidean counterparts, the techniques have quadratic time complexity due to the underlying quadratic dissimilarity matrix. Thus, they are infeasible already for medium sized data sets. The contribution of this article is twofold: On the one hand we propose a novel supervised prototype based classification technique for dissimilarity data based on popular learning vector quantization (LVQ), on the other hand we transfer a linear time approximation technique, the Nyström approximation, to this algorithm and an unsupervised counterpart, the relational generative topographic mapping (GTM). This way, linear time and space methods result. We evaluate the techniques on three examples from the biomedical domain.
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Code of Federal Regulations, 2010 CFR
2010-07-01
... Protection of Environment ENVIRONMENTAL PROTECTION AGENCY GRANTS AND OTHER FEDERAL ASSISTANCE STATE AND LOCAL ASSISTANCE Environmental Program Grants for Tribes Public Water System Supervision (section 1443(a) and... water system supervision grants to Tribes and Intertribal Consortia authorized under sections 1443(a...
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Code of Federal Regulations, 2011 CFR
2011-07-01
... Protection of Environment ENVIRONMENTAL PROTECTION AGENCY GRANTS AND OTHER FEDERAL ASSISTANCE STATE AND LOCAL ASSISTANCE Environmental Program Grants for Tribes Public Water System Supervision (section 1443(a) and... water system supervision grants to Tribes and Intertribal Consortia authorized under sections 1443(a...
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NASA Astrophysics Data System (ADS)
Gao, Yuan; Ma, Jiayi; Yuille, Alan L.
2017-05-01
This paper addresses the problem of face recognition when there is only few, or even only a single, labeled examples of the face that we wish to recognize. Moreover, these examples are typically corrupted by nuisance variables, both linear (i.e., additive nuisance variables such as bad lighting, wearing of glasses) and non-linear (i.e., non-additive pixel-wise nuisance variables such as expression changes). The small number of labeled examples means that it is hard to remove these nuisance variables between the training and testing faces to obtain good recognition performance. To address the problem we propose a method called Semi-Supervised Sparse Representation based Classification (S$^3$RC). This is based on recent work on sparsity where faces are represented in terms of two dictionaries: a gallery dictionary consisting of one or more examples of each person, and a variation dictionary representing linear nuisance variables (e.g., different lighting conditions, different glasses). The main idea is that (i) we use the variation dictionary to characterize the linear nuisance variables via the sparsity framework, then (ii) prototype face images are estimated as a gallery dictionary via a Gaussian Mixture Model (GMM), with mixed labeled and unlabeled samples in a semi-supervised manner, to deal with the non-linear nuisance variations between labeled and unlabeled samples. We have done experiments with insufficient labeled samples, even when there is only a single labeled sample per person. Our results on the AR, Multi-PIE, CAS-PEAL, and LFW databases demonstrate that the proposed method is able to deliver significantly improved performance over existing methods.
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Dong, Yadong; Sun, Yongqi; Qin, Chao
2018-01-01
The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.
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23 CFR 635.105 - Supervising agency.
Code of Federal Regulations, 2012 CFR
2012-04-01
... CONSTRUCTION AND MAINTENANCE Contract Procedures § 635.105 Supervising agency. (a) The STD has responsibility... authorizing performance of the work by a local public agency or other Federal agency. The STD shall be... projects are completed in conformance with approved plans and specifications. (b) Although the STD may...
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23 CFR 635.105 - Supervising agency.
Code of Federal Regulations, 2013 CFR
2013-04-01
... CONSTRUCTION AND MAINTENANCE Contract Procedures § 635.105 Supervising agency. (a) The STD has responsibility... authorizing performance of the work by a local public agency or other Federal agency. The STD shall be... projects are completed in conformance with approved plans and specifications. (b) Although the STD may...
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23 CFR 635.105 - Supervising agency.
Code of Federal Regulations, 2014 CFR
2014-04-01
... CONSTRUCTION AND MAINTENANCE Contract Procedures § 635.105 Supervising agency. (a) The STD has responsibility... authorizing performance of the work by a local public agency or other Federal agency. The STD shall be... projects are completed in conformance with approved plans and specifications. (b) Although the STD may...
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23 CFR 635.105 - Supervising agency.
Code of Federal Regulations, 2011 CFR
2011-04-01
... CONSTRUCTION AND MAINTENANCE Contract Procedures § 635.105 Supervising agency. (a) The STD has responsibility... authorizing performance of the work by a local public agency or other Federal agency. The STD shall be... projects are completed in conformance with approved plans and specifications. (b) Although the STD may...
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32 CFR 634.41 - Compliance with State laws.
Code of Federal Regulations, 2010 CFR
2010-07-01
...) Been involved in traffic accidents. (3) Prompt notice of actions by a State or host nation to suspend... CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.41 Compliance with... employees to comply with State and local traffic laws when operating government motor vehicles. (b...
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40 CFR 35.935-8 - Supervision.
Code of Federal Regulations, 2010 CFR
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... any project involving Step 3, the grantee will provide and maintain competent and adequate engineering...
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Mentoring and Supervision for Teacher Development.
ERIC Educational Resources Information Center
Reiman, Alan J.; Thies-Sprinthall, Lois
The fields of instructional supervision, adult development, teacher education and mentoring, and ongoing professional development are synthesized in this text. Examples and case studies are drawn from local systems in North Carolina as well as state, national, and international public school/university consortia to identify emerging trends in…
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Measuring the Effectiveness of a Genetic Counseling Supervision Training Conference.
Atzinger, Carrie L; He, Hua; Wusik, Katie
2016-08-01
Genetic counselors who receive formal training report increased confidence and competence in their supervisory roles. The effectiveness of specific formal supervision training has not been assessed previously. A day-long GC supervision conference was designed based on published supervision competencies and was attended by 37 genetic counselors. Linear Mixed Model and post-hoc paired t-test was used to compare Psychotherapy Supervisor Development Scale (PSDS) scores among/between individuals pre and post conference. Generalized Estimating Equation (GEE) model and post-hoc McNemar's test was used to determine if the conference had an effect on GC supervision competencies. PSDS scores were significantly increased 1 week (p < 0.001) and 6 months (p < 0.001) following the conference. For three supervision competencies, attendees were more likely to agree they were able to perform them after the conference than before. These effects remained significant 6 months later. For the three remaining competencies, the majority of supervisors agreed they could perform these before the conference; therefore, no change was found. This exploratory study showed this conference increased the perceived confidence and competence of the supervisors who attended and increased their self-reported ability to perform certain supervision competencies. While still preliminary, this supports the idea that a one day conference on supervision has the potential to impact supervisor development.
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Web-conference supervision for advanced psychotherapy training: a practical guide.
Abbass, Allan; Arthey, Stephen; Elliott, Jason; Fedak, Tim; Nowoweiski, Dion; Markovski, Jasmina; Nowoweiski, Sarah
2011-06-01
The advent of readily accessible, inexpensive Web-conferencing applications has opened the door for distance psychotherapy supervision, using video recordings of treated clients. Although relatively new, this method of supervision is advantageous given the ease of use and low cost of various Internet applications. This method allows periodic supervision from point to point around the world, with no travel costs and no long gaps between direct training contacts. Web-conferencing permits face-to-face training so that the learner and supervisor can read each other's emotional responses while reviewing case material. It allows group learning from direct supervision to complement local peer-to-peer learning methods. In this article, we describe the relevant literature on this type of learning method, the practical points in its utilization, its limitations, and its benefits.
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[Development of the role scale for municipal supervising public health nurses].
Hatono, Yoko; Suzuki, Hiroko; Masaki, Naoko
2013-05-01
As public health nurses are becoming increasingly decentralized in municipalities, recommendations for allocating supervising public health nurses are being made. This study aimed to develop a scale for measuring the implementation of role of municipal supervising public health nurses and to test its reliability and validity. Scale items were developed using results of a qualitative inductive analysis of interview data, and the items were then revised following an examination of content validity by experts, resulting in a provisional scale of 17 items. A self-administered, written questionnaire was then completed by supervising public health nurses or public health nurses holding the most senior positions in all municipalities nationwide, with the exception of three prefectures in the Tohoku region (total 1,621 locations). In total, 1,036 responses were received, and 931 were used for analysis (valid response rate = 57.4%). Of these, 406 were completed by supervising public health nurses. After deleting one item as a result of item analysis and conducting principal component analysis, factor analysis was conducted using the major factor method and Promax rotation. One item with high loading on multiple factors was deleted, resulting in a scale comprising 15 items and 3 factors. The cumulative contribution ratio was 56.10%. The three factors were labeled "Promotion of health activities across the whole locality," "Coordination as a PHN role leader," and "Development of the skills of public health nurses". The reliability coefficient of the RMSP (Role Scale for Municipal Supervising Public Health Nurses) as a whole was 0.84 using the split-half method (Spearman-Brown formula) and 0.91 using Cronbach's alpha, confirming internal consistency. In terms of validity, an examination was conducted of the correlation of two RMSP scale scores (strength of awareness of role as a supervising public health nurse and confidence as a supervising public health nurse) and scores on existing scales assessing management abilities, and a significant correlation (P < 0.01) was obtained. Additionally, a comparison of the RMSP scores of decentralized local public health nurses according to rank and years of service in areas where there were no supervising public health nurses with the RMSP scores of supervising public health nurses showed that the scores of supervising public health nurses were higher. The developed scale was found to be reliable and valid for measuring the implementation of supervising public health nurses' role.
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Mendes, Renata Gonçalves; Simões, Rodrigo Polaquini; De Souza Melo Costa, Fernando; Pantoni, Camila Bianca Falasco; Di Thommazo, Luciana; Luzzi, Sérgio; Catai, Aparecida Maria; Arena, Ross; Borghi-Silva, Audrey
2010-01-01
Coronary artery bypass grafting (CABG) is accompanied by severe impairment of cardiac autonomous regulation (CAR). This study aimed to determine whether a short-term physiotherapy exercise protocol post-CABG, during inpatient cardiac rehabilitation (CR), might improve CAR. Seventy-four patients eligible for CABG were recruited and randomised into physiotherapy exercise group (EG) or physiotherapy usual care group (UCG). EG patients underwent a short-term supervised inpatient physiotherapy exercise protocol consisting of an early mobilisation with progressive exercises plus usual care (respiratory exercises). UCG only received respiratory exercises. Forty-seven patients (24 EG and 23 UGC) completed the study. Outcome measures of CAR included linear and non-linear measures of heart rate variability (HRV) assessed before discharge. By hospital discharge, EG presented significantly higher parasympathetic HRV values [rMSSD, high frequency (HF), SD1)], global power (STD RR, SD2), non-linear HRV indexes [detrended fluctuation analysis (DFA)alpha1, DFAalpha2, approximate entropy (ApEn)] and mean RR compared to UCG (p<0.05). Conversely, higher values of mean HR, low frequency (LF) (sympathetic activity) and the LF/HF (global sympatho-vagal balance) were found in the UCG. A short-term supervised physiotherapy exercise protocol during inpatient CR improves CAR at the time of discharge. Thus, exercise-based inpatient CR might be an effective non-pharmacological tool to improve autonomic cardiac tone in patient's post-CABG.
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White Matter Tract Segmentation as Multiple Linear Assignment Problems
Sharmin, Nusrat; Olivetti, Emanuele; Avesani, Paolo
2018-01-01
Diffusion magnetic resonance imaging (dMRI) allows to reconstruct the main pathways of axons within the white matter of the brain as a set of polylines, called streamlines. The set of streamlines of the whole brain is called the tractogram. Organizing tractograms into anatomically meaningful structures, called tracts, is known as the tract segmentation problem, with important applications to neurosurgical planning and tractometry. Automatic tract segmentation techniques can be unsupervised or supervised. A common criticism of unsupervised methods, like clustering, is that there is no guarantee to obtain anatomically meaningful tracts. In this work, we focus on supervised tract segmentation, which is driven by prior knowledge from anatomical atlases or from examples, i.e., segmented tracts from different subjects. We present a supervised tract segmentation method that segments a given tract of interest in the tractogram of a new subject using multiple examples as prior information. Our proposed tract segmentation method is based on the idea of streamline correspondence i.e., on finding corresponding streamlines across different tractograms. In the literature, streamline correspondence has been addressed with the nearest neighbor (NN) strategy. Differently, here we formulate the problem of streamline correspondence as a linear assignment problem (LAP), which is a cornerstone of combinatorial optimization. With respect to the NN, the LAP introduces a constraint of one-to-one correspondence between streamlines, that forces the correspondences to follow the local anatomical differences between the example and the target tract, neglected by the NN. In the proposed solution, we combined the Jonker-Volgenant algorithm (LAPJV) for solving the LAP together with an efficient way of computing the nearest neighbors of a streamline, which massively reduces the total amount of computations needed to segment a tract. Moreover, we propose a ranking strategy to merge correspondences coming from different examples. We validate the proposed method on tractograms generated from the human connectome project (HCP) dataset and compare the segmentations with the NN method and the ROI-based method. The results show that LAP-based segmentation is vastly more accurate than ROI-based segmentation and substantially more accurate than the NN strategy. We provide a Free/OpenSource implementation of the proposed method. PMID:29467600
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White Matter Tract Segmentation as Multiple Linear Assignment Problems.
Sharmin, Nusrat; Olivetti, Emanuele; Avesani, Paolo
2017-01-01
Diffusion magnetic resonance imaging (dMRI) allows to reconstruct the main pathways of axons within the white matter of the brain as a set of polylines, called streamlines. The set of streamlines of the whole brain is called the tractogram. Organizing tractograms into anatomically meaningful structures, called tracts, is known as the tract segmentation problem, with important applications to neurosurgical planning and tractometry. Automatic tract segmentation techniques can be unsupervised or supervised. A common criticism of unsupervised methods, like clustering, is that there is no guarantee to obtain anatomically meaningful tracts. In this work, we focus on supervised tract segmentation, which is driven by prior knowledge from anatomical atlases or from examples, i.e., segmented tracts from different subjects. We present a supervised tract segmentation method that segments a given tract of interest in the tractogram of a new subject using multiple examples as prior information. Our proposed tract segmentation method is based on the idea of streamline correspondence i.e., on finding corresponding streamlines across different tractograms. In the literature, streamline correspondence has been addressed with the nearest neighbor (NN) strategy. Differently, here we formulate the problem of streamline correspondence as a linear assignment problem (LAP), which is a cornerstone of combinatorial optimization. With respect to the NN, the LAP introduces a constraint of one-to-one correspondence between streamlines, that forces the correspondences to follow the local anatomical differences between the example and the target tract, neglected by the NN. In the proposed solution, we combined the Jonker-Volgenant algorithm (LAPJV) for solving the LAP together with an efficient way of computing the nearest neighbors of a streamline, which massively reduces the total amount of computations needed to segment a tract. Moreover, we propose a ranking strategy to merge correspondences coming from different examples. We validate the proposed method on tractograms generated from the human connectome project (HCP) dataset and compare the segmentations with the NN method and the ROI-based method. The results show that LAP-based segmentation is vastly more accurate than ROI-based segmentation and substantially more accurate than the NN strategy. We provide a Free/OpenSource implementation of the proposed method.
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Zhang, Zhao; Zhao, Mingbo; Chow, Tommy W S
2012-12-01
In this work, sub-manifold projections based semi-supervised dimensionality reduction (DR) problem learning from partial constrained data is discussed. Two semi-supervised DR algorithms termed Marginal Semi-Supervised Sub-Manifold Projections (MS³MP) and orthogonal MS³MP (OMS³MP) are proposed. MS³MP in the singular case is also discussed. We also present the weighted least squares view of MS³MP. Based on specifying the types of neighborhoods with pairwise constraints (PC) and the defined manifold scatters, our methods can preserve the local properties of all points and discriminant structures embedded in the localized PC. The sub-manifolds of different classes can also be separated. In PC guided methods, exploring and selecting the informative constraints is challenging and random constraint subsets significantly affect the performance of algorithms. This paper also introduces an effective technique to select the informative constraints for DR with consistent constraints. The analytic form of the projection axes can be obtained by eigen-decomposition. The connections between this work and other related work are also elaborated. The validity of the proposed constraint selection approach and DR algorithms are evaluated by benchmark problems. Extensive simulations show that our algorithms can deliver promising results over some widely used state-of-the-art semi-supervised DR techniques. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Factors associated with adverse clinical outcomes among obstetric trainees
Aiken PhD, Catherine E.; Aiken, Abigail; Park, Hannah; Brockelsby, Jeremy C.; Prentice, Andrew
2016-01-01
Objective To determine whether UK obstetric trainees transitioning from directly to indirectly-supervised practice have a higher likelihood of adverse patient outcomes from operative deliveries compared to other indirectly supervised trainees and to examine whether performing more procedures under direct supervision is associated with fewer adverse outcomes in initial indirect practice. Methods We examined all deliveries (13,861) conducted by obstetricians at a single centre over 5 years (2008-2013). Mixed-effects logistic regression models were used to compare estimated blood loss, maternal trauma, umbilical arterial pH, delayed neonatal respiration, failed instrumental delivery, and critical incidents for trainees in their first indirectly-supervised year with trainees in all other years of indirect practice. Outcomes for trainees in their first indirectly-supervised 3 months were compared to their outcomes for the remainder of the year. Linear regression was used to examine the relationship between number of procedures performed under direct supervision and initial outcomes under indirect supervision. Results Trainees in their first indirectly-supervised year had a higher likelihood of >2 litres estimated blood loss at any delivery (OR 1.32;CI(1.01-1.64) p<0.05) and of failed instrumental delivery (OR 2.33;CI(1.37-3.29) p<0.05) compared with other indirectly-supervised trainees. Other measured outcomes showed no significant differences. Within the first three months of indirect supervision, the likelihood of operative vaginal deliveries with >1litre estimated blood loss (OR 2.54;CI(1.88-3.20) p<0.05) was higher compared to the remainder of the first year. Performing more deliveries under direct supervision prior to beginning indirectly-supervised training was associated with decreased risk of >1litre estimated blood loss (p<0.05). Conclusions Obstetric trainees in their first year of indirectly-supervised practice have a higher likelihood of immediate adverse delivery outcomes, which are primarily maternal rather than neonatal. Undertaking more directly supervised procedures prior to transitioning to indirectly-supervised practice may reduce adverse outcomes, suggesting that experience is a key consideration in obstetric training programme design. PMID:26077215
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Large-scale weakly supervised object localization via latent category learning.
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.
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Supervision of tunnelling constructions and software used for their evaluation
NASA Astrophysics Data System (ADS)
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.
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NASA Astrophysics Data System (ADS)
Davoudi, Alireza; Shiry Ghidary, Saeed; Sadatnejad, Khadijeh
2017-06-01
Objective. In this paper, we propose a nonlinear dimensionality reduction algorithm for the manifold of symmetric positive definite (SPD) matrices that considers the geometry of SPD matrices and provides a low-dimensional representation of the manifold with high class discrimination in a supervised or unsupervised manner. Approach. The proposed algorithm tries to preserve the local structure of the data by preserving distances to local means (DPLM) and also provides an implicit projection matrix. DPLM is linear in terms of the number of training samples. Main results. We performed several experiments on the multi-class dataset IIa from BCI competition IV and two other datasets from BCI competition III including datasets IIIa and IVa. The results show that our approach as dimensionality reduction technique—leads to superior results in comparison with other competitors in the related literature because of its robustness against outliers and the way it preserves the local geometry of the data. Significance. The experiments confirm that the combination of DPLM with filter geodesic minimum distance to mean as the classifier leads to superior performance compared with the state of the art on brain-computer interface competition IV dataset IIa. Also the statistical analysis shows that our dimensionality reduction method performs significantly better than its competitors.
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NASA Astrophysics Data System (ADS)
Wen, Gezheng; Markey, Mia K.
2015-03-01
It is resource-intensive to conduct human studies for task-based assessment of medical image quality and system optimization. Thus, numerical model observers have been developed as a surrogate for human observers. The Hotelling observer (HO) is the optimal linear observer for signal-detection tasks, but the high dimensionality of imaging data results in a heavy computational burden. Channelization is often used to approximate the HO through a dimensionality reduction step, but how to produce channelized images without losing significant image information remains a key challenge. Kernel local Fisher discriminant analysis (KLFDA) uses kernel techniques to perform supervised dimensionality reduction, which finds an embedding transformation that maximizes betweenclass separability and preserves within-class local structure in the low-dimensional manifold. It is powerful for classification tasks, especially when the distribution of a class is multimodal. Such multimodality could be observed in many practical clinical tasks. For example, primary and metastatic lesions may both appear in medical imaging studies, but the distributions of their typical characteristics (e.g., size) may be very different. In this study, we propose to use KLFDA as a novel channelization method. The dimension of the embedded manifold (i.e., the result of KLFDA) is a counterpart to the number of channels in the state-of-art linear channelization. We present a simulation study to demonstrate the potential usefulness of KLFDA for building the channelized HOs (CHOs) and generating reliable decision statistics for clinical tasks. We show that the performance of the CHO with KLFDA channels is comparable to that of the benchmark CHOs.
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Bromuri, Stefano; Zufferey, Damien; Hennebert, Jean; Schumacher, Michael
2014-10-01
This research is motivated by the issue of classifying illnesses of chronically ill patients for decision support in clinical settings. Our main objective is to propose multi-label classification of multivariate time series contained in medical records of chronically ill patients, by means of quantization methods, such as bag of words (BoW), and multi-label classification algorithms. Our second objective is to compare supervised dimensionality reduction techniques to state-of-the-art multi-label classification algorithms. The hypothesis is that kernel methods and locality preserving projections make such algorithms good candidates to study multi-label medical time series. We combine BoW and supervised dimensionality reduction algorithms to perform multi-label classification on health records of chronically ill patients. The considered algorithms are compared with state-of-the-art multi-label classifiers in two real world datasets. Portavita dataset contains 525 diabetes type 2 (DT2) patients, with co-morbidities of DT2 such as hypertension, dyslipidemia, and microvascular or macrovascular issues. MIMIC II dataset contains 2635 patients affected by thyroid disease, diabetes mellitus, lipoid metabolism disease, fluid electrolyte disease, hypertensive disease, thrombosis, hypotension, chronic obstructive pulmonary disease (COPD), liver disease and kidney disease. The algorithms are evaluated using multi-label evaluation metrics such as hamming loss, one error, coverage, ranking loss, and average precision. Non-linear dimensionality reduction approaches behave well on medical time series quantized using the BoW algorithm, with results comparable to state-of-the-art multi-label classification algorithms. Chaining the projected features has a positive impact on the performance of the algorithm with respect to pure binary relevance approaches. The evaluation highlights the feasibility of representing medical health records using the BoW for multi-label classification tasks. The study also highlights that dimensionality reduction algorithms based on kernel methods, locality preserving projections or both are good candidates to deal with multi-label classification tasks in medical time series with many missing values and high label density. Copyright © 2014 Elsevier Inc. All rights reserved.
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Smith, Jennifer L.; Carpenter, Kenneth M.; Amrhein, Paul C.; Brooks, Adam C.; Levin, Deborah; Schreiber, Elizabeth A.; Travaglini, Laura A.; Hu, Mei-Chen; Nunes, Edward V.
2012-01-01
Background Training through traditional workshops is relatively ineffective for changing counseling practices. Tele-conferencing Supervision (TCS) was developed to provide remote, live supervision for training motivational interviewing (MI). Method 97 community drug treatment counselors completed a 2-day MI workshop and were randomized to: live supervision via tele-conferencing (TCS; n=32), standard tape-based supervision (Tape; n=32), or workshop alone (Workshop; n=33). Supervision conditions received 5 weekly supervision sessions at their sites using actors as standard patients. Sessions with clients were rated for MI skill with the Motivational Interviewing Treatment Integrity (MITI) coding system pre-workshop and 1, 8, and 20 weeks post-workshop. Mixed effects linear models were used to test training condition on MI skill at 8 and 20 weeks. Results TCS scored better than Workshop on the MITI for Spirit (mean difference = 0.76; p < .0001; d = 1.01) and Empathy (mean difference = 0.68; p < .001; d = 0.74). Tape supervision fell between TCS and Workshop, with Tape superior to Workshop for Spirit (mean difference = 0.40; p < .05). TCS was superior to Workshop in reducing MI non-adherence and increasing MI adherence, and was superior to Workshp and Tape in increasing the reflection to question ratio. Tape was superior to TCS in increasing complex reflections. Percentage of counselors meeting proficiency differed significantly between training conditions for the most stringent threshold (Spirit and Empathy scores ≥ 6), and were modest, ranging from 13% to 67%, for TCS and Tape. Conclusion TCS shows promise for promoting new counseling behaviors following participation in workshop training. However, further work is needed to improve supervision methods in order to bring more clinicians to high levels of proficiency and facilitate the dissemination of evidence-based practices. PMID:22506795
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Teacher and learner: Supervised and unsupervised learning in communities.
Shafto, Michael G; Seifert, Colleen M
2015-01-01
How far can teaching methods go to enhance learning? Optimal methods of teaching have been considered in research on supervised and unsupervised learning. Locally optimal methods are usually hybrids of teaching and self-directed approaches. The costs and benefits of specific methods have been shown to depend on the structure of the learning task, the learners, the teachers, and the environment.
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Deep Visual Attention Prediction
NASA Astrophysics Data System (ADS)
Wang, Wenguan; Shen, Jianbing
2018-05-01
In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.
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23 CFR 660.515 - Project administration.
Code of Federal Regulations, 2010 CFR
2010-04-01
... PROGRAMS (DIRECT FEDERAL) Defense Access Roads § 660.515 Project administration. (a) Determination of the... or local highway agency. (b) Defense access road projects under the supervision of a State or local... commitment from the State or local highway agency, within whose jurisdiction the access road lies, that it...
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A Study on the Autonomy of Educational Administration. Regular Report 86-21.
ERIC Educational Resources Information Center
Chung, Chan-young; And Others
Excessive centralized control begets uniformity, which denies local need and school uniqueness. Further, control, order, and supervision create impassivity and work against autonomy. The decentralization of authority to lower echelons more familar with local needs may provide a more relevant administration that encourages local initiatives; school…
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Hatfield, B; Shaw, J; Pinfold, V; Bindman, J; Evans, S; Huxley, P; Thornicroft, G
2001-10-01
Two measures in the English Mental Health Act allow requirements to be imposed upon patients living in the community. These are Guardianship (Section 7) and Supervised Discharge (Section 25A). The paper aims to compare patients with mental illnesses, made subject to Guardianship or Supervised Discharge. Data on patient characteristics, impairment, needs and interventions were collected from keyworkers in a random national sample of Trusts and local authorities. Ratings were obtained on standardised measures of disability, impairment and needs. Patients placed on Supervised Discharge were more likely to have problems of treatment compliance and drug misuse, whilst those on Guardianship were more likely to have problems of social welfare and higher ratings of disability and impairment. Supervised Discharge has a higher proportion of African-Caribbean patients. Interventions delivered are rated as effective for both measures. Legal changes proposed in England include a single power for supervision in the community. This should not mean a focus on risk management to the neglect of social welfare interventions.
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Fuzzy self-learning control for magnetic servo system
NASA Technical Reports Server (NTRS)
Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.
1994-01-01
It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.
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Block versus longitudinal integrated clerkships: students' views of rural clinical supervision.
Witney, Martin; Isaac, Vivian; Playford, Denese; Walker, Leesa; Garne, David; Walters, Lucie
2018-07-01
Medical students undertaking longitudinal integrated clerkships (LICs) train in multiple disciplines concurrently, compared with students in block rotations who typically address one medical discipline at a time. Current research suggests that LICs afford students increased access to patients and continuity of clinical supervision. However, these factors are less of an issue in rural placements where there are fewer learners. The aim of this study was to compare rural LIC and rural block rotation students' reported experiences of clinical supervision. De-identified data from the 2015 version of the Australian national rural clinical schools (RCSs) exit survey was used to compare students in LICs with those in block rotations in relation to how they evaluate their clinical supervisors and how they rate their own clinical competence. Multivariate general linear modelling showed no association between placement type (LIC versus Block) and reported clinical supervision. The single independent predictor of positive perception of clinical supervisors was choosing an RCS as a first preference. There was also no association between placement type (LIC versus Block) and self-rated clinical competence. Instead, the clinical supervision score and male gender predicted more positive self-ratings of clinical competence. The quality of clinical supervision in block placements and LIC programmes in rural Australian settings was reported by students as equivalent. © 2018 John Wiley & Sons Ltd and The Association for the Study of Medical Education.
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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).
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Improving Non-Linear Approaches to Anomaly Detection, Class Separation, and Visualization
2014-12-26
Chainlink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2.3 Modified Banana ...45 3.3 LLE Example for the Modified Banana Dataset. . . . . . . . . . . . . . . . . . 47 x...Figure Page 3.4 Banana Dataset RLLE and Supervised RLLE Example. . . . . . . . . . . . . . 51 3.5 DWT Decomposition [162
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Kutner, Bryan A.; Smith, Jennifer L.; Carpenter, K. M.; Hu, M-C.; Amrhein, Paul C.; Nunes, E. V.
2015-01-01
The objective of this study was to investigate the relation between self-report and objective assessment of Motivational Interviewing (MI) skills following training and supervision. After an MI workshop, 96 clinicians from 26 community programs (age 21–68, 65% female, 40.8% Black, 29.6% Caucasian, 24.5% Hispanic, 2.0% Asian, 3.1% other) were randomized to supervision (tele-conferencing or tape-based), or workshop only. At four time points, trainees completed a self-report of MI skill, using items from the MI Understanding questionnaire (MIU), and were objectively assessed by raters using the Motivational Interviewing Treatment Integrity (MITI) system. Correlations were calculated between MIU and MITI scores. A generalized linear mixed model was tested on MIU scores, with MITI scores, supervision condition and time as independent variables. MIU scores increased from pre-workshop (Mean = 4.74, SD = 1.79) to post-workshop (Mean = 6.31, SD = 1.03) (t = 8.69, p < .0001). With supervision, scores continued to increase, from post-workshop to week 8 (Mean = 7.07, SD = 0.91, t = 5.60, p < .0001) and from week 8 to week 20 (Mean = 7.28, SD = 0.94, t = 2.43, p = .02). However, MIU scores did not significantly correlate with MITI scores, with or without supervision. Self- reported ability increased with supervision, but self-report was not an indicator of objectively measured skill. This suggests that training does not increase correspondence between self-report and objective assessment, so community treatment programs should not rely on clinician self- report to assess the need for ongoing training and supervision and it may be necessary to train clinicians to accurately assess their own skill. PMID:25963775
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Wain, R Morgan; Kutner, Bryan A; Smith, Jennifer L; Carpenter, Kenneth M; Hu, Mei-Chen; Amrhein, Paul C; Nunes, Edward V
2015-10-01
The objective of this study was to investigate the relation between self-report and objective assessment of motivational interviewing (MI) skills following training and supervision. After an MI workshop, 96 clinicians from 26 community programs (age 21-68, 65% female, 40.8% Black, 29.6% Caucasian, 24.5% Hispanic, 2.0% Asian, 3.1% other) were randomized to supervision (tele-conferencing or tape-based), or workshop only. At four time points, trainees completed a self-report of MI skill, using items from the MI understanding questionnaire (MIU), and were objectively assessed by raters using the Motivational Interviewing Treatment Integrity (MITI) system. Correlations were calculated between MIU and MITI scores. A generalized linear mixed model was tested on MIU scores, with MITI scores, supervision condition and time as independent variables. MIU scores increased from pre-workshop (mean = 4.74, SD = 1.79) to post-workshop (mean = 6.31, SD = 1.03) (t = 8.69, p < .0001). With supervision, scores continued to increase, from post-workshop to week 8 (mean = 7.07, SD = 0.91, t = 5.60, p < .0001) and from week 8 to week 20 (mean = 7.28, SD = 0.94, t = 2.43, p = .02). However, MIU scores did not significantly correlate with MITI scores, with or without supervision. Self-reported ability increased with supervision, but self-report was not an indicator of objectively measured skill. This suggests that training does not increase correspondence between self-report and objective assessment, so community treatment programs should not rely on clinician self-report to assess the need for ongoing training and supervision and it may be necessary to train clinicians to accurately assess their own skill. Copyright © 2015 Elsevier Inc. All rights reserved.
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12 CFR 560.42 - State and local government obligations.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 5 2010-01-01 2010-01-01 false State and local government obligations. 560.42 Section 560.42 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY LENDING AND INVESTMENT Lending and Investment Powers for Federal Savings Associations § 560.42 State and local government...
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Rapid Training of Information Extraction with Local and Global Data Views
2012-05-01
56 xiii 4.1 An example of words and their bit string representations. Bold ones are transliterated Arabic words...Natural Language Processing ( NLP ) community faces new tasks and new domains all the time. Without enough labeled data of a new task or a new domain to...conduct supervised learning, semi-supervised learning is particularly attractive to NLP researchers since it only requires a handful of labeled examples
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Weakly supervised visual dictionary learning by harnessing image attributes.
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.
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Task-driven dictionary learning.
Mairal, Julien; Bach, Francis; Ponce, Jean
2012-04-01
Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal processing. For signals such as natural images that admit such sparse representations, it is now well established that these models are well suited to restoration tasks. In this context, learning the dictionary amounts to solving a large-scale matrix factorization problem, which can be done efficiently with classical optimization tools. The same approach has also been used for learning features from data for other purposes, e.g., image classification, but tuning the dictionary in a supervised way for these tasks has proven to be more difficult. In this paper, we present a general formulation for supervised dictionary learning adapted to a wide variety of tasks, and present an efficient algorithm for solving the corresponding optimization problem. Experiments on handwritten digit classification, digital art identification, nonlinear inverse image problems, and compressed sensing demonstrate that our approach is effective in large-scale settings, and is well suited to supervised and semi-supervised classification, as well as regression tasks for data that admit sparse representations.
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Meyer, Raquel M; O'Brien-Pallas, Linda; Doran, Diane; Streiner, David; Ferguson-Paré, Mary; Duffield, Christine
2011-07-01
To examine the influence of nurse manager span (number of direct report staff), time in staff contact, transformational leadership practices and operational hours on nurse supervision satisfaction. Increasing role complexity has intensified the boundary spanning functions of managers. Because work demands and scope vary by management position, time in staff contact rather than span may better explain managers' capacity to support staff. A descriptive, correlational design was used to collect cross-sectional survey and prospective work log and administrative data from a convenience sample of 558 nurses in 51 clinical areas and 31 front-line nurse managers from four acute care hospitals in 2007-2008. Data were analysed using hierarchical linear modelling. Span, but not time in staff contact, interacted with leadership and operational hours to explain supervision satisfaction. With compressed operational hours, supervision satisfaction was lower with highly transformational leadership in combination with wider spans. With extended operational hours, supervision satisfaction was higher with highly transformational leadership, and this effect was more pronounced under wider spans. Operational hours, which influence the manager's daily span (average number of direct report staff working per weekday), should be factored into the design of front-line management positions. © 2011 The Authors. Journal compilation © 2011 Blackwell Publishing Ltd.
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Two-layer contractive encodings for learning stable nonlinear features.
Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven
2015-04-01
Unsupervised learning of feature hierarchies is often a good strategy to initialize deep architectures for supervised learning. Most existing deep learning methods build these feature hierarchies layer by layer in a greedy fashion using either auto-encoders or restricted Boltzmann machines. Both yield encoders which compute linear projections of input followed by a smooth thresholding function. In this work, we demonstrate that these encoders fail to find stable features when the required computation is in the exclusive-or class. To overcome this limitation, we propose a two-layer encoder which is less restricted in the type of features it can learn. The proposed encoder is regularized by an extension of previous work on contractive regularization. This proposed two-layer contractive encoder potentially poses a more difficult optimization problem, and we further propose to linearly transform hidden neurons of the encoder to make learning easier. We demonstrate the advantages of the two-layer encoders qualitatively on artificially constructed datasets as well as commonly used benchmark datasets. We also conduct experiments on a semi-supervised learning task and show the benefits of the proposed two-layer encoders trained with the linear transformation of perceptrons. Copyright © 2014 Elsevier Ltd. All rights reserved.
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[Treatment of chronic shoulder tendinitis].
Brox, J I; Bøhmer, A S; Ljunggren, A E; Staff, P H
1994-02-20
The authors review current treatment modalities and present a study comparing supervised exercises and arthroscopic surgery in patients with rotator cuff disease. Exercises supervised by a physiotherapist emphasize relearning of normal patterns of movement and local endurance training to improve tendon and muscle tissue, and are supplemented by ergonomic advice. The clinician should try to elucidate whether the patient is supposed to benefit solely from information and self-treatment. For several of the currently used treatment modalities, such as ultrasound, soft laser, heat and massage, no effect has been documented. Surgery should be reserved for persons who do not benefit from supervised exercises. Careful rehabilitation is necessary for patients who report having a physically demanding job.
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Craig, Pippa L; Phillips, Christine; Hall, Sally
2016-08-01
To describe outcomes of a model of service learning in interprofessional learning (IPL) aimed at developing a sustainable model of training that also contributed to service strengthening. A total of 57 semi-structured interviews with key informants and document review exploring the impacts of interprofessional student teams engaged in locally relevant IPL activities. Six rural towns in South East New South Wales. Local facilitators, staff of local health and other services, health professionals who supervised the 89 students in 37 IPL teams, and academic and administrative staff. Perceived benefits as a consequence of interprofessional, service-learning interventions in these rural towns. Reported outcomes included increased local awareness of a particular issue addressed by the team; improved communication between different health professions; continued use of the team's product or a changed procedure in response to the teams' work; and evidence of improved use of a particular local health service. Given the limited workforce available in rural areas to supervise clinical IPL placements, a service-learning IPL model that aims to build social capital may be a useful educational model. © 2015 National Rural Health Alliance Inc.
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YADCLAN: yet another digitally-controlled linear artificial neuron.
Frenger, Paul
2003-01-01
This paper updates the author's 1999 RMBS presentation on digitally controlled linear artificial neuron design. Each neuron is based on a standard operational amplifier having excitatory and inhibitory inputs, variable gain, an amplified linear analog output and an adjustable threshold comparator for digital output. This design employs a 1-wire serial network of digitally controlled potentiometers and resistors whose resistance values are set and read back under microprocessor supervision. This system embodies several unique and useful features, including: enhanced neuronal stability, dynamic reconfigurability and network extensibility. This artificial neuronal is being employed for feature extraction and pattern recognition in an advanced robotic application.
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Rapid Training of Information Extraction with Local and Global Data Views
2012-05-01
relation type extension system based on active learning a relation type extension system based on semi-supervised learning, and a crossdomain...bootstrapping system for domain adaptive named entity extraction. The active learning procedure adopts features extracted at the sentence level as the local
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ERIC Educational Resources Information Center
Maxwell, Tim
2013-01-01
The evolving role of the educational psychologist (EP) is discussed with an emphasis on the supervision provided for a team of support workers for vulnerable adolescents, working within a Local Service Team. This development is considered in the context of the Every Child Matters (DfES, 2004) agenda and the Farrell, Woods, Lewis, Rooney, Squire…
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Andersson, Katarina; Hanberger, Anders; Nygren, Lennart
2018-02-22
This article explores how local politicians and care unit managers in Swedish eldercare experience and respond to state supervision (SSV). Twelve politicians and twelve managers in 15 previously inspected municipalities were interviewed about their experiences of and reactions to SSV in relation to their views of care quality and routines in eldercare practice. The findings indicate that local managers and political chairs perceived SSV in eldercare positively at a superficial level but were critical of and disappointed with specific aspects of it. In terms of (a) governance, chairs and managers said SSV strengthened implementation of national policies via local actors, but they were critical of SSV's narrow focus on control and flaws in eldercare practice. With regard to (b) accountability, SSV was seen as limited to accountability for finances and systemic performance, and regarding (c) organizational development, SSV was seen as limited to improving routines and compliance with legislation, while local definitions of quality are broader than that. In general, local actors regarded SSV as improving administrative aspects and routines in practice but ignoring the relational content of eldercare quality.
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Perry, Thomas Ernest; Zha, Hongyuan; Zhou, Ke; Frias, Patricio; Zeng, Dadan; Braunstein, Mark
2014-02-01
Electronic health records possess critical predictive information for machine-learning-based diagnostic aids. However, many traditional machine learning methods fail to simultaneously integrate textual data into the prediction process because of its high dimensionality. In this paper, we present a supervised method using Laplacian Eigenmaps to enable existing machine learning methods to estimate both low-dimensional representations of textual data and accurate predictors based on these low-dimensional representations at the same time. We present a supervised Laplacian Eigenmap method to enhance predictive models by embedding textual predictors into a low-dimensional latent space, which preserves the local similarities among textual data in high-dimensional space. The proposed implementation performs alternating optimization using gradient descent. For the evaluation, we applied our method to over 2000 patient records from a large single-center pediatric cardiology practice to predict if patients were diagnosed with cardiac disease. In our experiments, we consider relatively short textual descriptions because of data availability. We compared our method with latent semantic indexing, latent Dirichlet allocation, and local Fisher discriminant analysis. The results were assessed using four metrics: the area under the receiver operating characteristic curve (AUC), Matthews correlation coefficient (MCC), specificity, and sensitivity. The results indicate that supervised Laplacian Eigenmaps was the highest performing method in our study, achieving 0.782 and 0.374 for AUC and MCC, respectively. Supervised Laplacian Eigenmaps showed an increase of 8.16% in AUC and 20.6% in MCC over the baseline that excluded textual data and a 2.69% and 5.35% increase in AUC and MCC, respectively, over unsupervised Laplacian Eigenmaps. As a solution, we present a supervised Laplacian Eigenmap method to embed textual predictors into a low-dimensional Euclidean space. This method allows many existing machine learning predictors to effectively and efficiently capture the potential of textual predictors, especially those based on short texts.
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Learning relevant features of data with multi-scale tensor networks
NASA Astrophysics Data System (ADS)
Miles Stoudenmire, E.
2018-07-01
Inspired by coarse-graining approaches used in physics, we show how similar algorithms can be adapted for data. The resulting algorithms are based on layered tree tensor networks and scale linearly with both the dimension of the input and the training set size. Computing most of the layers with an unsupervised algorithm, then optimizing just the top layer for supervised classification of the MNIST and fashion MNIST data sets gives very good results. We also discuss mixing a prior guess for supervised weights together with an unsupervised representation of the data, yielding a smaller number of features nevertheless able to give good performance.
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28 CFR 2.16 - Parole of prisoner in state, local, or territorial institution.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Parole of prisoner in state, local, or territorial institution. 2.16 Section 2.16 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT OF PRISONERS, YOUTH OFFENDERS, AND JUVENILE DELINQUENTS United States Code...
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28 CFR 2.16 - Parole of prisoner in state, local, or territorial institution.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Parole of prisoner in state, local, or territorial institution. 2.16 Section 2.16 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT OF PRISONERS, YOUTH OFFENDERS, AND JUVENILE DELINQUENTS United States Code...
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DeBeck, Kora; Wood, Evan; Zhang, Ruth; Tyndall, Mark; Montaner, Julio; Kerr, Thomas
2008-05-07
In various settings, drug market policing strategies have been found to have unintended negative effects on health service use among injection drug users (IDU). This has prompted calls for more effective coordination of policing and public health efforts. In Vancouver, Canada, a supervised injection facility (SIF) was established in 2003. We sought to determine if local police impacted utilization of the SIF. We used generalized estimating equations (GEE) to prospectively identify the prevalence and correlates of being referred by local police to Vancouver's SIF among IDU participating in the Scientific Evaluation of Supervised Injecting (SEOSI) cohort during the period of December 2003 to November 2005. Among 1090 SIF clients enrolled in SEOSI, 182 (16.7%) individuals reported having ever been referred to the SIF by local police. At baseline, 22 (2.0%) participants reported that they first learned of the SIF via police. In multivariate analyses, factors positively associated with being referred to the SIF by local police when injecting in public include: sex work (Adjusted Odds Ratio [AOR] = 1.80, 95%CI 1.28-2.53); daily cocaine injection (AOR = 1.54, 95%CI 1.14-2.08); and unsafe syringe disposal (AOR = 1.46, 95%CI 1.00-2.11). These findings indicate that local police are facilitating use of the SIF by IDU at high risk for various adverse health outcomes. We further found that police may be helping to address public order concerns by referring IDU who are more likely to discard used syringes in public spaces. Our study suggests that the SIF provides an opportunity to coordinate policing and public health efforts and thereby resolve some of the existing tensions between public order and health initiatives.
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Kumar, Saravana; Osborne, Kate; Lehmann, Tanya
2015-10-01
Recent times have witnessed dramatic changes in health care with overt recognition for quality and safety to underpin health care service delivery. In addition to systems-wide focus, the importance of supporting and mentoring people delivering the care has also been recognised. This can be achieved through quality clinical supervision. In 2010, Country Health South Australia Local Health Network developed a holistic allied health clinical governance structure, which was implemented in 2011. This research reports on emergent findings from the evaluation of the clinical governance structure, which included mandating clinical supervision for all allied health staff. A mixed method approach was chosen with evaluation of the impact of clinical supervision undertaken by a psychometrically sound instrument (Manchester Clinical Supervision Scale 26-item version), collected through an anonymous online survey and qualitative data collected through semistructured interviews and focus groups. Overall, 189 allied health professionals responded to the survey. Survey responses indicated allied health professionals recognised the importance of and valued receiving clinical supervision (normative domain), had levels of trust and rapport with, and were supported by supervisors (restorative domain) and positively affected their delivery of care and improvement in skills (formative domain). Qualitative data identified enablers such as profession specific gains, improved opportunities and consistency for clinical supervision and barriers such as persistent organisational issues, lack of clarity (delineation of roles) and communication issues. The findings from this research highlight that while clinical supervision has an important role to play, it is not a panacea for all the ills of the health care system. © 2015 National Rural Health Alliance Inc.
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Deep Learning for Extreme Weather Detection
NASA Astrophysics Data System (ADS)
Prabhat, M.; Racah, E.; Biard, J.; Liu, Y.; Mudigonda, M.; Kashinath, K.; Beckham, C.; Maharaj, T.; Kahou, S.; Pal, C.; O'Brien, T. A.; Wehner, M. F.; Kunkel, K.; Collins, W. D.
2017-12-01
We will present our latest results from the application of Deep Learning methods for detecting, localizing and segmenting extreme weather patterns in climate data. We have successfully applied supervised convolutional architectures for the binary classification tasks of detecting tropical cyclones and atmospheric rivers in centered, cropped patches. We have subsequently extended our architecture to a semi-supervised formulation, which is capable of learning a unified representation of multiple weather patterns, predicting bounding boxes and object categories, and has the capability to detect novel patterns (w/ few, or no labels). We will briefly present our efforts in scaling the semi-supervised architecture to 9600 nodes of the Cori supercomputer, obtaining 15PF performance. Time permitting, we will highlight our efforts in pixel-level segmentation of weather patterns.
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Jaarsma, Debbie A D C; Muijtjens, Arno M M; Dolmans, Diana H J M; Schuurmans, Eva M; Van Beukelen, Peter; Scherpbier, Albert J J A
2009-05-01
The learning environment of undergraduate research internships has received little attention, compared to postgraduate research training. This study investigates students' experiences with research internships, particularly the quality of supervision, development of research skills, the intellectual and social climate, infrastructure support, and the clarity of goals and the relationship between the experiences and the quality of students' research reports and their overall satisfaction with internships. A questionnaire (23 items, a 5-point Likert scale) was administered to 101 Year five veterinary students after completion of a research internship. Multiple linear regression analyses were conducted with quality of supervision, development of research skills, climate, infrastructure and clarity of goals as independent variables and the quality of students' research reports and students' overall satisfaction as dependent variables. The response rate was 79.2%. Students' experiences are generally positive. Students' experiences with the intellectual and social climate are significantly correlated with the quality of research reports whilst the quality of supervision is significantly correlated with both the quality of research reports and students' overall satisfaction with the internship. Both the quality of supervision and the climate are found to be crucial factors in students' research learning and satisfaction with the internship.
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Sustainable vector control and management of Chagas disease in the Gran Chaco, Argentina
Gürtler, Ricardo E.; Kitron, Uriel; Cecere, M. Carla; Segura, Elsa L.; Cohen, Joel E.
2007-01-01
Chagas disease remains a serious obstacle to health and economic development in Latin America, especially for the rural poor. We report the long-term effects of interventions in rural villages in northern Argentina during 1984–2006. Two community-wide campaigns of residual insecticide spraying immediately and strongly reduced domestic infestation and infection with Trypanosoma cruzi in Triatoma infestans bugs and dogs and more gradually reduced the seroprevalence of children <15 years of age. Because no effective surveillance and control actions followed the first campaign in 1985, transmission resurged in 2–3 years. Renewed interventions in 1992 followed by sustained, supervised, community-based vector control largely suppressed the reestablishment of domestic bug colonies and finally led to the interruption of local human T. cruzi transmission. Human incidence of infection was nearly an order of magnitude higher in peripheral rural areas under pulsed, unsupervised, community-based interventions, where human transmission became apparent in 2000. The sustained, supervised, community-based strategy nearly interrupted domestic transmission to dogs but did not eliminate T. infestans despite the absence of pyrethroid-insecticide resistance. T. infestans persisted in part because of the lack of major changes in housing construction and quality. Sustained community participation grew out of establishing a trusted relationship with the affected communities and the local schools. The process included health promotion and community mobilization, motivation, and supervision in close cooperation with locally nominated leaders. PMID:17913895
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44 CFR 302.4 - Merit personnel systems.
Code of Federal Regulations, 2012 CFR
2012-10-01
... HOMELAND SECURITY PREPAREDNESS CIVIL DEFENSE-STATE AND LOCAL EMERGENCY MANAGEMENT ASSISTANCE PROGRAM (EMA... maintained in public agencies administering or supervising the administration of the civil defense program in...
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Supervision Manual: Social Studies Program.
ERIC Educational Resources Information Center
Szabo, Lester John
This manual is designed to help school personnel implement a social studies program in grades K-12 in New York State. It provides the State mandates for social studies, recommends the scope and sequence of the social studies program, and suggests a procedure for implementing social studies revisions at the local level. How to form a local social…
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Pneumothorax detection in chest radiographs using local and global texture signatures
NASA Astrophysics Data System (ADS)
Geva, Ofer; Zimmerman-Moreno, Gali; Lieberman, Sivan; Konen, Eli; Greenspan, Hayit
2015-03-01
A novel framework for automatic detection of pneumothorax abnormality in chest radiographs is presented. The suggested method is based on a texture analysis approach combined with supervised learning techniques. The proposed framework consists of two main steps: at first, a texture analysis process is performed for detection of local abnormalities. Labeled image patches are extracted in the texture analysis procedure following which local analysis values are incorporated into a novel global image representation. The global representation is used for training and detection of the abnormality at the image level. The presented global representation is designed based on the distinctive shape of the lung, taking into account the characteristics of typical pneumothorax abnormalities. A supervised learning process was performed on both the local and global data, leading to trained detection system. The system was tested on a dataset of 108 upright chest radiographs. Several state of the art texture feature sets were experimented with (Local Binary Patterns, Maximum Response filters). The optimal configuration yielded sensitivity of 81% with specificity of 87%. The results of the evaluation are promising, establishing the current framework as a basis for additional improvements and extensions.
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Effect of denoising on supervised lung parenchymal clusters
NASA Astrophysics Data System (ADS)
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.
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NASA Astrophysics Data System (ADS)
Su, Zuqiang; Xiao, Hong; Zhang, Yi; Tang, Baoping; Jiang, Yonghua
2017-04-01
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.
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Boareto, Marcelo; Cesar, Jonatas; Leite, Vitor B P; Caticha, Nestor
2015-01-01
We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational method is applied to a cost function that penalizes large intraclass distances and favors small interclass distances. We find analytically the metric tensor that minimizes the cost function. Preprocessing the patterns by doing linear transformations using the metric tensor yields a dataset which can be more efficiently classified. We test our methods using publicly available datasets, for some standard classifiers. Among these datasets, two were tested by the MAQC-II project and, even without the use of further preprocessing, our results improve on their performance.
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Multilabel user classification using the community structure of online networks
Papadopoulos, Symeon; Kompatsiaris, Yiannis
2017-01-01
We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user’s graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score. PMID:28278242
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Multilabel user classification using the community structure of online networks.
Rizos, Georgios; Papadopoulos, Symeon; Kompatsiaris, Yiannis
2017-01-01
We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.
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Multilinear Graph Embedding: Representation and Regularization for Images.
Chen, Yi-Lei; Hsu, Chiou-Ting
2014-02-01
Given a set of images, finding a compact and discriminative representation is still a big challenge especially when multiple latent factors are hidden in the way of data generation. To represent multifactor images, although multilinear models are widely used to parameterize the data, most methods are based on high-order singular value decomposition (HOSVD), which preserves global statistics but interprets local variations inadequately. To this end, we propose a novel method, called multilinear graph embedding (MGE), as well as its kernelization MKGE to leverage the manifold learning techniques into multilinear models. Our method theoretically links the linear, nonlinear, and multilinear dimensionality reduction. We also show that the supervised MGE encodes informative image priors for image regularization, provided that an image is represented as a high-order tensor. From our experiments on face and gait recognition, the superior performance demonstrates that MGE better represents multifactor images than classic methods, including HOSVD and its variants. In addition, the significant improvement in image (or tensor) completion validates the potential of MGE for image regularization.
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Canizo, Brenda V; Escudero, Leticia B; Pérez, María B; Pellerano, Roberto G; Wuilloud, Rodolfo G
2018-03-01
The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Carpenter, Kenneth M.; Cheng, Wendy Y.; Smith, Jennifer L.; Brooks, Adam C.; Amrhein, Paul C.; Wain, R. Morgan; Nunes, Edward V.
2012-01-01
Objective The relationships between the occupational, educational, and verbal-cognitive characteristics of health care professionals and their Motivational Interviewing (MI) skills before, during, and after training were investigated. Method Fifty-eight community-based addiction clinicians (M = 42.1 yrs., SD =10.0; 66% Female) were assessed prior to enrolling in a two-day MI training workshop and being randomized to one of three post-workshop supervision programs: live supervision via tele-conferencing (TCS), standard tape-based supervision (Tape), or workshop training alone. Audiotaped sessions with clients were rated for MI skillfulness with the Motivational Interviewing Treatment Integrity (MITI) coding system v 2.0 at pre-workshop and 1, 8, and 20 weeks post-workshop. Correlation coefficients and generalized linear models were used to test the relationships between clinician characteristics and MI skill at each assessment point. Results Baseline MI skill levels were the most robust predictors of pre- and post-supervision performances. Clinician characteristics were associated with MI Spirit and reflective listening skill throughout training and moderated the effect of post-workshop supervision method on MI skill. TCS, which provided immediate feedback during practice sessions, was most effective for increasing MI Spirit and reflective listening among clinicians with no graduate degree and stronger vocabulary performances. Tape supervision was more effective for increasing these skills among clinicians with a graduate degree. Further, TCS and Tape were most likely to enhance MI Spirit among clinicians with low average to average verbal and abstract reasoning performances. Conclusions Clinician attributes influence the effectiveness of methods used to promote the acquisition of evidence-based practices among community-based practitioners. PMID:22563640
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Lou, Xiaoying; Enter, Daniel; Sheen, Luke; Adams, Katherine; Reed, Carolyn E; McCarthy, Patrick M; Calhoon, John H; Verrier, Edward D; Lee, Richard
2013-06-01
Given declining interest in cardiothoracic (CT) training programs during the last decade, increasing emphasis has been placed on engaging candidates early in their training. We examined the effect of supervised and unsupervised practice on medical students' interest in CT surgery. Forty-five medical students participated in this study. Participants' interest level in surgery, CT surgery, and simulation were collected before and after a pretest session. Subsequently, participants were randomized to one of three groups: control (n = 15), unsupervised training on a low-fidelity task simulator (n = 15), or supervised training with a CT surgeon or fellow on the same simulator (n = 15). After 3 weeks, attitudes were reassessed at a posttest session. Interest levels were compared before and after the pretest using paired t tests, and the effects of training on interests were assessed with multiple linear regression analyses. After the pretest session, participants were significantly more interested in simulation (p = 0.001) but not in surgery or CT surgery. After training, compared with control group participants, supervised trainees demonstrated a significant increase in their interest level in pursuing a career in surgery (p = 0.028) and an increasing trend towards a career in CT surgery (p = 0.060), whereas unsupervised trainees did not. Supervised training on low-fidelity simulators enhances interest in a career in surgery. Practice that lacks supervision does not, possibly related to the complexity of the simulated task. Mentorship efforts may need to involve sustained interaction to provide medical students with enough exposure to appreciate a surgical career. Copyright © 2013 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
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Year 5 Pupils Reading an "Interactive Storybook" on CD-ROM: Losing the Plot?
ERIC Educational Resources Information Center
Trushell, John; Burrell, Clare; Maitland, Amanda
2001-01-01
This study examined whether small groups of grade 5 students in a London primary school, without teacher supervision, progressed linearly through an interactive storybook on CD-ROM, and whether such diversions as cued animations affected pupil comprehension. Results showed students' recall of the storyline was poor. (Author/LRW)
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The Coordination Role in Research Education: Emerging Understandings and Dilemmas for Leadership
ERIC Educational Resources Information Center
Boud, David; Brew, Angela; Dowling, Robyn; Kiley, Margaret; McKenzie, Jo; Malfroy, Janne; Ryland, Kevin; Solomon, Nicky
2014-01-01
Changes in expectations of research education worldwide have seen the rise of new demands beyond supervision and have highlighted the need for academic leadership in research education at a local level. Based on an interview study of those who have taken up local leadership roles in four Australian universities, this paper maps and analyses…
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Land Use and the Legislatures: The Politics of State Innovation. Land Use Series.
ERIC Educational Resources Information Center
Rosenbaum, Nelson
This study analyzes and predicts the spread of three different types of land use legislation: mandatory local growth management, major facility siting, and critical areas protection. Chapter 2 focuses on innovative statutes that provide a new or expanded role for state agencies in supervising local control of development. The three statutes…
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Outside-bark form class volume tables for some southern Appalachian species
Jesse H. Buell
1942-01-01
Board-foot volume tables applicable to restricted localities are in continual demand. Pulic foresters need local tables for use on lands under their supervision or for helping farmers and other owners of small woodlands to prepae forest management plans. Privatr foresteres need tables which wil give dependable results in a wide variety of stands.
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ERIC Educational Resources Information Center
Elmore, Richard F., Ed.; Fuhrman, Susan H., Ed.
The United States is moving toward a more national, performance-based view of curriculum policy. The federal government will play a modest role in nationalizing curriculum policy issues, largely by pressuring states and localities through national standards. The chief agents of nationalization will continue to be state and locally based…
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Tan, Lirong; Holland, Scott K; Deshpande, Aniruddha K; Chen, Ye; Choo, Daniel I; Lu, Long J
2015-12-01
We developed a machine learning model to predict whether or not a cochlear implant (CI) candidate will develop effective language skills within 2 years after the CI surgery by using the pre-implant brain fMRI data from the candidate. The language performance was measured 2 years after the CI surgery by the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2). Based on the CELF-P2 scores, the CI recipients were designated as either effective or ineffective CI users. For feature extraction from the fMRI data, we constructed contrast maps using the general linear model, and then utilized the Bag-of-Words (BoW) approach that we previously published to convert the contrast maps into feature vectors. We trained both supervised models and semi-supervised models to classify CI users as effective or ineffective. Compared with the conventional feature extraction approach, which used each single voxel as a feature, our BoW approach gave rise to much better performance for the classification of effective versus ineffective CI users. The semi-supervised model with the feature set extracted by the BoW approach from the contrast of speech versus silence achieved a leave-one-out cross-validation AUC as high as 0.97. Recursive feature elimination unexpectedly revealed that two features were sufficient to provide highly accurate classification of effective versus ineffective CI users based on our current dataset. We have validated the hypothesis that pre-implant cortical activation patterns revealed by fMRI during infancy correlate with language performance 2 years after cochlear implantation. The two brain regions highlighted by our classifier are potential biomarkers for the prediction of CI outcomes. Our study also demonstrated the superiority of the semi-supervised model over the supervised model. It is always worthwhile to try a semi-supervised model when unlabeled data are available.
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Supervised self-organization of homogeneous swarms using ergodic projections of Markov chains.
Chattopadhyay, Ishanu; Ray, Asok
2009-12-01
This paper formulates a self-organization algorithm to address the problem of global behavior supervision in engineered swarms of arbitrarily large population sizes. The swarms considered in this paper are assumed to be homogeneous collections of independent identical finite-state agents, each of which is modeled by an irreducible finite Markov chain. The proposed algorithm computes the necessary perturbations in the local agents' behavior, which guarantees convergence to the desired observed state of the swarm. The ergodicity property of the swarm, which is induced as a result of the irreducibility of the agent models, implies that while the local behavior of the agents converges to the desired behavior only in the time average, the overall swarm behavior converges to the specification and stays there at all times. A simulation example illustrates the underlying concept.
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Supervised exercise versus non-supervised exercise for reducing weight in obese adults.
Nicolaï, S P A; Kruidenier, L M; Leffers, P; Hardeman, R; Hidding, A; Teijink, J A W
2009-03-01
The prevalence of obesity is rising. Because obesity is positively associated with many health related risks and negatively associated with life expectancy this is a threat to public health. Physical exercise is a well known method to lose fat mass. Due to shame of their appearance, bad general condition and social isolation, starting and continuing physical exercise tends to be problematic for obese adults. A supervised training program could be useful to overcome such negative factors. In this study we hypothesized that offering a supervised exercise program for obese adults would lead to greater benefits in body fat and total body mass reduction than a non-specific oral advice to increase their physical activity. Thirty-four participants were randomised to a supervised exercise program group (N.=17) and a control group (N.=17). Fifteen candidates in the intervention group and 12 in the control group appeared for baseline measurements and bought an all inclusive sports pass to a health club for Euro 10, per month. The control group just received the oral advice to increase their physical activity at their convenience. The supervised exercise group received biweekly exercise sessions of 2 hours with an estimated energy expenditure of 2 500 kJ per hour. Both groups received no dietary advice. After 4 months the overall decrease in body mass in the intervention group was 8.0 kg (SD 6.2) and the decrease in body fat was 6.2 kg (SD 4.5). The control group lost 2.8 kg overall (SD 4.2) and the decrease in body fat was 1.7 kg (SD 3.1). Correction for differences between groups in gender and age by multiple linear regression analysis showed significantly greater loss of total body mass (P = 0.001) and fat mass (P =0.002) in the intervention group compared with the control group. Stimulation of physical activity alone seems to result in a slight short term body mass and fat mass reduction in obese adults who are eager to lose weight. Supervised exercise under supervision of a qualified fitness instructor leads to a larger decrease.
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2016-12-01
Reports an error in "Is supervision necessary? Examining the effects of internet-based CBT training with and without supervision" by Sarah G. Rakovshik, Freda McManus, Maria Vazquez-Montes, Kate Muse and Dennis Ougrin ( Journal of Consulting and Clinical Psychology , 2016[Mar], Vol 84[3], 191-199). In the article, the department and affiliation were misspelled for author Kate Muse. The department and affiliation should have read Psychology Department, University of Worcester. All versions of this article has been corrected. (The following abstract of the original article appeared in record 2016-03513-001.) Objective: 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. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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Ellipsoidal fuzzy learning for smart car platoons
NASA Astrophysics Data System (ADS)
Dickerson, Julie A.; Kosko, Bart
1993-12-01
A neural-fuzzy system combined supervised and unsupervised learning to find and tune the fuzzy-rules. An additive fuzzy system approximates a function by covering its graph with fuzzy rules. A fuzzy rule patch can take the form of an ellipsoid in the input-output space. Unsupervised competitive learning found the statistics of data clusters. The covariance matrix of each synaptic quantization vector defined on ellipsoid centered at the centroid of the data cluster. Tightly clustered data gave smaller ellipsoids or more certain rules. Sparse data gave larger ellipsoids or less certain rules. Supervised learning tuned the ellipsoids to improve the approximation. The supervised neural system used gradient descent to find the ellipsoidal fuzzy patches. It locally minimized the mean-squared error of the fuzzy approximation. Hybrid ellipsoidal learning estimated the control surface for a smart car controller.
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NASA Astrophysics Data System (ADS)
Cruz-Roa, Angel; Arevalo, John; Basavanhally, Ajay; Madabhushi, Anant; González, Fabio
2015-01-01
Learning data representations directly from the data itself is an approach that has shown great success in different pattern recognition problems, outperforming state-of-the-art feature extraction schemes for different tasks in computer vision, speech recognition and natural language processing. Representation learning applies unsupervised and supervised machine learning methods to large amounts of data to find building-blocks that better represent the information in it. Digitized histopathology images represents a very good testbed for representation learning since it involves large amounts of high complex, visual data. This paper presents a comparative evaluation of different supervised and unsupervised representation learning architectures to specifically address open questions on what type of learning architectures (deep or shallow), type of learning (unsupervised or supervised) is optimal. In this paper we limit ourselves to addressing these questions in the context of distinguishing between anaplastic and non-anaplastic medulloblastomas from routine haematoxylin and eosin stained images. The unsupervised approaches evaluated were sparse autoencoders and topographic reconstruct independent component analysis, and the supervised approach was convolutional neural networks. Experimental results show that shallow architectures with more neurons are better than deeper architectures without taking into account local space invariances and that topographic constraints provide useful invariant features in scale and rotations for efficient tumor differentiation.
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A Survey of the Medical Needs of a Group of Small Factories*
Lee, W. R.
1962-01-01
The present interest in medical services for small factories is matched by the limited objective information which is available on the demand for and needs of such services. As a teaching project, a survey was made of factories with between 30 and 200 employees on an estate in the North West where there was no organized medical service. Unfortunately, time allowed only 22 factories to be visited. The findings, therefore, are regarded as indicative rather than conclusive, but this does not detract from their interest. Factories were visited by two or three postgraduate students who completed a questionnaire designed to standardize their findings. The questionnaire is included as an appendix to this paper. Regarding the demand for medical services, four of the 22 factories were subsidiaries of larger organizations and had part-time medical advice, 14 expressed no interest even if this would have involved no financial commitment, and the remaining four were interested for differing reasons. The needs of the factories in this context were found to be, first, advice and perhaps better supervision of non-mechanical hazards and, secondly, supervision of the first aid arrangements. From the ambulance journey records of the local authority there appeared to be no great demand for local casualty facilities. To meet these needs it is suggested that the functions of the appointed factory doctor might be modified to include wider supervision of non-mechanical hazards and supervision of first aid arrangements. It is also suggested that the National Health Service should form the basis for dealing with those cases requiring more than first aid. PMID:14463582
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44 CFR 302.8 - Waiver of “single” State agency requirements.
Code of Federal Regulations, 2012 CFR
2012-10-01
... AGENCY, DEPARTMENT OF HOMELAND SECURITY PREPAREDNESS CIVIL DEFENSE-STATE AND LOCAL EMERGENCY MANAGEMENT... requires that plans for civil defense of the United States be administered or supervised by a single State...
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44 CFR 302.8 - Waiver of “single” State agency requirements.
Code of Federal Regulations, 2014 CFR
2014-10-01
... AGENCY, DEPARTMENT OF HOMELAND SECURITY PREPAREDNESS CIVIL DEFENSE-STATE AND LOCAL EMERGENCY MANAGEMENT... requires that plans for civil defense of the United States be administered or supervised by a single State...
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44 CFR 302.8 - Waiver of “single” State agency requirements.
Code of Federal Regulations, 2013 CFR
2013-10-01
... AGENCY, DEPARTMENT OF HOMELAND SECURITY PREPAREDNESS CIVIL DEFENSE-STATE AND LOCAL EMERGENCY MANAGEMENT... requires that plans for civil defense of the United States be administered or supervised by a single State...
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44 CFR 302.8 - Waiver of “single” State agency requirements.
Code of Federal Regulations, 2011 CFR
2011-10-01
... AGENCY, DEPARTMENT OF HOMELAND SECURITY PREPAREDNESS CIVIL DEFENSE-STATE AND LOCAL EMERGENCY MANAGEMENT... requires that plans for civil defense of the United States be administered or supervised by a single State...
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44 CFR 302.8 - Waiver of “single” State agency requirements.
Code of Federal Regulations, 2010 CFR
2010-10-01
... AGENCY, DEPARTMENT OF HOMELAND SECURITY PREPAREDNESS CIVIL DEFENSE-STATE AND LOCAL EMERGENCY MANAGEMENT... requires that plans for civil defense of the United States be administered or supervised by a single State...
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Local-aggregate modeling for big data via distributed optimization: Applications to neuroimaging.
Hu, Yue; Allen, Genevera I
2015-12-01
Technological advances have led to a proliferation of structured big data that have matrix-valued covariates. We are specifically motivated to build predictive models for multi-subject neuroimaging data based on each subject's brain imaging scans. This is an ultra-high-dimensional problem that consists of a matrix of covariates (brain locations by time points) for each subject; few methods currently exist to fit supervised models directly to this tensor data. We propose a novel modeling and algorithmic strategy to apply generalized linear models (GLMs) to this massive tensor data in which one set of variables is associated with locations. Our method begins by fitting GLMs to each location separately, and then builds an ensemble by blending information across locations through regularization with what we term an aggregating penalty. Our so called, Local-Aggregate Model, can be fit in a completely distributed manner over the locations using an Alternating Direction Method of Multipliers (ADMM) strategy, and thus greatly reduces the computational burden. Furthermore, we propose to select the appropriate model through a novel sequence of faster algorithmic solutions that is similar to regularization paths. We will demonstrate both the computational and predictive modeling advantages of our methods via simulations and an EEG classification problem. © 2015, The International Biometric Society.
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Corn Clubs: Building the Foundation for Agricultural and Extension Education
ERIC Educational Resources Information Center
Uricchio, Cassandra; Moore, Gary; Coley, Michael
2013-01-01
Corn clubs played an important role in improving agriculture at the turn of the 20th century. Corn clubs were local organizations consisting of boys who cultivated corn on one acre of land under the supervision of a local club leader. The purpose of this historical research study was to document the organization, operation, and outcomes of corn…
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Yin, Zhong; Zhang, Jianhua
2014-07-01
Identifying the abnormal changes of mental workload (MWL) over time is quite crucial for preventing the accidents due to cognitive overload and inattention of human operators in safety-critical human-machine systems. It is known that various neuroimaging technologies can be used to identify the MWL variations. In order to classify MWL into a few discrete levels using representative MWL indicators and small-sized training samples, a novel EEG-based approach by combining locally linear embedding (LLE), support vector clustering (SVC) and support vector data description (SVDD) techniques is proposed and evaluated by using the experimentally measured data. The MWL indicators from different cortical regions are first elicited by using the LLE technique. Then, the SVC approach is used to find the clusters of these MWL indicators and thereby to detect MWL variations. It is shown that the clusters can be interpreted as the binary class MWL. Furthermore, a trained binary SVDD classifier is shown to be capable of detecting slight variations of those indicators. By combining the two schemes, a SVC-SVDD framework is proposed, where the clear-cut (smaller) cluster is detected by SVC first and then a subsequent SVDD model is utilized to divide the overlapped (larger) cluster into two classes. Finally, three-class MWL levels (low, normal and high) can be identified automatically. The experimental data analysis results are compared with those of several existing methods. It has been demonstrated that the proposed framework can lead to acceptable computational accuracy and has the advantages of both unsupervised and supervised training strategies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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Smedts, Anna M; Campbell, Narelle; Sweet, Linda
2013-01-01
This study sought to characterise the allied health professional (AHP) workforce of the Northern Territory (NT), Australia, in order to understand the influence of student supervision on workload, job satisfaction, and recruitment and retention. The national Rural Allied Health Workforce Study survey was adapted for the NT context and distributed through local AHP networks. Valid responses (n=179) representing 16 professions were collated and categorised into 'supervisor' and 'non-supervisor' groups for further analysis. The NT AHP workforce is predominantly female, non-Indigenous, raised in an urban environment, trained outside the NT, now concentrated in the capital city, and principally engaged in individual patient care. Allied health professionals cited income and type of work or clientele as the most frequent factors for attraction to their current positions. While 62% provided student supervision, only half reported having training in mentoring or supervision. Supervising students accounted for an estimated 9% of workload. Almost 20% of existing supervisors and 33% of non-supervising survey respondents expressed an interest in greater supervisory responsibilities. Despite indicating high satisfaction with their current positions, 67% of respondents reported an intention to leave their jobs in less than 5 years. Student supervision was not linked to perceived job satisfaction; however, this study found that professionals who were engaged in student supervision were significantly more likely to report intention to stay in their current jobs (>5 years; p<0.05). The findings are important for supporting ongoing work-integrated learning opportunities for students in a remote context, and highlight the need for efforts to be focused on the training and retention of AHPs as student supervisors.
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Zheng, Wu; Blake, Catherine
2015-10-01
Databases of curated biomedical knowledge, such as the protein-locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to curate knowledge bases with automated approaches that leverage the increased availability of full-text scientific articles. This paper describes experiments that use distant supervised learning to identify protein subcellular localizations, which are important to understand protein function and to identify candidate drug targets. Experiments consider Swiss-Prot, the manually annotated subset of the UniProtKB protein knowledge base, and 43,000 full-text articles from the Journal of Biological Chemistry that contain just under 11.5 million sentences. The system achieves 0.81 precision and 0.49 recall at sentence level and an accuracy of 57% on held-out instances in a test set. Moreover, the approach identifies 8210 instances that are not in the UniProtKB knowledge base. Manual inspection of the 50 most likely relations showed that 41 (82%) were valid. These results have immediate benefit to researchers interested in protein function, and suggest that distant supervision should be explored to complement other manual data curation efforts. Copyright © 2015 Elsevier Inc. All rights reserved.
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Code of Federal Regulations, 2010 CFR
2010-07-01
... Protection of Environment ENVIRONMENTAL PROTECTION AGENCY GRANTS AND OTHER FEDERAL ASSISTANCE STATE AND LOCAL... carry out public water system supervision programs including implementation and enforcement of the... program regulations are found in 40 CFR parts 141, 142, and 143. ...
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Code of Federal Regulations, 2011 CFR
2011-07-01
... Protection of Environment ENVIRONMENTAL PROTECTION AGENCY GRANTS AND OTHER FEDERAL ASSISTANCE STATE AND LOCAL... carry out public water system supervision programs including implementation and enforcement of the... program regulations are found in 40 CFR parts 141, 142, and 143. ...
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Robust head pose estimation via supervised manifold learning.
Wang, Chao; Song, Xubo
2014-05-01
Head poses can be automatically estimated using manifold learning algorithms, with the assumption that with the pose being the only variable, the face images should lie in a smooth and low-dimensional manifold. However, this estimation approach is challenging due to other appearance variations related to identity, head location in image, background clutter, facial expression, and illumination. To address the problem, we propose to incorporate supervised information (pose angles of training samples) into the process of manifold learning. The process has three stages: neighborhood construction, graph weight computation and projection learning. For the first two stages, we redefine inter-point distance for neighborhood construction as well as graph weight by constraining them with the pose angle information. For Stage 3, we present a supervised neighborhood-based linear feature transformation algorithm to keep the data points with similar pose angles close together but the data points with dissimilar pose angles far apart. The experimental results show that our method has higher estimation accuracy than the other state-of-art algorithms and is robust to identity and illumination variations. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Mubuuke, AG; Oria, H; Dhabangi, A; Kiguli, S; Sewankambo, NK
2015-01-01
Introduction To produce health professionals who are oriented towards addressing community priority health needs, the training in medical schools has been transformed to include a component of community-based training. During this period, students spend a part of their training in the communities they are likely to serve upon graduation. They engage and empower local people in the communities to address their health needs during their placements, and at the same time learn from the people. During the community-based component, students are constantly supervised by faculty from the university to ensure that the intended objectives are achieved. The purpose of the present study was to explore student experiences of support supervision from university faculty during their community-based education, research and service (COBERS placements) and to identify ways in which the student learning can be improved through improved faculty supervision. Methods This was a cross-sectional study involving students at the College of Health Sciences, Makerere University, Uganda, who had a community-based component during their training. Data were collected using both questionnaires and focus group discussions. Quantitative data were analyzed using statistical software and thematic approaches were used for the analysis of qualitative data. Results Most students reported satisfaction with the COBERS supervision; however, junior students were less satisfied with the supervision than the more senior students with more experience of community-based training. Although many supervisors assisted students before departure to COBERS sites, a significant number of supervisors made little follow-up while students were in the community. Incorporating the use of information technology avenues such as emails and skype sessions was suggested as a potential way of enhancing supervision amidst resource constraints without faculty physically visiting the sites. Conclusions Although many students were satisfied with COBERS supervision, there are still some challenges, mostly seen with the more junior students. Using information technology could be a solution to some of these challenges. PMID:26626014
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Mubuuke, Aloysius G; Oria, Hussein; Dhabangi, Aggrey; Kiguli, Sarah; Sewankambo, Nelson K
2015-01-01
To produce health professionals who are oriented towards addressing community priority health needs, the training in medical schools has been transformed to include a component of community-based training. During this period, students spend a part of their training in the communities they are likely to serve upon graduation. They engage and empower local people in the communities to address their health needs during their placements, and at the same time learn from the people. During the community-based component, students are constantly supervised by faculty from the university to ensure that the intended objectives are achieved. The purpose of the present study was to explore student experiences of support supervision from university faculty during their community-based education, research and service (COBERS placements) and to identify ways in which the student learning can be improved through improved faculty supervision. This was a cross-sectional study involving students at the College of Health Sciences, Makerere University, Uganda, who had a community-based component during their training. Data were collected using both questionnaires and focus group discussions. Quantitative data were analyzed using statistical software and thematic approaches were used for the analysis of qualitative data. Most students reported satisfaction with the COBERS supervision; however, junior students were less satisfied with the supervision than the more senior students with more experience of community-based training. Although many supervisors assisted students before departure to COBERS sites, a significant number of supervisors made little follow-up while students were in the community. Incorporating the use of information technology avenues such as emails and skype sessions was suggested as a potential way of enhancing supervision amidst resource constraints without faculty physically visiting the sites. Although many students were satisfied with COBERS supervision, there are still some challenges, mostly seen with the more junior students. Using information technology could be a solution to some of these challenges.
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Schriver, Michael; Cubaka, Vincent Kalumire; Vedsted, Peter; Besigye, Innocent; Kallestrup, Per
2018-01-01
External supervision of primary health care facilities to monitor and improve services is common in low-income countries. Currently there are no tools to measure the quality of support in external supervision in these countries. To develop a provider-reported instrument to assess the support delivered through external supervision in Rwanda and other countries. "External supervision: Provider Evaluation of Supervisor Support" (ExPRESS) was developed in 18 steps, primarily in Rwanda. Content validity was optimised using systematic search for related instruments, interviews, translations, and relevance assessments by international supervision experts as well as local experts in Nigeria, Kenya, Uganda and Rwanda. Construct validity and reliability were examined in two separate field tests, the first using exploratory factor analysis and a test-retest design, the second for confirmatory factor analysis. We included 16 items in section A ('The most recent experience with an external supervisor'), and 13 items in section B ('The overall experience with external supervisors'). Item-content validity index was acceptable. In field test I, test-retest had acceptable kappa values and exploratory factor analysis suggested relevant factors in sections A and B used for model hypotheses. In field test II, models were tested by confirmatory factor analysis fitting a 4-factor model for section A, and a 3-factor model for section B. ExPRESS is a promising tool for evaluation of the quality of support of primary health care providers in external supervision of primary health care facilities in resource-constrained settings. ExPRESS may be used as specific feedback to external supervisors to help identify and address gaps in the supervision they provide. Further studies should determine optimal interpretation of scores and the number of respondents needed per supervisor to obtain precise results, as well as test the functionality of section B.
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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 classifier, suggest that quasi-supervised image texture labelling may be a useful method in the analysis and classification of pathological slides but further study is required to improve the results. Copyright © 2013 Elsevier Ltd. All rights reserved.
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APPLICATION OF NEURAL NETWORK ALGORITHMS FOR BPM LINEARIZATION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Musson, John C.; Seaton, Chad; Spata, Mike F.
2012-11-01
Stripline BPM sensors contain inherent non-linearities, as a result of field distortions from the pickup elements. Many methods have been devised to facilitate corrections, often employing polynomial fitting. The cost of computation makes real-time correction difficult, particulalry when integer math is utilized. The application of neural-network technology, particularly the multi-layer perceptron algorithm, is proposed as an efficient alternative for electrode linearization. A process of supervised learning is initially used to determine the weighting coefficients, which are subsequently applied to the incoming electrode data. A non-linear layer, known as an activation layer, is responsible for the removal of saturation effects. Implementationmore » of a perceptron in an FPGA-based software-defined radio (SDR) is presented, along with performance comparisons. In addition, efficient calculation of the sigmoidal activation function via the CORDIC algorithm is presented.« less
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NASA Astrophysics Data System (ADS)
Vasefi, Fartash; Kittle, David S.; Nie, Zhaojun; Falcone, Christina; Patil, Chirag G.; Chu, Ray M.; Mamelak, Adam N.; Black, Keith L.; Butte, Pramod V.
2016-04-01
We have developed and tested a system for real-time intra-operative optical identification and classification of brain tissues using time-resolved fluorescence spectroscopy (TRFS). A supervised learning algorithm using linear discriminant analysis (LDA) employing selected intrinsic fluorescence decay temporal points in 6 spectral bands was employed to maximize statistical significance difference between training groups. The linear discriminant analysis on in vivo human tissues obtained by TRFS measurements (N = 35) were validated by histopathologic analysis and neuronavigation correlation to pre-operative MRI images. These results demonstrate that TRFS can differentiate between normal cortex, white matter and glioma.
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Simultaneously Discovering and Localizing Common Objects in Wild Images.
Wang, Zhenzhen; Yuan, Junsong
2018-09-01
Motivated by the recent success of supervised and weakly supervised common object discovery, in this paper, we move forward one step further to tackle common object discovery in a fully unsupervised way. Generally, object co-localization aims at simultaneously localizing objects of the same class across a group of images. Traditional object localization/detection usually trains specific object detectors which require bounding box annotations of object instances, or at least image-level labels to indicate the presence/absence of objects in an image. Given a collection of images without any annotations, our proposed fully unsupervised method is to simultaneously discover images that contain common objects and also localize common objects in corresponding images. Without requiring to know the total number of common objects, we formulate this unsupervised object discovery as a sub-graph mining problem from a weighted graph of object proposals, where nodes correspond to object proposals, and edges represent the similarities between neighbouring proposals. The positive images and common objects are jointly discovered by finding sub-graphs of strongly connected nodes, with each sub-graph capturing one object pattern. The optimization problem can be efficiently solved by our proposed maximal-flow-based algorithm. Instead of assuming that each image contains only one common object, our proposed solution can better address wild images where each image may contain multiple common objects or even no common object. Moreover, our proposed method can be easily tailored to the task of image retrieval in which the nodes correspond to the similarity between query and reference images. Extensive experiments on PASCAL VOC 2007 and Object Discovery data sets demonstrate that even without any supervision, our approach can discover/localize common objects of various classes in the presence of scale, view point, appearance variation, and partial occlusions. We also conduct broad experiments on image retrieval benchmarks, Holidays and Oxford5k data sets, to show that our proposed method, which considers both the similarity between query and reference images and also similarities among reference images, can help to improve the retrieval results significantly.
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Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning.
Peng, Yong; Lu, Bao-Liang; Wang, Suhang
2015-05-01
Constructing an informative and discriminative graph plays an important role in various pattern recognition tasks such as clustering and classification. Among the existing graph-based learning models, low-rank representation (LRR) is a very competitive one, which has been extensively employed in spectral clustering and semi-supervised learning (SSL). In SSL, the graph is composed of both labeled and unlabeled samples, where the edge weights are calculated based on the LRR coefficients. However, most of existing LRR related approaches fail to consider the geometrical structure of data, which has been shown beneficial for discriminative tasks. In this paper, we propose an enhanced LRR via sparse manifold adaption, termed manifold low-rank representation (MLRR), to learn low-rank data representation. MLRR can explicitly take the data local manifold structure into consideration, which can be identified by the geometric sparsity idea; specifically, the local tangent space of each data point was sought by solving a sparse representation objective. Therefore, the graph to depict the relationship of data points can be built once the manifold information is obtained. We incorporate a regularizer into LRR to make the learned coefficients preserve the geometric constraints revealed in the data space. As a result, MLRR combines both the global information emphasized by low-rank property and the local information emphasized by the identified manifold structure. Extensive experimental results on semi-supervised classification tasks demonstrate that MLRR is an excellent method in comparison with several state-of-the-art graph construction approaches. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Ten Commandments for Microcomputer Facility Planners.
ERIC Educational Resources Information Center
Espinosa, Leonard J.
1991-01-01
Presents factors involved in designing a microcomputer facility, including how computers will be used in the instructional program; educational specifications; planning committees; user input; quality of purchases; visual supervision considerations; location; workstation design; turnkey systems; electrical requirements; local area networks;…
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Mayer, John M; Quillen, William S; Verna, Joe L; Chen, Ren; Lunseth, Paul; Dagenais, Simon
2015-01-01
Low back pain is a leading cause of disability in firefighters and is related to poor muscular endurance. This study examined the impact of supervised worksite exercise on back and core muscular endurance in firefighters. A cluster randomized controlled trial was used for this study. The study occurred in fire stations of a municipal fire department (Tampa, Florida). Subjects were 96 full-duty career firefighters who were randomly assigned by fire station to exercise (n = 54) or control (n = 42) groups. Exercise group participants completed a supervised exercise targeting the back and core muscles while on duty, two times per week for 24 weeks, in addition to their usual fitness regimen. Control group participants continued their usual fitness regimen. Back and core muscular endurance was assessed with the Biering-Sorensen test and plank test, respectively. Changes in back and core muscular endurance from baseline to 24 weeks were compared between groups using analysis of covariance and linear mixed effects models. After 24 weeks, the exercise group had 12% greater (p = .021) back muscular endurance and 21% greater (p = .0006) core muscular endurance than did the control group. The exercise intervention did not disrupt operations or job performance. A supervised worksite exercise program was safe and effective in improving back and core muscular endurance in firefighters, which could protect against future low back pain.
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Supervised learning with decision margins in pools of spiking neurons.
Le Mouel, Charlotte; Harris, Kenneth D; Yger, Pierre
2014-10-01
Learning to categorise sensory inputs by generalising from a few examples whose category is precisely known is a crucial step for the brain to produce appropriate behavioural responses. At the neuronal level, this may be performed by adaptation of synaptic weights under the influence of a training signal, in order to group spiking patterns impinging on the neuron. Here we describe a framework that allows spiking neurons to perform such "supervised learning", using principles similar to the Support Vector Machine, a well-established and robust classifier. Using a hinge-loss error function, we show that requesting a margin similar to that of the SVM improves performance on linearly non-separable problems. Moreover, we show that using pools of neurons to discriminate categories can also increase the performance by sharing the load among neurons.
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Gaia eclipsing binary and multiple systems. Supervised classification and self-organizing maps
NASA Astrophysics Data System (ADS)
Süveges, M.; Barblan, F.; Lecoeur-Taïbi, I.; Prša, A.; Holl, B.; Eyer, L.; Kochoska, A.; Mowlavi, N.; Rimoldini, L.
2017-07-01
Context. Large surveys producing tera- and petabyte-scale databases require machine-learning and knowledge discovery methods to deal with the overwhelming quantity of data and the difficulties of extracting concise, meaningful information with reliable assessment of its uncertainty. This study investigates the potential of a few machine-learning methods for the automated analysis of eclipsing binaries in the data of such surveys. Aims: We aim to aid the extraction of samples of eclipsing binaries from such databases and to provide basic information about the objects. We intend to estimate class labels according to two different, well-known classification systems, one based on the light curve morphology (EA/EB/EW classes) and the other based on the physical characteristics of the binary system (system morphology classes; detached through overcontact systems). Furthermore, we explore low-dimensional surfaces along which the light curves of eclipsing binaries are concentrated, and consider their use in the characterization of the binary systems and in the exploration of biases of the full unknown Gaia data with respect to the training sets. Methods: We have explored the performance of principal component analysis (PCA), linear discriminant analysis (LDA), Random Forest classification and self-organizing maps (SOM) for the above aims. We pre-processed the photometric time series by combining a double Gaussian profile fit and a constrained smoothing spline, in order to de-noise and interpolate the observed light curves. We achieved further denoising, and selected the most important variability elements from the light curves using PCA. Supervised classification was performed using Random Forest and LDA based on the PC decomposition, while SOM gives a continuous 2-dimensional manifold of the light curves arranged by a few important features. We estimated the uncertainty of the supervised methods due to the specific finite training set using ensembles of models constructed on randomized training sets. Results: We obtain excellent results (about 5% global error rate) with classification into light curve morphology classes on the Hipparcos data. The classification into system morphology classes using the Catalog and Atlas of Eclipsing binaries (CALEB) has a higher error rate (about 10.5%), most importantly due to the (sometimes strong) similarity of the photometric light curves originating from physically different systems. When trained on CALEB and then applied to Kepler-detected eclipsing binaries subsampled according to Gaia observing times, LDA and SOM provide tractable, easy-to-visualize subspaces of the full (functional) space of light curves that summarize the most important phenomenological elements of the individual light curves. The sequence of light curves ordered by their first linear discriminant coefficient is compared to results obtained using local linear embedding. The SOM method proves able to find a 2-dimensional embedded surface in the space of the light curves which separates the system morphology classes in its different regions, and also identifies a few other phenomena, such as the asymmetry of the light curves due to spots, eccentric systems, and systems with a single eclipse. Furthermore, when data from other surveys are projected to the same SOM surface, the resulting map yields a good overview of the general biases and distortions due to differences in time sampling or population.
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Semi-supervised protein subcellular localization.
Xu, Qian; Hu, Derek Hao; Xue, Hong; Yu, Weichuan; Yang, Qiang
2009-01-30
Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data. In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions. Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.
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Hybrid region merging method for segmentation of high-resolution remote sensing images
NASA Astrophysics Data System (ADS)
Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi; Wang, Jiangeng; Wang, Zuo
2014-12-01
Image segmentation remains a challenging problem for object-based image analysis. In this paper, a hybrid region merging (HRM) method is proposed to segment high-resolution remote sensing images. HRM integrates the advantages of global-oriented and local-oriented region merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region, which provides an elegant way to avoid the problem of starting point assignment and to enhance the optimization ability for local-oriented region merging. During the region growing procedure, the merging iterations are constrained within the local vicinity, so that the segmentation is accelerated and can reflect the local context, as compared with the global-oriented method. A set of high-resolution remote sensing images is used to test the effectiveness of the HRM method, and three region-based remote sensing image segmentation methods are adopted for comparison, including the hierarchical stepwise optimization (HSWO) method, the local-mutual best region merging (LMM) method, and the multiresolution segmentation (MRS) method embedded in eCognition Developer software. Both the supervised evaluation and visual assessment show that HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM and MRS are visually comparable, but HRM can describe objects as single regions better than MRS, and the supervised and unsupervised evaluation results further prove the superiority of HRM.
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A survey of local anaesthesia education in European dental schools.
Brand, H S; Kuin, D; Baart, J A
2008-05-01
A survey of European dental schools was conducted in 2006 to determine the curricular structure, techniques and materials used in local anaesthesia teaching to dental students. A questionnaire was designed to collect information about local anaesthesia education. The questionnaires were sent to the Dean of each dental school in Europe and Israel; 49 returned the completed survey, resulting in a response rate of 18.4%. Results from this survey show that dental schools are managing local anaesthesia education in different ways. At most schools, theoretical teaching begins during the first half of the third year (41%), half a year before the practical instruction (43%). In 37% of the dental schools, students use non-human objects to practice before they inject an anaesthetic in humans. The first injection in humans, usually a fellow student (61%), is mostly supervised by an oral and maxillofacial surgeon (65%). The number of injections under supervision usually depends on the individual capabilities of the student (41%). Ten per cent of the schools need permission of a medical ethics committee for the practical instruction on fellow students. All dental curricula include teaching of mandibular block anaesthesia. The majority also include instruction of infiltration anaesthesia of the upper (98%) and lower (92%) jaws in addition to infra-orbital block anaesthesia (57%). Although 82% of the schools are satisfied with the current curriculum with regard to local anaesthesia, 43% are planning changes, frequently the introduction of preclinical training models. Local anaesthesia teaching programmes show considerable variation across the surveyed European dental schools.
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Vansintejan, G A; Glaser, W A
1988-01-01
During the 1980's in Karawa, Northwestern Zaire, a motion picture was produced which showed the interaction of the modern and traditional systems. The maternity center of the Karawa hospital was central to this effort. Traditional birth attendants (TBAs) became leading participants. Locally trained midwives were key trainers. The training and supervision programs had been ongoing for 2 years when Karawa was chosen as the movie site in 1986. The script was written by a midwife who had trained trainers of TBAs and TBAs themselves. All the steps in the selection, training, supervision, and supplying of TBAs in Karawa and its neighboring villages are included in the script. A Zairian team shot the script. The 5-member crew were employees of the Office Zairois de la Radio-Television (OZRT), the country's official television, radio, and film service. "Wibange" has separate sound tracks in French and English. Costs of the movie were met by contributions from both the US Agency for International Development and from Zaire. "Wibange--Traditional Birth Attendants: Their Training and Supervision" was developed in New York City. There are 2 final productions, a French and an English version. Running time is 23 minutes.
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Jovanović, N; Podlesek, A; Volpe, U; Barrett, E; Ferrari, S; Rojnic Kuzman, M; Wuyts, P; Papp, S; Nawka, A; Vaida, A; Moscoso, A; Andlauer, O; Tateno, M; Lydall, G; Wong, V; Rujevic, J; Platz Clausen, N; Psaras, R; Delic, A; Losevich, M A; Flegar, S; Crépin, P; Shmunk, E; Kuvshinov, I; Loibl-Weiß, E; Beezhold, J
2016-02-01
Postgraduate medical trainees experience high rates of burnout, but evidence regarding psychiatric trainees is missing. We aim to determine burnout rates among psychiatric trainees, and identify individual, educational and work-related factors associated with severe burnout. In an online survey psychiatric trainees from 22 countries were asked to complete the Maslach Burnout Inventory (MBI-GS) and provide information on individual, educational and work-related parameters. Linear mixed models were used to predict the MBI-GS scores, and a generalized linear mixed model to predict severe burnout. This is the largest study on burnout and training conditions among psychiatric trainees to date. Complete data were obtained from 1980 out of 7625 approached trainees (26%; range 17.8-65.6%). Participants were 31.9 (SD 5.3) years old with 2.8 (SD 1.9) years of training. Severe burnout was found in 726 (36.7%) trainees. The risk was higher for trainees who were younger (P<0.001), without children (P=0.010), and had not opted for psychiatry as a first career choice (P=0.043). After adjustment for socio-demographic characteristics, years in training and country differences in burnout, severe burnout remained associated with long working hours (P<0.001), lack of supervision (P<0.001), and not having regular time to rest (P=0.001). Main findings were replicated in a sensitivity analysis with countries with response rate above 50%. Besides previously described risk factors such as working hours and younger age, this is the first evidence of negative influence of lack of supervision and not opting for psychiatry as a first career choice on trainees' burnout. Copyright © 2016. Published by Elsevier Masson SAS.
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NASA Astrophysics Data System (ADS)
Huayang, Yin; Di, Zhou; Bing, Cui
2018-02-01
Using soft budget theory to explore the formation mechanism and the deep institutional incentive of the local financing platform debt expansion from the perspective of fiscal / financial decentralization, construct theoretical framework which explain the expansion of local debt financing platform and conduct an empirical test, the results showed that the higher the degree of fiscal decentralization, fiscal autonomy as a soft constraint body of local government the stronger, local financing platform debt scale is greater; the higher the degree of financial decentralization, local government and financial institutions have the higher autonomy with respect to the central, local financing platform debt scale is bigger; financial synergy degree is stronger, local government financial mutual supervision prompted the local government debt more transparency, local debt financing platform size is smaller.
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Local Anaesthetic Inguinal Hernia Repair Performed Under Supervision: Early and Long-Term Outcomes
Sanjay, P; Woodward, A
2009-01-01
INTRODUCTION Local anaesthetic inguinal hernia repair may be technically demanding. There are minimal data regarding the outcomes of local anaesthetic hernia repair by trainees in comparison with consultants. PATIENTS AND METHODS All consecutive local anaesthetic repairs performed by trainees and one consultant over a 9-year period were reviewed. Operation time, volume of local anaesthetic used, early and long-term complications were assessed. A postal survey was conducted to assess chronic groin pain and satisfaction rates. RESULTS A total of 369 repairs were reviewed of which 265 repairs were performed by the consultant and 104 by trainees. The male-to-female ratio was 25:1 and the median age of the study group was 61 years (range, 18–93 years). The volume of local anaesthetic used was significantly higher for trainees than the consultant (42 ml versus 69 ml; P = 0.03). The operative time for the consultant and the trainees was 35 min and 40 min (P = 0.8). The day-case rate was higher for the consultant than the trainees (84% versus 69%; P = 0.02). Three patients operated by trainees required conversion to a general anaesthetic repair. No difference was noted in chronic groin pain (consultant 28% versus trainees 32%; P = 0.52) on the postal survey. The median follow-up was 5 years (range, 2–7 years). CONCLUSIONS Local anaesthetic inguinal hernia repair can be performed safely by surgical trainees under consultant supervision with minimal short- and long-term morbidity. A large volume dilute solution of Lignocaine and Marcaine is recommended when hernia repair is undertaken by trainees. PMID:19785942
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Code of Federal Regulations, 2010 CFR
2010-07-01
... REQUIREMENTS NATIONAL MINE HEALTH AND SAFETY ACADEMY Tuition Fees § 42.10 Tuition fees. The National Mine... attending Academy courses, except employees of Federal, State, or local governments, persons attending the... the Agency's judgment, contribute to improved conduct, supervision, or management of a function or...
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SLLE for predicting membrane protein types.
Wang, Meng; Yang, Jie; Xu, Zhi-Jie; Chou, Kuo-Chen
2005-01-07
Introduction of the concept of pseudo amino acid composition (PROTEINS: Structure, Function, and Genetics 43 (2001) 246; Erratum: ibid. 44 (2001) 60) has made it possible to incorporate a considerable amount of sequence-order effects by representing a protein sample in terms of a set of discrete numbers, and hence can significantly enhance the prediction quality of membrane protein type. As a continuous effort along such a line, the Supervised Locally Linear Embedding (SLLE) technique for nonlinear dimensionality reduction is introduced (Science 22 (2000) 2323). The advantage of using SLLE is that it can reduce the operational space by extracting the essential features from the high-dimensional pseudo amino acid composition space, and that the cluster-tolerant capacity can be increased accordingly. As a consequence by combining these two approaches, high success rates have been observed during the tests of self-consistency, jackknife and independent data set, respectively, by using the simplest nearest neighbour classifier. The current approach represents a new strategy to deal with the problems of protein attribute prediction, and hence may become a useful vehicle in the area of bioinformatics and proteomics.
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Gray, Thomas G; Hood, Gill; Farrell, Tom
2015-11-06
Feedback drives learning in medical education. Healthcare Supervision Logbook (HSL) is a Smartphone App developed at Sheffield Teaching Hospitals for providing feedback on medical training, from both a trainee's and a supervisor's perspective. In order to establish a mandate for the role of HSL in clinical practice, a large survey was carried out. Two surveys (one for doctors undertaking specialty training and a second for consultants supervising their training) were designed. The survey for doctors-in-training was distributed to all specialty trainees in the South and West localities of the Health Education Yorkshire and the Humber UK region. The survey for supervisors was distributed to all consultants involved in educational and clinical supervision of specialty trainees at Sheffield Teaching Hospitals. The results confirm that specialty trainees provide feedback on their training infrequently-66 % do so only annually. 96 % of the specialty trainees owned a Smartphone and 45 % said that they would be willing to use a Smartphone App to provide daily feedback on the clinical and educational supervision they receive. Consultant supervisors do not receive regular feedback on the educational and clinical supervision they provide to trainees-56 % said they never received such feedback and 33 % said it was only on an annual basis. 86 % of consultants surveyed owned a Smartphone and 41 % said they would be willing to use a Smartphone App to provide feedback on the performance of trainees they were supervising. Feedback on medical training is recorded by specialty trainees infrequently and consultants providing educational and clinical supervision often do not receive any feedback on their performance in this area. HSL is a simple, quick and efficient way to collect and collate feedback on medical training to improve this situation. Good support and education needs to be provided when implementing this new technology.
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Pang, Junbiao; Qin, Lei; Zhang, Chunjie; Zhang, Weigang; Huang, Qingming; Yin, Baocai
2015-12-01
Local coordinate coding (LCC) is a framework to approximate a Lipschitz smooth function by combining linear functions into a nonlinear one. For locally linear classification, LCC requires a coding scheme that heavily determines the nonlinear approximation ability, posing two main challenges: 1) the locality making faraway anchors have smaller influences on current data and 2) the flexibility balancing well between the reconstruction of current data and the locality. In this paper, we address the problem from the theoretical analysis of the simplest local coding schemes, i.e., local Gaussian coding and local student coding, and propose local Laplacian coding (LPC) to achieve the locality and the flexibility. We apply LPC into locally linear classifiers to solve diverse classification tasks. The comparable or exceeded performances of state-of-the-art methods demonstrate the effectiveness of the proposed method.
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Mei, L; Tobe, R G; Geng, H; Ma, Y B; Li, R Y; Wang, W B; Selotlegeng, L; Wang, X Z; Xu, L Z
2012-12-01
Disposal of sputum from patients with pulmonary tuberculosis (TB) who are treated at home is an important aspect of preventing the spread of TB. However, few studies have examined disposal of sputum by patients with TB who are treated at home. Patients with pulmonary TB who are treated at home were surveyed regarding sputum handling and supervision. A cross-sectional survey of a representative sample of patients with pulmonary TB who are treated at home was conducted in Shandong Province. Participants were individuals with TB who had been registered with a local agency responsible for TB control. Participants completed a questionnaire with both qualitative and quantitative questions. How sputum was handled was determined and factors associated with sputum disposal were analyzed using a non-parametric test, logistic regression, and content analysis. Responses were received from 720 participants. Patients expectorated sputum 4.56 ± 10.367 times a day, and 68.6% of patients responded that they correctly disposed of their sputum. Supervision as part of TB control focused on the efforts of health agencies and paid little attention to waste management by patients. A non-parametric test showed that sputum disposal was significantly associated with gender, age, education, sputum smear results, attitudes toward waste management, and attitudes toward supervision (all p < 0.05). Logistic regression analysis showed that gender (OR = 0.482, 95% CI: 0.329-0.704), sputum smear results (OR = 1.300, 95% CI: 1.037-1.629), and level of education (OR = 0.685, 95% CI: 0.528-0.889) were associated with receipt of TB health education (all p < 0.05). Sputum handling by and supervision of patients with pulmonary TB who are treated at home is severely wanting. From a policy perspective, special attention should be given to the definition, details, and methods of supervision of waste management by patients with TB to give them relevant health education and enhance their willingness to be supervised. A financial incentive should be provided to health workers supervising management of TB-related waste.
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Kim, Harris H-S; Chun, JongSerl
2018-06-01
This study investigates the extent to which friendship network, family relations, and school context are related to adolescent cigarette smoking. Friendship network is measured in terms of delinquent peers; family relations in terms of parental supervision; and school environment in terms of objective (eg, antismoking policy) and subjective (eg, school attachment) characteristics. Findings are based on the secondary analysis of the health behavior in school-aged children, 2009-2010. Two-level hierarchical generalized linear models are estimated using hierarchical linear modeling 7. At the student level, ties to delinquent friends is significantly related to higher odds of smoking, while greater parental supervision is associated with lower odds. At the school level, antismoking policy and curriculum independently lower smoking behavior. Better within-class peer relations, greater school attachment, and higher academic performance are also negatively related to smoking. Last, the positive association between delinquent friends and smoking is weaker in schools with a formally enacted antismoking policy. However, this association is stronger in schools with better peer relations. Adolescent smoking behavior is embedded in a broader ecological setting. This research reveals that a proper understanding of it requires comprehensive analysis that incorporates factors measured at individual (student) and contextual (school) levels. © 2018, American School Health Association.
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Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis
Cárdenas-Peña, David; Collazos-Huertas, Diego; Castellanos-Dominguez, German
2016-01-01
Dementia is a growing problem that affects elderly people worldwide. More accurate evaluation of dementia diagnosis can help during the medical examination. Several methods for computer-aided dementia diagnosis have been proposed using resonance imaging scans to discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and healthy controls (NC). Nonetheless, the computer-aided diagnosis is especially challenging because of the heterogeneous and intermediate nature of MCI. We address the automated dementia diagnosis by introducing a novel supervised pretraining approach that takes advantage of the artificial neural network (ANN) for complex classification tasks. The proposal initializes an ANN based on linear projections to achieve more discriminating spaces. Such projections are estimated by maximizing the centered kernel alignment criterion that assesses the affinity between the resonance imaging data kernel matrix and the label target matrix. As a result, the performed linear embedding allows accounting for features that contribute the most to the MCI class discrimination. We compare the supervised pretraining approach to two unsupervised initialization methods (autoencoders and Principal Component Analysis) and against the best four performing classification methods of the 2014 CADDementia challenge. As a result, our proposal outperforms all the baselines (7% of classification accuracy and area under the receiver-operating-characteristic curve) at the time it reduces the class biasing. PMID:27148392
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25 CFR 38.10 - Conditions of employment of educators.
Code of Federal Regulations, 2010 CFR
2010-04-01
... duly adopted school board policies, including those relating to tribal culture or language. (c... Conditions of employment of educators. (a) Supervision not delegated to school boards. School boards may not... each local school or agency to provide specific information regarding: (1) The working and hiring...
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ADVANCED ADULT EDUCATION IN ISRAEL.
ERIC Educational Resources Information Center
Ministry of Education and Culture, Jerusalem (Israel).
ADULT EDUCATION IN ISRAEL IS UNDER THE SUPERVISION OF THE CULTURAL DEPARTMENT, WHICH RECOMMENDS TEACHERS AND LECTURERS AND IS RESPONSIBLE FOR INSPECTION AND FINANCIAL SUPPORT. STUDENT FEES ARE COLLECTED LOCALLY. PREVIOUSLY DEVOTED TO JEWISH TOPICS AND HEBREW LANGUAGE, THE PROGRAM HAS BEEN EXPANDED TO INCLUDE FORMAL SECONDARY EDUCATION, HUMANITIES,…
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9 CFR 355.28 - Unfit material to be condemned.
Code of Federal Regulations, 2010 CFR
2010-01-01
... INSPECTION AND CERTIFICATION CERTIFIED PRODUCTS FOR DOGS, CATS, AND OTHER CARNIVORA; INSPECTION... legitimate use for some purpose other than the preparation of the certified products, they may be released by authorized inspectors for such other purpose for disposition under the supervision of the proper local, State...
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Juvenile Drug Courts and Teen Substance Abuse
ERIC Educational Resources Information Center
Butts, Jeffrey A., Ed.; Roman, John, Ed.
2004-01-01
Juvenile justice officials across the United States are embracing a new method of dealing with adolescent substance abuse. Importing a popular innovation from adult courts, state and local governments have started hundreds of specialized drug courts to provide judicial supervision and coordinate substance abuse treatment for drug-involved…
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NASA Astrophysics Data System (ADS)
Govorov, Michael; Gienko, Gennady; Putrenko, Viktor
2018-05-01
In this paper, several supervised machine learning algorithms were explored to define homogeneous regions of con-centration of uranium in surface waters in Ukraine using multiple environmental parameters. The previous study was focused on finding the primary environmental parameters related to uranium in ground waters using several methods of spatial statistics and unsupervised classification. At this step, we refined the regionalization using Artifi-cial Neural Networks (ANN) techniques including Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Convolutional Neural Network (CNN). The study is focused on building local ANN models which may significantly improve the prediction results of machine learning algorithms by taking into considerations non-stationarity and autocorrelation in spatial data.
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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.
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Assessment of Schrodinger Eigenmaps for target detection
NASA Astrophysics Data System (ADS)
Dorado Munoz, Leidy P.; Messinger, David W.; Czaja, Wojtek
2014-06-01
Non-linear dimensionality reduction methods have been widely applied to hyperspectral imagery due to its structure as the information can be represented in a lower dimension without losing information, and because the non-linear methods preserve the local geometry of the data while the dimension is reduced. One of these methods is Laplacian Eigenmaps (LE), which assumes that the data lies on a low dimensional manifold embedded in a high dimensional space. LE builds a nearest neighbor graph, computes its Laplacian and performs the eigendecomposition of the Laplacian. These eigenfunctions constitute a basis for the lower dimensional space in which the geometry of the manifold is preserved. In addition to the reduction problem, LE has been widely used in tasks such as segmentation, clustering, and classification. In this regard, a new Schrodinger Eigenmaps (SE) method was developed and presented as a semi-supervised classification scheme in order to improve the classification performance and take advantage of the labeled data. SE is an algorithm built upon LE, where the former Laplacian operator is replaced by the Schrodinger operator. The Schrodinger operator includes a potential term V, that, taking advantage of the additional information such as labeled data, allows clustering of similar points. In this paper, we explore the idea of using SE in target detection. In this way, we present a framework where the potential term V is defined as a barrier potential: a diagonal matrix encoding the spatial position of the target, and the detection performance is evaluated by using different targets and different hyperspectral scenes.
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Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 6 2013-01-01 2012-01-01 true Discovery. 509.102 Section 509.102 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY RULES OF PRACTICE AND PROCEDURE IN ADJUDICATORY PROCEEDINGS Local Rules § 509.102 Discovery. (a) In general. A party may take the deposition of an...
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Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 6 2014-01-01 2012-01-01 true Discovery. 509.102 Section 509.102 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY RULES OF PRACTICE AND PROCEDURE IN ADJUDICATORY PROCEEDINGS Local Rules § 509.102 Discovery. (a) In general. A party may take the deposition of an...
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Code of Federal Regulations, 2011 CFR
2011-01-01
... 12 Banks and Banking 5 2011-01-01 2011-01-01 false Discovery. 509.102 Section 509.102 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY RULES OF PRACTICE AND PROCEDURE IN ADJUDICATORY PROCEEDINGS Local Rules § 509.102 Discovery. (a) In general. A party may take the deposition of an...
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Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 6 2012-01-01 2012-01-01 false Discovery. 509.102 Section 509.102 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY RULES OF PRACTICE AND PROCEDURE IN ADJUDICATORY PROCEEDINGS Local Rules § 509.102 Discovery. (a) In general. A party may take the deposition of an...
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Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Discovery. 509.102 Section 509.102 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY RULES OF PRACTICE AND PROCEDURE IN ADJUDICATORY PROCEEDINGS Local Rules § 509.102 Discovery. (a) In general. A party may take the deposition of an...
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School Partnerships: Technology Rich Classrooms and the Student Teaching Experience
ERIC Educational Resources Information Center
VanSlyke-Briggs, Kjersti; Hogan, Molly; Waffle, Julene; Samplaski, Jessica
2014-01-01
Building upon an established relationship between a college and a local school district, this project formally designated a Partnership School, at which education students conduct field experience. In addition to providing these participating pre-service teachers (students) with a clinically rich experience through closer supervision by and…
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Status Report on the Program for Effective Teaching (PET).
ERIC Educational Resources Information Center
Arkansas State Dept. of Education, Little Rock.
During the 1979-80 school year, the Arkansas Department of Education, in cooperation with institutions of higher education and local education agencies, initiated a comprehensive staff development and instructional supervision program in school districts throughout the state. The purpose of the program, called Program for Effective Teaching (PET),…
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Nicholls, David P.
Over the past four years the Principal Investigator (PI) David Nicholls has worked on several projects in connection with award DE-SC0001549. Of the greatest import has been the continued supervision of ve Ph.D. students (Robyn Canning, Travis McBride, Andrew Sward, Zheng Fang, and Venu Tammali). Canning and McBride defended their theses and graduated in May 2012, while Sward defended his thesis and graduated in May 2013. Both Fang and Tammali plan to defend their theses within the year and graduate in May 2015. Fang is now a very experienced graduate researcher with one paper accepted for publication and another inmore » preparation. Tammali is nearly to the point of writing a paper and will work this summer as an intern at Argonne National Laboratory in the Mathematics and Computer Science Division under the supervision of Paul Fischer.« less
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Image fusion using sparse overcomplete feature dictionaries
Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt
2015-10-06
Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.
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Huang, Tao; Li, Xiao-yu; Jin, Rui; Ku, Jing; Xu, Sen-miao; Xu, Meng-ling; Wu, Zhen-zhong; Kong, De-guo
2015-04-01
The present paper put forward a non-destructive detection method which combines semi-transmission hyperspectral imaging technology with manifold learning dimension reduction algorithm and least squares support vector machine (LSSVM) to recognize internal and external defects in potatoes simultaneously. Three hundred fifteen potatoes were bought in farmers market as research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images of normal external defects (bud and green rind) and internal defect (hollow heart) potatoes. In order to conform to the actual production, defect part is randomly put right, side and back to the acquisition probe when the hyperspectral images of external defects potatoes are acquired. The average spectrums (390-1,040 nm) were extracted from the region of interests for spectral preprocessing. Then three kinds of manifold learning algorithm were respectively utilized to reduce the dimension of spectrum data, including supervised locally linear embedding (SLLE), locally linear embedding (LLE) and isometric mapping (ISOMAP), the low-dimensional data gotten by manifold learning algorithms is used as model input, Error Correcting Output Code (ECOC) and LSSVM were combined to develop the multi-target classification model. By comparing and analyzing results of the three models, we concluded that SLLE is the optimal manifold learning dimension reduction algorithm, and the SLLE-LSSVM model is determined to get the best recognition rate for recognizing internal and external defects potatoes. For test set data, the single recognition rate of normal, bud, green rind and hollow heart potato reached 96.83%, 86.96%, 86.96% and 95% respectively, and he hybrid recognition rate was 93.02%. The results indicate that combining the semi-transmission hyperspectral imaging technology with SLLE-LSSVM is a feasible qualitative analytical method which can simultaneously recognize the internal and external defects potatoes and also provide technical reference for rapid on-line non-destructive detecting of the internal and external defects potatoes.
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Transfer Learning for Adaptive Relation Extraction
2011-09-13
other NLP tasks, however, supervised learning approach fails when there is not a sufficient amount of labeled data for training, which is often the case...always 12 Syntactic Pattern Relation Instance Relation Type (Subtype) arg-2 arg-1 Arab leaders OTHER-AFF (Ethnic) his father PER-SOC (Family) South...for x. For sequence labeling tasks in NLP , linear-chain conditional random field has been rather suc- cessful. It is an undirected graphical model in
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1944-05-14
German military administrator for FRANCE with full control-of all local French officials. He administers local defense, internal security, supervision of...CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING...Date: 3 May 44* ANNEX 1 (INTELLIGENCE) Hq, 82d A/B Div, APO 469s U. S. Army, to 3 lMay 1944 F. 0. 6 MAPS: FRANCE , 1/25,000 GSG6 4347 1/50,000 GSGS 4250 1
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Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.
2014-01-01
Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953
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Sweeney, Elizabeth M; Vogelstein, Joshua T; Cuzzocreo, Jennifer L; Calabresi, Peter A; Reich, Daniel S; Crainiceanu, Ciprian M; Shinohara, Russell T
2014-01-01
Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.
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Identification of Alfalfa Leaf Diseases Using Image Recognition Technology
Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang
2016-01-01
Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease. PMID:27977767
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Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.
Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang
2016-01-01
Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease.
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Garcia-Chimeno, Yolanda; Garcia-Zapirain, Begonya
2015-01-01
The classification of subjects' pathologies enables a rigorousness to be applied to the treatment of certain pathologies, as doctors on occasions play with so many variables that they can end up confusing some illnesses with others. Thanks to Machine Learning techniques applied to a health-record database, it is possible to make using our algorithm. hClass contains a non-linear classification of either a supervised, non-supervised or semi-supervised type. The machine is configured using other techniques such as validation of the set to be classified (cross-validation), reduction in features (PCA) and committees for assessing the various classifiers. The tool is easy to use, and the sample matrix and features that one wishes to classify, the number of iterations and the subjects who are going to be used to train the machine all need to be introduced as inputs. As a result, the success rate is shown either via a classifier or via a committee if one has been formed. A 90% success rate is obtained in the ADABoost classifier and 89.7% in the case of a committee (comprising three classifiers) when PCA is applied. This tool can be expanded to allow the user to totally characterise the classifiers by adjusting them to each classification use.
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Medically supervised water-only fasting in the treatment of borderline hypertension.
Goldhamer, Alan C; Lisle, Douglas J; Sultana, Peter; Anderson, Scott V; Parpia, Banoo; Hughes, Barry; Campbell, T Colin
2002-10-01
Hypertension-related diseases are the leading causes of morbidity and mortality in industrially developed societies. Surprisingly, 68% of all mortality attributed to high blood pressure (BP) occurs with systolic BP between 120 and 140 mm Hg and diastolic BP below 90 mm Hg. Dietary and lifestyle modifications are effective in the treatment of borderline hypertension. One such lifestyle intervention is the use of medically supervised water-only fasting as a safe and effective means of normalizing BP and initiating health-promoting behavioral changes. Sixty-eight (68) consecutive patients with borderline hypertension with systolic BP in excess of 119 mm Hg and diastolic BP less than 91 mm Hg were treated in an inpatient setting under medical supervision. The treatment program consisted of a short prefasting period (approximately 1-2 days on average) during which food consumption was limited to fruits and vegetables followed by medically supervised water-only fasting (approximately 13.6 days on average). Fasting was followed by a refeeding period (approximately 6.0 days on average). The refeeding program consisted of a low-fat, low-sodium, plant-based, vegan diet. Approximately 82% of the subjects achieved BP at or below 120/80 mm Hg by the end of the treatment program. The mean BP reduction was 20/7 mm Hg, with the greatest decrease being observed for subjects with the highest baseline BP. A linear regression of BP decrease against baseline BP showed that the estimated BP below which no further decrease would be expected was 96.0/67.0 mm Hg at the end of the fast and 99.2/67.3 mm Hg at the end of refeeding. These levels are in agreement with other estimates of the BP below which stroke events are eliminated, thus suggesting that these levels could be regarded as the "ideal" BP values. Medically supervised water-only fasting appears to be a safe and effective means of normalizing BP and may assist in motivating health-promoting diet and lifestyle changes.
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Weakly Supervised Segmentation-Aided Classification of Urban Scenes from 3d LIDAR Point Clouds
NASA Astrophysics Data System (ADS)
Guinard, S.; Landrieu, L.
2017-05-01
We consider the problem of the semantic classification of 3D LiDAR point clouds obtained from urban scenes when the training set is limited. We propose a non-parametric segmentation model for urban scenes composed of anthropic objects of simple shapes, partionning the scene into geometrically-homogeneous segments which size is determined by the local complexity. This segmentation can be integrated into a conditional random field classifier (CRF) in order to capture the high-level structure of the scene. For each cluster, this allows us to aggregate the noisy predictions of a weakly-supervised classifier to produce a higher confidence data term. We demonstrate the improvement provided by our method over two publicly-available large-scale data sets.
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Mackridge, Adam John; Gray, Nicola Jane; Krska, Janet
2017-07-10
This study aims to provide a national picture of the extent and nature of public health services commissioned by local authorities (LAs) from community pharmacies across England in financial year 2014/15. Cross-sectional survey of public health services commissioned in community pharmacies by LAs, gathered via freedom of information requests and documentary analysis. All 152 LAs in England. A total of 833 commissioned services were reported across England (range 3-10 per LA). Four services were commissioned by over 90% of LAs: emergency hormonal contraception (EHC), smoking cessation support, supervised consumption of methadone or other opiates and needle and syringe programmes (NSPs). The proportion of pharmacies commissioned to deliver these services varied considerably between LAs from <10% to 100%. This variation was not related to differences in relevant proxy measures of need. NHS Health Checks and alcohol screening and brief advice were commissioned by fewer LAs (32% and 15%, respectively), again with no relationship to relevant measures of need. A range of other services were commissioned less frequently, by fewer than 10% of LAs.Supervised consumption and NSPs were the most frequently used services, with over 4.4 million individual supervisions and over 1.4 million needle packs supplied. Pharmacies provided over 200 000 consultations for supply of EHC, over 30 000 supplies of free condoms and almost 16 000 chlamydia screening kits. More than 55 000 people registered to stop smoking in a community pharmacy, almost 30 000 were screened for alcohol use and over 26 000 NHS Health Checks were delivered. There is significant variation in commissioning and delivery of public health services in community pharmacies across England, which correlate poorly with potential benefit to local populations. Research to ascertain reasons for this variation is needed to ensure that future commissioning and delivery of these services matches local need. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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Refining Linear Fuzzy Rules by Reinforcement Learning
NASA Technical Reports Server (NTRS)
Berenji, Hamid R.; Khedkar, Pratap S.; Malkani, Anil
1996-01-01
Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.
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ERIC Educational Resources Information Center
Tolich, Martin; Scarth, Bonnie; Shephard, Kerry
2015-01-01
This article examines the experiences of final year undergraduate sociology students enrolled in an internship course where they researched a local community project, mostly in small groups, for a client. A sociology lecturer supervised their projects. Course-related outcomes were assessed using conventional university procedures but a research…
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ERIC Educational Resources Information Center
Hangartner, Judith; Svaton, Carla Jana
2014-01-01
This article discusses insights from an ethnographic study of local governance practices in the Canton of Bern, Switzerland, under changing policy conditions. Recent reforms introduced and strengthened the position of head teachers, enhanced the responsibility of the municipalities and introduced new quality management procedures in local…
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33 CFR 334.50 - Piscataqua River at Portsmouth Naval Shipyard, Kittery, Maine; restricted areas.
Code of Federal Regulations, 2013 CFR
2013-07-01
... Naval Shipyard, Kittery, Maine; restricted areas. 334.50 Section 334.50 Navigation and Navigable Waters... REGULATIONS § 334.50 Piscataqua River at Portsmouth Naval Shipyard, Kittery, Maine; restricted areas. (a) The..., except those vessels under the supervision of or contract to local military or naval authority, are...
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33 CFR 334.50 - Piscataqua River at Portsmouth Naval Shipyard, Kittery, Maine; restricted areas.
Code of Federal Regulations, 2012 CFR
2012-07-01
... Naval Shipyard, Kittery, Maine; restricted areas. 334.50 Section 334.50 Navigation and Navigable Waters... REGULATIONS § 334.50 Piscataqua River at Portsmouth Naval Shipyard, Kittery, Maine; restricted areas. (a) The..., except those vessels under the supervision of or contract to local military or naval authority, are...
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33 CFR 334.50 - Piscataqua River at Portsmouth Naval Shipyard, Kittery, Maine; restricted areas.
Code of Federal Regulations, 2014 CFR
2014-07-01
... Naval Shipyard, Kittery, Maine; restricted areas. 334.50 Section 334.50 Navigation and Navigable Waters... REGULATIONS § 334.50 Piscataqua River at Portsmouth Naval Shipyard, Kittery, Maine; restricted areas. (a) The..., except those vessels under the supervision of or contract to local military or naval authority, are...
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Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-02
... DEPARTMENT OF DEFENSE Department of the Army, Corps of Engineers 33 CFR Part 334 United States Navy Restricted Area, SUPSHIP Bath Maine Detachment Mobile at AUSTAL, USA, Mobile, AL; Restricted Area... craft, except those vessels under the supervision or contract to local military or Naval authority...
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Unlocking Potential: How Political Skill Can Maximize Superintendent Effectiveness
ERIC Educational Resources Information Center
Hill, Paul; Jochim, Ashley
2018-01-01
Local superintendents must do an important job while equipped with, at best, modest authority. Superintendents are ultimately responsible for all the schools in their district, and they at least nominally supervise everything that happens in those schools. Yet superintendents cannot count on obedience or even support from the people who work for…
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Understanding Discourse on Work and Job-Related Well-Being in Public Social Media
Liu, Tong; Homan, Christopher M.; Alm, Cecilia Ovesdotter; White, Ann Marie; Lytle, Megan C.; Kautz, Henry A.
2016-01-01
We construct a humans-in-the-loop supervised learning framework that integrates crowdsourcing feedback and local knowledge to detect job-related tweets from individual and business accounts. Using data-driven ethnography, we examine discourse about work by fusing language-based analysis with temporal, geospational, and labor statistics information. PMID:27795613
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ERIC Educational Resources Information Center
Valley Springs School District 2, AR.
A project was conducted to promote and develop individual Supervised Agricultural Experience (SAE) programs in Arkansas through the development of laboratories. It was felt that strong SAE programs enhance the instructional portion of agriculture education, serve as a motivational tool, and improve the relations between the local school and…
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Dewaelheyns, Nico; Eeckloo, Kristof; Van Hulle, Cynthia
2011-01-01
Using a unique data set, this study explores how type of ownership (government/private) is related to processes of governance. The findings suggest that the neo-institutional perspective and the self-interest rationale of the agency perspective are helpful in explaining processes of governance in both government- and privately owned non-profit organizations. Due to adverse incentives and the quest for legitimacy, supervising governance bodies within local government-owned non-profit institutions pay relatively less attention to the development of high quality supervising bodies and delegate little to management. Our findings also indicate that governance processes in private institutions are more aligned with the business model and that this alignment is likely driven by a concern to improve decision making. By contrast, our data also suggest that in local government-owned institutions re-election concerns of politicians-trustees are an important force in the governance processes of these institutions. In view of these adverse incentives - in contrast to the case of private organizations - a governance code is unlikely to entail much improvement in government-owned organizations. Copyright © 2010 John Wiley & Sons, Ltd.
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Hernández, Alison R; Hurtig, Anna-Karin; Dahlblom, Kjerstin; San Sebastián, Miguel
2014-03-06
Mid-level health workers (MLHWs) form the front-line of service delivery in many low- and middle-income countries. Supervision is a critical institutional intervention linking their work to the health system, and it consists of activities intended to support health workers' motivation and enable them to perform. However its impact depends not only on the frequency of these activities but also how they are carried out and received. This study aims to deepen understanding of the mechanisms through which supervision activities support the performance of auxiliary nurses, a cadre of MLHWs, in rural Guatemala. A multiple case study was conducted to examine the operation of supervision of five health posts using a realist evaluation approach. A program theory was formulated describing local understanding of how supervision activities are intended to work. Data was collected through interviews and document review to test the theory. Analysis focused on comparison of activities, outcomes, mechanisms and the influence of context across cases, leading to revision of the program theory. The supervisor's orientation was identified as the main mechanism contributing to variation observed in activities and their outcomes. Managerial control was the dominant orientation, reflecting the influence of standardized performance criteria and institutional culture. Humanized support was present in one case where the auxiliary nurse was motivated by the sense that the full scope of her work was valued. This orientation reflected the supervisor's integration of her professional identity as a nurse. The nature of the support health workers received was shaped by supervisors' orientation, and in this study, nursing principles were central to humanized support. Efforts to strengthen the support that supervision provides to MLHWs should promote professional ethos as a means of developing shared performance goals and orient supervisors to a more holistic view of the health worker and their work.
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2014-01-01
Background Mid-level health workers (MLHWs) form the front-line of service delivery in many low- and middle-income countries. Supervision is a critical institutional intervention linking their work to the health system, and it consists of activities intended to support health workers’ motivation and enable them to perform. However its impact depends not only on the frequency of these activities but also how they are carried out and received. This study aims to deepen understanding of the mechanisms through which supervision activities support the performance of auxiliary nurses, a cadre of MLHWs, in rural Guatemala. Methods A multiple case study was conducted to examine the operation of supervision of five health posts using a realist evaluation approach. A program theory was formulated describing local understanding of how supervision activities are intended to work. Data was collected through interviews and document review to test the theory. Analysis focused on comparison of activities, outcomes, mechanisms and the influence of context across cases, leading to revision of the program theory. Results The supervisor’s orientation was identified as the main mechanism contributing to variation observed in activities and their outcomes. Managerial control was the dominant orientation, reflecting the influence of standardized performance criteria and institutional culture. Humanized support was present in one case where the auxiliary nurse was motivated by the sense that the full scope of her work was valued. This orientation reflected the supervisor’s integration of her professional identity as a nurse. Conclusions The nature of the support health workers received was shaped by supervisors’ orientation, and in this study, nursing principles were central to humanized support. Efforts to strengthen the support that supervision provides to MLHWs should promote professional ethos as a means of developing shared performance goals and orient supervisors to a more holistic view of the health worker and their work. PMID:24602196
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Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong
2016-01-01
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. PMID:27367703
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Application of Local Linear Embedding to Nonlinear Exploratory Latent Structure Analysis
ERIC Educational Resources Information Center
Wang, Haonan; Iyer, Hari
2007-01-01
In this paper we discuss the use of a recent dimension reduction technique called Locally Linear Embedding, introduced by Roweis and Saul, for performing an exploratory latent structure analysis. The coordinate variables from the locally linear embedding describing the manifold on which the data reside serve as the latent variable scores. We…
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Hu, Ding; Xie, Shuqun; Yu, Donglan; Zheng, Zhensheng; Wang, Kuijian
2010-04-01
The development of external counterpulsation (ECP) local area network system and extensible markup language (XML)-based remote ECP medical information system conformable to digital imaging and communications in medicine (DICOM) standard has been improving the digital interchangeablity and sharability of ECP data. However, the therapy process of ECP is a continuous and longtime supervision which builds a mass of waveform data. In order to reduce the storage space and improve the transmission efficiency, the waveform data with the normative format of ECP data files have to be compressed. In this article, we introduced the compression arithmetic of template matching and improved quick fitting of linear approximation distance thresholding (LADT) in combimation with the characters of enhanced external counterpulsation (EECP) waveform signal. The DICOM standard is used as the storage and transmission standard to make our system compatible with hospital information system. According to the rules of transfer syntaxes, we defined private transfer syntax for one-dimensional compressed waveform data and stored EECP data into a DICOM file. Testing result indicates that the compressed and normative data can be correctly transmitted and displayed between EECP workstations in our EECP laboratory.
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Secure Fusion Estimation for Bandwidth Constrained Cyber-Physical Systems Under Replay Attacks.
Chen, Bo; Ho, Daniel W C; Hu, Guoqiang; Yu, Li; Bo Chen; Ho, Daniel W C; Guoqiang Hu; Li Yu; Chen, Bo; Ho, Daniel W C; Hu, Guoqiang; Yu, Li
2018-06-01
State estimation plays an essential role in the monitoring and supervision of cyber-physical systems (CPSs), and its importance has made the security and estimation performance a major concern. In this case, multisensor information fusion estimation (MIFE) provides an attractive alternative to study secure estimation problems because MIFE can potentially improve estimation accuracy and enhance reliability and robustness against attacks. From the perspective of the defender, the secure distributed Kalman fusion estimation problem is investigated in this paper for a class of CPSs under replay attacks, where each local estimate obtained by the sink node is transmitted to a remote fusion center through bandwidth constrained communication channels. A new mathematical model with compensation strategy is proposed to characterize the replay attacks and bandwidth constrains, and then a recursive distributed Kalman fusion estimator (DKFE) is designed in the linear minimum variance sense. According to different communication frameworks, two classes of data compression and compensation algorithms are developed such that the DKFEs can achieve the desired performance. Several attack-dependent and bandwidth-dependent conditions are derived such that the DKFEs are secure under replay attacks. An illustrative example is given to demonstrate the effectiveness of the proposed methods.
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Improved classification accuracy by feature extraction using genetic algorithms
NASA Astrophysics Data System (ADS)
Patriarche, Julia; Manduca, Armando; Erickson, Bradley J.
2003-05-01
A feature extraction algorithm has been developed for the purposes of improving classification accuracy. The algorithm uses a genetic algorithm / hill-climber hybrid to generate a set of linearly recombined features, which may be of reduced dimensionality compared with the original set. The genetic algorithm performs the global exploration, and a hill climber explores local neighborhoods. Hybridizing the genetic algorithm with a hill climber improves both the rate of convergence, and the final overall cost function value; it also reduces the sensitivity of the genetic algorithm to parameter selection. The genetic algorithm includes the operators: crossover, mutation, and deletion / reactivation - the last of these effects dimensionality reduction. The feature extractor is supervised, and is capable of deriving a separate feature space for each tissue (which are reintegrated during classification). A non-anatomical digital phantom was developed as a gold standard for testing purposes. In tests with the phantom, and with images of multiple sclerosis patients, classification with feature extractor derived features yielded lower error rates than using standard pulse sequences, and with features derived using principal components analysis. Using the multiple sclerosis patient data, the algorithm resulted in a mean 31% reduction in classification error of pure tissues.
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Graph embedding and extensions: a general framework for dimensionality reduction.
Yan, Shuicheng; Xu, Dong; Zhang, Benyu; Zhang, Hong-Jiang; Yang, Qiang; Lin, Stephen
2007-01-01
Over the past few decades, a large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to provide different solutions to the problem of dimensionality reduction. Despite the different motivations of these algorithms, we present in this paper a general formulation known as graph embedding to unify them within a common framework. In graph embedding, each algorithm can be considered as the direct graph embedding or its linear/kernel/tensor extension of a specific intrinsic graph that describes certain desired statistical or geometric properties of a data set, with constraints from scale normalization or a penalty graph that characterizes a statistical or geometric property that should be avoided. Furthermore, the graph embedding framework can be used as a general platform for developing new dimensionality reduction algorithms. By utilizing this framework as a tool, we propose a new supervised dimensionality reduction algorithm called Marginal Fisher Analysis in which the intrinsic graph characterizes the intraclass compactness and connects each data point with its neighboring points of the same class, while the penalty graph connects the marginal points and characterizes the interclass separability. We show that MFA effectively overcomes the limitations of the traditional Linear Discriminant Analysis algorithm due to data distribution assumptions and available projection directions. Real face recognition experiments show the superiority of our proposed MFA in comparison to LDA, also for corresponding kernel and tensor extensions.
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NASA Astrophysics Data System (ADS)
Gangeh, Mehrdad J.; Fung, Brandon; Tadayyon, Hadi; Tran, William T.; Czarnota, Gregory J.
2016-03-01
A non-invasive computer-aided-theragnosis (CAT) system was developed for the early assessment of responses to neoadjuvant chemotherapy in patients with locally advanced breast cancer. The CAT system was based on quantitative ultrasound spectroscopy methods comprising several modules including feature extraction, a metric to measure the dissimilarity between "pre-" and "mid-treatment" scans, and a supervised learning algorithm for the classification of patients to responders/non-responders. One major requirement for the successful design of a high-performance CAT system is to accurately measure the changes in parametric maps before treatment onset and during the course of treatment. To this end, a unified framework based on Hilbert-Schmidt independence criterion (HSIC) was used for the design of feature extraction from parametric maps and the dissimilarity measure between the "pre-" and "mid-treatment" scans. For the feature extraction, HSIC was used to design a supervised dictionary learning (SDL) method by maximizing the dependency between the scans taken from "pre-" and "mid-treatment" with "dummy labels" given to the scans. For the dissimilarity measure, an HSIC-based metric was employed to effectively measure the changes in parametric maps as an indication of treatment effectiveness. The HSIC-based feature extraction and dissimilarity measure used a kernel function to nonlinearly transform input vectors into a higher dimensional feature space and computed the population means in the new space, where enhanced group separability was ideally obtained. The results of the classification using the developed CAT system indicated an improvement of performance compared to a CAT system with basic features using histogram of intensity.
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King, Stephanie; Vanicek, Natalie; Mockford, Katherine A; Coughlin, Patrick A
2012-10-01
The management of peripheral arterial disease with intermittent claudication includes angioplasty, pharmaceutical therapy, risk factor modification and exercise therapy. Supervised exercise programmes are used sporadically but may improve the distance that an individual with claudication can walk. The purpose of this study was to evaluate the effectiveness of a 3-month supervised exercise programme on improving gait parameters in patients with intermittent claudication. 12 participants were recruited (mean (SD) - age: 67.3 (6.8) years, height: 1.67 (0.09) m, mass: 79.4 (14.0) kg, ankle brachial pressure index: 0.73 (0.17)) from the local vascular unit and enrolled in a supervised exercise programme. Kinematic and kinetic data were collected at the following time points: pain-free walking, initial claudication pain, absolute claudication pain and after a patient-defined rest period. Data were collected before and after the 3-month supervised exercise programme. No significant differences were found in any of the gait parameters post-intervention including pain-free walking speed (P=0.274), peak hip extension (P=0.125), peak ankle plantarflexion (P=0.254), or first vertical ground reaction force peak (P=0.654). No significant gait differences were found across different levels of pain pre- or post-intervention. The lack of improvement post-intervention observed suggests that the current exercise protocol was not tailored to elicit significant improvements in patients with intermittent claudication, specifically. The results indicate that exercise programmes may show improved results post-intervention if they are longer in duration and varied in intensity. Further research into more detailed muscle and biomechanical adaptations is needed to inform exercise programmes specific to this population. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Trends Impacting One Public School Program for Students Who Are Deaf or Hard-of-Hearing
ERIC Educational Resources Information Center
Miller, Kevin J.
2014-01-01
This article reflects on the author's experience supervising a public school program for students who are deaf or hard-of-hearing, specifically addressing national, regional, and local trends affecting it. These trends included teacher efficacy, changes in educational service delivery, advances in technology, the selection of the listening and…
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2008-02-01
It is important that a CNN understands their employer's local policies, procedures and clinical protocols. To enable a CNN to practise, they must be appropriately trained, have clinical supervision and work in partnership with others. A CNN must maintain client confidentiality, and act accordingly with all partnership communications. A CNN has a duty of care to themselves, the clients, colleagues and the employer.
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33 CFR 334.45 - Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine.
Code of Federal Regulations, 2013 CFR
2013-07-01
... Shipyard, naval restricted area, Bath, Maine. 334.45 Section 334.45 Navigation and Navigable Waters CORPS... REGULATIONS § 334.45 Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine. (a) The... and other craft, except those vessels under the supervision or contract to local military or Naval...
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33 CFR 334.45 - Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine.
Code of Federal Regulations, 2012 CFR
2012-07-01
... Shipyard, naval restricted area, Bath, Maine. 334.45 Section 334.45 Navigation and Navigable Waters CORPS... REGULATIONS § 334.45 Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine. (a) The... and other craft, except those vessels under the supervision or contract to local military or Naval...
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33 CFR 334.45 - Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine.
Code of Federal Regulations, 2014 CFR
2014-07-01
... Shipyard, naval restricted area, Bath, Maine. 334.45 Section 334.45 Navigation and Navigable Waters CORPS... REGULATIONS § 334.45 Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine. (a) The... and other craft, except those vessels under the supervision or contract to local military or Naval...
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33 CFR 334.45 - Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine.
Code of Federal Regulations, 2011 CFR
2011-07-01
... Shipyard, naval restricted area, Bath, Maine. 334.45 Section 334.45 Navigation and Navigable Waters CORPS... REGULATIONS § 334.45 Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine. (a) The... and other craft, except those vessels under the supervision or contract to local military or Naval...
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33 CFR 334.45 - Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine.
Code of Federal Regulations, 2010 CFR
2010-07-01
... Shipyard, naval restricted area, Bath, Maine. 334.45 Section 334.45 Navigation and Navigable Waters CORPS... REGULATIONS § 334.45 Kennebec River, Bath Iron Works Shipyard, naval restricted area, Bath, Maine. (a) The... and other craft, except those vessels under the supervision or contract to local military or Naval...
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"Who Has Time for This?" Negotiating Roles in Instructional Supervision and Evaluation
ERIC Educational Resources Information Center
Willis, Chris; Ingle, W. Kyle
2015-01-01
This case examines how school leaders manage the increased demands of a new state-mandated teacher evaluation process. Subject to negotiations, districts and their local teacher unions can allow for teachers to be credentialed and serve as evaluators within their own schools. The challenge is examined through both the opportunity costs of this new…
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26 CFR 53.4958-3 - Definition of disqualified person.
Code of Federal Regulations, 2011 CFR
2011-04-01
... by profession, works part-time at R, a local museum. In the first taxable year in which R employs N, R pays N a salary and provides no additional benefits to N except for free admission to the museum... responsibility for supervising Z's day-to-day operations. For example, E can hire faculty members and staff, make...
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Towards Building Direct Educational Partnership: The Foundation of Shanxi University in 1902
ERIC Educational Resources Information Center
Li, Aisi
2014-01-01
The foundation of Shanxi University is a prime example of the collaborative efforts in higher education between the Chinese and British in late Qing China (1842-1912). Both sides made compromises, with the Chinese adapting their ideas of educational sovereignty, and the British agreeing to work under the supervision of the local government. Such a…
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Choreographing a Life: Kimberly Bolan--Taney Webster Public Library, NY
ERIC Educational Resources Information Center
Library Journal, 2004
2004-01-01
When Kim Taney is not tending 80 workstations on the Webster Public Library's local area network, supervising the pages, working the reference desk, and advising libraries on how to improve teen services, she teaches ballet and choreographs her dance studio's productions. Choreography is a useful skill for someone with such a multifaceted life. As…
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Relocation and the characteristics of hospital and hostel regimes.
Booth, T; Simons, K; Booth, W
1991-01-01
Drawing on evidence from a research evaluation of a local community care programme, this paper explores whether relocation from a British National Health Service mental handicap hospital into local authority hostels (supervised residential facilities) brought about a qualitative change in the residential environment of movers towards less restrictive management practices and caring routines, more responsive attitudes towards their rights and needs as individuals, and greater control over their own lives. The conclusions point to the existence of a substantial measure of overlap in the fundamental characteristics of the hospital and hostel regimes.
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1991-07-01
MTF, or establishing a standard CGR should be done cautiously since health care is a local phenomenon and a number of factors influence (1) the...goals should be formulated locally. That is, each MTF must identify for itself those beneficiaries in its catchment area with billable insurance who...this, managers must know the work they supervise. 8. Drive out fear. Employees should not be afraid to point out problems for fear of argument or being
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Local problems, local solutions: improving tuberculosis control at the district level in Malawi.
Kelly, P. M.
2001-01-01
OBJECTIVE: To examine the causes of a low cure rate at the district level of a tuberculosis (TB) control programme and to formulate, implement, and evaluate an intervention to improve the situation. METHODS: The study setting was Mzuzu (population 60,000), where the annual smear-positive pulmonary TB incidence was 160 per 100,000 and the human immunodeficiency virus (HIV) seroprevalence was 67% among TB patients. There is one TB treatment unit, but several other organizations are involved with TB control. An examination of case-holding activities was carried out, potential areas for improvement were identified, and interventions performed. FINDINGS: In 1990-91, the cure rate was 24% among smear-positive cases (29% among survivors to end of treatment). Problems identified included a fragmented TB control programme; inadequate training and supervision; suboptimal recording of patients' addresses; and nonadherence to national TB control programme protocols. These problems were addressed, and in 1992-93 the cure rate rose to 68% (relative risk (RR) = 2.85 (95% confidence interval (CI) = 1.63, 4.96)) and to 92% among survivors to the end of treatment (RR = 3.12 (95% CI = 1.84, 5.29)). High cure rates are therefore achievable despite high HIV prevalence. CONCLUSIONS: Simple, inexpensive, local programmatic interventions can dramatically improve TB case holding. This study demonstrates the need for evaluation, training, and supervision at all levels of the programme. PMID:11242817
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Takahashi, Masanori; Maruyama, Hitoshi; Shimada, Taro; Kamezaki, Hidehiro; Okabe, Shinichiro; Kanai, Fumihiko; Yoshikawa, Masaharu; Yokosuka, Osamu
2012-11-01
This prospective study was performed in 179 hepatocellular carcinoma (HCC) lesions treated by radio-frequency ablation (RFA) to explore the clinical outcome of "linear enhancement" on contrast-enhanced sonogram. Thirty-three lesions (18.4%) showed linear enhancement, a linear-shaped positive enhancement in the RFA-treated area. Seventeen of them were followed up with no treatment (remaining 16; dropout in eight, additional RFA in six and ineffective treatment in two) and three lesions (3/17, 17.6%) showed local tumor progression corresponding to linear enhancement at 7, 14, 19 months after RFA. Although there was no significant difference in local recurrence rate between the lesions with (3/17) and without linear enhancement (10/35), local tumor progression inside the ablation zone occurred only in the lesions with linear enhancement. In conclusion, linear enhancement inside the RFA-treated area should be followed up within 7 months because it has a risk of local tumor progression. Histology of linear enhancement and its influence on distant recurrence remain to be solved. Copyright © 2012 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
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Adaptive learning in complex reproducing kernel Hilbert spaces employing Wirtinger's subgradients.
Bouboulis, Pantelis; Slavakis, Konstantinos; Theodoridis, Sergios
2012-03-01
This paper presents a wide framework for non-linear online supervised learning tasks in the context of complex valued signal processing. The (complex) input data are mapped into a complex reproducing kernel Hilbert space (RKHS), where the learning phase is taking place. Both pure complex kernels and real kernels (via the complexification trick) can be employed. Moreover, any convex, continuous and not necessarily differentiable function can be used to measure the loss between the output of the specific system and the desired response. The only requirement is the subgradient of the adopted loss function to be available in an analytic form. In order to derive analytically the subgradients, the principles of the (recently developed) Wirtinger's calculus in complex RKHS are exploited. Furthermore, both linear and widely linear (in RKHS) estimation filters are considered. To cope with the problem of increasing memory requirements, which is present in almost all online schemes in RKHS, the sparsification scheme, based on projection onto closed balls, has been adopted. We demonstrate the effectiveness of the proposed framework in a non-linear channel identification task, a non-linear channel equalization problem and a quadrature phase shift keying equalization scheme, using both circular and non circular synthetic signal sources.
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Variable Star Signature Classification using Slotted Symbolic Markov Modeling
NASA Astrophysics Data System (ADS)
Johnston, K. B.; Peter, A. M.
2017-01-01
With the advent of digital astronomy, new benefits and new challenges have been presented to the modern day astronomer. No longer can the astronomer rely on manual processing, instead the profession as a whole has begun to adopt more advanced computational means. This paper focuses on the construction and application of a novel time-domain signature extraction methodology and the development of a supporting supervised pattern classification algorithm for the identification of variable stars. A methodology for the reduction of stellar variable observations (time-domain data) into a novel feature space representation is introduced. The methodology presented will be referred to as Slotted Symbolic Markov Modeling (SSMM) and has a number of advantages which will be demonstrated to be beneficial; specifically to the supervised classification of stellar variables. It will be shown that the methodology outperformed a baseline standard methodology on a standardized set of stellar light curve data. The performance on a set of data derived from the LINEAR dataset will also be shown.
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Variable Star Signature Classification using Slotted Symbolic Markov Modeling
NASA Astrophysics Data System (ADS)
Johnston, Kyle B.; Peter, Adrian M.
2016-01-01
With the advent of digital astronomy, new benefits and new challenges have been presented to the modern day astronomer. No longer can the astronomer rely on manual processing, instead the profession as a whole has begun to adopt more advanced computational means. Our research focuses on the construction and application of a novel time-domain signature extraction methodology and the development of a supporting supervised pattern classification algorithm for the identification of variable stars. A methodology for the reduction of stellar variable observations (time-domain data) into a novel feature space representation is introduced. The methodology presented will be referred to as Slotted Symbolic Markov Modeling (SSMM) and has a number of advantages which will be demonstrated to be beneficial; specifically to the supervised classification of stellar variables. It will be shown that the methodology outperformed a baseline standard methodology on a standardized set of stellar light curve data. The performance on a set of data derived from the LINEAR dataset will also be shown.
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Subsampled Hessian Newton Methods for Supervised Learning.
Wang, Chien-Chih; Huang, Chun-Heng; Lin, Chih-Jen
2015-08-01
Newton methods can be applied in many supervised learning approaches. However, for large-scale data, the use of the whole Hessian matrix can be time-consuming. Recently, subsampled Newton methods have been proposed to reduce the computational time by using only a subset of data for calculating an approximation of the Hessian matrix. Unfortunately, we find that in some situations, the running speed is worse than the standard Newton method because cheaper but less accurate search directions are used. In this work, we propose some novel techniques to improve the existing subsampled Hessian Newton method. The main idea is to solve a two-dimensional subproblem per iteration to adjust the search direction to better minimize the second-order approximation of the function value. We prove the theoretical convergence of the proposed method. Experiments on logistic regression, linear SVM, maximum entropy, and deep networks indicate that our techniques significantly reduce the running time of the subsampled Hessian Newton method. The resulting algorithm becomes a compelling alternative to the standard Newton method for large-scale data classification.
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Dissecting psychiatric spectrum disorders by generative embedding☆☆☆
Brodersen, Kay H.; Deserno, Lorenz; Schlagenhauf, Florian; Lin, Zhihao; Penny, Will D.; Buhmann, Joachim M.; Stephan, Klaas E.
2013-01-01
This proof-of-concept study examines the feasibility of defining subgroups in psychiatric spectrum disorders by generative embedding, using dynamical system models which infer neuronal circuit mechanisms from neuroimaging data. To this end, we re-analysed an fMRI dataset of 41 patients diagnosed with schizophrenia and 42 healthy controls performing a numerical n-back working-memory task. In our generative-embedding approach, we used parameter estimates from a dynamic causal model (DCM) of a visual–parietal–prefrontal network to define a model-based feature space for the subsequent application of supervised and unsupervised learning techniques. First, using a linear support vector machine for classification, we were able to predict individual diagnostic labels significantly more accurately (78%) from DCM-based effective connectivity estimates than from functional connectivity between (62%) or local activity within the same regions (55%). Second, an unsupervised approach based on variational Bayesian Gaussian mixture modelling provided evidence for two clusters which mapped onto patients and controls with nearly the same accuracy (71%) as the supervised approach. Finally, when restricting the analysis only to the patients, Gaussian mixture modelling suggested the existence of three patient subgroups, each of which was characterised by a different architecture of the visual–parietal–prefrontal working-memory network. Critically, even though this analysis did not have access to information about the patients' clinical symptoms, the three neurophysiologically defined subgroups mapped onto three clinically distinct subgroups, distinguished by significant differences in negative symptom severity, as assessed on the Positive and Negative Syndrome Scale (PANSS). In summary, this study provides a concrete example of how psychiatric spectrum diseases may be split into subgroups that are defined in terms of neurophysiological mechanisms specified by a generative model of network dynamics such as DCM. The results corroborate our previous findings in stroke patients that generative embedding, compared to analyses of more conventional measures such as functional connectivity or regional activity, can significantly enhance both the interpretability and performance of computational approaches to clinical classification. PMID:24363992
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Robust linear discriminant analysis with distance based estimators
NASA Astrophysics Data System (ADS)
Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina
2017-11-01
Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.
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Su, Hang; Yin, Zhaozheng; Huh, Seungil; Kanade, Takeo
2013-10-01
Phase-contrast microscopy is one of the most common and convenient imaging modalities to observe long-term multi-cellular processes, which generates images by the interference of lights passing through transparent specimens and background medium with different retarded phases. Despite many years of study, computer-aided phase contrast microscopy analysis on cell behavior is challenged by image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose (1) a phase contrast microscopy image restoration method that produces phase retardation features, which are intrinsic features of phase contrast microscopy, and (2) a semi-supervised learning based algorithm for cell segmentation, which is a fundamental task for various cell behavior analysis. Specifically, the image formation process of phase contrast microscopy images is first computationally modeled with a dictionary of diffraction patterns; as a result, each pixel of a phase contrast microscopy image is represented by a linear combination of the bases, which we call phase retardation features. Images are then partitioned into phase-homogeneous atoms by clustering neighboring pixels with similar phase retardation features. Consequently, cell segmentation is performed via a semi-supervised classification technique over the phase-homogeneous atoms. Experiments demonstrate that the proposed approach produces quality segmentation of individual cells and outperforms previous approaches. Copyright © 2013 Elsevier B.V. All rights reserved.
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Kawaguchi, Atsushi; Yamashita, Fumio
2017-10-01
This article proposes a procedure for describing the relationship between high-dimensional data sets, such as multimodal brain images and genetic data. We propose a supervised technique to incorporate the clinical outcome to determine a score, which is a linear combination of variables with hieratical structures to multimodalities. This approach is expected to obtain interpretable and predictive scores. The proposed method was applied to a study of Alzheimer's disease (AD). We propose a diagnostic method for AD that involves using whole-brain magnetic resonance imaging (MRI) and positron emission tomography (PET), and we select effective brain regions for the diagnostic probability and investigate the genome-wide association with the regions using single nucleotide polymorphisms (SNPs). The two-step dimension reduction method, which we previously introduced, was considered applicable to such a study and allows us to partially incorporate the proposed method. We show that the proposed method offers classification functions with feasibility and reasonable prediction accuracy based on the receiver operating characteristic (ROC) analysis and reasonable regions of the brain and genomes. Our simulation study based on the synthetic structured data set showed that the proposed method outperformed the original method and provided the characteristic for the supervised feature. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Remote Supervision and Control of Air Conditioning Systems in Different Modes
NASA Astrophysics Data System (ADS)
Rafeeq, Mohammed; Afzal, Asif; Rajendra, Sree
2018-01-01
In the era of automation, most of the application of engineering and science are interrelated with system for optimal operation. To get the efficient result of an operation and desired response, interconnected systems should be controlled by directing, regulating and commanding. Here, air conditioning (AC) system is considered for experimentation, to supervise and control its functioning in both, automated and manual mode. This paper reports the work intended to design and develop an automated and manual AC system working in remote and local mode, to increase the level of comfort, easy operation, reducing human intervention and faults occurring in the system. The Programmable Logical Controller (PLC) and Supervisory Control and Data Acquisition (SCADA) system were used for remote supervision and monitoring of AC systems using series ninety protocol and remote terminal unit modbus protocol as communication module to operate in remote mode. PLC was used as remote terminal for continuous supervision and control of AC system. SCADA software was used as a tool for designing user friendly graphical user interface. The proposed SCADA AC system successfully monitors and controls in accordance within the parameter limits like temperature, pressure, humidity and voltage. With all the features, this designed system is capable of efficient handling of the resources like the compressor, humidifier etc., with all the levels of safety and durability. This system also maintains the temperature and controls the humidity of the remote location and also looks after the health of the compressor.
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Das, Samarjit; Amoedo, Breogan; De la Torre, Fernando; Hodgins, Jessica
2012-01-01
In this paper, we propose to use a weakly supervised machine learning framework for automatic detection of Parkinson's Disease motor symptoms in daily living environments. Our primary goal is to develop a monitoring system capable of being used outside of controlled laboratory settings. Such a system would enable us to track medication cycles at home and provide valuable clinical feedback. Most of the relevant prior works involve supervised learning frameworks (e.g., Support Vector Machines). However, in-home monitoring provides only coarse ground truth information about symptom occurrences, making it very hard to adapt and train supervised learning classifiers for symptom detection. We address this challenge by formulating symptom detection under incomplete ground truth information as a multiple instance learning (MIL) problem. MIL is a weakly supervised learning framework that does not require exact instances of symptom occurrences for training; rather, it learns from approximate time intervals within which a symptom might or might not have occurred on a given day. Once trained, the MIL detector was able to spot symptom-prone time windows on other days and approximately localize the symptom instances. We monitored two Parkinson's disease (PD) patients, each for four days with a set of five triaxial accelerometers and utilized a MIL algorithm based on axis parallel rectangle (APR) fitting in the feature space. We were able to detect subject specific symptoms (e.g. dyskinesia) that conformed with a daily log maintained by the patients.
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Cernuda, Carlos; Lughofer, Edwin; Klein, Helmut; Forster, Clemens; Pawliczek, Marcin; Brandstetter, Markus
2017-01-01
During the production process of beer, it is of utmost importance to guarantee a high consistency of the beer quality. For instance, the bitterness is an essential quality parameter which has to be controlled within the specifications at the beginning of the production process in the unfermented beer (wort) as well as in final products such as beer and beer mix beverages. Nowadays, analytical techniques for quality control in beer production are mainly based on manual supervision, i.e., samples are taken from the process and analyzed in the laboratory. This typically requires significant lab technicians efforts for only a small fraction of samples to be analyzed, which leads to significant costs for beer breweries and companies. Fourier transform mid-infrared (FT-MIR) spectroscopy was used in combination with nonlinear multivariate calibration techniques to overcome (i) the time consuming off-line analyses in beer production and (ii) already known limitations of standard linear chemometric methods, like partial least squares (PLS), for important quality parameters Speers et al. (J I Brewing. 2003;109(3):229-235), Zhang et al. (J I Brewing. 2012;118(4):361-367) such as bitterness, citric acid, total acids, free amino nitrogen, final attenuation, or foam stability. The calibration models are established with enhanced nonlinear techniques based (i) on a new piece-wise linear version of PLS by employing fuzzy rules for local partitioning the latent variable space and (ii) on extensions of support vector regression variants (-PLSSVR and ν-PLSSVR), for overcoming high computation times in high-dimensional problems and time-intensive and inappropriate settings of the kernel parameters. Furthermore, we introduce a new model selection scheme based on bagged ensembles in order to improve robustness and thus predictive quality of the final models. The approaches are tested on real-world calibration data sets for wort and beer mix beverages, and successfully compared to linear methods, showing a clear out-performance in most cases and being able to meet the model quality requirements defined by the experts at the beer company. Figure Workflow for calibration of non-Linear model ensembles from FT-MIR spectra in beer production .
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Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen
2017-01-01
An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.
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On the Implementation of a Land Cover Classification System for SAR Images Using Khoros
NASA Technical Reports Server (NTRS)
Medina Revera, Edwin J.; Espinosa, Ramon Vasquez
1997-01-01
The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.
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NASA Technical Reports Server (NTRS)
Paradella, W. R. (Principal Investigator); Vitorello, I.; Monteiro, M. D.
1984-01-01
Enhancement techniques and thematic classifications were applied to the metasediments of Bambui Super Group (Upper Proterozoic) in the Region of Serra do Ramalho, SW of the state of Bahia. Linear contrast stretch, band-ratios with contrast stretch, and color-composites allow lithological discriminations. The effects of human activities and of vegetation cover mask and limit, in several ways, the lithological discrimination with digital MSS data. Principal component images and color composite of linear contrast stretch of these products, show lithological discrimination through tonal gradations. This set of products allows the delineations of several metasedimentary sequences to a level superior to reconnaissance mapping. Supervised (maximum likelihood classifier) and nonsupervised (K-Means classifier) classification of the limestone sequence, host to fluorite mineralization show satisfactory results.
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ERIC Educational Resources Information Center
Steffes, Tracy L.
2008-01-01
In 1918, Minnesota county superintendent Julius Arp argued that the greatest educational problem facing the American people was the Rural School Problem, saying: "There is no defect more glaring today than the inequality that exists between the educational facilities of the urban and rural communities. Rural education in the United States has…
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The Market, the Media and the Family in a School Excursion Rape Case
ERIC Educational Resources Information Center
Gannon, Susanne
2007-01-01
This paper examines a local and specific instance of the effects of neoliberal markets on individual and institutional subjects of schooling. It reviews a court case between a prestigious private girls' school and an ex-student who sued the school for failing to provide adequate supervision on a school trip to Europe during which she was raped. It…
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NASA Astrophysics Data System (ADS)
Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz
2015-10-01
In this paper, a new Spectral-Unmixing-based approach, using Nonnegative Matrix Factorization (NMF), is proposed to locally multi-sharpen hyperspectral data by integrating a Digital Surface Model (DSM) obtained from LIDAR data. In this new approach, the nature of the local mixing model is detected by using the local variance of the object elevations. The hyper/multispectral images are explored using small zones. In each zone, the variance of the object elevations is calculated from the DSM data in this zone. This variance is compared to a threshold value and the adequate linear/linearquadratic spectral unmixing technique is used in the considered zone to independently unmix hyperspectral and multispectral data, using an adequate linear/linear-quadratic NMF-based approach. The obtained spectral and spatial information thus respectively extracted from the hyper/multispectral images are then recombined in the considered zone, according to the selected mixing model. Experiments based on synthetic hyper/multispectral data are carried out to evaluate the performance of the proposed multi-sharpening approach and literature linear/linear-quadratic approaches used on the whole hyper/multispectral data. In these experiments, real DSM data are used to generate synthetic data containing linear and linear-quadratic mixed pixel zones. The DSM data are also used for locally detecting the nature of the mixing model in the proposed approach. Globally, the proposed approach yields good spatial and spectral fidelities for the multi-sharpened data and significantly outperforms the used literature methods.
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Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets
NASA Astrophysics Data System (ADS)
Kim, S. K.; Prabhat, M.; Williams, D. N.
2017-12-01
Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.
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Is the local linearity of space-time inherited from the linearity of probabilities?
NASA Astrophysics Data System (ADS)
Müller, Markus P.; Carrozza, Sylvain; Höhn, Philipp A.
2017-02-01
The appearance of linear spaces, describing physical quantities by vectors and tensors, is ubiquitous in all of physics, from classical mechanics to the modern notion of local Lorentz invariance. However, as natural as this seems to the physicist, most computer scientists would argue that something like a ‘local linear tangent space’ is not very typical and in fact a quite surprising property of any conceivable world or algorithm. In this paper, we take the perspective of the computer scientist seriously, and ask whether there could be any inherently information-theoretic reason to expect this notion of linearity to appear in physics. We give a series of simple arguments, spanning quantum information theory, group representation theory, and renormalization in quantum gravity, that supports a surprising thesis: namely, that the local linearity of space-time might ultimately be a consequence of the linearity of probabilities. While our arguments involve a fair amount of speculation, they have the virtue of being independent of any detailed assumptions on quantum gravity, and they are in harmony with several independent recent ideas on emergent space-time in high-energy physics.
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Feature weight estimation for gene selection: a local hyperlinear learning approach
2014-01-01
Background Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried in high-dimensional irrelevant noises. RELIEF is a popular and widely used approach for feature selection owing to its low computational cost and high accuracy. However, RELIEF based methods suffer from instability, especially in the presence of noisy and/or high-dimensional outliers. Results We propose an innovative feature weighting algorithm, called LHR, to select informative genes from highly noisy data. LHR is based on RELIEF for feature weighting using classical margin maximization. The key idea of LHR is to estimate the feature weights through local approximation rather than global measurement, which is typically used in existing methods. The weights obtained by our method are very robust in terms of degradation of noisy features, even those with vast dimensions. To demonstrate the performance of our method, extensive experiments involving classification tests have been carried out on both synthetic and real microarray benchmark datasets by combining the proposed technique with standard classifiers, including the support vector machine (SVM), k-nearest neighbor (KNN), hyperplane k-nearest neighbor (HKNN), linear discriminant analysis (LDA) and naive Bayes (NB). Conclusion Experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed feature selection method combined with supervised learning in three aspects: 1) high classification accuracy, 2) excellent robustness to noise and 3) good stability using to various classification algorithms. PMID:24625071
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Spatial Systems Lipidomics Reveals Nonalcoholic Fatty Liver Disease Heterogeneity
2018-01-01
Hepatocellular lipid accumulation characterizes nonalcoholic fatty liver disease (NAFLD). However, the types of lipids associated with disease progression are debated, as is the impact of their localization. Traditional lipidomics analysis using liver homogenates or plasma dilutes and averages lipid concentrations, and does not provide spatial information about lipid distribution. We aimed to characterize the distribution of specific lipid species related to NAFLD severity by performing label-free molecular analysis by mass spectrometry imaging (MSI). Fresh frozen liver biopsies from obese subjects undergoing bariatric surgery (n = 23) with various degrees of NAFLD were cryosectioned and analyzed by matrix-assisted laser desorption/ionization (MALDI)-MSI. Molecular identification was verified by tandem MS. Tissue sections were histopathologically stained, annotated according to the Kleiner classification, and coregistered with the MSI data set. Lipid pathway analysis was performed and linked to local proteome networks. Spatially resolved lipid profiles showed pronounced differences between nonsteatotic and steatotic tissues. Lipid identification and network analyses revealed phosphatidylinositols and arachidonic acid metabolism in nonsteatotic regions, whereas low–density lipoprotein (LDL) and very low–density lipoprotein (VLDL) metabolism was associated with steatotic tissue. Supervised and unsupervised discriminant analysis using lipid based classifiers outperformed simulated analysis of liver tissue homogenates in predicting steatosis severity. We conclude that lipid composition of steatotic and nonsteatotic tissue is highly distinct, implying that spatial context is important for understanding the mechanisms of lipid accumulation in NAFLD. MSI combined with principal component–linear discriminant analysis linking lipid and protein pathways represents a novel tool enabling detailed, comprehensive studies of the heterogeneity of NAFLD. PMID:29570976
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Time-dependent grid adaptation for meshes of triangles and tetrahedra
NASA Technical Reports Server (NTRS)
Rausch, Russ D.
1993-01-01
This paper presents in viewgraph form a method of optimizing grid generation for unsteady CFD flow calculations that distributes the numerical error evenly throughout the mesh. Adaptive meshing is used to locally enrich in regions of relatively large errors and to locally coarsen in regions of relatively small errors. The enrichment/coarsening procedures are robust for isotropic cells; however, enrichment of high aspect ratio cells may fail near boundary surfaces with relatively large curvature. The enrichment indicator worked well for the cases shown, but in general requires user supervision for a more efficient solution.
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Prakash, J; Srinivasan, K
2009-07-01
In this paper, the authors have represented the nonlinear system as a family of local linear state space models, local PID controllers have been designed on the basis of linear models, and the weighted sum of the output from the local PID controllers (Nonlinear PID controller) has been used to control the nonlinear process. Further, Nonlinear Model Predictive Controller using the family of local linear state space models (F-NMPC) has been developed. The effectiveness of the proposed control schemes has been demonstrated on a CSTR process, which exhibits dynamic nonlinearity.
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ERIC Educational Resources Information Center
Sinecka, Jitka
2009-01-01
This dissertation is a qualitative research study of two people labeled with developmental disabilities who live in residential settings with various supports provided by local agencies. Scott is 43 years old and lives in a Residential Supported Home with four other housemates and permanent staff support and supervision. Pat is 29 years old and…
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(abstract) An Ada Language Modular Telerobot Task Execution System
NASA Technical Reports Server (NTRS)
Backes, Paul; Long, Mark; Steele, Robert
1993-01-01
A telerobotic task execution system is described which has been developed for space flight applications. The Modular Telerobot Task Execution System (MOTES) provides the remote site task execution capability in a local-remote telerobotic system. The system provides supervised autonomous control, shared control, and teleoperation for a redundant manipulator. The system is capable of nominal task execution as well as monitoring and reflex motion.
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Dynamical localization of coupled relativistic kicked rotors
NASA Astrophysics Data System (ADS)
Rozenbaum, Efim B.; Galitski, Victor
2017-02-01
A periodically driven rotor is a prototypical model that exhibits a transition to chaos in the classical regime and dynamical localization (related to Anderson localization) in the quantum regime. In a recent work [Phys. Rev. B 94, 085120 (2016), 10.1103/PhysRevB.94.085120], A. C. Keser et al. considered a many-body generalization of coupled quantum kicked rotors, and showed that in the special integrable linear case, dynamical localization survives interactions. By analogy with many-body localization, the phenomenon was dubbed dynamical many-body localization. In the present work, we study nonintegrable models of single and coupled quantum relativistic kicked rotors (QRKRs) that bridge the gap between the conventional quadratic rotors and the integrable linear models. For a single QRKR, we supplement the recent analysis of the angular-momentum-space dynamics with a study of the spin dynamics. Our analysis of two and three coupled QRKRs along with the proved localization in the many-body linear model indicate that dynamical localization exists in few-body systems. Moreover, the relation between QRKR and linear rotor models implies that dynamical many-body localization can exist in generic, nonintegrable many-body systems. And localization can generally result from a complicated interplay between Anderson mechanism and limiting integrability, since the many-body linear model is a high-angular-momentum limit of many-body QRKRs. We also analyze the dynamics of two coupled QRKRs in the highly unusual superballistic regime and find that the resonance conditions are relaxed due to interactions. Finally, we propose experimental realizations of the QRKR model in cold atoms in optical lattices.
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Shultz, Laura A Schwent; Pedersen, Heather A; Roper, Brad L; Rey-Casserly, Celiane
2014-01-01
Within the psychology supervision literature, most theoretical models and practices pertain to general clinical or counseling psychology. Supervision specific to clinical neuropsychology has garnered little attention. This survey study explores supervision training, practices, and perspectives of neuropsychology supervisors. Practicing neuropsychologists were invited to participate in an online survey via listservs and email lists. Of 451 respondents, 382 provided supervision to students, interns, and/or fellows in settings such as VA medical centers (37%), university medical centers (35%), and private practice (15%). Most supervisors (84%) reported supervision was discussed in graduate school "minimally" or "not at all." Although 67% completed informal didactics or received continuing education in supervision, only 27% reported receiving training specific to neuropsychology supervision. Notably, only 39% were satisfied with their training in providing supervision and 77% indicated they would likely participate in training in providing supervision, if available at professional conferences. Results indicate that clinical neuropsychology as a specialty has paid scant attention to developing supervision models and explicit training in supervision skills. We recommend that the specialty develop models of supervision for neuropsychological practice, supervision standards and competencies, training methods in provision of supervision, and benchmark measures for supervision competencies.
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Rotheram-Borus, Mary Jane; Le Roux, Karl; Le Roux, Ingrid M; Christodoulou, Joan; Laurenzi, Christina; Mbewu, Nokwanele; Tomlinson, Mark
2017-08-07
Concurrent epidemics of HIV, depression, alcohol abuse, and partner violence threaten maternal and child health (MCH) in South Africa. Although home visiting has been repeatedly demonstrated efficacious in research evaluations, efficacy disappears when programs are scaled broadly. In this cluster randomized controlled trial (RCT), we examine whether the benefits of ongoing accountability and supervision within an existing government funded and implemented community health workers (CHW) home visiting program ensure the effectiveness of home visiting. In the deeply rural, Eastern Cape of South Africa, CHW will be hired by the government and will be initially trained by the Philani Programme to conduct home visits with all pregnant mothers and their children until the children are 2 years old. Eight clinics will be randomized to receive either (1) the Accountable Care Condition in which additional monitoring and accountability systems that Philani routinely uses are implemented (4 clinics, 16 CHW, 450 households); or (2) a Standard Care Condition of initial Philani training, but with supervision and monitoring being delivered by local government structures and systems (4 clinics, 21 CHW, 450 households). In the Accountable Care Condition areas, the CHW's mobile phone reports, which are time-location stamped, will be monitored and data-informed supervision will be provided, as well as monitoring growth, medical adherence, mental health, and alcohol use outcomes. Interviewers will independently assess outcomes at pregnancy at 3, 6, 15, and 24 months post-birth. The primary outcome will be a composite score of documenting maternal HIV/TB testing, linkage to care, treatment adherence and retention, as well as child physical growth, cognitive functioning, and child behavior and developmental milestones. The proposed cluster RCT will evaluate whether routinely implementing supervision and accountability procedures and monitoring CHWs' over time will improve MCH outcomes over the first 2 years of life. ClinicalTrials.gov registration #NCT02957799 , registered on October 26, 2016.
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28 CFR 2.206 - Travel approval and transfers of supervision.
Code of Federal Regulations, 2010 CFR
2010-07-01
... supervision. 2.206 Section 2.206 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION... Supervised Releasees § 2.206 Travel approval and transfers of supervision. (a) A releasee's supervision officer may approve travel outside the district of supervision without approval of the Commission in the...
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28 CFR 2.206 - Travel approval and transfers of supervision.
Code of Federal Regulations, 2011 CFR
2011-07-01
... supervision. 2.206 Section 2.206 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION... Supervised Releasees § 2.206 Travel approval and transfers of supervision. (a) A releasee's supervision officer may approve travel outside the district of supervision without approval of the Commission in the...
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28 CFR 2.206 - Travel approval and transfers of supervision.
Code of Federal Regulations, 2013 CFR
2013-07-01
... supervision. 2.206 Section 2.206 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION... Supervised Releasees § 2.206 Travel approval and transfers of supervision. (a) A releasee's supervision officer may approve travel outside the district of supervision without approval of the Commission in the...
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Local Linear Observed-Score Equating
ERIC Educational Resources Information Center
Wiberg, Marie; van der Linden, Wim J.
2011-01-01
Two methods of local linear observed-score equating for use with anchor-test and single-group designs are introduced. In an empirical study, the two methods were compared with the current traditional linear methods for observed-score equating. As a criterion, the bias in the equated scores relative to true equating based on Lord's (1980)…
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Predictive Model of Linear Antimicrobial Peptides Active against Gram-Negative Bacteria.
Vishnepolsky, Boris; Gabrielian, Andrei; Rosenthal, Alex; Hurt, Darrell E; Tartakovsky, Michael; Managadze, Grigol; Grigolava, Maya; Makhatadze, George I; Pirtskhalava, Malak
2018-05-29
Antimicrobial peptides (AMPs) have been identified as a potential new class of anti-infectives for drug development. There are a lot of computational methods that try to predict AMPs. Most of them can only predict if a peptide will show any antimicrobial potency, but to the best of our knowledge, there are no tools which can predict antimicrobial potency against particular strains. Here we present a predictive model of linear AMPs being active against particular Gram-negative strains relying on a semi-supervised machine-learning approach with a density-based clustering algorithm. The algorithm can well distinguish peptides active against particular strains from others which may also be active but not against the considered strain. The available AMP prediction tools cannot carry out this task. The prediction tool based on the algorithm suggested herein is available on https://dbaasp.org.
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Unusual self-electrocution simulating judicial electrocution by an adolescent.
Murty, O P
2008-06-01
Electrocution is one of the rarest modes of suicide. In this case, one school going adolescent committed suicide by electrocution using bare electric wire. This is a rare case of suicidal death by applying live wires around the wrists, simulating the act of judicial electrocution. He positioned himself on armed chair and placed the nude wire loops from a cable around both wrists and switched on the current by plugging in to nearest socket by foot. There were linear electric contact wounds completely encircling around the both wrists. In addition to these linear electric burns all around wrists, there were electrical burns over both hands. This death highlights the need of supervision and close watch on children for self-destructing activities and behavior. This case also highlights unusual method adopted by adolescent to end his life.
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The relationship between unsupervised time after school and physical activity in adolescent girls.
Rushovich, Berenice R; Voorhees, Carolyn C; Davis, C E; Neumark-Sztainer, Dianne; Pfeiffer, Karin A; Elder, John P; Going, Scott; Marino, Vivian G
2006-07-31
Rising obesity and declining physical activity levels are of great concern because of the associated health risks. Many children are left unsupervised after the school day ends, but little is known about the association between unsupervised time and physical activity levels. This paper seeks to determine whether adolescent girls who are without adult supervision after school are more or less active than their peers who have a caregiver at home. A random sample of girls from 36 middle schools at 6 field sites across the U.S. was selected during the fall of the 2002-2003 school year to participate in the baseline measurement activities of the Trial of Activity for Adolescent Girls (TAAG). Information was collected using six-day objectively measured physical activity, self-reported physical activity using a three-day recall, and socioeconomic and psychosocial measures. Complete information was available for 1422 out of a total of 1596 respondents.Categorical variables were analyzed using chi square and continuous variables were analyzed by t-tests. The four categories of time alone were compared using a mixed linear model controlling for clustering effects by study center. Girls who spent more time after school (> or = 2 hours per day, > or = 2 days per week) without adult supervision were more active than those with adult supervision (p = 0.01). Girls alone for > or = 2 hours after school, > or = 2 days a week, on average accrue 7.55 minutes more moderate to vigorous physical activity (MVPA) per day than do girls who are supervised (95% confidence interval ([C.I]). These results adjusted for ethnicity, parent's education, participation in the free/reduced lunch program, neighborhood resources, or available transportation. Unsupervised girls (n = 279) did less homework (53.1% vs. 63.3%), spent less time riding in a car or bus (48.0% vs. 56.6%), talked on the phone more (35.5% vs. 21.1%), and watched more television (59.9% vs. 52.6%) than supervised girls (n = 569). However, unsupervised girls also were more likely to be dancing (14.0% vs. 9.3%) and listening to music (20.8% vs. 12.0%) (p < .05). Girls in an unsupervised environment engaged in fewer structured activities and did not immediately do their homework, but they were more likely to be physically active than supervised girls. These results may have implications for parents, school, and community agencies as to how to structure activities in order to encourage teenage girls to be more physically active.
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The relationship between unsupervised time after school and physical activity in adolescent girls
Rushovich, Berenice R; Voorhees, Carolyn C; Davis, CE; Neumark-Sztainer, Dianne; Pfeiffer, Karin A; Elder, John P; Going, Scott; Marino, Vivian G
2006-01-01
Background Rising obesity and declining physical activity levels are of great concern because of the associated health risks. Many children are left unsupervised after the school day ends, but little is known about the association between unsupervised time and physical activity levels. This paper seeks to determine whether adolescent girls who are without adult supervision after school are more or less active than their peers who have a caregiver at home. Methods A random sample of girls from 36 middle schools at 6 field sites across the U.S. was selected during the fall of the 2002–2003 school year to participate in the baseline measurement activities of the Trial of Activity for Adolescent Girls (TAAG). Information was collected using six-day objectively measured physical activity, self-reported physical activity using a three-day recall, and socioeconomic and psychosocial measures. Complete information was available for 1422 out of a total of 1596 respondents. Categorical variables were analyzed using chi square and continuous variables were analyzed by t-tests. The four categories of time alone were compared using a mixed linear model controlling for clustering effects by study center. Results Girls who spent more time after school (≥2 hours per day, ≥2 days per week) without adult supervision were more active than those with adult supervision (p = 0.01). Girls alone for ≥2 hours after school, ≥2 days a week, on average accrue 7.55 minutes more moderate to vigorous physical activity (MVPA) per day than do girls who are supervised (95% confidence interval ([C.I]). These results adjusted for ethnicity, parent's education, participation in the free/reduced lunch program, neighborhood resources, or available transportation. Unsupervised girls (n = 279) did less homework (53.1% vs. 63.3%), spent less time riding in a car or bus (48.0% vs. 56.6%), talked on the phone more (35.5% vs. 21.1%), and watched more television (59.9% vs. 52.6%) than supervised girls (n = 569). However, unsupervised girls also were more likely to be dancing (14.0% vs. 9.3%) and listening to music (20.8% vs. 12.0%) (p < .05). Conclusion Girls in an unsupervised environment engaged in fewer structured activities and did not immediately do their homework, but they were more likely to be physically active than supervised girls. These results may have implications for parents, school, and community agencies as to how to structure activities in order to encourage teenage girls to be more physically active. PMID:16879750
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Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam
2009-01-01
This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.
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Carlin, Charles H.; Milam, Jennifer L.; Carlin, Emily L.; Owen, Ashley
2012-01-01
E-supervision has a potential role in addressing speech-language personnel shortages in rural and difficult to staff school districts. The purposes of this article are twofold: to determine how e-supervision might support graduate speech-language pathologist (SLP) interns placed in rural, remote, and difficult to staff public school districts; and, to investigate interns’ perceptions of in-person supervision compared to e-supervision. The study used a mixed methodology approach and collected data from surveys, supervision documents and records, and interviews. The results showed the use of e-supervision allowed graduate SLP interns to be adequately supervised across a variety of clients and professional activities in a manner that was similar to in-person supervision. Further, e-supervision was perceived as a more convenient and less stressful supervision format when compared to in-person supervision. Other findings are discussed and implications and limitations provided. PMID:25945201
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McCarron, R H; Eade, J; Delmage, E
2018-04-01
WHAT IS KNOWN ON THE SUBJECT?: Regular and effective clinical supervision for mental health nurses and healthcare assistants (HCAs) is an important tool in helping to reduce stress and burnout, and in ensuring safe, effective and high-quality mental health care. Previous studies of clinical supervision within secure mental health environments have found both a low availability of clinical supervision, and a low level of staff acceptance of its value, particularly for HCAs. WHAT DOES THIS PAPER ADD TO EXISTING KNOWLEDGE?: In previous studies, the understanding shown by HCAs and nurses around the benefits of clinical supervision may have been limited by the methods used. This study was specifically designed to help them best express their views. In contrast to previous studies, both nurses and HCAs showed a good understanding of the function and value of clinical supervision. Significant improvements in the experience of, and access to, clinical supervision for nurses and HCAs working in secure mental health services may be achieved by raising staff awareness, demonstrating organizational support and increasing monitoring of clinical supervision. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Organizations should consider reviewing their approach to supervision to include raising staff awareness, multidisciplinary supervision, group supervision, and recording and tracking of supervision rates. Organizations should be mindful of the need to provide effective clinical supervision to HCAs as well as nurses. Introduction Studies have found a low availability and appreciation of clinical supervision, especially for healthcare assistants (HCAs). Qualitative research is needed to further understand this. Aims Increase understanding of nurses' and HCAs' experiences of, and access to, clinical supervision. Identify nurses' and HCAs' perceptions of the value and function of clinical supervision. Assess how interventions affect staff's experiences of clinical supervision. Methods In 2013, HCAs and nurses in a secure adolescent service were surveyed about clinical supervision. Forty-nine HCAs and 20 nurses responded. In 2014, interventions to facilitate supervision were introduced. In 2016, the study was repeated. Forty HCAs and 30 nurses responded. Responses were analysed using a mixed methods approach. Results Significantly more HCAs found supervision to be a positive experience in 2016, and both nurses and HCAs reported significantly fewer challenges in accessing supervision. HCAs and nurses understood the value of clinical supervision. Discussion Significant improvements in the experience of clinical supervision were achieved following increased staff awareness, multidisciplinary and group supervision, and recording supervision rates. HCAs and nurses understood the consequences of inadequate supervision. Implications for practice Organizations could adopt the interventions to facilitate clinical supervision. Supervision should not be overlooked for HCAs. © 2017 John Wiley & Sons Ltd.
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Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.
Choi, Jae-Seok; Kim, Munchurl
2017-03-01
Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.
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An Approach to Supervision for Doctoral and Entry-Level Group Counseling Students
ERIC Educational Resources Information Center
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.…
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Spectral Learning for Supervised Topic Models.
Ren, Yong; Wang, Yining; Zhu, Jun
2018-03-01
Supervised topic models simultaneously model the latent topic structure of large collections of documents and a response variable associated with each document. Existing inference methods are based on variational approximation or Monte Carlo sampling, which often suffers from the local minimum defect. Spectral methods have been applied to learn unsupervised topic models, such as latent Dirichlet allocation (LDA), with provable guarantees. This paper investigates the possibility of applying spectral methods to recover the parameters of supervised LDA (sLDA). We first present a two-stage spectral method, which recovers the parameters of LDA followed by a power update method to recover the regression model parameters. Then, we further present a single-phase spectral algorithm to jointly recover the topic distribution matrix as well as the regression weights. Our spectral algorithms are provably correct and computationally efficient. We prove a sample complexity bound for each algorithm and subsequently derive a sufficient condition for the identifiability of sLDA. Thorough experiments on synthetic and real-world datasets verify the theory and demonstrate the practical effectiveness of the spectral algorithms. In fact, our results on a large-scale review rating dataset demonstrate that our single-phase spectral algorithm alone gets comparable or even better performance than state-of-the-art methods, while previous work on spectral methods has rarely reported such promising performance.
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NASA Technical Reports Server (NTRS)
Sloss, J. M.; Kranzler, S. K.
1972-01-01
The equivalence of a considered integral equation form with an infinite system of linear equations is proved, and the localization of the eigenvalues of the infinite system is expressed. Error estimates are derived, and the problems of finding upper bounds and lower bounds for the eigenvalues are solved simultaneously.
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Utility of local health registers in measuring perinatal mortality: A case study in rural Indonesia
2011-01-01
Background Perinatal mortality is an important indicator of obstetric and newborn care services. Although the vast majority of global perinatal mortality is estimated to occur in developing countries, there is a critical paucity of reliable data at the local level to inform health policy, plan health care services, and monitor their impact. This paper explores the utility of information from village health registers to measure perinatal mortality at the sub district level in a rural area of Indonesia. Methods A retrospective pregnancy cohort for 2007 was constructed by triangulating data from antenatal care, birth, and newborn care registers in a sample of villages in three rural sub districts in Central Java, Indonesia. For each pregnancy, birth outcome and first week survival were traced and recorded from the different registers, as available. Additional local death records were consulted to verify perinatal mortality, or identify deaths not recorded in the health registers. Analyses were performed to assess data quality from registers, and measure perinatal mortality rates. Qualitative research was conducted to explore knowledge and practices of village midwives in register maintenance and reporting of perinatal mortality. Results Field activities were conducted in 23 villages, covering a total of 1759 deliveries that occurred in 2007. Perinatal mortality outcomes were 23 stillbirths and 15 early neonatal deaths, resulting in a perinatal mortality rate of 21.6 per 1000 live births in 2007. Stillbirth rates for the study population were about four times the rates reported in the routine Maternal and Child Health program information system. Inadequate awareness and supervision, and alternate workload were cited by local midwives as factors resulting in inconsistent data reporting. Conclusions Local maternal and child health registers are a useful source of information on perinatal mortality in rural Indonesia. Suitable training, supervision, and quality control, in conjunction with computerisation to strengthen register maintenance can provide routine local area measures of perinatal mortality for health policy, and monitoring of newborn care interventions. Similar efforts are required to strengthen routine health data in all developing countries, to guide planned progress towards reduction in the local, national and international burden from perinatal mortality. PMID:21410993
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Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features.
Youji Feng; Lixin Fan; Yihong Wu
2016-01-01
The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key point detection and descriptor extraction. It is empirically demonstrated that the localization speed is improved by an order of magnitude as compared with state-of-the-art methods, while comparable registration rate and localization accuracy are still maintained.
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Utility of local health registers in measuring perinatal mortality: a case study in rural Indonesia.
Burke, Leona; Suswardany, Dwi Linna; Michener, Keryl; Mazurki, Setiawaty; Adair, Timothy; Elmiyati, Catur; Rao, Chalapati
2011-03-17
Perinatal mortality is an important indicator of obstetric and newborn care services. Although the vast majority of global perinatal mortality is estimated to occur in developing countries, there is a critical paucity of reliable data at the local level to inform health policy, plan health care services, and monitor their impact. This paper explores the utility of information from village health registers to measure perinatal mortality at the sub district level in a rural area of Indonesia. A retrospective pregnancy cohort for 2007 was constructed by triangulating data from antenatal care, birth, and newborn care registers in a sample of villages in three rural sub districts in Central Java, Indonesia. For each pregnancy, birth outcome and first week survival were traced and recorded from the different registers, as available. Additional local death records were consulted to verify perinatal mortality, or identify deaths not recorded in the health registers. Analyses were performed to assess data quality from registers, and measure perinatal mortality rates. Qualitative research was conducted to explore knowledge and practices of village midwives in register maintenance and reporting of perinatal mortality. Field activities were conducted in 23 villages, covering a total of 1759 deliveries that occurred in 2007. Perinatal mortality outcomes were 23 stillbirths and 15 early neonatal deaths, resulting in a perinatal mortality rate of 21.6 per 1000 live births in 2007. Stillbirth rates for the study population were about four times the rates reported in the routine Maternal and Child Health program information system. Inadequate awareness and supervision, and alternate workload were cited by local midwives as factors resulting in inconsistent data reporting. Local maternal and child health registers are a useful source of information on perinatal mortality in rural Indonesia. Suitable training, supervision, and quality control, in conjunction with computerisation to strengthen register maintenance can provide routine local area measures of perinatal mortality for health policy, and monitoring of newborn care interventions. Similar efforts are required to strengthen routine health data in all developing countries, to guide planned progress towards reduction in the local, national and international burden from perinatal mortality.
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NASA Astrophysics Data System (ADS)
Briones, J. C.; Heras, V.; Abril, C.; Sinchi, E.
2017-08-01
The proper control of built heritage entails many challenges related to the complexity of heritage elements and the extent of the area to be managed, for which the available resources must be efficiently used. In this scenario, the preventive conservation approach, based on the concept that prevent is better than cure, emerges as a strategy to avoid the progressive and imminent loss of monuments and heritage sites. Regular monitoring appears as a key tool to identify timely changes in heritage assets. This research demonstrates that the supervised learning model (Support Vector Machines - SVM) is an ideal tool that supports the monitoring process detecting visible elements in aerial images such as roofs structures, vegetation and pavements. The linear, gaussian and polynomial kernel functions were tested; the lineal function provided better results over the other functions. It is important to mention that due to the high level of segmentation generated by the classification procedure, it was necessary to apply a generalization process through opening a mathematical morphological operation, which simplified the over classification for the monitored elements.
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Multi-test cervical cancer diagnosis with missing data estimation
NASA Astrophysics Data System (ADS)
Xu, Tao; Huang, Xiaolei; Kim, Edward; Long, L. Rodney; Antani, Sameer
2015-03-01
Cervical cancer is a leading most common type of cancer for women worldwide. Existing screening programs for cervical cancer suffer from low sensitivity. Using images of the cervix (cervigrams) as an aid in detecting pre-cancerous changes to the cervix has good potential to improve sensitivity and help reduce the number of cervical cancer cases. In this paper, we present a method that utilizes multi-modality information extracted from multiple tests of a patient's visit to classify the patient visit to be either low-risk or high-risk. Our algorithm integrates image features and text features to make a diagnosis. We also present two strategies to estimate the missing values in text features: Image Classifier Supervised Mean Imputation (ICSMI) and Image Classifier Supervised Linear Interpolation (ICSLI). We evaluate our method on a large medical dataset and compare it with several alternative approaches. The results show that the proposed method with ICSLI strategy achieves the best result of 83.03% specificity and 76.36% sensitivity. When higher specificity is desired, our method can achieve 90% specificity with 62.12% sensitivity.
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Nonlinear Deep Kernel Learning for Image Annotation.
Jiu, Mingyuan; Sahbi, Hichem
2017-02-08
Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.
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STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION.
Fan, Jianqing; Xue, Lingzhou; Zou, Hui
2014-06-01
Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression.
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STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION
Fan, Jianqing; Xue, Lingzhou; Zou, Hui
2014-01-01
Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression. PMID:25598560
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Dörenkamp, Sarah; Mesters, Ilse; de Bie, Rob; Teijink, Joep; van Breukelen, Gerard
2016-01-01
The aim of this study is to investigate the association between age, gender, body-mass index, smoking behavior, orthopedic comorbidity, neurologic comorbidity, cardiac comorbidity, vascular comorbidity, pulmonic comorbidity, internal comorbidity and Initial Claudication Distance during and after Supervised Exercise Therapy at 1, 3, 6 and 12 months in a large sample of patients with Intermittent Claudication. Data was prospectively collected in standard physiotherapy care. Patients received Supervised Exercise Therapy according to the guideline Intermittent Claudication of the Royal Dutch Society for Physiotherapy. Three-level mixed linear regression analysis was carried out to analyze the association between patient characteristics, comorbidities and Initial Claudication Distance at 1, 3, 6 and 12 months. Data from 2995 patients was analyzed. Results showed that being female, advanced age and a high body-mass index were associated with lower Initial Claudication Distance at all-time points (p = 0.000). Besides, a negative association between cardiac comorbidity and Initial Claudication Distance was revealed (p = 0.011). The interaction time by age, time by body-mass index and time by vascular comorbidity were significantly associated with Initial Claudication Distance (p≤ 0.05). Per year increase in age (range: 33-93 years), the reduction in Initial Claudication Distance was 8m after 12 months of Supervised Exercise Therapy. One unit increase in body-mass index (range: 16-44 kg/m2) led to 10 m less improvement in Initial Claudication Distance after 12 months and for vascular comorbidity the reduction in improvement was 85 m after 12 months. This study reveals that females, patients at advanced age, patients with a high body-mass index and cardiac comorbidity are more likely to show less improvement in Initial Claudication Distances (ICD) after 1, 3, 6 and 12 months of Supervised Exercise Therapy. Further research should elucidate treatment adaptations that optimize treatment outcomes for these subgroups.
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Reilly, E T C; Freeman, R M; Waterfield, M R; Waterfield, A E; Steggles, P; Pedlar, F
2014-12-01
To test whether supervised pelvic floor exercises antenatally will reduce the incidence of postpartum stress incontinence in at-risk primigravidae with bladder neck mobility, ultrasonically proven. Single blind, randomised controlled trial. Antenatal clinic in a UK NHS Trust Hospital. Two hundred and sixty-eight primigravidae attending an antenatal clinic at approximately 20 weeks of gestation with bladder neck mobility, on standardised valsalva, of 5 mm or more linear movement. The median age was 28, ranging from 16 to 47 years. Patients randomised to supervised pelvic floor exercises (n = 139) attended a physiotherapist at monthly intervals from 20 weeks until delivery. The exercises comprised three repetitions of eight contractions each held for six seconds, with two minutes rest between repetitions. These were repeated twice daily. At 34 weeks of gestation the number of contractions per repetition was increased to 12. Both the untreated control group and the study group received verbal advice on pelvic floor exercises from their midwives antenatally. Subjective reporting of stress incontinence at three months postpartum. Pelvic floor strength, using perineometry, and bladder neck mobility measured by perineal ultrasound. Of the 268 women enrolled, information on the main outcome variable was available for 110 in the control group and 120 in the study group. Fewer women in the supervised pelvic floor exercise group reported postpartum stress incontinence, 19.2% compared with 32.7% in the control group (RR 0.59 [0.37-0.92]). There was no change in bladder neck mobility and no difference in pelvic floor strength between groups after exercise, although all those developing postpartum stress incontinence had significantly poorer perineometry scores than those who were continent. The findings suggest that antenatal supervised pelvic floor exercises are effective in reducing the risk of postpartum stress incontinence in primigravidae with bladder neck mobility. © RCOG 2002 BJOG: an International Journal of Obstetrics and Gynaecology.
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Scheduling for Locality in Shared-Memory Multiprocessors
1993-05-01
Submitted in Partial Fulfillment of the Requirements for the Degree ’)iIC Q(JALfryT INSPECTED 5 DOCTOR OF PHILOSOPHY I Accesion For Supervised by NTIS CRAM... architecture on parallel program performance, explain the implications of this trend on popular parallel programming models, and propose system software to 0...decomoosition and scheduling algorithms. I. SUIUECT TERMS IS. NUMBER OF PAGES shared-memory multiprocessors; architecture trends; loop 110 scheduling
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2010-08-01
NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND...management; leads military in case of specialized survey; supervises more than 25 local civilian employees ; acts as technical expert during contract...Security Assistance Force Head- quarters Camp. I knew I could handle the job of project manager, but wondered about acting as contract manager, technical ex
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Hyaluronidase: Purification and Inhibition by a Gold Complex and a Steroid Derivative.
1987-12-11
supervision of gas turbine propulsion plants and graduated from the Surface Warfare Officer School, Newport, Rhode Island, in November, 1980. He served one...localized in the lysosomes of those tissues. The liver enzyme was shown to give an even numbered of oligosaccharide products, which are identical to...molecular weight substrate is first cleaved by hyaluronidase, and the oligosaccharides produced are further attacked by exopolysaccharidases. AK 13 Among
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An Evaluation of Trauma Focused Cognitive Behavioral Therapy for Children in Zambia
Murray, Laura K; Familiar, Itziar; Skavenski, Stephanie; Jere, Elizabeth; Cohen, Judy; Imasiku, Mwiya; Mayeya, John; Bass, Judith K; Bolton, Paul
2013-01-01
Objectives To monitor and evaluate the feasibility of implementing Trauma Focused-Cognitive Behavioral Therapy (TF-CBT) to address trauma and stress-related symptoms in orphans and vulnerable children (OVC) in Zambia as part of ongoing programming within a non-governmental organization (NGO). Methods As part of ongoing programming, voluntary care-workers administered locally validated assessments to identify children who met criteria for moderate to severe trauma symptomatology. Local lay counselors implemented TF-CBT with identified families, while participating in ongoing supervision. Fifty-eight children and adolescents aged 5–18 completed the TF-CBT treatment, with pre- and post-assessments. Results The mean number of traumas reported by the treatment completers (N=58) was 4.11. Post assessments showed significant reductions in severity of trauma symptoms (p<0.0001), and severity of shame symptoms (p<0.0001). Conclusions Our results suggest that TF-CBT is a feasible treatment option in Zambia for OVC. A decrease in symptoms suggests that a controlled trial is warranted. Implementation factors monitored suggest that it is feasible to integrate and evaluate evidence-based mental health assessments and intervention into programmatic services run by an NGO in low/middle resource countries. Results also support the effectiveness of implementation strategies such as task shifting, and the apprenticeship model of training and supervision. PMID:23768939
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2011-01-01
Background Recent global mental health research suggests that mental health interventions can be adapted for use across cultures and in low resource environments. As evidence for the feasibility and effectiveness of certain specific interventions begins to accumulate, guidelines are needed for how to train, supervise, and ideally sustain mental health treatment delivery by local providers in low- and middle-income countries (LMIC). Model and case presentations This paper presents an apprenticeship model for lay counselor training and supervision in mental health treatments in LMIC, developed and used by the authors in a range of mental health intervention studies conducted over the last decade in various low-resource settings. We describe the elements of this approach, the underlying logic, and provide examples drawn from our experiences working in 12 countries, with over 100 lay counselors. Evaluation We review the challenges experienced with this model, and propose some possible solutions. Discussion We describe and discuss how this model is consistent with, and draws on, the broader dissemination and implementation (DI) literature. Conclusion In our experience, the apprenticeship model provides a useful framework for implementation of mental health interventions in LMIC. Our goal in this paper is to provide sufficient details about the apprenticeship model to guide other training efforts in mental health interventions. PMID:22099582
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The need for innovative strategies to improve immunisation services in rural Zimbabwe.
Chadambuka, Addmore; Chimusoro, Anderson; Apollo, Tsitsilina; Tshimanga, Mufuta; Namusisi, Olivia; Luman, Elizabeth T
2012-01-01
Gokwe South, a rural district in Midlands Province, Zimbabwe, reported the lowest rate of immunisation coverage in the country in 2005: 55 per cent of children vaccinated with three doses of diphtheria/pertussis/tetanus vaccine (DPT3) and 35 per cent dropout between the first and third dose of DPT. In January 2007, the authors assessed local barriers to immunisation and proposed strategies to improve immunisation rates in the district, in the face of nationwide economic and political challenges. A situational analysis was performed to assess barriers to immunisation using focus-group discussions with health workers, key informant interviews with health management and community leaders, and desk reviews of records. Responses were categorised and solutions proposed. Health workers and key informants reported that immunisation service delivery was hampered by insufficient availability of gas for cold-chain equipment, limited transport and fuel to conduct basic activities, and inadequate staff and supervision. Improving coverage will require prioritising gas for vaccine cold-chain equipment, identifying reliable transportation or alternative transportation solutions, and increased staff, training and supervision. Local assessment is critical to pinpointing site-specific barriers, and innovative strategies are needed to overcome existing contextual challenges. © 2012 The Author(s). Disasters © Overseas Development Institute, 2012.
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Estimating the remaining useful life of bearings using a neuro-local linear estimator-based method.
Ahmad, Wasim; Ali Khan, Sheraz; Kim, Jong-Myon
2017-05-01
Estimating the remaining useful life (RUL) of a bearing is required for maintenance scheduling. While the degradation behavior of a bearing changes during its lifetime, it is usually assumed to follow a single model. In this letter, bearing degradation is modeled by a monotonically increasing function that is globally non-linear and locally linearized. The model is generated using historical data that is smoothed with a local linear estimator. A neural network learns this model and then predicts future levels of vibration acceleration to estimate the RUL of a bearing. The proposed method yields reasonably accurate estimates of the RUL of a bearing at different points during its operational life.
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Hippocampus Segmentation Based on Local Linear Mapping
Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin
2017-01-01
We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively. PMID:28368016
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Hippocampus Segmentation Based on Local Linear Mapping.
Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin
2017-04-03
We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively.
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Hippocampus Segmentation Based on Local Linear Mapping
NASA Astrophysics Data System (ADS)
Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin
2017-04-01
We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively.
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Associations between attending physician workload, teaching effectiveness, and patient safety.
Wingo, Majken T; Halvorsen, Andrew J; Beckman, Thomas J; Johnson, Matthew G; Reed, Darcy A
2016-03-01
Prior studies suggest that high workload among attending physicians may be associated with reduced teaching effectiveness and poor patient outcomes, but these relationships have not been investigated using objective measures of workload and safety. To examine associations between attending workload, teaching effectiveness, and patient safety, hypothesizing that higher workload would be associated with lower teaching effectiveness and negative patient outcomes. We conducted a retrospective study of 69,386 teaching evaluation items submitted by 543 internal medicine residents for 107 attending physicians who supervised inpatient teaching services from July 2, 2005 to July 1, 2011. Attending workload measures included hospital service census, patient length of stay, daily admissions, daily discharges, and concurrent outpatient duties. Teaching effectiveness was measured using residents' evaluations of attendings. Patient outcomes considered were applicable patient safety indicators (PSIs), intensive care unit transfers, cardiopulmonary resuscitation/rapid response team calls, and patient deaths. Mixed linear models and generalized linear regression models were used for statistical analysis. Workload measures of midnight census and daily discharges were associated with lower teaching evaluation scores (both β = -0.026, P < 0.0001). The number of daily admissions was associated with higher teaching scores (β = 0.021, P = 0.001) and increased PSIs (odds ratio = 1.81, P = 0.0001). Several measures of attending physician workload were associated with slightly lower teaching effectiveness, and patient safety may be compromised when teams are managing new admissions. Ongoing efforts by residency programs to optimize the learning environment should include strategies to manage the workload of supervising attendings. © 2016 Society of Hospital Medicine.
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NASA Astrophysics Data System (ADS)
Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te
2018-03-01
Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p = 0.002 518), sigma (p = 0.002 781), uniformity (p = 0.032 41), and entropy (p = 0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.
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Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te
2018-03-14
Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p = 0.002 518), sigma (p = 0.002 781), uniformity (p = 0.032 41), and entropy (p = 0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.
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New developments in technology-assisted supervision and training: a practical overview.
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.
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Special Issue on Clinical Supervision: A Reflection
ERIC Educational Resources Information Center
Bernard, Janine M.
2010-01-01
This special issue about clinical supervision offers an array of contributions with disparate insights into the supervision process. Using a synergy of supervision model, the articles are categorized as addressing the infrastructure required for adequate supervision, the relationship dynamics endemic to supervision, or the process of delivering…
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Hill, Zelee; Dumbaugh, Mari; Benton, Lorna; Källander, Karin; Strachan, Daniel; Asbroek, Augustinus ten; Tibenderana, James; Kirkwood, Betty; Meek, Sylvia
2014-01-01
Background Community health workers (CHWs) are an increasingly important component of health systems and programs. Despite the recognized role of supervision in ensuring CHWs are effective, supervision is often weak and under-supported. Little is known about what constitutes adequate supervision and how different supervision strategies influence performance, motivation, and retention. Objective To determine the impact of supervision strategies used in low- and middle-income countries and discuss implementation and feasibility issues with a focus on CHWs. Design A search of peer-reviewed, English language articles evaluating health provider supervision strategies was conducted through November 2013. Included articles evaluated the impact of supervision in low- or middle-income countries using a controlled, pre-/post- or observational design. Implementation and feasibility literature included both peer-reviewed and gray literature. Results A total of 22 impact papers were identified. Papers were from a range of low- and middle-income countries addressing the supervision of a variety of health care providers. We classified interventions as testing supervision frequency, the supportive/facilitative supervision package, supervision mode (peer, group, and community), tools (self-assessment and checklists), focus (quality assurance/problem solving), and training. Outcomes included coverage, performance, and perception of quality but were not uniform across studies. Evidence suggests that improving supervision quality has a greater impact than increasing frequency of supervision alone. Supportive supervision packages, community monitoring, and quality improvement/problem-solving approaches show the most promise; however, evaluation of all strategies was weak. Conclusion Few supervision strategies have been rigorously tested and data on CHW supervision is particularly sparse. This review highlights the diversity of supervision approaches that policy makers have to choose from and, while choices should be context specific, our findings suggest that high-quality supervision that focuses on supportive approaches, community monitoring, and/or quality assurance/problem solving may be most effective. PMID:24815075
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ERIC Educational Resources Information Center
Jin, Lijun; Cox, Jackie L.
This study examined the effects of a clinical supervision course on cooperating teachers' supervision of student teachers. Participants were cooperating teachers enrolled in a clinical supervision class in which supervision strategies were introduced and modeled. Before supervision theories and techniques were introduced, participants completed…
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Performance and Attitudes as a Function of Degree of Supervision in a School Laboratory Setting
ERIC Educational Resources Information Center
Kazanas, H. C.; Burns, G. G.
1977-01-01
High- and low-mental-ability secondary school students randomly divided into three supervision treatment groups (no supervision, supervision without verbal exchange from the teacher, and supervision with verbal exchange) showed no performance variations but evidenced better attitudes with the third supervision treatment. (MJB)
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Direct Supervision in Outpatient Psychiatric Graduate Medical Education.
Galanter, Cathryn A; Nikolov, Roumen; Green, Norma; Naidoo, Shivana; Myers, Michael F; Merlino, Joseph P
2016-02-01
The authors describe a stimulus case that led training staff to examine and revise the supervision policy of the adult and child and adolescent psychiatry clinics. To inform the revisions, the authors reviewed the literature and national policies. The authors conducted a literature review in PubMed using the following criteria: Supervision, Residents, Training, Direct, and Indirect and a supplemental review in Academic Psychiatry. The authors reviewed institutional and Accreditation Council for Graduate Medical Education resident and fellow supervision policies to develop an outpatient and fellow supervision policy. Research is limited in psychiatry with three experimental articles demonstrating positive impact of direct supervision and several suggesting different techniques for direct supervision. In other areas of medicine, direct supervision is associated with improved educational and patient outcomes. The authors present details of our new supervision policy including triggers for direct supervision. The term direct supervision is relatively new in psychiatry and medical education. There is little published on the extent of implementation of direct supervision and on its impact on the educational experience of psychiatry trainees and other medical specialties. Direct supervision has been associated with improved educational and patient outcomes in nonpsychiatric fields of medicine. More research is needed on the implementation of, indications for, and effects of direct supervision on trainee education and on patient outcomes.
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Contrast effects on speed perception for linear and radial motion.
Champion, Rebecca A; Warren, Paul A
2017-11-01
Speed perception is vital for safe activity in the environment. However, considerable evidence suggests that perceived speed changes as a function of stimulus contrast, with some investigators suggesting that this might have meaningful real-world consequences (e.g. driving in fog). In the present study we investigate whether the neural effects of contrast on speed perception occur at the level of local or global motion processing. To do this we examine both speed discrimination thresholds and contrast-dependent speed perception for two global motion configurations that have matched local spatio-temporal structure. Specifically we compare linear and radial configurations, the latter of which arises very commonly due to self-movement. In experiment 1 the stimuli comprised circular grating patches. In experiment 2, to match stimuli even more closely, motion was presented in multiple local Gabor patches equidistant from central fixation. Each patch contained identical linear motion but the global configuration was either consistent with linear or radial motion. In both experiments 1 and 2, discrimination thresholds and contrast-induced speed biases were similar in linear and radial conditions. These results suggest that contrast-based speed effects occur only at the level of local motion processing, irrespective of global structure. This result is interpreted in the context of previous models of speed perception and evidence suggesting differences in perceived speed of locally matched linear and radial stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Local Linear Regression for Data with AR Errors.
Li, Runze; Li, Yan
2009-07-01
In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and the profile least squares techniques. We further propose the SCAD penalized profile least squares method to determine the order of auto-regressive process. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedure, and to compare the performance of the proposed procedures with the existing one. From our empirical studies, the newly proposed procedures can dramatically improve the accuracy of naive local linear regression with working-independent error structure. We illustrate the proposed methodology by an analysis of real data set.
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The Need for Data-Informed Clinical Supervision in Substance Use Disorder Treatment
Ramsey, Alex T.; Baumann, Ana; Silver Wolf, David Patterson; Yan, Yan; Cooper, Ben; Proctor, Enola
2017-01-01
Background Effective clinical supervision is necessary for high-quality care in community-based substance use disorder treatment settings, yet little is known about current supervision practices. Some evidence suggests that supervisors and counselors differ in their experiences of clinical supervision; however, the impact of this misalignment on supervision quality is unclear. Clinical information monitoring systems may support supervision in substance use disorder treatment, but the potential use of these tools must first be explored. Aims First, this study examines the extent to which misaligned supervisor-counselor perceptions impact supervision satisfaction and emphasis on evidence-based treatments. This study also reports on formative work to develop a supervision-based clinical dashboard, an electronic information monitoring system and data visualization tool providing real-time clinical information to engage supervisors and counselors in a coordinated and data-informed manner, help align supervisor-counselor perceptions about supervision, and improve supervision effectiveness. Methods Clinical supervisors and frontline counselors (N=165) from five Midwestern agencies providing substance abuse services completed an online survey using Research Electronic Data Capture (REDCap) software, yielding a 75% response rate. Valid quantitative measures of supervision effectiveness were assessed, along with qualitative perceptions of a supervision-based clinical dashboard. Results Through within-dyad analyses, misalignment between supervisor and counselor perceptions of supervision practices was negatively associated with satisfaction of supervision and reported frequency of discussing several important clinical supervision topics, including evidence-based treatments and client rapport. Participants indicated the most useful clinical dashboard functions and reported important benefits and challenges to using the proposed tool. Discussion Clinical supervision tends to be largely an informal and unstructured process in substance abuse treatment, which may compromise the quality of care. Clinical dashboards may be a well-targeted approach to facilitate data-informed clinical supervision in community-based treatment agencies. PMID:28166480
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The need for data-informed clinical supervision in substance use disorder treatment.
Ramsey, Alex T; Baumann, Ana; Patterson Silver Wolf, David; Yan, Yan; Cooper, Ben; Proctor, Enola
2017-01-01
Effective clinical supervision is necessary for high-quality care in community-based substance use disorder treatment settings, yet little is known about current supervision practices. Some evidence suggests that supervisors and counselors differ in their experiences of clinical supervision; however, the impact of this misalignment on supervision quality is unclear. Clinical information monitoring systems may support supervision in substance use disorder treatment, but the potential use of these tools must first be explored. First, the current study examines the extent to which misaligned supervisor-counselor perceptions impact supervision satisfaction and emphasis on evidence-based treatments. This study also reports on formative work to develop a supervision-based clinical dashboard, an electronic information monitoring system and data visualization tool providing real-time clinical information to engage supervisors and counselors in a coordinated and data-informed manner, help align supervisor-counselor perceptions about supervision, and improve supervision effectiveness. Clinical supervisors and frontline counselors (N = 165) from five Midwestern agencies providing substance abuse services completed an online survey using Research Electronic Data Capture software, yielding a 75% response rate. Valid quantitative measures of supervision effectiveness were administered, along with qualitative perceptions of a supervision-based clinical dashboard. Through within-dyad analyses, misalignment between supervisor and counselor perceptions of supervision practices was negatively associated with satisfaction of supervision and reported frequency of discussing several important clinical supervision topics, including evidence-based treatments and client rapport. Participants indicated the most useful clinical dashboard functions and reported important benefits and challenges to using the proposed tool. Clinical supervision tends to be largely an informal and unstructured process in substance abuse treatment, which may compromise the quality of care. Clinical dashboards may be a well-targeted approach to facilitate data-informed clinical supervision in community-based treatment agencies.
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System architecture for asynchronous multi-processor robotic control system
NASA Technical Reports Server (NTRS)
Steele, Robert D.; Long, Mark; Backes, Paul
1993-01-01
The architecture for the Modular Telerobot Task Execution System (MOTES) as implemented in the Supervisory Telerobotics (STELER) Laboratory is described. MOTES is the software component of the remote site of a local-remote telerobotic system which is being developed for NASA for space applications, in particular Space Station Freedom applications. The system is being developed to provide control and supervised autonomous control to support both space based operation and ground-remote control with time delay. The local-remote architecture places task planning responsibilities at the local site and task execution responsibilities at the remote site. This separation allows the remote site to be designed to optimize task execution capability within a limited computational environment such as is expected in flight systems. The local site task planning system could be placed on the ground where few computational limitations are expected. MOTES is written in the Ada programming language for a multiprocessor environment.
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Gonge, Henrik; Buus, Niels
2015-04-01
To test the effects of a meta-supervision intervention in terms of participation, effectiveness and benefits of clinical supervision of psychiatric nursing staff. Clinical supervision is regarded as a central component in developing mental health nursing practices, but the evidence supporting positive outcomes of clinical supervision in psychiatric nursing is not convincing. The study was designed as a randomized controlled trial. All permanently employed nursing staff members at three general psychiatric wards at a Danish university hospital (n = 83) were allocated to either 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. 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. The main result was that it was possible to motivate staff in the intervention group to participate significantly more frequently in sessions of the ongoing supervision compared with the control group. However, more frequent participation was not reflected in the experienced effectiveness of the clinical supervision or in the general formative or restorative benefits. The intervention had a positive effect on individuals or wards already actively engaged in clinical supervision, which suggested that individuals and wards without well-established supervision practices may require more comprehensive interventions targeting individual and organizational barriers to clinical supervision. © 2014 John Wiley & Sons Ltd.
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Evaluation d’une grille de supervision des laboratoires des leishmanioses cutanées au Maroc
El Mansouri, Bouchra; Amarir, Fatima; Hajli, Yamina; Fellah, Hajiba; Sebti, Faiza; Delouane, Bouchra; Sadak, Abderrahim; Adlaoui, El Bachir; Rhajaoui, Mohammed
2017-01-01
Introduction Afin d’évaluer une grille de contrôle standardisée de laboratoire de diagnostic des leishmanioses, comme nouveau outil de supervision. Méthodes Un essai pilote a été pratiqué sur sept laboratoires provinciaux, appartenant à quatre provinces au Maroc, en suivant l’évolution de leurs performances tous les deux ans, entre l’année 2006 et 2014. Cette étude détaille la situation des laboratoires provinciaux avant et après la mise en œuvre de la grille de supervision. Au total vingt et une grille sont analysées. Résultats En 2006, les résultats ont montré clairement une insuffisance des performances des laboratoires: besoin en formation (41.6%), personnel pratiquant le prélèvement cutané (25%), pénurie en matériels et réactifs (65%), gestions documentaire et local non conformes (85%). Différentes actions correctives ont été menées par le Laboratoire National de Référence des Leishmanioses (LNRL) durant la période d’étude. En 2014, le LNRL a enregistré une nette amélioration des performances des laboratoires. Les besoins en matière de formation, qualité du prélèvement, dotation en matériels et réactifs ont été comblés et une coordination efficace s’est établie entre le LNRL et les laboratoires provinciaux. Conclusion Ceci montre l'efficacité de la grille comme outil de supervision de grande qualité, et comme pierre angulaire de tout progrès qui doit être obtenu dans les programmes de lutte contre les leishmanioses. PMID:29187922
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Casey, Máire-Bríd; Smart, Keith; Segurado, Ricardo; Hearty, Conor; Gopal, Hari; Lowry, Damien; Flanagan, Dearbhail; McCracken, Lance; Doody, Catherine
2018-03-22
Acceptance and Commitment Therapy (ACT) is a form of cognitive behavioural therapy, which may be beneficial for people with chronic pain. The approach aims to enhance daily functioning through increased psychological flexibility. Whilst the therapeutic model behind ACT appears well suited to chronic pain, there is a need for further research to test its effectiveness in clinical practice, particularly with regards to combining ACT with physical exercise. This prospective, two-armed, parallel-group, single-centre randomised controlled trial (RCT) will assess the effectiveness of a combined Exercise and ACT programme, in comparison to supervised exercise for chronic pain. One hundred and sixty patients, aged 18 years and over, who have been diagnosed with a chronic pain condition by a physician will be recruited to the trial. Participants will be individually randomised to one of two 8-week, group interventions. The combined group will take part in weekly psychology sessions based on the ACT approach, in addition to supervised exercise classes led by a physiotherapist. The control group will attend weekly supervised exercise classes but will not take part in an ACT programme. The primary outcome will be pain interference at 12-week follow-up, measured using the Brief Pain Inventory-Interference Scale. Secondary outcomes will include self-reported pain severity, self-perception of change, patient satisfaction, quality of life, depression, anxiety and healthcare utilisation. Treatment process measures will include self-efficacy, pain catastrophising, fear avoidance, pain acceptance and committed action. Physical activity will be measured using Fitbit Zip TM activity trackers. Both groups will be followed up post intervention and again after 12 weeks. Estimates of treatment effects at follow-up will be based on an intention-to-treat framework, implemented using a linear mixed-effects model. Individual and focus group qualitative interviews will be undertaken with a purposeful sample of participants to explore patient experiences of both treatments. To our knowledge, this will be the first RCT to examine whether combining exercise with ACT produces greater benefit for patients with chronic pain, compared to a standalone supervised exercise programme. www.ClinicalTrials.gov, ID: NCT03050528 . Registered on 13 February 2017.
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Object matching using a locally affine invariant and linear programming techniques.
Li, Hongsheng; Huang, Xiaolei; He, Lei
2013-02-01
In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.
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Analysis and application of ERTS-1 data for regional geological mapping
NASA Technical Reports Server (NTRS)
Gold, D. P.; Parizek, R. R.; Alexander, S. A.
1973-01-01
Combined visual and digital techniques of analysing ERTS-1 data for geologic information have been tried on selected areas in Pennsylvania. The major physiolographic and structural provinces show up well. Supervised mapping, following the imaged expression of known geologic features on ERTS band 5 enlargements (1:250,000) of parts of eastern Pennsylvania, delimited the Diabase Sills and the Precambrian rocks of the Reading Prong with remarkable accuracy. From unsupervised mapping, transgressive linear features are apparent in unexpected density, and exhibit strong control over river valley and stream channel directions. They are unaffected by bedrock type, age, or primary structural boundaries, which suggests they are either rejuvenated basement joint directions on different scales, or they are a recently impressed structure possibly associated with a drifting North American plate. With ground mapping and underflight data, 6 scales of linear features have been recognized.
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Data on microbiological quality assessment of rural drinking water supplies in Poldasht county.
Yousefi, Mahmood; Saleh, Hossein Najafi; Yaseri, Mehdi; Mahvi, Amir Hossein; Soleimani, Hamed; Saeedi, Zhyar; Zohdi, Sara; Mohammadi, Ali Akbar
2018-04-01
In this research, the villages with water supply systems under the supervision of the Water and Wastewater Company in Poldasht County, Iran in 2015 was studied. 648 samples were taken from 57 villages during 12month period to test for microbial quality according to the latest guidelines of WHO. Fecal coliform, coliform, turbidity, pH and free residual chlorine were analyzed. Also we used linear Regression statistical analysis for collected data. Result of Data showed that 13.6% of the villages under study had contaminated water resources. In 100 percent of the water sample resource the turbidity level was less than Iranian maximum permissible levels (5 NTU). There was a linear relation between the Free residual color and Coliform in different month of follow up ( r = -0.154, P < 0.001). Data suggests water resources should be comprehensively planned and monitored keeping in view the WHO recommended parameters.
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Variational and robust density fitting of four-center two-electron integrals in local metrics
NASA Astrophysics Data System (ADS)
Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjærgaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Høst, Stinne; Salek, Paweł
2008-09-01
Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.
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Variational and robust density fitting of four-center two-electron integrals in local metrics.
Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjaergaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Host, Stinne; Salek, Paweł
2008-09-14
Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.
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Adequate supervision for children and adolescents.
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.
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ERIC Educational Resources Information Center
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…
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Alfonsson, Sven; Parling, Thomas; Spännargård, Åsa; Andersson, Gerhard; Lundgren, Tobias
2018-05-01
Clinical supervision is a central part of psychotherapist training but the empirical support for specific supervision theories or features is unclear. The aims of this study were to systematically review the empirical research literature regarding the effects of clinical supervision on therapists' competences and clinical outcomes within Cognitive Behavior Therapy (CBT). A comprehensive database search resulted in 4103 identified publications. Of these, 133 were scrutinized and in the end 5 studies were included in the review for data synthesis. The five studies were heterogeneous in scope and quality and only one provided firm empirical support for the positive effects of clinical supervision on therapists' competence. The remaining four studies suffered from methodological weaknesses, but provided some preliminary support that clinical supervision may be beneficiary for novice therapists. No study could show benefits from supervision for patients. The research literature suggests that clinical supervision may have some potential effects on novice therapists' competence compared to no supervision but the effects on clinical outcomes are still unclear. While bug-in-the-eye live supervision may be more effective than standard delayed supervision, the effects of specific supervision models or features are also unclear. There is a continued need for high-quality empirical studies on the effects of clinical supervision in psychotherapy.
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Supervision of Facilitators in a Multisite Study: Goals, Process, and Outcomes
2010-01-01
Objective To describe the aims, implementation, and desired outcomes of facilitator supervision for both interventions (treatment and control) in Project Eban and to present the Eban Theoretical Framework for Supervision that guided the facilitators’ supervision. The qualifications and training of supervisors and facilitators are also described. Design This article provides a detailed description of supervision in a multisite behavioral intervention trial. The Eban Theoretical Framework for Supervision is guided by 3 theories: cognitive behavior therapy, the Life-long Model of Supervision, and “Empowering supervisees to empower others: a culturally responsive supervision model.” Methods Supervision is based on the Eban Theoretical Framework for Supervision, which provides guidelines for implementing both interventions using goals, process, and outcomes. Results Because of effective supervision, the interventions were implemented with fidelity to the protocol and were standard across the multiple sites. Conclusions Supervision of facilitators is a crucial aspect of multisite intervention research quality assurance. It provides them with expert advice, optimizes the effectiveness of facilitators, and increases adherence to the protocol across multiple sites. Based on the experience in this trial, some of the challenges that arise when conducting a multisite randomized control trial and how they can be handled by implementing the Eban Theoretical Framework for Supervision are described. PMID:18724192
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Islam in Tanzania and Kenya: Ally or Foe in the War on Terror?
2009-01-01
US foreign policy in the region. The recent US strategy of intelligence-sharing with Kenya, training and military support to both Kenya and Tanzania...assisted one another in establishing businesses , houses, schools, and so forth.43 Indeed, they were among the first Muslim groups to establish...be debated at that level , although under supervision from the central government. Also, local elections occurred for representatives, even if both
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Guidelines for clinical supervision in health service psychology.
2015-01-01
This document outlines guidelines for supervision of students in health service psychology education and training programs. The goal was to capture optimal performance expectations for psychologists who supervise. It is based on the premises that supervisors (a) strive to achieve competence in the provision of supervision and (b) employ a competency-based, meta-theoretical approach to the supervision process. The Guidelines on Supervision were developed as a resource to inform education and training regarding the implementation of competency-based supervision. The Guidelines on Supervision build on the robust literatures on competency-based education and clinical supervision. They are organized around seven domains: supervisor competence; diversity; relationships; professionalism; assessment/evaluation/feedback; problems of professional competence, and ethical, legal, and regulatory considerations. The Guidelines on Supervision represent the collective effort of a task force convened by the American Psychological Association (APA) Board of Educational Affairs (BEA). PsycINFO Database Record (c) 2015 APA, all rights reserved.
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Patch-based automatic retinal vessel segmentation in global and local structural context.
Cao, Shuoying; Bharath, Anil A; Parker, Kim H; Ng, Jeffrey
2012-01-01
In this paper, we extend our published work [1] and propose an automated system to segment retinal vessel bed in digital fundus images with enough adaptability to analyze images from fluorescein angiography. This approach takes into account both the global and local context and enables both vessel segmentation and microvascular centreline extraction. These tools should allow researchers and clinicians to estimate and assess vessel diameter, capillary blood volume and microvascular topology for early stage disease detection, monitoring and treatment. Global vessel bed segmentation is achieved by combining phase-invariant orientation fields with neighbourhood pixel intensities in a patch-based feature vector for supervised learning. This approach is evaluated against benchmarks on the DRIVE database [2]. Local microvascular centrelines within Regions-of-Interest (ROIs) are segmented by linking the phase-invariant orientation measures with phase-selective local structure features. Our global and local structural segmentation can be used to assess both pathological structural alterations and microemboli occurrence in non-invasive clinical settings in a longitudinal study.
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Code of Federal Regulations, 2010 CFR
2010-04-01
... of withdrawal from supervision as a supervised investment bank holding company shall become effective... investment bank holding company within a shorter or longer period to help ensure effective supervision of the... the Commission as a supervised investment bank holding company. 240.17i-3 Section 240.17i-3 Commodity...
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Bearman, Sarah Kate; Schneiderman, Robyn L; Zoloth, Emma
2017-03-01
Treatments that are efficacious in research trials perform less well under routine conditions; differences in supervision may be one contributing factor. This study compared the effect of supervision using active learning techniques (e.g. role play, corrective feedback) versus "supervision as usual" on therapist cognitive restructuring fidelity, overall CBT competence, and CBT expertise. Forty therapist trainees attended a training workshop and were randomized to supervision condition. Outcomes were assessed using behavioral rehearsals pre- and immediately post-training, and after three supervision meetings. EBT knowledge, attitudes, and fidelity improved for all participants post-training, but only the SUP+ group demonstrated improvement following supervision.
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Dorsey, Shannon; Pullmann, Michael D; Kerns, Suzanne E U; Jungbluth, Nathaniel; Meza, Rosemary; Thompson, Kelly; Berliner, Lucy
2017-11-01
Supervisors are an underutilized resource for supporting evidence-based treatments (EBTs) in community mental health. Little is known about how EBT-trained supervisors use supervision time. Primary aims were to describe supervision (e.g., modality, frequency), examine functions of individual supervision, and examine factors associated with time allocation to supervision functions. Results from 56 supervisors and 207 clinicians from 25 organizations indicate high prevalence of individual supervision, often alongside group and informal supervision. Individual supervision serves a wide range of functions, with substantial variation at the supervisor-level. Implementation climate was the strongest predictor of time allocation to clinical and EBT-relevant functions.
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NASA Astrophysics Data System (ADS)
Muller, Sybrand Jacobus; van Niekerk, Adriaan
2016-07-01
Soil salinity often leads to reduced crop yield and quality and can render soils barren. Irrigated areas are particularly at risk due to intensive cultivation and secondary salinization caused by waterlogging. Regular monitoring of salt accumulation in irrigation schemes is needed to keep its negative effects under control. The dynamic spatial and temporal characteristics of remote sensing can provide a cost-effective solution for monitoring salt accumulation at irrigation scheme level. This study evaluated a range of pan-fused SPOT-5 derived features (spectral bands, vegetation indices, image textures and image transformations) for classifying salt-affected areas in two distinctly different irrigation schemes in South Africa, namely Vaalharts and Breede River. The relationship between the input features and electro conductivity measurements were investigated using regression modelling (stepwise linear regression, partial least squares regression, curve fit regression modelling) and supervised classification (maximum likelihood, nearest neighbour, decision tree analysis, support vector machine and random forests). Classification and regression trees and random forest were used to select the most important features for differentiating salt-affected and unaffected areas. The results showed that the regression analyses produced weak models (<0.4 R squared). Better results were achieved using the supervised classifiers, but the algorithms tend to over-estimate salt-affected areas. A key finding was that none of the feature sets or classification algorithms stood out as being superior for monitoring salt accumulation at irrigation scheme level. This was attributed to the large variations in the spectral responses of different crops types at different growing stages, coupled with their individual tolerances to saline conditions.
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Martin, Priya; Kumar, Saravana; Lizarondo, Lucylynn; Tyack, Zephanie
2016-10-01
Clinical supervision is important for effective health service delivery, professional development and practice. Despite its importance there is a lack of evidence regarding the factors that improve its quality. This study aimed to investigate the factors that influence the quality of clinical supervision of occupational therapists employed in a large public sector health service covering mental health, paediatrics, adult physical and other practice areas. A mixed method, sequential explanatory study design was used consisting of two phases. This article reports the quantitative phase (Phase One) which involved administration of the Manchester Clinical Supervision Scale (MCSS-26) to 207 occupational therapists. Frequency of supervision sessions, choice of supervisor and the type of supervision were found to be the predictor variables with a positive and significant influence on the quality of clinical supervision. Factors such as age, length of supervision and the area of practice were found to be the predictor variables with a negative and significant influence on the quality of clinical supervision. Factors that influence the perceived quality of clinical supervision among occupational therapists have been identified. High quality clinical supervision is an important component of clinical governance and has been shown to be beneficial to practitioners, patients and the organisation. Information on factors that make clinical supervision effective identified in this study can be added to existing supervision training and practices to improve the quality of clinical supervision. © 2016 Occupational Therapy Australia.
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Supervision Experiences of Professional Counselors Providing Crisis Counseling
ERIC Educational Resources Information Center
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.
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Tian, Zengshan; Xu, Kunjie; Yu, Xiang
2014-01-01
This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. PMID:24683349
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Zhou, Mu; Tian, Zengshan; Xu, Kunjie; Yu, Xiang; Wu, Haibo
2014-01-01
This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future.
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28 CFR 810.1 - Supervision contact requirements.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 28 Judicial Administration 2 2011-07-01 2011-07-01 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...
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28 CFR 810.1 - Supervision contact requirements.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 28 Judicial Administration 2 2014-07-01 2014-07-01 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...
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28 CFR 810.1 - Supervision contact requirements.
Code of Federal Regulations, 2010 CFR
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...
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28 CFR 810.1 - Supervision contact requirements.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 28 Judicial Administration 2 2012-07-01 2012-07-01 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...
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28 CFR 810.1 - Supervision contact requirements.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 28 Judicial Administration 2 2013-07-01 2013-07-01 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...
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20 CFR 656.21 - Supervised recruitment.
Code of Federal Regulations, 2010 CFR
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...
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Foxwell, Aleksandra A; Kennard, Beth D; Rodgers, Cynthia; Wolfe, Kristin L; Cassedy, Hannah F; Thomas, Anna
2017-12-01
Supervision has recently been recognized as a core competency for clinical psychologists. This recognition of supervision as a distinct competency has evolved in the context of an overall focus on competency-based education and training in health service psychology, and has recently gained momentum. Few clinical psychology doctoral programs offer formal training experiences in providing supervision. A pilot peer mentorship program (PMP) where graduate students were trained in the knowledge and practice of supervision was developed. The focus of the PMP was to develop basic supervision skills in advanced clinical psychology graduate students, as well as to train junior doctoral students in fundamental clinical and practical skills. Advanced doctoral students were matched to junior doctoral students to gain experience in and increase knowledge base in best practices of supervision skills. The 9-month program consisted of monthly mentorship meetings and three training sessions. The results suggested that mentors reported a 30% or more shift from the category of not competent to needs improvement or competent, in the following supervision competencies: theories of supervision, improved skill in supervision modalities, acquired knowledge in supervision, and supervision experience. Furthermore, 50% of the mentors reported that they were not competent in supervision experience at baseline and only 10% reported that they were not competent at the end of the program. Satisfaction data suggested that satisfaction with the program was high, with 75% of participants indicating increased knowledge base in supervision, and 90% indicating that it was a positive addition to their training program. This program was feasible and acceptable and appears to have had a positive impact on the graduate students who participated. Students reported both high satisfaction with the program as well as an increase in knowledge base and experience in supervision skills.
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NASA Astrophysics Data System (ADS)
Molina, J. M.; Zaitchik, B. F.
2016-12-01
Recent findings considering high CO2 emission scenarios (RCP8.5) suggest that the tropical Andes may experience a massive warming and a significant precipitation increase (decrease) during the wet (dry) seasons by the end of the 21st century. Variations on rainfall-streamflow relationships and seasonal crop yields significantly affect human development in this region and make local communities highly vulnerable to climate change and variability. We developed an expert-informed empirical statistical downscaling (ESD) algorithm to explore and construct robust global climate predictors to perform skillful RCP8.5 projections of in-situ March-May (MAM) precipitation required for impact modeling and adaptation studies. We applied our framework to a topographically-complex region of the Colombian Andes where a number of previous studies have reported El Niño-Southern Oscillation (ENSO) as the main driver of climate variability. Supervised machine learning algorithms were trained with customized and bias-corrected predictors from NCEP reanalysis, and a cross-validation approach was implemented to assess both predictive skill and model selection. We found weak and not significant teleconnections between precipitation and lagged seasonal surface temperatures over El Niño3.4 domain, which suggests that ENSO fails to explain MAM rainfall variability in the study region. In contrast, series of Sea Level Pressure (SLP) over American Samoa -likely associated with the South Pacific Convergence Zone (SPCZ)- explains more than 65% of the precipitation variance. The best prediction skill was obtained with Selected Generalized Additive Models (SGAM) given their ability to capture linear/nonlinear relationships present in the data. While SPCZ-related series exhibited a positive linear effect in the rainfall response, SLP predictors in the north Atlantic and central equatorial Pacific showed nonlinear effects. A multimodel (MIROC, CanESM2 and CCSM) ensemble of ESD projections revealed an increased variability and a positive and significant trend in the MAM precipitation mean in the next decades, with accentuated changes and projection uncertainty after 2050. ESD traces (2050-2100) from MIROC presented the highest changes in the precipitation mean ( 60%) when compared with the observations.
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NASA Technical Reports Server (NTRS)
Cho, Jeongho; Principe, Jose C.; Erdogmus, Deniz; Motter, Mark A.
2005-01-01
The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.
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28 CFR 2.94 - Supervision reports to Commission.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Supervision reports to Commission. 2.94 Section 2.94 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT... Parolees § 2.94 Supervision reports to Commission. An initial supervision report to confirm the...
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28 CFR 2.207 - Supervision reports to Commission.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Supervision reports to Commission. 2.207 Section 2.207 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT....207 Supervision reports to Commission. A regular supervision report shall be submitted to the...
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28 CFR 2.94 - Supervision reports to Commission.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 28 Judicial Administration 1 2013-07-01 2013-07-01 false Supervision reports to Commission. 2.94 Section 2.94 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT... Parolees § 2.94 Supervision reports to Commission. An initial supervision report to confirm the...
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28 CFR 2.94 - Supervision reports to Commission.
Code of Federal Regulations, 2010 CFR
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... Parolees § 2.94 Supervision reports to Commission. An initial supervision report to confirm the...
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28 CFR 2.207 - Supervision reports to Commission.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 28 Judicial Administration 1 2013-07-01 2013-07-01 false Supervision reports to Commission. 2.207 Section 2.207 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT....207 Supervision reports to Commission. A regular supervision report shall be submitted to the...
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28 CFR 2.94 - Supervision reports to Commission.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 28 Judicial Administration 1 2014-07-01 2014-07-01 false Supervision reports to Commission. 2.94 Section 2.94 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT... Parolees § 2.94 Supervision reports to Commission. An initial supervision report to confirm the...
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28 CFR 2.207 - Supervision reports to Commission.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 28 Judicial Administration 1 2012-07-01 2012-07-01 false Supervision reports to Commission. 2.207 Section 2.207 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT....207 Supervision reports to Commission. A regular supervision report shall be submitted to the...
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28 CFR 2.207 - Supervision reports to Commission.
Code of Federal Regulations, 2010 CFR
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....207 Supervision reports to Commission. A regular supervision report shall be submitted to the...
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28 CFR 2.94 - Supervision reports to Commission.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 28 Judicial Administration 1 2012-07-01 2012-07-01 false Supervision reports to Commission. 2.94 Section 2.94 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT... Parolees § 2.94 Supervision reports to Commission. An initial supervision report to confirm the...
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28 CFR 2.207 - Supervision reports to Commission.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 28 Judicial Administration 1 2014-07-01 2014-07-01 false Supervision reports to Commission. 2.207 Section 2.207 Judicial Administration DEPARTMENT OF JUSTICE PAROLE, RELEASE, SUPERVISION AND RECOMMITMENT....207 Supervision reports to Commission. A regular supervision report shall be submitted to the...
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Effectiveness of Group Supervision versus Combined Group and Individual Supervision.
ERIC Educational Resources Information Center
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…
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Touchet, Bryan; Walker, Ashley; Flanders, Sarah; McIntosh, Heather
2018-04-01
In the first year of training, psychiatry residents progress from direct supervision to indirect supervision but factors predicting time to transition between these levels of supervision are unknown. This study aimed to examine times for transition to indirect levels of supervision and to identify resident factors associated with slower progression. The authors compiled data from training files from years 2011-2015, including licensing exam scores, age, gender, medical school, month of first inpatient psychiatry rotation, and transition times between levels of supervision. Correlational analysis examined the relationship between these factors. Univariate analysis further examined the relationship between medical school training and transition times between supervision levels. Among the factors studied, only international medical school training was positively correlated with time to transition to indirect supervision and between levels of indirect supervision. International medical graduate (IMG) interns in psychiatry training may benefit from additional training and support to reach competencies required for the transition to indirect supervision.
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Receptive field optimisation and supervision of a fuzzy spiking neural network.
Glackin, Cornelius; Maguire, Liam; McDaid, Liam; Sayers, Heather
2011-04-01
This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train firing rates and behave in a similar manner as fuzzy membership functions. The connectivity of the hidden and output layers in the fuzzy spiking neural network (FSNN) is representative of a fuzzy rule base. Fuzzy C-Means clustering is utilised to produce clusters that represent the antecedent part of the fuzzy rule base that aid classification of the feature data. Suitable cluster widths are determined using two strategies; subjective thresholding and evolutionary thresholding respectively. The former technique typically results in compact solutions in terms of the number of neurons, and is shown to be particularly suited to small data sets. In the latter technique a pool of cluster candidates is generated using Fuzzy C-Means clustering and then a genetic algorithm is employed to select the most suitable clusters and to specify cluster widths. In both scenarios, the network is supervised but learning only occurs locally as in the biological case. The advantages and disadvantages of the network topology for the Fisher Iris and Wisconsin Breast Cancer benchmark classification tasks are demonstrated and directions of current and future work are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Agoraphobia: an outreach treatment programme.
Croft, Alison; Hackmann, Ann
2013-05-01
Agoraphobia is disabling and clients find it hard to access effective treatment. This paper describes the development of an inexpensive service, delivered by trained volunteers in or near the client's own home. We describe the development of the service, including selection, training and supervision. Outcomes were evaluated over 5 years, and compared with those available from the local psychology service. Effect sizes on all measures were high. Benchmarking indicated that results on comparable measures were not significantly different from the local psychology service. As in many previous studies drop-out rate was fairly high. This model worked well, and was inexpensive and effective. Further research on long term outcome and methods of enhancing engagement is needed.
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Buus, Niels; Delgado, Cynthia; Traynor, Michael; Gonge, Henrik
2018-04-01
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 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 an informant was in favour of supervision, but presented practical reasons for not participating; and (ii) 'deliberate rejection', where an informant intentionally chose to not to participate in supervision. Furthermore, we described two typical themes drawn upon by informants in their positioning: 'difficulties related to participating in supervision' and 'limited need for and benefits from supervision'. The findings indicated that group clinical supervision extended a space for group discussion that generated or accentuated anxiety because of already-existing conflicts and a fundamental lack of trust between group members. Many informants perceived group clinical supervision as an unacceptable intrusion, which could indicate a need for developing more acceptable types of post-registration clinical education and reflective practice for this group. © 2017 Australian College of Mental Health Nurses Inc.
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McMahon, Aisling; Errity, Darina
2014-01-01
This study aimed to provide the first detailed survey of Irish psychologists' supervision practices as well as to identify what is related to satisfaction with supervisory support and to confidence in providing supervision. An online survey was distributed nationwide to Irish psychologists. Participants were mostly clinical and counselling psychologists. Three-quarters of the participants constituted 51% of the total population of Irish health service psychologists, the remainder working in various non-health service settings. The results showed that most Irish psychologists attend supervision but at a low frequency, typically once monthly. One-third were dissatisfied with their supervision, greater satisfaction being related to having more frequent clinical supervision and having external individual clinical supervision. Having a safe and trustworthy relationship with supervisors was a dominant issue, and two-thirds of psychologists wanted separation of their clinical and line management supervision. Although 70% were supervisors, only 40% were confident in their supervisory skills and just 16% had formal supervisor training. Independent predictors of supervisory confidence were experience as a psychologist, having formal supervisor training, experience as a supervisor and confidence as a therapist. A novel finding was that longer experience of personal therapy was related to greater confidence as a supervisor. This study indicates the need for access to more frequent clinical supervision to be facilitated for psychologists and for there to be clear separation of line management and clinical supervision. It is also essential that more resources are put into training supervisors. While most psychologists are engaged in supervision, frequency of attendance is low, with more satisfied psychologists having more frequent supervision. Most psychologists want separation of their clinical and line management supervision and have a preference for external supervision, safe and trustworthy relationships with supervisors being their primary concern. Only 16% of psychologists had formal training in supervision but having such training significantly contributed to greater confidence as a supervisor, indicating an urgent need to provide more supervisor training for psychologists. Copyright © 2013 John Wiley & Sons, Ltd.
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Post-Degree Clinical Supervision of School Counselors.
ERIC Educational Resources Information Center
Sutton, John M., Jr.; Page, Betsy J.
1994-01-01
Questionnaires were mailed to public school counselors to examine the latter's state of supervision. Although 63% of counselors desired supervision, only 20% were being supervised. This lack of involvement by counselors may indicate confusion in an evolving profession as well as the profession's ambivalent feelings toward supervision. (RJM)
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Lazarus, M
1999-01-01
HIV-positive support groups, together with hospital pharmacists in Thailand are fighting the high cost and lack of access to pharmaceuticals by producing and distributing herbal medicines. In Theung district, Chiang Rai province, members of the local support group for people with HIV produce their own, low-cost, herbal medicines. Although the herbal medicines they produce do not provide a cure for HIV/AIDS, they do offer relief for some of the symptoms of opportunistic infections. The herbs are prepared by the group members under the supervision of the pharmacy department at the district hospital. Local people judge their effectiveness by hearing testimonials from people who have witnessed improvement in symptoms. In response to the popularity and effectiveness of herbal medicines, the Ministry of Public Health has approved plans to sell products derived from local herbs in the pharmacies of government hospitals.
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1999-06-01
This project seeks to help reduce the vulnerability of young Cambodians aged 12-25 to HIV/AIDS and sexually transmitted diseases (STDs) by strengthening nongovernmental organization (NGO) capacity to develop sustainable, effective and appropriate responses to HIV/AIDS and STDs. The strategies include strengthening local NGO capacity, sharing technical support concerning HIV/AIDS, and working together to develop information, education and communication on HIV/AIDS. Main activities included in the project are: 1) enable NGOs to undertake broader response to HIV/STDs by mobilizing, selecting, contracting, monitoring and supervising local NGO projects; 2) enhance local NGO capacity to work with the youth by organizing specialist training workshops, providing technical support and training in external relations and sustainability, and promoting local NGO/youth volunteer exchange and exposure programs; 3) strengthen the capacity of local NGOs through training, skill building, technical support and development of NGO support program; and 4) improve the knowledge base of programming for youth by identifying, documenting and disseminating effective programming models and tools.
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7 CFR 800.215 - Activities that shall be supervised.
Code of Federal Regulations, 2010 CFR
2010-01-01
... REGULATIONS Supervision, Monitoring, and Equipment Testing § 800.215 Activities that shall be supervised. (a) General. Supervision of the activities described in this section shall be performed in accordance with the... 7 Agriculture 7 2010-01-01 2010-01-01 false Activities that shall be supervised. 800.215 Section...
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Feminist Identity and Theories as Correlates of Feminist Supervision Practices. Conference
ERIC Educational Resources Information Center
Szymanski, Dawn M.
2005-01-01
Although feminist supervision approaches have been advanced in the literature as alternatives or adjuncts to traditional supervision models, little is known about those who utilize feminist supervision practices. This study was designed to examine if feminist supervision practices were related to one's own feminist identity and various beliefs…
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Clinical Supervision Strategies for School Counselors Working with Twice-Exceptional Students
ERIC Educational Resources Information Center
Goldsmith, SaDohl K.
2012-01-01
Clinical supervision is a way for counselors in training to develop needed skills (Bernard & Goodyear, 1998). Best practices indicate that counselors trained in the application of supervision theory should provide clinical supervision. However, many school counselors receive administrative supervision by non-counseling professionals who may…
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Educational Supervision Appropriate for Psychiatry Trainee's Needs
ERIC Educational Resources Information Center
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…
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27 CFR 19.75 - Assignment of officers and supervision of operations.
Code of Federal Regulations, 2010 CFR
2010-04-01
... supervision of operations. 19.75 Section 19.75 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX... Miscellaneous Provisions Activities Not Subject to This Part § 19.75 Assignment of officers and supervision of... maintain supervision of operations conducted at such plants. When supervision is necessary: (1) The...
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20 CFR 702.407 - Supervision of medical care.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 20 Employees' Benefits 3 2011-04-01 2011-04-01 false Supervision of medical care. 702.407 Section... Care and Supervision § 702.407 Supervision of medical care. The Director, OWCP, through the district... the Act. Such supervision shall include: (a) The requirement that periodic reports on the medical care...
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48 CFR 52.247-12 - Supervision, Labor, or Materials.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 48 Federal Acquisition Regulations System 2 2011-10-01 2011-10-01 false Supervision, Labor, or....247-12 Supervision, Labor, or Materials. As prescribed in 47.207-5(b), insert a clause substantially... when the contractor is required to furnish supervision, labor, or materials: Supervision, Labor, or...
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20 CFR 702.407 - Supervision of medical care.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 20 Employees' Benefits 4 2013-04-01 2013-04-01 false Supervision of medical care. 702.407 Section... Care and Supervision § 702.407 Supervision of medical care. The Director, OWCP, through the district... the Act. Such supervision shall include: (a) The requirement that periodic reports on the medical care...
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27 CFR 19.706 - Supervision of operations.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 27 Alcohol, Tobacco Products and Firearms 1 2013-04-01 2013-04-01 false Supervision of operations... Authorities § 19.706 Supervision of operations. TTB may assign appropriate TTB officers to supervise...), § 19.13 (assignment of officers and supervision of operations), § 19.17 (detention of containers), § 19...
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27 CFR 19.706 - Supervision of operations.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 27 Alcohol, Tobacco Products and Firearms 1 2012-04-01 2012-04-01 false Supervision of operations... Authorities § 19.706 Supervision of operations. TTB may assign appropriate TTB officers to supervise...), § 19.13 (assignment of officers and supervision of operations), § 19.17 (detention of containers), § 19...
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48 CFR 52.247-12 - Supervision, Labor, or Materials.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 2 2010-10-01 2010-10-01 false Supervision, Labor, or....247-12 Supervision, Labor, or Materials. As prescribed in 47.207-5(b), insert a clause substantially... when the contractor is required to furnish supervision, labor, or materials: Supervision, Labor, or...
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27 CFR 19.706 - Supervision of operations.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 27 Alcohol, Tobacco Products and Firearms 1 2014-04-01 2014-04-01 false Supervision of operations... Authorities § 19.706 Supervision of operations. TTB may assign appropriate TTB officers to supervise...), § 19.13 (assignment of officers and supervision of operations), § 19.17 (detention of containers), § 19...
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20 CFR 702.407 - Supervision of medical care.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 20 Employees' Benefits 4 2014-04-01 2014-04-01 false Supervision of medical care. 702.407 Section... Care and Supervision § 702.407 Supervision of medical care. The Director, OWCP, through the district... the Act. Such supervision shall include: (a) The requirement that periodic reports on the medical care...
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48 CFR 52.247-12 - Supervision, Labor, or Materials.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 48 Federal Acquisition Regulations System 2 2014-10-01 2014-10-01 false Supervision, Labor, or....247-12 Supervision, Labor, or Materials. As prescribed in 47.207-5(b), insert a clause substantially... when the contractor is required to furnish supervision, labor, or materials: Supervision, Labor, or...
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20 CFR 702.407 - Supervision of medical care.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 20 Employees' Benefits 4 2012-04-01 2012-04-01 false Supervision of medical care. 702.407 Section... Care and Supervision § 702.407 Supervision of medical care. The Director, OWCP, through the district... the Act. Such supervision shall include: (a) The requirement that periodic reports on the medical care...
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27 CFR 19.706 - Supervision of operations.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 27 Alcohol, Tobacco Products and Firearms 1 2011-04-01 2011-04-01 false Supervision of operations... Authorities § 19.706 Supervision of operations. TTB may assign appropriate TTB officers to supervise...), § 19.13 (assignment of officers and supervision of operations), § 19.17 (detention of containers), § 19...
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20 CFR 702.407 - Supervision of medical care.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Supervision of medical care. 702.407 Section... and Supervision § 702.407 Supervision of medical care. The Director, OWCP, through the district... the Act. Such supervision shall include: (a) The requirement that periodic reports on the medical care...
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Opportunities to Learn Scientific Thinking in Joint Doctoral Supervision
ERIC Educational Resources Information Center
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…
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28 CFR 810.3 - Consequences of violating the conditions of supervision.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 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. (a) If your CSO has reason to believe that you are...
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An Investigation of Factors Involved When Educational Psychologists sSupervise Other Professionals
ERIC Educational Resources Information Center
Callicott, Katie; Leadbetter, Jane
2013-01-01
Inter-professional supervision combines the social processes of supervision and multi-agency working: both complex and often poorly understood processes. This paper discusses the first author's research of inter-professional supervision, involving an educational psychologist (EP) supervising another professional and complements the recently…
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48 CFR 52.247-12 - Supervision, Labor, or Materials.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 2 2012-10-01 2012-10-01 false Supervision, Labor, or....247-12 Supervision, Labor, or Materials. As prescribed in 47.207-5(b), insert a clause substantially... when the contractor is required to furnish supervision, labor, or materials: Supervision, Labor, or...
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48 CFR 52.247-12 - Supervision, Labor, or Materials.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 2 2013-10-01 2013-10-01 false Supervision, Labor, or....247-12 Supervision, Labor, or Materials. As prescribed in 47.207-5(b), insert a clause substantially... when the contractor is required to furnish supervision, labor, or materials: Supervision, Labor, or...
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28 CFR 2.204 - Conditions of supervised release.
Code of Federal Regulations, 2011 CFR
2011-07-01
... schedule. (iii) If the term of supervision results from a conviction for a domestic violence crime, and... the program of a community corrections center, or both, for all or part of the period of supervision... Columbia; (2) Supervision officer means a Community Supervision Officer of the District of Columbia Court...
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Security system signal supervision
DOE Office of Scientific and Technical Information (OSTI.GOV)
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.
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Sirola-Karvinen, Pirjo; Hyrkäs, Kristiina
2008-07-01
The aim of this article is to increase knowledge and understanding of administrative clinical supervision. Administrative clinical supervision is a learning process for leaders that is based on experiences. Only a few studies have focused on administrative clinical supervision. The materials for this study were evaluations collected in 2002-2005 using a clinical supervision evaluation scale (MCSS). The respondents (n = 126) in the study were nursing leaders representing different specialties. The data were analysed statistically. The findings showed that the supervision succeeded very well. The contents of the sessions differed depending on the nurse leader's position. Significant differences were found in the evaluations between specialties and within years of work experience. Clinical supervision was utilized best in the psychiatric and mental health sector. The supervisees' who had long work experience scored the importance and value of clinical supervision as high. Clinical supervision is beneficial for nursing leaders. The experiences were positive and the nursing leaders appreciated the importance and value of clinical supervision. It is important to plan and coordinate a longitudinal evaluation so that clinical supervision for nursing leaders is systematically implemented and continuously developed.
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Yee, Kwang Chien; Madden, Angela; Nash, Rosie; Connolly, Michael
2017-01-01
Clinical communication and clinical supervision of junior healthcare professionals are identified as the two most common preventable factors to reduce medical errors. While multiple strategies have been implemented to improve clinical communication, clinical supervision has not attracted as much attention. This is in part due to the lack of understanding of clinical supervision. Furthermore, there is a lack of exploration of information communication technology (ICT) in assisting the delivery of clinical supervision from the perspective of users (i.e. junior clinicians). This paper presents a study to understand clinical supervision from the perspective of medical and pharmacy interns. The important elements of good clinical supervisors and good clinical supervision have been presented in this paper based on our study. More importantly, our results suggest a distinction between good supervisors and good supervisions. Both these factors impact on patient safety. Through discussion of user requirements of good supervision by users (interns), this paper then explores and presents a conceptual framework to assist in the discussion and design of ICT by healthcare organisations to improve clinical supervision of interns and therefore improve patient safety.
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Adaptive local linear regression with application to printer color management.
Gupta, Maya R; Garcia, Eric K; Chin, Erika
2008-06-01
Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of neighbors used in estimation is fixed to be a global "optimal" value, chosen by cross validation. This paper proposes adapting the number of neighbors used for estimation to the local geometry of the data, without need for cross validation. The term enclosing neighborhood is introduced to describe a set of neighbors whose convex hull contains the test point when possible. It is proven that enclosing neighborhoods yield bounded estimation variance under some assumptions. Three such enclosing neighborhood definitions are presented: natural neighbors, natural neighbors inclusive, and enclosing k-NN. The effectiveness of these neighborhood definitions with local linear regression is tested for estimating lookup tables for color management. Significant improvements in error metrics are shown, indicating that enclosing neighborhoods may be a promising adaptive neighborhood definition for other local learning tasks as well, depending on the density of training samples.
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Trapé, Átila Alexandre; Marques, Renato Francisco Rodrigues; Lizzi, Elisângela Aparecida da Silva; Yoshimura, Fernando Eidi; Franco, Laercio Joel; Zago, Anderson Saranz
2017-01-01
To investigate the association between both demographic and socioeconomic conditions with physical fitness and regular practice of physical exercises in participants of community projects, supervised by a physical education teacher. This enabled to investigate whether the adoption of an active lifestyle depends only on the personal choice or has any influence of socioeconomic factors. 213 individuals aged over 50 years joined the study, and provided information about their socioeconomic status (age, gender, education/years of study, and income); usual level of physical activity (ULPA); and physical fitness, by a physical battery tests which allowed the calculation of general functional fitness index (GFFI). The generalized linear model showed that participants ranked in the highest GFFI groups (good and very good) had more years of study and higher income (p < 0.05). The multiple linear regression model complements the previous analysis, demonstrating the magnitude of the change in the GFFI in association with the years of study (group > 15), income (all groups) and age (p < 0.05). By means of analysis of variance, a difference between the groups was verified and longer practice of exercises (> 6 months) were also associated with education and income (p < 0.05); among the groups with exercise practice whether greater than or equal to six months, that supervised showed better results in the GFFI (p < 0.05). The association between variables strengthens the hypothesis that adherence and maintenance of physical exercise might not be only dependent of individual's choice, but also the socioeconomic factors, which can influence the choice for any active lifestyle.
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Dazard, Jean-Eudes; Rao, J. Sunil
2010-01-01
The search for structures in real datasets e.g. in the form of bumps, components, classes or clusters is important as these often reveal underlying phenomena leading to scientific discoveries. One of these tasks, known as bump hunting, is to locate domains of a multidimensional input space where the target function assumes local maxima without pre-specifying their total number. A number of related methods already exist, yet are challenged in the context of high dimensional data. We introduce a novel supervised and multivariate bump hunting strategy for exploring modes or classes of a target function of many continuous variables. This addresses the issues of correlation, interpretability, and high-dimensionality (p ≫ n case), while making minimal assumptions. The method is based upon a divide and conquer strategy, combining a tree-based method, a dimension reduction technique, and the Patient Rule Induction Method (PRIM). Important to this task, we show how to estimate the PRIM meta-parameters. Using accuracy evaluation procedures such as cross-validation and ROC analysis, we show empirically how the method outperforms a naive PRIM as well as competitive non-parametric supervised and unsupervised methods in the problem of class discovery. The method has practical application especially in the case of noisy high-throughput data. It is applied to a class discovery problem in a colon cancer micro-array dataset aimed at identifying tumor subtypes in the metastatic stage. Supplemental Materials are available online. PMID:22399839
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NASA Astrophysics Data System (ADS)
Förner, K.; Polifke, W.
2017-10-01
The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.
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NASA Technical Reports Server (NTRS)
Barker, L. E., Jr.; Bowles, R. L.; Williams, L. H.
1973-01-01
High angular rates encountered in real-time flight simulation problems may require a more stable and accurate integration method than the classical methods normally used. A study was made to develop a general local linearization procedure of integrating dynamic system equations when using a digital computer in real-time. The procedure is specifically applied to the integration of the quaternion rate equations. For this application, results are compared to a classical second-order method. The local linearization approach is shown to have desirable stability characteristics and gives significant improvement in accuracy over the classical second-order integration methods.
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Semi-supervised vibration-based classification and condition monitoring of compressors
NASA Astrophysics Data System (ADS)
Potočnik, Primož; Govekar, Edvard
2017-09-01
Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors.
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Automated Detection of Microaneurysms Using Scale-Adapted Blob Analysis and Semi-Supervised Learning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Adal, Kedir M.; Sidebe, Desire; Ali, Sharib
2014-01-07
Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are then introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier to detect true MAs. The developed system is built using onlymore » few manually labeled and a large number of unlabeled retinal color fundus images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. A competition performance measure (CPM) of 0.364 shows the competitiveness of the proposed system against state-of-the art techniques as well as the applicability of the proposed features to analyze fundus images.« less
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Malmberg-Heimonen, Ira; Natland, Sidsel; Tøge, Anne Grete; Hansen, Helle Cathrine
2016-01-01
Using a cluster-randomised design, this study analyses the effects of a government-administered skill training programme for social workers in Norway. The training programme aims to improve social workers' professional competences by enhancing and systematising follow-up work directed towards longer-term unemployed clients in the following areas: encountering the user, system-oriented efforts and administrative work. The main tools and techniques of the programme are based on motivational interviewing and appreciative inquiry. The data comprise responses to baseline and eighteen-month follow-up questionnaires administered to all social workers (n = 99) in eighteen participating Labour and Welfare offices randomised into experimental and control groups. The findings indicate that the skill training programme positively affected the social workers' evaluations of their professional competences and quality of work supervision received. The acquisition and mastering of combinations of specific tools and techniques, a comprehensive supervision structure and the opportunity to adapt the learned skills to local conditions were important in explaining the results. PMID:27559232
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Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites
Schiess, Mathieu; Urbanczik, Robert; Senn, Walter
2016-01-01
In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the unique advantage of active dendrites for implementing powerful synaptic plasticity rules that have access to downstream information via backpropagation of action potentials. PMID:26841235
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Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław
2014-06-05
"SmartMonitor" is an intelligent security system based on image analysis that combines the advantages of alarm, video surveillance and home automation systems. The system is a complete solution that automatically reacts to every learned situation in a pre-specified way and has various applications, e.g., home and surrounding protection against unauthorized intrusion, crime detection or supervision over ill persons. The software is based on well-known and proven methods and algorithms for visual content analysis (VCA) that were appropriately modified and adopted to fit specific needs and create a video processing model which consists of foreground region detection and localization, candidate object extraction, object classification and tracking. In this paper, the "SmartMonitor" system is presented along with its architecture, employed methods and algorithms, and object analysis approach. Some experimental results on system operation are also provided. In the paper, focus is put on one of the aforementioned functionalities of the system, namely supervision over ill persons.
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Mahapatra, Dwarikanath; Schueffler, Peter; Tielbeek, Jeroen A W; Buhmann, Joachim M; Vos, Franciscus M
2013-10-01
Increasing incidence of Crohn's disease (CD) in the Western world has made its accurate diagnosis an important medical challenge. The current reference standard for diagnosis, colonoscopy, is time-consuming and invasive while magnetic resonance imaging (MRI) has emerged as the preferred noninvasive procedure over colonoscopy. Current MRI approaches assess rate of contrast enhancement and bowel wall thickness, and rely on extensive manual segmentation for accurate analysis. We propose a supervised learning method for the identification and localization of regions in abdominal magnetic resonance images that have been affected by CD. Low-level features like intensity and texture are used with shape asymmetry information to distinguish between diseased and normal regions. Particular emphasis is laid on a novel entropy-based shape asymmetry method and higher-order statistics like skewness and kurtosis. Multi-scale feature extraction renders the method robust. Experiments on real patient data show that our features achieve a high level of accuracy and perform better than two competing methods.
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Clinical supervision: the state of the art.
Falender, Carol A; Shafranske, Edward P
2014-11-01
Since the recognition of clinical supervision as a distinct professional competence and a core competence, attention has turned to ensuring supervisor competence and effective supervision practice. In this article, we highlight recent developments and the state of the art in supervision, with particular emphasis on the competency-based approach. We present effective clinical supervision strategies, providing an integrated snapshot of the current status. We close with consideration of current training practices in supervision and challenges. © 2014 Wiley Periodicals, Inc.
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SemiBoost: boosting for semi-supervised learning.
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.
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Noh, Min-Ki; Lee, Baek-Soo; Kim, Shin-Yeop; Jeon, Hyeran Helen; Kim, Seong-Hun; Nelson, Gerald
2017-11-01
This article presents an alternate surgical treatment method to correct a severe anterior protrusion in an adult patient with an extremely thin alveolus. To accomplish an effective and efficient anterior segmental retraction without periodontal complications, the authors performed, under local anesthesia, a wide linear corticotomy and corticision in the maxilla and an anterior segmental osteotomy in mandible. In the maxilla, a wide linear corticotomy was performed under local anesthesia. In the maxillary first premolar area, a wide section of cortical bone was removed. Retraction forces were applied buccolingually with the aid of temporary skeletal anchorage devices. Corticision was later performed to close residual extraction space. In the mandible, an anterior segmental osteotomy was performed and the first premolars were extracted under local anesthesia. In the maxilla, a wide linear corticotomy facilitated a bony block movement with temporary skeletal anchorage devices, without complications. The remaining extraction space after the bony block movement was closed effectively, accelerated by corticision. In the mandible, anterior segmental retraction was facilitated by an anterior segmental osteotomy performed under local anesthesia. Corticision was later employed to accelerate individual tooth movements. A wide linear corticotomy and an anterior segmental osteotomy combined with corticision can be an effective and efficient alternative to conventional orthodontic treatment in the bialveolar protrusion patient with an extremely thin alveolar housing.
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Rethinking Research Supervision: Some Reflections from the Field of Employment Relations
ERIC Educational Resources Information Center
Bingham, Cecilie; Durán-Palma, Fernando
2014-01-01
This essay offers some reflections for the theory and practice of research supervision drawn from the field of employment relations. It argues that rethinking supervision in terms of the employment relationship can advance dialogue and debate about supervision. This is twofold. (1) Reframing supervision in terms of the employment relationship can…
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ERIC Educational Resources Information Center
Tubsuli, Nattapong; Julsuwan, Suwat; Tesaputa, Kowat
2017-01-01
Internal supervision in the school is currently experiencing various problems. Supervision preparation problems are related to: lacking of supervision plan, lacking of holistic and systematic planning, and lacking of analysis in current conditions or requirements. While supervision operational problems are included: lacking of supervision…
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Supervision that Improves Teaching: Strategies and Techniques. Second Edition
ERIC Educational Resources Information Center
Sullivan, Susan; Glanz, Jeffrey
2004-01-01
In this exciting, new edition of "Supervision That Improves Teaching," the authors have taken their reflective clinical supervision process to a new level, with the planning conference now the heart of the supervision cycle. Sullivan and Glanz have addressed the dilemmas of preserving meaningful supervision in an era of high-stakes…
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Gonge, Henrik; Buus, Niels
2016-05-01
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 (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 that a) diminishing experience of social support from colleagues was associated with reduced participation in clinical supervision, while b) additional quantitative demands were associated with staff reporting difficulties finding time for supervision. This probably explained a negative development in the experienced effectiveness of supervision. It is concluded that organizational support is an imperative for implementation of clinical supervision.
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NASA Astrophysics Data System (ADS)
Lin, Chuang; Wang, Binghui; Jiang, Ning; Farina, Dario
2018-04-01
Objective. This paper proposes a novel simultaneous and proportional multiple degree of freedom (DOF) myoelectric control method for active prostheses. Approach. The approach is based on non-negative matrix factorization (NMF) of surface EMG signals with the inclusion of sparseness constraints. By applying a sparseness constraint to the control signal matrix, it is possible to extract the basis information from arbitrary movements (quasi-unsupervised approach) for multiple DOFs concurrently. Main Results. In online testing based on target hitting, able-bodied subjects reached a greater throughput (TP) when using sparse NMF (SNMF) than with classic NMF or with linear regression (LR). Accordingly, the completion time (CT) was shorter for SNMF than NMF or LR. The same observations were made in two patients with unilateral limb deficiencies. Significance. The addition of sparseness constraints to NMF allows for a quasi-unsupervised approach to myoelectric control with superior results with respect to previous methods for the simultaneous and proportional control of multi-DOF. The proposed factorization algorithm allows robust simultaneous and proportional control, is superior to previous supervised algorithms, and, because of minimal supervision, paves the way to online adaptation in myoelectric control.
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Learning With Mixed Hard/Soft Pointwise Constraints.
Gnecco, Giorgio; Gori, Marco; Melacci, Stefano; Sanguineti, Marcello
2015-09-01
A learning paradigm is proposed and investigated, in which the classical framework of learning from examples is enhanced by the introduction of hard pointwise constraints, i.e., constraints imposed on a finite set of examples that cannot be violated. Such constraints arise, e.g., when requiring coherent decisions of classifiers acting on different views of the same pattern. The classical examples of supervised learning, which can be violated at the cost of some penalization (quantified by the choice of a suitable loss function) play the role of soft pointwise constraints. Constrained variational calculus is exploited to derive a representer theorem that provides a description of the functional structure of the optimal solution to the proposed learning paradigm. It is shown that such an optimal solution can be represented in terms of a set of support constraints, which generalize the concept of support vectors and open the doors to a novel learning paradigm, called support constraint machines. The general theory is applied to derive the representation of the optimal solution to the problem of learning from hard linear pointwise constraints combined with soft pointwise constraints induced by supervised examples. In some cases, closed-form optimal solutions are obtained.
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Memarian, Negar; Torre, Jared B.; Haltom, Kate E.; Stanton, Annette L.
2017-01-01
Abstract 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. PMID:28992270
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An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.
Kundu, Kousik; Backofen, Rolf
2017-01-01
Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.
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Parker, Stephen; Suetani, Shuichi; Motamarri, Balaji
2017-12-01
The importance of clinical supervision is emphasised in psychiatric training programs. Despite this, the purpose and processes of supervision are often poorly defined. There is limited guidance available for trainees about their role in making supervision work. This paper considers the nature of supervision in psychiatric training and provides practical advice to help supervisees take active steps to make supervision work. In obtaining value from supervision, the active role of the supervisee in seeking feedback, finding value in criticism and building autonomy is emphasised. Additionally, the importance of exploring what value a supervisor can offer and maintaining realistic expectations is considered. Trainees can benefit from taking an active role in planning and managing their supervision to maximise their learning.
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Localized scleroderma: a series of 52 patients.
Toledano, C; Rabhi, S; Kettaneh, A; Fabre, B; Fardet, L; Tiev, K P; Cabane, J
2009-05-01
Localized scleroderma also called morphea is a skin disorder of undetermined cause. The widely recognized Mayo Clinic Classification identifies 5 main morphea types: plaque, generalized, bullous, linear and deep. Whether each of these distinct types has a particular clinical course or is associated with some patient-related features is still unclear. We report here a retrospective series of patients with localized scleroderma with an attempt to identify features related to the type of lesion involved. The medical records of all patients with a diagnosis of localized scleroderma were reviewed by skilled practitioners. Lesions were classified according to the Mayo Clinic Classification. The relationship between each lesion type and various clinical features was tested by non-parametrical methods. The sample of 52 patients included 43 females and 9 males. Median age at onset was 30 y (range 1-76). Frequencies of patients according to morphea types were: plaque morphea 41 (78.8%) (including morphea en plaque 30 (57.7%) and atrophoderma of Pasini-Pierini 11 (21.1%)), linear scleroderma 14 (26.9%). Nine patients (17.3%) had both types of localized scleroderma. Median age at onset was lower in patients with linear scleroderma (8 y (range 3-44)) than in others (36 y (range 1-77)) (p=0.0003). Head involvement was more common in patients with linear scleroderma (37.5%) than in other subtypes (11.1%) (p=0.05). Atrophoderma of Pasini-Pierini was never located at the head. Systemic symptoms, antinuclear antibodies and the rheumatic factor were not associated with localized scleroderma types or subtypes. These results suggest that morphea types, in adults are not associated with distinct patient features except for age at disease onset (lower) and the localization on the head (more frequent), in patients with lesions of the linear type.
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Martin, Priya; Kumar, Saravana; Lizarondo, Lucylynn; VanErp, Ans
2015-09-24
Health professionals practising in countries with dispersed populations such as Australia rely on clinical supervision for professional support. While there are directives and guidelines in place to govern clinical supervision, little is known about how it is actually conducted and what makes it effective. The purpose of this study was to explore the enablers of and barriers to high quality clinical supervision among occupational therapists across Queensland in Australia. This qualitative study took place as part of a broader project. Individual, in-depth, semi-structured interviews were conducted with occupational therapy supervisees in Queensland. The interviews explored the enablers of and barriers to high quality clinical supervision in this group. They further explored some findings from the initial quantitative study. Content analysis of the interview data resulted in eight themes. These themes were broadly around the importance of the supervisory relationship, the impact of clinical supervision and the enablers of and barriers to high quality clinical supervision. This study identified a number of factors that were perceived to be associated with high quality clinical supervision. Supervisor-supervisee matching and fit, supervisory relationship and availability of supervisor for support in between clinical supervision sessions appeared to be associated with perceptions of higher quality of clinical supervision received. Some face-to-face contact augmented with telesupervision was found to improve perceptions of the quality of clinical supervision received via telephone. Lastly, dual roles where clinical supervision and line management were provided by the same person were not considered desirable by supervisees. A number of enablers of and barriers to high quality clinical supervision were also identified. With clinical supervision gaining increasing prominence as part of organisational and professional governance, this study provides important lessons for successful and sustainable clinical supervision in practice contexts.
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Saxby, Christine; Wilson, Jill; Newcombe, Peter
2015-09-01
Clinical supervision is widely recognised as a mechanism for providing professional support, professional development and clinical governance for healthcare workers. There have been limited studies about the effectiveness of clinical supervision for allied health and minimal studies conducted within the Australian health context. The aim of the present study was to identify whether clinical supervision was perceived to be effective by allied health professionals and to identify components that contributed to effectiveness. Participants completed an anonymous online questionnaire, administered through the health service's intranet. A cross-sectional study was conducted with community allied health workers (n = 82) 8 months after implementation of structured clinical supervision. Demographic data (age, gender), work-related history (profession employment level, years of experience), and supervision practice (number and length of supervision sessions) were collected through an online survey. The outcome measure, clinical supervision effectiveness, was operationalised using the Manchester Clinical Supervision Scale-26 (MCSS-26). Data were analysed with Pearson correlation (r) and independent sample t-tests (t) with significance set at 0.05 (ie the probability of significant difference set at P < 0.05). The length of the supervision sessions (r(s) ≥ 0.44), the number of sessions (r(s) ≥ 0.35) and the total period supervision had been received (r(s) ≥ 0.42) were all significantly positively correlated with the MCSS-26 domains of clinical supervision effectiveness. Three individual variables, namely 'receiving clinical supervision', 'having some choice in the allocation of clinical supervisor' and 'having a completed clinical supervision agreement', were also significantly associated with higher total MCSS-26 scores (P(s) < 0.014). The results of the study demonstrate that when clinical supervision uses best practice principles, it can provide professional support for allied health workers, even during times of rapid organisational change.
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Recent work on material interface reconstruction
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mosso, S.J.; Swartz, B.K.
1997-12-31
For the last 15 years, many Eulerian codes have relied on a series of piecewise linear interface reconstruction algorithms developed by David Youngs. In a typical Youngs` method, the material interfaces were reconstructed based upon nearly cell values of volume fractions of each material. The interfaces were locally represented by linear segments in two dimensions and by pieces of planes in three dimensions. The first step in such reconstruction was to locally approximate an interface normal. In Youngs` 3D method, a local gradient of a cell-volume-fraction function was estimated and taken to be the local interface normal. A linear interfacemore » was moved perpendicular to the now known normal until the mass behind it matched the material volume fraction for the cell in question. But for distorted or nonorthogonal meshes, the gradient normal estimate didn`t accurately match that of linear material interfaces. Moreover, curved material interfaces were also poorly represented. The authors will present some recent work in the computation of more accurate interface normals, without necessarily increasing stencil size. Their estimate of the normal is made using an iterative process that, given mass fractions for nearby cells of known but arbitrary variable density, converges in 3 or 4 passes in practice (and quadratically--like Newton`s method--in principle). The method reproduces a linear interface in both orthogonal and nonorthogonal meshes. The local linear approximation is generally 2nd-order accurate, with a 1st-order accurate normal for curved interfaces in both two and three dimensional polyhedral meshes. Recent work demonstrating the interface reconstruction for curved surfaces will /be discussed.« less
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Parlesak, Alexandr; Geelhoed, Diederike; Robertson, Aileen
2014-06-01
Chronic undernutrition is prevalent in Mozambique, where children suffer from stunting, vitamin A deficiency, anemia, and other nutrition-related disorders. Complete diet formulation products (CDFPs) are increasingly promoted to prevent chronic undernutrition. Using linear programming, to investigate whether diet diversification using local foods should be prioritized in order to reduce the prevalence of chronic undernutrition. Market prices of local foods were collected in Tete City, Mozambique. Linear programming was applied to calculate the cheapest possible fully nutritious food baskets (FNFB) by stepwise addition of micronutrient-dense localfoods. Only the top quintile of Mozambican households, using average expenditure data, could afford the FNFB that was designed using linear programming from a spectrum of local standard foods. The addition of beef heart or liver, dried fish and fresh moringa leaves, before applying linear programming decreased the price by a factor of up to 2.6. As a result, the top three quintiles could afford the FNFB optimized using both diversification strategy and linear programming. CDFPs, when added to the baskets, were unable to overcome the micronutrient gaps without greatly exceeding recommended energy intakes, due to their high ratio of energy to micronutrient density. Dietary diversification strategies using local, low-cost, nutrient-dense foods can meet all micronutrient recommendations and overcome all micronutrient gaps. The success of linear programming to identify a low-cost FNFB depends entirely on the investigators' ability to select appropriate micronutrient-dense foods. CDFPs added to food baskets are unable to overcome micronutrient gaps without greatly exceeding recommended energy intake.
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Carlin, Charles H.; Boarman, Katie; Carlin, Emily; Inselmann, Karissa
2013-01-01
In the present feasibility study, e-supervision was used to provide university liaison supervision to speech-language pathology (SLP) graduate students enrolled in student teaching practica. Utilizing a mixed methodology approach, interview and survey data were compared in order to identify similarities and differences between in-person and e-supervision, and guide future practice. Results showed e-supervised graduate students perceived that they received adequate supervision, feedback, support, and communication. Further, e-supervision provided additional benefits to supervisors, children on the caseload, and universities. Despite the benefits, disadvantages emerged. Implications for future practice and limitations of the study were identified. PMID:25945215
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Methods of feminist family therapy supervision.
Prouty, A M; Thomas, V; Johnson, S; Long, J K
2001-01-01
Although feminist family therapy has been studied and practiced for more than 20 years, writing about feminist supervision in family therapy has been limited. Three supervision methods 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. In addition to a description of the participants' experiences of these methods, we discuss their fit with previous theoretical descriptions of feminist supervision and offer suggestions for future research.
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Clinical supervision in a community setting.
Evans, Carol; Marcroft, Emma
Clinical supervision is a formal process of professional support, reflection and learning that contributes to individual development. First Community Health and Care is committed to providing clinical supervision to nurses and allied healthcare professionals to support the provision and maintenance of high-quality care. In 2012, we developed new guidelines for nurses and AHPs on supervision, incorporating a clinical supervision framework. This offers a range of options to staff so supervision accommodates variations in work settings and individual learning needs and styles.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Adcock, T. A. A.; Taylor, P. H.
2016-01-15
The non-linear Schrödinger equation and its higher order extensions are routinely used for analysis of extreme ocean waves. This paper compares the evolution of individual wave-packets modelled using non-linear Schrödinger type equations with packets modelled using fully non-linear potential flow models. The modified non-linear Schrödinger Equation accurately models the relatively large scale non-linear changes to the shape of wave-groups, with a dramatic contraction of the group along the mean propagation direction and a corresponding extension of the width of the wave-crests. In addition, as extreme wave form, there is a local non-linear contraction of the wave-group around the crest whichmore » leads to a localised broadening of the wave spectrum which the bandwidth limited non-linear Schrödinger Equations struggle to capture. This limitation occurs for waves of moderate steepness and a narrow underlying spectrum.« less
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ERIC Educational Resources Information Center
Brown, Carleton H.; Olivárez, Artura, Jr.; DeKruyf, Loraine
2018-01-01
Supervision is a critical element in the professional identity development of school counselors; however, available school counseling-specific supervision training is lacking. The authors describe a 4-hour supervision workshop based on the School Counselor Supervision Model (SCSM; Luke & Bernard, 2006) attended by 31 school counselors from…
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31 CFR Appendix L to Subpart C of... - Office of Thrift Supervision
Code of Federal Regulations, 2012 CFR
2012-07-01
... 31 Money and Finance: Treasury 1 2012-07-01 2012-07-01 false Office of Thrift Supervision L... Supervision 1. In general. This appendix applies to the Office of Thrift Supervision. It sets forth specific... and accountings of disclosures for the Office of Thrift Supervision, will be made by the head of the...
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31 CFR Appendix L to Subpart C of... - Office of Thrift Supervision
Code of Federal Regulations, 2014 CFR
2014-07-01
... 31 Money and Finance: Treasury 1 2014-07-01 2014-07-01 false Office of Thrift Supervision L... Supervision 1. In general. This appendix applies to the Office of Thrift Supervision. It sets forth specific... and accountings of disclosures for the Office of Thrift Supervision, will be made by the head of the...
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31 CFR Appendix L to Subpart A of... - Office of Thrift Supervision
Code of Federal Regulations, 2012 CFR
2012-07-01
... 31 Money and Finance: Treasury 1 2012-07-01 2012-07-01 false Office of Thrift Supervision L...—Office of Thrift Supervision 1. In general. This appendix applies to the Office of Thrift Supervision... public reading room for the Office of Thrift Supervision is maintained at the following location: 1700 G...
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31 CFR Appendix L to Subpart A of... - Office of Thrift Supervision
Code of Federal Regulations, 2014 CFR
2014-07-01
... 31 Money and Finance: Treasury 1 2014-07-01 2014-07-01 false Office of Thrift Supervision L...—Office of Thrift Supervision 1. In general. This appendix applies to the Office of Thrift Supervision... public reading room for the Office of Thrift Supervision is maintained at the following location: 1700 G...
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31 CFR Appendix L to Subpart C of... - Office of Thrift Supervision
Code of Federal Regulations, 2013 CFR
2013-07-01
... 31 Money and Finance: Treasury 1 2013-07-01 2013-07-01 false Office of Thrift Supervision L... Supervision 1. In general. This appendix applies to the Office of Thrift Supervision. It sets forth specific... and accountings of disclosures for the Office of Thrift Supervision, will be made by the head of the...
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31 CFR Appendix L to Subpart A of... - Office of Thrift Supervision
Code of Federal Regulations, 2013 CFR
2013-07-01
... 31 Money and Finance: Treasury 1 2013-07-01 2013-07-01 false Office of Thrift Supervision L...—Office of Thrift Supervision 1. In general. This appendix applies to the Office of Thrift Supervision... public reading room for the Office of Thrift Supervision is maintained at the following location: 1700 G...
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ICT Strategies and Tools for the Improvement of Instructional Supervision. The Virtual Supervision
ERIC Educational Resources Information Center
Cano, Esteban Vazquez; Garcia, Ma. Luisa Sevillano
2013-01-01
This study aims to evaluate and analyze strategies, proposals, and ICT tools to promote a paradigm shift in educational supervision that enhances the schools of this century involved not only in teaching-face learning, but e-learning and blended learning. Traditional models of educational supervision do not guarantee adequate supervision of the…
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Imam, Bita; Miller, William C; Finlayson, Heather C; Eng, Janice J; Payne, Michael Wc; Jarus, Tal; Goldsmith, Charles H; Mitchell, Ian M
2014-12-22
The number of older adults living with lower limb amputation (LLA) who require rehabilitation for improving their walking capacity and mobility is growing. Existing rehabilitation practices frequently fail to meet this demand. Nintendo Wii Fit may be a valuable tool to enable rehabilitation interventions. Based on pilot studies, we have developed "Wii.n.Walk", an in-home telehealth Wii Fit intervention targeted to improve walking capacity in older adults with LLA. The objective of this study is to determine whether the Wii.n.Walk intervention enhances walking capacity compared to an attention control group. This project is a multi-site (Vancouver BC, London ON), parallel, evaluator-blind randomized controlled trial. Participants include community-dwelling older adults over the age of 50 years with unilateral transtibial or transfemoral amputation. Participants will be stratified by site and block randomized in triplets to either the Wii.n.Walk intervention or an attention control group employing the Wii Big Brain cognitive software. This trial will include both supervised and unsupervised phases. During the supervised phase, both groups will receive 40-minute sessions of supervised group training three times per week for a duration of 4 weeks. Participants will complete the first week of the intervention in groups of three at their local rehabilitation center with a trainer. The remaining 3 weeks will take place at participants' homes using remote supervision by the trainer using Apple iPad technology. At the end of 4 weeks, the supervised period will end and the unsupervised period will begin. Participants will retain the Wii console and be encouraged to continue using the program for an additional 4 weeks' duration. The primary outcome measure will be the "Two-Minute Walk Test" to measure walking capacity. Outcome measures will be evaluated for all participants at baseline, after the end of both the supervised and unsupervised phases, and after 1-year follow up. Study staff have been hired and trained at both sites and recruitment is currently underway. No participants have been enrolled yet. Wii.n.Walk is a promising in-home telehealth intervention that may have useful applications for older adults with LLA who are discharged from rehabilitation or live in remote areas having limited or no access to existing rehabilitation programs. Clinicaltrial.gov NCT01942798; http://clinicaltrials.gov/ct2/show/NCT01942798 (Archived by WebCite at http://www.webcitation.org/6V0w8baKP).
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Localized Energy-Based Normalization of Medical Images: Application to Chest Radiography.
Philipsen, R H H M; Maduskar, P; Hogeweg, L; Melendez, J; Sánchez, C I; van Ginneken, B
2015-09-01
Automated quantitative analysis systems for medical images often lack the capability to successfully process images from multiple sources. Normalization of such images prior to further analysis is a possible solution to this limitation. This work presents a general method to normalize medical images and thoroughly investigates its effectiveness for chest radiography (CXR). The method starts with an energy decomposition of the image in different bands. Next, each band's localized energy is scaled to a reference value and the image is reconstructed. We investigate iterative and local application of this technique. The normalization is applied iteratively to the lung fields on six datasets from different sources, each comprising 50 normal CXRs and 50 abnormal CXRs. The method is evaluated in three supervised computer-aided detection tasks related to CXR analysis and compared to two reference normalization methods. In the first task, automatic lung segmentation, the average Jaccard overlap significantly increased from 0.72±0.30 and 0.87±0.11 for both reference methods to with normalization. The second experiment was aimed at segmentation of the clavicles. The reference methods had an average Jaccard index of 0.57±0.26 and 0.53±0.26; with normalization this significantly increased to . The third experiment was detection of tuberculosis related abnormalities in the lung fields. The average area under the Receiver Operating Curve increased significantly from 0.72±0.14 and 0.79±0.06 using the reference methods to with normalization. We conclude that the normalization can be successfully applied in chest radiography and makes supervised systems more generally applicable to data from different sources.
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Hannah, Sean T; Schaubroeck, John M; Peng, Ann C; Lord, Robert G; Trevino, Linda K; Kozlowski, Steve W J; Avolio, Bruce J; Dimotakis, Nikolaos; Doty, Joseph
2013-07-01
We develop and test a model based on social cognitive theory (Bandura, 1991) that links abusive supervision to followers' ethical intentions and behaviors. Results from a sample of 2,572 military members show that abusive supervision was negatively related to followers' moral courage and their identification with the organization's core values. In addition, work unit contexts with varying degrees of abusive supervision, reflected by the average level of abusive supervision reported by unit members, moderated relationships between the level of abusive supervision personally experienced by individuals and both their moral courage and their identification with organizational values. Moral courage and identification with organizational values accounted for the relationship between abusive supervision and followers' ethical intentions and unethical behaviors. These findings suggest that abusive supervision may undermine moral agency and that being personally abused is not required for abusive supervision to negatively influence ethical outcomes. PsycINFO Database Record (c) 2013 APA, all rights reserved.
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Long, C G; Harding, S; Payne, K; Collins, L
2014-03-01
In secure psychiatric services where the potential for 'burnout' by nurses is high, clinical supervision is viewed as a key to reflective practice to support staff in stressful working environments. Barriers to the uptake of clinical supervision in such service settings are personal and organizational. The study was prompted by the need to evaluate the effectiveness of supervision for registered nurses and health-care assistants (HCAs) and a desire to use survey findings to improve the quality and uptake of supervision. The study examined the perceived benefits, the best practice elements and the practical aspects of clinical supervision including how to improve practice. An approximate uptake of clinical supervision by 50% of staff confirmed previous findings; that HCAs were significantly less likely to engage in supervision and less likely to perceive benefit from it. Initiatives to address the training and managerial obstacles to the provision of formal supervision are described. © 2013 John Wiley & Sons Ltd.
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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
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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.
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Schmidt, Lasse M; Foli-Andersen, Nina J
2017-02-01
Psychotherapy training is mandatory for physicians to qualify as psychiatrists in Denmark. Evidence for the effectiveness of psychotherapy has increased, and psychotherapy is increasingly included in international treatment guidelines. The authors investigated how psychiatrists in training in Denmark evaluate the opportunities to practice psychotherapy in their training and the quality of the supervision they receive in psychotherapy training, particularly for cognitive behavioral therapy (CBT). The authors conducted a survey regarding psychotherapy training and CBT supervision among psychiatrists in training at Danish psychiatric specialist training courses. They investigated respondents' interest and experience in psychotherapy and respondents' views on the relevance and feasibility of performing psychotherapy and receiving supervision in their psychiatry training. Eighty-eight percent of the psychiatrists in training found psychotherapy to be a relevant part of their training; however, 77 % found it difficult to find time to practice psychotherapy and 44 % felt that practicing psychotherapy was a strain on their employer. Thirty-six percent and 53 %, respectively, had difficulties securing psychodynamic and CBT supervision. In CBT supervision, more than 60 % reported supervision that appeared to be below the expected CBT supervision standard and often so much below it might not qualify as CBT supervision. There is a need to focus on how to better integrate psychotherapy and supervision in the Danish psychiatric training program. Good CBT supervision may be lacking, and a way to ensure high-quality supervision is required.
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O'Connell, Meghan; Wonodi, Chizoba
2016-03-01
Since 2002, the Nigerian government has deployed consultants to states to provide technical assistance for routine immunization (RI). RI consultants are expected to play a role in supportive supervision of health facility staff, capacity building, advocacy, and monitoring and evaluation. We conducted a retrospective review of the RI consultant program's strengths and weaknesses in 7 states and at the national level from June to September 2014 using semi-structured interviews and online surveys. Participants included RI consultants, RI program leaders, and implementers purposively drawn from national, state, and local government levels. Thematic analysis was used to analyze qualitative data from the interviews, which were triangulated with results from the quantitative surveys. At the time of data collection, 23 of 36 states and the federal capital territory had an RI consultant. Of the 7 states visited during the study, only 3 states had present and visibly working consultants. We conducted 84 interviews with 101 participants across the 7 states and conducted data analysis on 70 interviews (with 82 individuals) that had complete data. Among the full sample of interview respondents (N = 101), most (66%) were men with an average age of 49 years (±5.6), and the majority were technical officers (63%) but a range of other roles were also represented, including consultants (22%), directors (13%), and health workers (2%). Fifteen consultants and 44 program leaders completed the online surveys. Interview data from the 3 states with active RI consultants indicated that the consultants' main contribution was supportive supervision at the local level, particularly for collecting and using RI data for decision making. They also acted as effective advocates for RI funding. In states without an RI consultant, gaps were highlighted in data management capacity and in monitoring of RI funds. Program design strengths: the broad terms of reference and autonomy of the consultants allowed work to be tailored to the local context; consultants were often integrated into state RI teams but could also work independently when necessary; and recruitment of experienced consultants with strong professional networks, familiarity with the local context, and ability to speak the local language facilitated advocacy efforts. Key programmatic challenges were related to inadequate and inconsistent inputs (salaries, transportation means, and dedicated office space) and gaps in communication between consultants and national leadership and in management of consultants, including lack of performance feedback, lack of formal orientation at inception, and no clear job performance targets. While weaknesses in managerial and material inputs affect current performance of RI consultants in Nigeria, the design of the RI consultant program employs a unique problem-focused, locally led model of development assistance that could prove valuable in strengthening the capacity of the government to implement such technical assistance on its own. Despite the lack of uniform deployment and implementation of RI consultants across the country, some consultants appear to have contributed to improved RI services through supportive supervision, capacity building, and advocacy. © O’Connell and Wonodi.
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O’Connell, Meghan; Wonodi, Chizoba
2016-01-01
ABSTRACT Background: Since 2002, the Nigerian government has deployed consultants to states to provide technical assistance for routine immunization (RI). RI consultants are expected to play a role in supportive supervision of health facility staff, capacity building, advocacy, and monitoring and evaluation. Methods: We conducted a retrospective review of the RI consultant program’s strengths and weaknesses in 7 states and at the national level from June to September 2014 using semi-structured interviews and online surveys. Participants included RI consultants, RI program leaders, and implementers purposively drawn from national, state, and local government levels. Thematic analysis was used to analyze qualitative data from the interviews, which were triangulated with results from the quantitative surveys. Findings: At the time of data collection, 23 of 36 states and the federal capital territory had an RI consultant. Of the 7 states visited during the study, only 3 states had present and visibly working consultants. We conducted 84 interviews with 101 participants across the 7 states and conducted data analysis on 70 interviews (with 82 individuals) that had complete data. Among the full sample of interview respondents (N = 101), most (66%) were men with an average age of 49 years (±5.6), and the majority were technical officers (63%) but a range of other roles were also represented, including consultants (22%), directors (13%), and health workers (2%). Fifteen consultants and 44 program leaders completed the online surveys. Interview data from the 3 states with active RI consultants indicated that the consultants’ main contribution was supportive supervision at the local level, particularly for collecting and using RI data for decision making. They also acted as effective advocates for RI funding. In states without an RI consultant, gaps were highlighted in data management capacity and in monitoring of RI funds. Program design strengths: the broad terms of reference and autonomy of the consultants allowed work to be tailored to the local context; consultants were often integrated into state RI teams but could also work independently when necessary; and recruitment of experienced consultants with strong professional networks, familiarity with the local context, and ability to speak the local language facilitated advocacy efforts. Key programmatic challenges were related to inadequate and inconsistent inputs (salaries, transportation means, and dedicated office space) and gaps in communication between consultants and national leadership and in management of consultants, including lack of performance feedback, lack of formal orientation at inception, and no clear job performance targets. Conclusions: While weaknesses in managerial and material inputs affect current performance of RI consultants in Nigeria, the design of the RI consultant program employs a unique problem-focused, locally led model of development assistance that could prove valuable in strengthening the capacity of the government to implement such technical assistance on its own. Despite the lack of uniform deployment and implementation of RI consultants across the country, some consultants appear to have contributed to improved RI services through supportive supervision, capacity building, and advocacy. PMID:27016542
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Sci—Fri PM: Topics — 05: Experience with linac simulation software in a teaching environment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carlone, Marco; Harnett, Nicole; Jaffray, David
Medical linear accelerator education is usually restricted to use of academic textbooks and supervised access to accelerators. To facilitate the learning process, simulation software was developed to reproduce the effect of medical linear accelerator beam adjustments on resulting clinical photon beams. The purpose of this report is to briefly describe the method of operation of the software as well as the initial experience with it in a teaching environment. To first and higher orders, all components of medical linear accelerators can be described by analytical solutions. When appropriate calibrations are applied, these analytical solutions can accurately simulate the performance ofmore » all linear accelerator sub-components. Grouped together, an overall medical linear accelerator model can be constructed. Fifteen expressions in total were coded using MATLAB v 7.14. The program was called SIMAC. The SIMAC program was used in an accelerator technology course offered at our institution; 14 delegates attended the course. The professional breakdown of the participants was: 5 physics residents, 3 accelerator technologists, 4 regulators and 1 physics associate. The course consisted of didactic lectures supported by labs using SIMAC. At the conclusion of the course, eight of thirteen delegates were able to successfully perform advanced beam adjustments after two days of theory and use of the linac simulator program. We suggest that this demonstrates good proficiency in understanding of the accelerator physics, which we hope will translate to a better ability to understand real world beam adjustments on a functioning medical linear accelerator.« less
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Snow mapping and land use studies in Switzerland
NASA Technical Reports Server (NTRS)
Haefner, H. (Principal Investigator)
1977-01-01
The author has identified the following significant results. A system was developed for operational snow and land use mapping, based on a supervised classification method using various classification algorithms and representation of the results in maplike form on color film with a photomation system. Land use mapping, under European conditions, was achieved with a stepwise linear discriminant analysis by using additional ratio variables. On fall images, signatures of built-up areas were often not separable from wetlands. Two different methods were tested to correlate the size of settlements and the population with an accuracy for the densely populated Swiss Plateau between +2 or -12%.
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Supervisory autonomous local-remote control system design: Near-term and far-term applications
NASA Technical Reports Server (NTRS)
Zimmerman, Wayne; Backes, Paul
1993-01-01
The JPL Supervisory Telerobotics Laboratory (STELER) has developed a unique local-remote robot control architecture which enables management of intermittent bus latencies and communication delays such as those expected for ground-remote operation of Space Station robotic systems via the TDRSS communication platform. At the local site, the operator updates the work site world model using stereo video feedback and a model overlay/fitting algorithm which outputs the location and orientation of the object in free space. That information is relayed to the robot User Macro Interface (UMI) to enable programming of the robot control macros. The operator can then employ either manual teleoperation, shared control, or supervised autonomous control to manipulate the object under any degree of time-delay. The remote site performs the closed loop force/torque control, task monitoring, and reflex action. This paper describes the STELER local-remote robot control system, and further describes the near-term planned Space Station applications, along with potential far-term applications such as telescience, autonomous docking, and Lunar/Mars rovers.
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NASA Astrophysics Data System (ADS)
Ruske, S. T.; Topping, D. O.; Foot, V. E.; Kaye, P. H.; Stanley, W. R.; Morse, A. P.; Crawford, I.; Gallagher, M. W.
2016-12-01
Characterisation of bio-aerosols has important implications within Environment and Public Health sectors. Recent developments in Ultra-Violet Light Induced Fluorescence (UV-LIF) detectors such as the Wideband Integrated bio-aerosol Spectrometer (WIBS) and the newly introduced Multiparameter bio-aerosol Spectrometer (MBS) has allowed for the real time collection of fluorescence, size and morphology measurements for the purpose of discriminating between bacteria, fungal Spores and pollen. This new generation of instruments has enabled ever-larger data sets to be compiled with the aim of studying more complex environments, yet the algorithms used for specie classification remain largely invalidated. It is therefore imperative that we validate the performance of different algorithms that can be used for the task of classification, which is the focus of this study. For unsupervised learning we test Hierarchical Agglomerative Clustering with various different linkages. For supervised learning, ten methods were tested; including decision trees, ensemble methods: Random Forests, Gradient Boosting and AdaBoost; two implementations for support vector machines: libsvm and liblinear; Gaussian methods: Gaussian naïve Bayesian, quadratic and linear discriminant analysis and finally the k-nearest neighbours algorithm. The methods were applied to two different data sets measured using a new Multiparameter bio-aerosol Spectrometer. We find that clustering, in general, performs slightly worse than the supervised learning methods correctly classifying, at best, only 72.7 and 91.1 percent for the two data sets. For supervised learning the gradient boosting algorithm was found to be the most effective, on average correctly classifying 88.1 and 97.8 percent of the testing data respectively across the two data sets. We discuss the wider relevance of these results with regards to challenging existing classification in real-world environments.
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Cuddy, Monica M; Winward, Marcia L; Johnston, Mary M; Lipner, Rebecca S; Clauser, Brian E
2016-01-01
To add to the small body of validity research addressing whether scores from performance assessments of clinical skills are related to performance in supervised patient settings, the authors examined relationships between United States Medical Licensing Examination (USMLE) Step 2 Clinical Skills (CS) data gathering and data interpretation scores and subsequent performance in history taking and physical examination in internal medicine residency training. The sample included 6,306 examinees from 238 internal medicine residency programs who completed Step 2 CS for the first time in 2005 and whose performance ratings from their first year of residency training were available. Hierarchical linear modeling techniques were used to examine the relationships among Step 2 CS data gathering and data interpretation scores and history-taking and physical examination ratings. Step 2 CS data interpretation scores were positively related to both history-taking and physical examination ratings. Step 2 CS data gathering scores were not related to either history-taking or physical examination ratings after other USMLE scores were taken into account. Step 2 CS data interpretation scores provide useful information for predicting subsequent performance in history taking and physical examination in supervised practice and thus provide validity evidence for their intended use as an indication of readiness to enter supervised practice. The results show that there is less evidence to support the usefulness of Step 2 CS data gathering scores. This study provides important information for practitioners interested in Step 2 CS specifically or in performance assessments of medical students' clinical skills more generally.
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1994-07-01
lwir imagery (preliminary calibration) and local lapse rates. Type maps were developed using a supervised multi-spectral classification procedure., 2.5...Atmospherics Conference, R. Lee, chairman, 251-260. 4. Tofsted, D. H., 1993, "Effects of Nonuniform Aerosol Forward Scattering on Imagery," Proceedings of...than channel 4; 4) the channel 4 brightness temperature is high relative to the predicted clear scene temperature; and 5) LWIR channel difference is
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fRMSDPred: Predicting Local RMSD Between Structural Fragments Using Sequence Information
2007-04-04
machine learning approaches for estimating the RMSD value of a pair of protein fragments. These estimated fragment-level RMSD values can be used to construct the alignment, assess the quality of an alignment, and identify high-quality alignment segments. We present algorithms to solve this fragment-level RMSD prediction problem using a supervised learning framework based on support vector regression and classification that incorporates protein profiles, predicted secondary structure, effective information encoding schemes, and novel second-order pairwise exponential kernel
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Ensemble Semi-supervised Frame-work for Brain Magnetic Resonance Imaging Tissue Segmentation.
Azmi, Reza; Pishgoo, Boshra; Norozi, Narges; Yeganeh, Samira
2013-04-01
Brain magnetic resonance images (MRIs) tissue segmentation is one of the most important parts of the clinical diagnostic tools. Pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. Supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to obtain. Moreover, they cannot use unlabeled data to train classifiers. On the other hand, unsupervised segmentation methods have no prior knowledge and lead to low level of performance. However, semi-supervised learning which uses a few labeled data together with a large amount of unlabeled data causes higher accuracy with less trouble. In this paper, we propose an ensemble semi-supervised frame-work for segmenting of brain magnetic resonance imaging (MRI) tissues that it has been used results of several semi-supervised classifiers simultaneously. Selecting appropriate classifiers has a significant role in the performance of this frame-work. Hence, in this paper, we present two semi-supervised algorithms expectation filtering maximization and MCo_Training that are improved versions of semi-supervised methods expectation maximization and Co_Training and increase segmentation accuracy. Afterward, we use these improved classifiers together with graph-based semi-supervised classifier as components of the ensemble frame-work. Experimental results show that performance of segmentation in this approach is higher than both supervised methods and the individual semi-supervised classifiers.
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Exploring paraprofessional and classroom factors affecting teacher supervision.
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.
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Baldwin, DeWitt C; Daugherty, Steven R; Ryan, Patrick M; Yaghmour, Nicholas A; Philibert, Ingrid
2018-04-01
Medical errors and patient safety are major concerns for the medical and medical education communities. Improving clinical supervision for residents is important in avoiding errors, yet little is known about how residents perceive the adequacy of their supervision and how this relates to medical errors and other education outcomes, such as learning and satisfaction. We analyzed data from a 2009 survey of residents in 4 large specialties regarding the adequacy and quality of supervision they receive as well as associations with self-reported data on medical errors and residents' perceptions of their learning environment. Residents' reports of working without adequate supervision were lower than data from a 1999 survey for all 4 specialties, and residents were least likely to rate "lack of supervision" as a problem. While few residents reported that they received inadequate supervision, problems with supervision were negatively correlated with sufficient time for clinical activities, overall ratings of the residency experience, and attending physicians as a source of learning. Problems with supervision were positively correlated with resident reports that they had made a significant medical error, had been belittled or humiliated, or had observed others falsifying medical records. Although working without supervision was not a pervasive problem in 2009, when it happened, it appeared to have negative consequences. The association between inadequate supervision and medical errors is of particular concern.
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Bos, Elisabeth; Löfmark, Anna; Törnkvist, Lena
2009-11-01
Nursing students go through clinical supervision in primary health care settings but district nurses' (DNs) circumstances when supervising them are only briefly described in the literature. The aim of this study was to investigate DNs experience of supervising nursing students before and after the implementation of a new supervision model. Ninety-eight (74%) DNs answered a questionnaire before and 84 (65%) after implementation of the new supervision model. The study showed that DNs in most cases felt that conditions for supervision in the workplace were adequate. But about 70% lacked training for the supervisory role and 20% had no specialist district nurse training. They also experienced difficulty in keeping up-to-date with changes in nurse education programmes, in receiving support from the university and from their clinic managers, and in setting aside time for supervision. Improvements after the implementation of a new model chiefly concerned organisation; more DNs stated that one person had primary responsibility for students' clinical practice, that information packages for supervisors and students were available at the health care centres, and that conditions were in place for increasing the number of students they supervised. DNs also stated that supervisors and students benefited from supervision by more than one supervisor. To conclude, implementation of a new supervision model resulted in some improvements.
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Morrongiello, Barbara A; Zdzieborski, Daniel; Sandomierski, Megan; Lasenby-Lessard, Jennifer
2009-03-01
Recent research reveals that supervision can be a protective factor for childhood injury. Parents who closely supervise young children at home have children who experience fewer injuries. What is not known, however, is what messaging approaches (e.g., injury statistics, graphic images of injured children, personal testimonials by parents) are best to persuade parents to supervise more closely. Using video as the medium, the present focus group study of urban Canadian mothers explored their reactions to different formats and messages in order to: identify best practices to convince mothers that childhood injury prevention is important; determine how best to communicate messages about supervision to mothers; and identify what the nature and scope of these messages should be for motivating and empowering mothers to supervise closely. Results suggest that those who become aware of the scope of childhood injuries are motivated to pay attention to messaging about supervision, that such messages must be delivered with care so that parents do not feel guilty or blamed for acknowledging they could more closely supervise than they already are, that certain messages are not useful for encouraging closer supervision, and that both the content and presentation characteristics (images, accompanying sound) of messages are important determinants of effectiveness for motivating mothers to supervise more closely. Implications for developing interventions that effectively communicate information about child-injury risk and supervision to mothers are discussed.
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Deep Hashing for Scalable Image Search.
Lu, Jiwen; Liong, Venice Erin; Zhou, Jie
2017-05-01
In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.
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Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders.
Viejo, Guillaume; Cortier, Thomas; Peyrache, Adrien
2018-03-01
Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains.
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Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders
Cortier, Thomas; Peyrache, Adrien
2018-01-01
Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains. PMID:29565979
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Hill, Hamish R M; Crowe, Trevor P; Gonsalvez, Craig J
2016-01-01
To pilot an intervention involving reflective dialogue based on video recordings of clinical supervision. Fourteen participants (seven psychotherapists and their supervisors) completed a reflective practice protocol after viewing a video of their most recent supervision session, then shared their reflections in a second session. Thematic analysis of individual reflections and feedback resulted in the following dominant themes: (1) Increased discussion of supervisee anxiety and the tensions between autonomy and dependence; (2) intentions to alter supervisory roles and practice; (3) identification of and reflection on parallel process (defined as the dynamic transmission of relationship patterns between therapy and supervision); and (4) a range of perceived impacts including improvements in supervisory alliance. The results suggest that reflective dialogue based on supervision videos can play a useful role in psychotherapy supervision, including with relatively inexperienced supervisees. Suggestions are provided for the encouragement of ongoing reflective dialogue in routine supervision practice.
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Disciplinary supervision following ethics complaints: goals, tasks, and ethical dimensions.
Thomas, Janet T
2014-11-01
Clinical supervision is considered an integral component of the training of psychologists, and most of the professional literature is focused on this type of supervision. But psychologists also may supervise fully credentialed colleagues in other circumstances. One such context occurs when licensing boards mandate supervision as part of a disciplinary order. When supervision is provided in disciplinary cases, there are significant implications for the ethical dimensions of the supervisory relationship and concomitant ethical challenges for supervisors. Not only are the goals, objectives, and supervisory tasks of disciplinary supervision distinct from other types of supervision, but the supervisor's ethical responsibilities also encompass unique dimensions. Competence, informed consent, boundaries, confidentiality, and documentation are examined. Recommendations for reports to licensing boards include a statement of the clinical or ethical problems instigating discipline, description of how these problems have been addressed, and an assessment of the supervisee's current practices and ability to perform competently. © 2014 Wiley Periodicals, Inc.
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Clinical supervision of psychotherapy: essential ethics issues for supervisors and supervisees.
Barnett, Jeffrey E; Molzon, Corey H
2014-11-01
Clinical supervision is an essential aspect of every mental health professional's training. The importance of ensuring that supervision is provided competently, ethically, and legally is explained. The elements of the ethical practice of supervision are described and explained. Specific issues addressed include informed consent and the supervision contract, supervisor and supervisee competence, attention to issues of diversity and multicultural competence, boundaries and multiple relationships in the supervision relationship, documentation and record keeping by both supervisor and supervisee, evaluation and feedback, self-care and the ongoing promotion of wellness, emergency coverage, and the ending of the supervision relationship. Additionally, the role of clinical supervisor as mentor, professional role model, and gatekeeper for the profession are discussed. Specific recommendations are provided for ethically and effectively conducting the supervision relationship and for addressing commonly arising dilemmas that supervisors and supervisees may confront. © 2014 Wiley Periodicals, Inc.
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Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions.
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.
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Social constructionism and supervision: experiences of AAMFT supervisors and supervised therapists.
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.
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Locality-constrained anomaly detection for hyperspectral imagery
NASA Astrophysics Data System (ADS)
Liu, Jiabin; Li, Wei; Du, Qian; Liu, Kui
2015-12-01
Detecting a target with low-occurrence-probability from unknown background in a hyperspectral image, namely anomaly detection, is of practical significance. Reed-Xiaoli (RX) algorithm is considered as a classic anomaly detector, which calculates the Mahalanobis distance between local background and the pixel under test. Local RX, as an adaptive RX detector, employs a dual-window strategy to consider pixels within the frame between inner and outer windows as local background. However, the detector is sensitive if such a local region contains anomalous pixels (i.e., outliers). In this paper, a locality-constrained anomaly detector is proposed to remove outliers in the local background region before employing the RX algorithm. Specifically, a local linear representation is designed to exploit the internal relationship between linearly correlated pixels in the local background region and the pixel under test and its neighbors. Experimental results demonstrate that the proposed detector improves the original local RX algorithm.
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An improved artifact removal in exposure fusion with local linear constraints
NASA Astrophysics Data System (ADS)
Zhang, Hai; Yu, Mali
2018-04-01
In exposure fusion, it is challenging to remove artifacts because of camera motion and moving objects in the scene. An improved artifact removal method is proposed in this paper, which performs local linear adjustment in artifact removal progress. After determining a reference image, we first perform high-dynamic-range (HDR) deghosting to generate an intermediate image stack from the input image stack. Then, a linear Intensity Mapping Function (IMF) in each window is extracted based on the intensities of intermediate image and reference image, the intensity mean and variance of reference image. Finally, with the extracted local linear constraints, we reconstruct a target image stack, which can be directly used for fusing a single HDR-like image. Some experiments have been implemented and experimental results demonstrate that the proposed method is robust and effective in removing artifacts especially in the saturated regions of the reference image.
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Locally Dependent Linear Logistic Test Model with Person Covariates
ERIC Educational Resources Information Center
Ip, Edward H.; Smits, Dirk J. M.; De Boeck, Paul
2009-01-01
The article proposes a family of item-response models that allow the separate and independent specification of three orthogonal components: item attribute, person covariate, and local item dependence. Special interest lies in extending the linear logistic test model, which is commonly used to measure item attributes, to tests with embedded item…
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Self-Supervised Dynamical Systems
NASA Technical Reports Server (NTRS)
Zak, Michail
2003-01-01
Some progress has been made in a continuing effort to develop mathematical models of the behaviors of multi-agent systems known in biology, economics, and sociology (e.g., systems ranging from single or a few biomolecules to many interacting higher organisms). Living systems can be characterized by nonlinear evolution of probability distributions over different possible choices of the next steps in their motions. One of the main challenges in mathematical modeling of living systems is to distinguish between random walks of purely physical origin (for instance, Brownian motions) and those of biological origin. Following a line of reasoning from prior research, it has been assumed, in the present development, that a biological random walk can be represented by a nonlinear mathematical model that represents coupled mental and motor dynamics incorporating the psychological concept of reflection or self-image. The nonlinear dynamics impart the lifelike ability to behave in ways and to exhibit patterns that depart from thermodynamic equilibrium. Reflection or self-image has traditionally been recognized as a basic element of intelligence. The nonlinear mathematical models of the present development are denoted self-supervised dynamical systems. They include (1) equations of classical dynamics, including random components caused by uncertainties in initial conditions and by Langevin forces, coupled with (2) the corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces, denoted supervising forces, composed of probability densities and functionals thereof. The equations of classical mechanics represent motor dynamics that is, dynamics in the traditional sense, signifying Newton s equations of motion. The evolution of the probability densities represents mental dynamics or self-image. Then the interaction between the physical and metal aspects of a monad is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. This feedback is what makes the evolution of probability densities nonlinear. The deviation from linear evolution can be characterized, in a sense, as an expression of free will. It has been demonstrated that probability densities can approach prescribed attractors while exhibiting such patterns as shock waves, solitons, and chaos in probability space. The concept of self-supervised dynamical systems has been considered for application to diverse phenomena, including information-based neural networks, cooperation, competition, deception, games, and control of chaos. In addition, a formal similarity between the mathematical structures of self-supervised dynamical systems and of quantum-mechanical systems has been investigated.
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Estimating monotonic rates from biological data using local linear regression.
Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R
2017-03-01
Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.
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NASA Technical Reports Server (NTRS)
Emerson, Charles W.; Sig-NganLam, Nina; Quattrochi, Dale A.
2004-01-01
The accuracy of traditional multispectral maximum-likelihood image classification is limited by the skewed statistical distributions of reflectances from the complex heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze Landsat 7 imagery of Atlanta, Georgia. Although segmentation of panchromatic images is possible using indicators of spatial complexity, different land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification. The addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques.
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Mental health nurses' experiences of managing work-related emotions through supervision.
MacLaren, Jessica; Stenhouse, Rosie; Ritchie, Deborah
2016-10-01
The aim of this study was to explore emotion cultures constructed in supervision and consider how supervision functions as an emotionally safe space promoting critical reflection. Research published between 1995-2015 suggests supervision has a positive impact on nurses' emotional well-being, but there is little understanding of the processes involved in this and how styles of emotion interaction are established in supervision. A narrative approach was used to investigate mental health nurses' understandings and experiences of supervision. Eight semi-structured interviews were conducted with community mental health nurses in the UK during 2011. Analysis of audio data used features of speech to identify narrative discourse and illuminate meanings. A topic-centred analysis of interview narratives explored discourses shared between the participants. This supported the identification of feeling rules in participants' narratives and the exploration of the emotion context of supervision. Effective supervision was associated with three feeling rules: safety and reflexivity; staying professional; managing feelings. These feeling rules allowed the expression and exploration of emotions, promoting critical reflection. A contrast was identified between the emotion culture of supervision and the nurses' experience of their workplace cultures as requiring the suppression of difficult emotions. Despite this, contrast supervision functioned as an emotion micro-culture with its own distinctive feeling rules. The analytical construct of feeling rules allows us to connect individual emotional experiences to shared normative discourses, highlighting how these shape emotional processes taking place in supervision. This understanding supports an explanation of how supervision may positively influence nurses' emotion management and perhaps reduce burnout. © 2016 John Wiley & Sons Ltd.
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Competencies to enable learning-focused clinical supervision: a thematic analysis of the literature.
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 & Sons Ltd.
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Porta, A; Gasperi, C; Nollo, G; Lucini, D; Pizzinelli, P; Antolini, R; Pagani, M
2006-04-01
Global linear analysis has been traditionally performed to verify the relationship between pulse transit time (PTT) and systolic arterial pressure (SAP) at the level of their spontaneous beat-to-beat variabilities: PTT and SAP have been plotted in the plane (PTT,SAP) and a significant linear correlation has been found. However, this relationship is weak and in specific individuals cannot be found. This result prevents the utilization of the SAP-PTT relationship to derive arterial pressure changes from PTT measures on an individual basis. We propose a local linear approach to study the SAP-PTT relationship. This approach is based on the definition of short SAP-PTT sequences characterized by SAP increase (decrease) and PTT decrease (increase) and on their search in the SAP and PTT beat-to-beat series. This local approach was applied to PTT and SAP series derived from 13 healthy humans during incremental supine dynamic exercise (at 10, 20 and 30% of the nominal individual maximum effort) and compared to the global approach. While global approach failed in some subjects, local analysis allowed the extraction of the gain of the SAP-PTT relationship in all subjects both at rest and during exercise. When both local and global analyses were successful, the local SAP-PTT gain is more negative than the global one as a likely result of noise reduction.
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Watkins, C Edward
2014-01-01
What are some of the most recent, cutting-edge developments and innovations in psychotherapy supervision? And what is their particular significance for supervision now and into its future? In this special supervision issue of the American Journal of Psychotherapy, those questions are considered, and some compelling answers are provided. In what follows, I introduce this special journal issue: (a) define supervision and indicate its purposes; (b) summarize the contents of each innovative paper; and (c) accentuate the significance of each presented development/innovation. The papers contained in this issue boldly speak to supervision's future and provide exciting--and highly profitable--directions to pursue in forever making psychotherapy supervision a far more anchored, accountable, and educational experience.
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Supervising undergraduate research: a collective approach utilising groupwork and peer support.
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.
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Critical components of reflective supervision: responses from expert supervisors in the field.
Tomlin, Angela M; Weatherston, Deborah J; Pavkov, Thomas
2014-01-01
This article offers a brief review of the history of supervision, defines reflective supervision, and reports the results of a Delphi study designed to identify critical components of reflective supervision. Academicians and master clinicians skilled in providing reflective supervision participated in a three-phase survey to elicit beliefs about best practice when engaging in reflective supervision. The process yielded consensus descriptions of optimal characteristics and behaviors of supervisors and supervisees when entering into supervisory relationships that encourage reflective practice. These results, although preliminary, suggest that it is possible to identify elements that are integral to effective reflective supervision. These initial findings may be used for future study of the reflective supervisory process. © 2013 Michigan Association for Infant Mental Health.
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Current Risk Management Practices in Psychotherapy Supervision.
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.
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Qian, Jianjun; Yang, Jian; Xu, Yong
2013-09-01
This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.
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9 CFR 317.1 - Labels required; supervision by Program employee.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 9 Animals and Animal Products 2 2011-01-01 2011-01-01 false Labels required; supervision by... Labels required; supervision by Program employee. (a) When, in an official establishment, any inspected... supervision of a Program employee. ...
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9 CFR 317.1 - Labels required; supervision by Program employee.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 9 Animals and Animal Products 2 2014-01-01 2014-01-01 false Labels required; supervision by... Labels required; supervision by Program employee. (a) When, in an official establishment, any inspected... supervision of a Program employee. ...
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Simpson-Southward, Chloe; Waller, Glenn; Hardy, Gillian E
2016-02-01
Psychological treatments for depression are not always delivered effectively or consistently. Clinical supervision of therapists is often assumed to keep therapy on track, ensuring positive patient outcomes. However, there is a lack of empirical evidence supporting this assumption. This experimental study explored the focus of supervision of depression cases, comparing guidance given to supervisees of different genders and anxiety levels. Participants were clinical supervisors who supervised therapists working with patients with depression. Supervisors indicated their supervision focus for three supervision case vignettes. Supervisee anxiety and gender was varied across vignettes. Supervisors focused calm female supervisees more on therapeutic techniques than state anxious female supervisees. Males were supervised in the same way, regardless of their anxiety. Both male and female supervisors had this pattern of focus. Findings indicate that supervision is influenced by supervisors' own biases towards their supervisees. These factors may cause supervisors to drift from prompting their supervisees to deliver best practice. Suggestions are made for ways to improve the effectiveness of clinical supervision and how these results may inform future research practice. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery.
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.
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Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.
Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang
2017-11-01
Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.
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48 CFR 836.572 - Government supervision.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 5 2012-10-01 2012-10-01 false Government supervision... CATEGORIES OF CONTRACTING CONSTRUCTION AND ARCHITECT-ENGINEER CONTRACTS Contract Clauses 836.572 Government supervision. The contracting officer shall insert the clause at 852.236-78, Government supervision, in...
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48 CFR 836.572 - Government supervision.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Government supervision... CATEGORIES OF CONTRACTING CONSTRUCTION AND ARCHITECT-ENGINEER CONTRACTS Contract Clauses 836.572 Government supervision. The contracting officer shall insert the clause at 852.236-78, Government supervision, in...
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48 CFR 836.572 - Government supervision.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 5 2013-10-01 2013-10-01 false Government supervision... CATEGORIES OF CONTRACTING CONSTRUCTION AND ARCHITECT-ENGINEER CONTRACTS Contract Clauses 836.572 Government supervision. The contracting officer shall insert the clause at 852.236-78, Government supervision, in...
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48 CFR 836.572 - Government supervision.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 48 Federal Acquisition Regulations System 5 2014-10-01 2014-10-01 false Government supervision... CATEGORIES OF CONTRACTING CONSTRUCTION AND ARCHITECT-ENGINEER CONTRACTS Contract Clauses 836.572 Government supervision. The contracting officer shall insert the clause at 852.236-78, Government supervision, in...
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48 CFR 836.572 - Government supervision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 48 Federal Acquisition Regulations System 5 2011-10-01 2011-10-01 false Government supervision... CATEGORIES OF CONTRACTING CONSTRUCTION AND ARCHITECT-ENGINEER CONTRACTS Contract Clauses 836.572 Government supervision. The contracting officer shall insert the clause at 852.236-78, Government supervision, in...
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Competency-Based Student-Teacher Supervision
ERIC Educational Resources Information Center
Spanjer, R. Allan
1975-01-01
This author contends that student-teacher supervision cannot be done effectively in traditional ways. He discusses five myths of supervision and explains a program developed at Portland (Ore.) State University that puts the emphasis where it should be--on the supervising teacher. (Editor)
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The supervisor as gender analyst: feminist perspectives on group supervision and training.
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.
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NASA Technical Reports Server (NTRS)
Shahshahani, Behzad M.; Landgrebe, David A.
1992-01-01
The effect of additional unlabeled samples in improving the supervised learning process is studied in this paper. Three learning processes. supervised, unsupervised, and combined supervised-unsupervised, are compared by studying the asymptotic behavior of the estimates obtained under each process. Upper and lower bounds on the asymptotic covariance matrices are derived. It is shown that under a normal mixture density assumption for the probability density function of the feature space, the combined supervised-unsupervised learning is always superior to the supervised learning in achieving better estimates. Experimental results are provided to verify the theoretical concepts.
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[Nurse supervision in health basic units].
Correia, Valesca Silveira; Servo, Maria Lúcia Silva
2006-01-01
This qualitative study intends to evaluate the pattern of supervision of the nurse in health basic units, in Feira de Santana city (Bahía-Brasil), between August 2001 and June 2002. The objective was to describe the supervision and the existence of supervision systematics for the nurse. A questionnaire was used to take informations from a group of sixteen (16) nurses in actual professional work. Descriptive statistical procedures for data analysis were used. It can be concluded that systematic supervision is practiced in 64% of the nurses and in 36% of the cases systematic supervision do not occur.
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Evidence-based Practices Addressed in Community-based Children’s Mental Health Clinical Supervision
Accurso, Erin C.; Taylor, Robin M.; Garland, Ann F.
2013-01-01
Context Clinical supervision is the principal method of training for psychotherapeutic practice, however there is virtually no research on supervision practice in community settings. Of particular interest is the role supervision might play in facilitating implementation of evidence-based (EB) care in routine care settings. Objective This study examines the format and functions of clinical supervision sessions in routine care, as well as the extent to which supervision addresses psychotherapeutic practice elements common to EB care for children with disruptive behavior problems, who represent the majority of patients served in publicly-funded routine care settings. Methods Supervisors (n=7) and supervisees (n=12) from four publicly-funded community-based child mental health clinics reported on 130 supervision sessions. Results Supervision sessions were primarily individual in-person meetings lasting one hour. The most common functions included case conceptualization and therapy interventions. Coverage of practice elements common to EB treatments was brief. Discussion Despite the fact that most children presenting to public mental health services are referred for disruptive behavior problems, supervision sessions are infrequently focused on practice elements consistent with EB treatments for this population. Supervision is a promising avenue through which training in EB practices could be supported to improve the quality of care for children in community-based “usual care” clinics. PMID:24761163
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Competency-based Radiology Residency: A Survey of Expectations from Singapore's Perspective.
Yang, Hui; Tan, Colin J X; Lau, Doreen A H; Lim, Winston E H; Tay, Kiang Hiong; Kei, Pin Lin
2015-03-01
In response to the demands of an ageing nation, the postgraduate medical education in Singapore is currently in the early stage of transition into the American-styled residency programme. This study assessed the expectations of both radiology trainees and faculty on their ideal clinical learning environment (CLE) which facilitates the programme development. A modified 23-item questionnaire was administered to both trainees and faculty at a local training hospital. All items were scored according to their envisioned level of importance and categorised into 5 main CLE domains-supervision, formal training programme, work-based learning, social atmosphere and workload. 'Supervision' was identified as the most important domain of the CLE by both trainees and faculty, followed by 'formal training programmes', 'work-based learning' and 'social atmosphere'. 'Workload' was rated as the least important domain. For all domains, the reported expectation between both trainees and faculty respondents did not differ significantly. Intragroup comparison also showed no significant difference within each group of respondents. This study has provided valuable insights on both respondents' expectations on their ideal CLE that can best train competency in future radiologists. Various approaches to address these concerns were also discussed. The similarities in findings between ours and previous studies suggest that the 'supervision', 'formal training programmes' and 'work-based learning' domains are crucial for the success of a postgraduate medical training and should be emphasised in future curriculum. 'Workload' remains a challenge in postgraduate medical training, but attempts to address this will have an impact in future radiology training.
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Salam, Rehana A; Lassi, Zohra S; Das, Jai K; Bhutta, Zulfiqar A
2014-09-04
District level healthcare serves as a nexus between community and district level facilities. Inputs at the district level can be broadly divided into governance and accountability mechanisms; leadership and supervision; financial platforms; and information systems. This paper aims to evaluate the effectivness of district level inputs for imporving maternal and newborn health. We considered all available systematic reviews published before May 2013 on the pre-defined district level interventions and included 47 systematic reviews. Evidence suggests that supervision positively influenced provider's practice, knowledge and client/provider satisfaction. Involving local opinion leaders to promote evidence-based practice improved compliance to the desired practice. Audit and feedback mechanisms and tele-medicine were found to be associated with improved immunization rates and mammogram uptake. User-directed financial schemes including maternal vouchers, user fee exemption and community based health insurance showed significant impact on maternal health service utilization with voucher schemes showing the most significant positive impact across all range of outcomes including antenatal care, skilled birth attendant, institutional delivery, complicated delivery and postnatal care. We found insufficient evidence to support or refute the use of electronic health record systems and telemedicine technology to improve maternal and newborn health specific outcomes. There is dearth of evidence on the effectiveness of district level inputs to improve maternal newborn health outcomes. Future studies should evaluate the impact of supervision and monitoring; electronic health record and tele-communication interventions in low-middle-income countries.
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Durán, Claudio; Daminelli, Simone; Thomas, Josephine M; Haupt, V Joachim; Schroeder, Michael; Cannistraci, Carlo Vittorio
2017-04-26
The bipartite network representation of the drug-target interactions (DTIs) in a biosystem enhances understanding of the drugs' multifaceted action modes, suggests therapeutic switching for approved drugs and unveils possible side effects. As experimental testing of DTIs is costly and time-consuming, computational predictors are of great aid. Here, for the first time, state-of-the-art DTI supervised predictors custom-made in network biology were compared-using standard and innovative validation frameworks-with unsupervised pure topological-based models designed for general-purpose link prediction in bipartite networks. Surprisingly, our results show that the bipartite topology alone, if adequately exploited by means of the recently proposed local-community-paradigm (LCP) theory-initially detected in brain-network topological self-organization and afterwards generalized to any complex network-is able to suggest highly reliable predictions, with comparable performance with the state-of-the-art-supervised methods that exploit additional (non-topological, for instance biochemical) DTI knowledge. Furthermore, a detailed analysis of the novel predictions revealed that each class of methods prioritizes distinct true interactions; hence, combining methodologies based on diverse principles represents a promising strategy to improve drug-target discovery. To conclude, this study promotes the power of bio-inspired computing, demonstrating that simple unsupervised rules inspired by principles of topological self-organization and adaptiveness arising during learning in living intelligent systems (like the brain) can efficiently equal perform complicated algorithms based on advanced, supervised and knowledge-based engineering. © The Author 2017. Published by Oxford University Press.
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Ensemble Semi-supervised Frame-work for Brain Magnetic Resonance Imaging Tissue Segmentation
Azmi, Reza; Pishgoo, Boshra; Norozi, Narges; Yeganeh, Samira
2013-01-01
Brain magnetic resonance images (MRIs) tissue segmentation is one of the most important parts of the clinical diagnostic tools. Pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. Supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow to obtain. Moreover, they cannot use unlabeled data to train classifiers. On the other hand, unsupervised segmentation methods have no prior knowledge and lead to low level of performance. However, semi-supervised learning which uses a few labeled data together with a large amount of unlabeled data causes higher accuracy with less trouble. In this paper, we propose an ensemble semi-supervised frame-work for segmenting of brain magnetic resonance imaging (MRI) tissues that it has been used results of several semi-supervised classifiers simultaneously. Selecting appropriate classifiers has a significant role in the performance of this frame-work. Hence, in this paper, we present two semi-supervised algorithms expectation filtering maximization and MCo_Training that are improved versions of semi-supervised methods expectation maximization and Co_Training and increase segmentation accuracy. Afterward, we use these improved classifiers together with graph-based semi-supervised classifier as components of the ensemble frame-work. Experimental results show that performance of segmentation in this approach is higher than both supervised methods and the individual semi-supervised classifiers. PMID:24098863
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Rethinking Resident Supervision to Improve Safety: From Hierarchical to Interprofessional Models
Tamuz, Michal; Giardina, Traber Davis; Thomas, Eric J.; Menon, Shailaja; Singh, Hardeep
2011-01-01
Background Inadequate supervision is a significant contributing factor to medical errors involving trainees but supervision in high-risk settings such as the Intensive Care Unit (ICU) is not well studied. Objective We explored how residents in the ICU experienced supervision related to medication safety not only from supervising physicians but also from other professionals. Design, Setting, Measurements Using qualitative methods, we examined in-depth interviews with 17 residents working in ICUs of three tertiary-care hospitals. We analyzed residents' perspectives on receiving and initiating supervision from physicians within the traditional medical hierarchy and from other professionals, including nurses, staff pharmacists and clinical pharmacists (“interprofessional supervision”). Results While initiating their own supervision within the traditional hierarchy, residents believed in seeking assistance from fellows and attendings and articulated rules of thumb for doing so; however, they also experienced difficulties. Some residents were concerned that their questions would reflect poorly on them; others were embarrassed by their mistaken decisions. Conversely, residents described receiving interprofessional supervision from nurses and pharmacists, who proactively monitored, intervened in, and guided residents' decisions. Residents relied on nurses and pharmacists for non-judgmental answers to their queries, especially after-hours. To enhance both types of supervision, residents emphasized the importance of improving interpersonal communication skills. Conclusions Residents depended on interprofessional supervision when making decisions regarding medications in the ICU. Improving interprofessional supervision, which thus far has been under-recognized and underemphasized in graduate medical education, can potentially improve medication safety in high-risk settings. PMID:21990173
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Davidson, Peter J; Lopez, Andrea M; Kral, Alex H
2018-03-01
Supervised injection facilities (SIFs) are spaces where people can consume pre-obtained drugs in hygienic circumstances with trained staff in attendance to provide emergency response in the event of an overdose or other medical emergency, and to provide counselling and referral to other social and health services. Over 100 facilities with formal legal sanction exist in ten countries, and extensive research has shown they reduce overdose deaths, increase drug treatment uptake, and reduce social nuisance. No facility with formal legal sanction currently exists in the United States, however one community-based organization has successfully operated an 'underground' facility since September 2014. Twenty three qualitative interviews were conducted with people who used the underground facility, staff, and volunteers to examine the impact of the facility on peoples' lives, including the impact of lack of formal legal sanction on service provision. Participants reported that having a safe space to inject drugs had led to less injections in public spaces, greater ability to practice hygienic injecting practices, and greater protection from fatal overdose. Constructive aspects of being 'underground' included the ability to shape rules and procedures around user need rather than to meet political concerns, and the rapid deployment of the project, based on immediate need. Limitations associated with being underground included restrictions in the size and diversity of the population served by the site, and reduced ability to closely link the service to drug treatment and other health and social services. Unsanctioned supervised injection facilities can provide a rapid and user-driven response to urgent public health needs. This work draws attention to the need to ensure such services remain focused on user-defined need rather than external political concerns in jurisdictions where supervised injection facilities acquire local legal sanction. Copyright © 2017 Elsevier B.V. All rights reserved.
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Macananey, Oscar; O'Shea, Donal; Warmington, Stuart A; Green, Simon; Egaña, Mikel
2012-08-01
Supervised exercise (SE) in patients with type 2 diabetes improves oxygen uptake kinetics at the onset of exercise. Maintenance of these improvements, however, has not been examined when supervision is removed. We explored if potential improvements in oxygen uptake kinetics following a 12-week SE that combined aerobic and resistance training were maintained after a subsequent 12-week unsupervised exercise (UE). The involvement of cardiac output (CO) in these improvements was also tested. Nineteen volunteers with type 2 diabetes were recruited. Oxygen uptake kinetics and CO (inert gas rebreathing) responses to constant-load cycling at 50% ventilatory threshold (V(T)), 80% V(T), and mid-point between V(T) and peak workload (50% Δ) were examined at baseline (on 2 occasions) and following each 12-week training period. Participants decided to exercise at a local gymnasium during the UE. Thirteen subjects completed all the interventions. The time constant of phase 2 of oxygen uptake was significantly faster (p < 0.05) post-SE and post-UE compared with baseline at 50% V(T) (17.3 ± 10.7 s and 17.5 ± 5.9 s vs. 29.9 ± 10.7 s), 80% V(T) (18.9 ± 4.7 and 20.9 ± 8.4 vs. 34.3 ± 12.7s), and 50% Δ (20.4 ± 8.2 s and 20.2 ± 6.0 s vs. 27.6 ± 3.7 s). SE also induced faster heart rate kinetics at all 3 intensities and a larger increase in CO at 30 s in relation to 240 s at 80% V(T); and these responses were maintained post-UE. Unsupervised exercise maintained benefits in oxygen uptake kinetics obtained during a supervised exercise in subjects with diabetes, and these benefits were associated with a faster dynamic response of heart rate after training.
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Ibrahim, Abdulrasheed; Delia, Ibrahim Z; Edaigbini, Sunday A; Abubakar, Amina; Dahiru, Ismail L; Lawal, Zakari Y
2013-01-01
Background: The transformation of a surgical trainee into a surgeon is strongly influenced by the quality of teaching in the operating theater. This study investigates the perceptions of residents about the educational environment of the operating theater and identifies variables that may improve the operating theater education of our trainees. Materials and Methods: Residents in the department of surgery anonymously evaluated teaching in the operating room using the operating theater education environment measure. The residents evaluated 33 variables that might have an impact on their surgical skills within the operating theater. The variables were grouped into four subscales; teaching and training, learning opportunities, operating theater atmosphere and workload/supervision/support. Differences between male and female residents and junior and senior registrars were assessed using Mann-Whitney test. Statistical analysis was completed with the statistics package for the social sciences version 17. Results: A total of 33 residents were participated in this study. Twenty nine (88%) males and 4 (12%) females. 30 (90%) were junior registrars. The mean total score was 67.5%. Operating theater atmosphere subscale had the highest score of 79.2% while workload/supervision/support subscale had the least score of 48.3%. There were significant differences between male and female resident's perception of workload/supervision/support P < 0.05; however, there was no significant differences in junior registrar versus senior registrar's perception of the education environment in all the subscales P > 0.05. Conclusion: This study has shown a satisfactory teaching environment based on the existing local realities of means, resources and tools and highlighted the need for improvement in workload/supervision/support in our institution. An acceptable learning environment in the operating theatre will produce surgeons that are technically competent to bridge the gap in the enormous unmet need for surgical care in Nigeria. PMID:24497753
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Yan, Zheng; Wang, Jun
2014-03-01
This paper presents a neural network approach to robust model predictive control (MPC) for constrained discrete-time nonlinear systems with unmodeled dynamics affected by bounded uncertainties. The exact nonlinear model of underlying process is not precisely known, but a partially known nominal model is available. This partially known nonlinear model is first decomposed to an affine term plus an unknown high-order term via Jacobian linearization. The linearization residue combined with unmodeled dynamics is then modeled using an extreme learning machine via supervised learning. The minimax methodology is exploited to deal with bounded uncertainties. The minimax optimization problem is reformulated as a convex minimization problem and is iteratively solved by a two-layer recurrent neural network. The proposed neurodynamic approach to nonlinear MPC improves the computational efficiency and sheds a light for real-time implementability of MPC technology. Simulation results are provided to substantiate the effectiveness and characteristics of the proposed approach.
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Khanmohammadi, Mohammadreza; Bagheri Garmarudi, Amir; Samani, Simin; Ghasemi, Keyvan; Ashuri, Ahmad
2011-06-01
Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) microspectroscopy was applied for detection of colon cancer according to the spectral features of colon tissues. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. A total of 78 colon tissues were used in spectroscopy studies. Major spectral differences were observed in 1,740-900 cm(-1) spectral region. Several chemometric methods such as analysis of variance (ANOVA), cluster analysis (CA) and linear discriminate analysis (LDA) were applied for classification of IR spectra. Utilizing the chemometric techniques, clear and reproducible differences were observed between the spectra of normal and cancer cases, suggesting that infrared microspectroscopy in conjunction with spectral data processing would be useful for diagnostic classification. Using LDA technique, the spectra were classified into cancer and normal tissue classes with an accuracy of 95.8%. The sensitivity and specificity was 100 and 93.1%, respectively.
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Design of a biochemical circuit motif for learning linear functions
Lakin, Matthew R.; Minnich, Amanda; Lane, Terran; Stefanovic, Darko
2014-01-01
Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective. PMID:25401175
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Design of a biochemical circuit motif for learning linear functions.
Lakin, Matthew R; Minnich, Amanda; Lane, Terran; Stefanovic, Darko
2014-12-06
Learning and adaptive behaviour are fundamental biological processes. A key goal in the field of bioengineering is to develop biochemical circuit architectures with the ability to adapt to dynamic chemical environments. Here, we present a novel design for a biomolecular circuit capable of supervised learning of linear functions, using a model based on chemical reactions catalysed by DNAzymes. To achieve this, we propose a novel mechanism of maintaining and modifying internal state in biochemical systems, thereby advancing the state of the art in biomolecular circuit architecture. We use simulations to demonstrate that the circuit is capable of learning behaviour and assess its asymptotic learning performance, scalability and robustness to noise. Such circuits show great potential for building autonomous in vivo nanomedical devices. While such a biochemical system can tell us a great deal about the fundamentals of learning in living systems and may have broad applications in biomedicine (e.g. autonomous and adaptive drugs), it also offers some intriguing challenges and surprising behaviours from a machine learning perspective.
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Estimating False Positive Contamination in Crater Annotations from Citizen Science Data
NASA Astrophysics Data System (ADS)
Tar, P. D.; Bugiolacchi, R.; Thacker, N. A.; Gilmour, J. D.
2017-01-01
Web-based citizen science often involves the classification of image features by large numbers of minimally trained volunteers, such as the identification of lunar impact craters under the Moon Zoo project. Whilst such approaches facilitate the analysis of large image data sets, the inexperience of users and ambiguity in image content can lead to contamination from false positive identifications. We give an approach, using Linear Poisson Models and image template matching, that can quantify levels of false positive contamination in citizen science Moon Zoo crater annotations. Linear Poisson Models are a form of machine learning which supports predictive error modelling and goodness-of-fits, unlike most alternative machine learning methods. The proposed supervised learning system can reduce the variability in crater counts whilst providing predictive error assessments of estimated quantities of remaining true verses false annotations. In an area of research influenced by human subjectivity, the proposed method provides a level of objectivity through the utilisation of image evidence, guided by candidate crater identifications.
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NASA Astrophysics Data System (ADS)
Qin, Yan-Hong; Zhao, Li-Chen; Yang, Zhan-Ying; Yang, Wen-Li
2018-01-01
We investigate linear interference effects between a nonlinear plane wave and bright solitons, which are admitted by a pair-transition coupled two-component Bose-Einstein condensate. We demonstrate that the interference effects can induce several localized waves possessing distinctive wave structures, mainly including anti-dark solitons, W-shaped solitons, multi-peak solitons, Kuznetsov-Ma like breathers, and multi-peak breathers. Specifically, the explicit conditions for them are clarified by a phase diagram based on the linear interference properties. Furthermore, the interactions between these localized waves are discussed. The detailed analysis indicates that the soliton-soliton interaction induced phase shift brings the collision between these localized waves which can be inelastic for solitons involving collision and can be elastic for breathers. These characters come from the fact that the profile of solitons depends on the relative phase between bright solitons and a plane wave, and the profile of breathers does not depend on the relative phase. These results would motivate more discussions on linear interference between other nonlinear waves. Specifically, the solitons or breathers obtained here are not related to modulational instability. The underlying reasons are discussed in detail. In addition, possibilities to observe these localized waves are discussed in a two species Bose-Einstein condensate.
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Local linear discriminant analysis framework using sample neighbors.
Fan, Zizhu; Xu, Yong; Zhang, David
2011-07-01
The linear discriminant analysis (LDA) is a very popular linear feature extraction approach. The algorithms of LDA usually perform well under the following two assumptions. The first assumption is that the global data structure is consistent with the local data structure. The second assumption is that the input data classes are Gaussian distributions. However, in real-world applications, these assumptions are not always satisfied. In this paper, we propose an improved LDA framework, the local LDA (LLDA), which can perform well without needing to satisfy the above two assumptions. Our LLDA framework can effectively capture the local structure of samples. According to different types of local data structure, our LLDA framework incorporates several different forms of linear feature extraction approaches, such as the classical LDA and principal component analysis. The proposed framework includes two LLDA algorithms: a vector-based LLDA algorithm and a matrix-based LLDA (MLLDA) algorithm. MLLDA is directly applicable to image recognition, such as face recognition. Our algorithms need to train only a small portion of the whole training set before testing a sample. They are suitable for learning large-scale databases especially when the input data dimensions are very high and can achieve high classification accuracy. Extensive experiments show that the proposed algorithms can obtain good classification results.
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Enriching Student Teaching Relationships. Supervising Teacher Edition.
ERIC Educational Resources Information Center
Clothier, Grant; Kingsley, Elizabeth
This training series was developed to improve the working relationships between supervising teachers and their student teachers. This supervising teacher's edition contains suggestions for such teachers as regards various activities dealing with the supervising/teaching situation, behavior problems, change, conference sessions, communication,…
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Code of Federal Regulations, 2010 CFR
2010-01-01
... available to supervised financial institutions and financial institution supervisory agencies. 261.20... Supervised Institutions, Financial Institution Supervisory Agencies, Law Enforcement Agencies, and Others in Certain Circumstances § 261.20 Confidential supervisory information made available to supervised financial...
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Code of Federal Regulations, 2010 CFR
2010-04-01
... 27 Alcohol, Tobacco Products and Firearms 2 2010-04-01 2010-04-01 false Supervision. 70.609... From Disaster, Vandalism, or Malicious Mischief Destruction of Liquors § 70.609 Supervision. When... official or made unmarketable, the liquors shall be destroyed by suitable means under supervision...
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7 CFR 550.33 - Administrative supervision.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 7 Agriculture 6 2014-01-01 2014-01-01 false Administrative supervision. 550.33 Section 550.33... Agreements Program Management § 550.33 Administrative supervision. REE employees are prohibited from engaging... management issues. The cooperator is solely responsible for the administrative supervision of its employees. ...
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7 CFR 550.33 - Administrative supervision.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 7 Agriculture 6 2012-01-01 2012-01-01 false Administrative supervision. 550.33 Section 550.33... Agreements Program Management § 550.33 Administrative supervision. REE employees are prohibited from engaging... management issues. The cooperator is solely responsible for the administrative supervision of its employees. ...
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7 CFR 550.33 - Administrative supervision.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 7 Agriculture 6 2013-01-01 2013-01-01 false Administrative supervision. 550.33 Section 550.33... Agreements Program Management § 550.33 Administrative supervision. REE employees are prohibited from engaging... management issues. The cooperator is solely responsible for the administrative supervision of its employees. ...
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Code of Federal Regulations, 2014 CFR
2014-04-01
... 27 Alcohol, Tobacco Products and Firearms 2 2014-04-01 2014-04-01 false Supervision. 70.609... From Disaster, Vandalism, or Malicious Mischief Destruction of Liquors § 70.609 Supervision. When... official or made unmarketable, the liquors shall be destroyed by suitable means under supervision...
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7 CFR 550.33 - Administrative supervision.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 7 Agriculture 6 2011-01-01 2011-01-01 false Administrative supervision. 550.33 Section 550.33... Agreements Program Management § 550.33 Administrative supervision. REE employees are prohibited from engaging... management issues. The cooperator is solely responsible for the administrative supervision of its employees. ...
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Code of Federal Regulations, 2011 CFR
2011-04-01
... 27 Alcohol, Tobacco Products and Firearms 2 2011-04-01 2011-04-01 false Supervision. 70.609... From Disaster, Vandalism, or Malicious Mischief Destruction of Liquors § 70.609 Supervision. When... official or made unmarketable, the liquors shall be destroyed by suitable means under supervision...
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Code of Federal Regulations, 2013 CFR
2013-04-01
... 27 Alcohol, Tobacco Products and Firearms 2 2013-04-01 2013-04-01 false Supervision. 70.609... From Disaster, Vandalism, or Malicious Mischief Destruction of Liquors § 70.609 Supervision. When... official or made unmarketable, the liquors shall be destroyed by suitable means under supervision...
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48 CFR 852.236-78 - Government supervision.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 48 Federal Acquisition Regulations System 5 2014-10-01 2014-10-01 false Government supervision. 852.236-78 Section 852.236-78 Federal Acquisition Regulations System DEPARTMENT OF VETERANS AFFAIRS... Government supervision. As prescribed in 836.572, insert the following clause: Government Supervision (APR...
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48 CFR 852.236-78 - Government supervision.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 48 Federal Acquisition Regulations System 5 2011-10-01 2011-10-01 false Government supervision. 852.236-78 Section 852.236-78 Federal Acquisition Regulations System DEPARTMENT OF VETERANS AFFAIRS... Government supervision. As prescribed in 836.572, insert the following clause: Government Supervision (APR...
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48 CFR 852.236-78 - Government supervision.
Code of Federal Regulations, 2010 CFR
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... Government supervision. As prescribed in 836.572, insert the following clause: Government Supervision (APR...
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48 CFR 852.236-78 - Government supervision.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 5 2012-10-01 2012-10-01 false Government supervision. 852.236-78 Section 852.236-78 Federal Acquisition Regulations System DEPARTMENT OF VETERANS AFFAIRS... Government supervision. As prescribed in 836.572, insert the following clause: Government Supervision (APR...
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48 CFR 852.236-78 - Government supervision.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 5 2013-10-01 2013-10-01 false Government supervision. 852.236-78 Section 852.236-78 Federal Acquisition Regulations System DEPARTMENT OF VETERANS AFFAIRS... Government supervision. As prescribed in 836.572, insert the following clause: Government Supervision (APR...
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Multicultural Supervision: What Difference Does Difference Make?
ERIC Educational Resources Information Center
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…
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Global and local curvature in density functional theory.
Zhao, Qing; Ioannidis, Efthymios I; Kulik, Heather J
2016-08-07
Piecewise linearity of the energy with respect to fractional electron removal or addition is a requirement of an electronic structure method that necessitates the presence of a derivative discontinuity at integer electron occupation. Semi-local exchange-correlation (xc) approximations within density functional theory (DFT) fail to reproduce this behavior, giving rise to deviations from linearity with a convex global curvature that is evidence of many-electron, self-interaction error and electron delocalization. Popular functional tuning strategies focus on reproducing piecewise linearity, especially to improve predictions of optical properties. In a divergent approach, Hubbard U-augmented DFT (i.e., DFT+U) treats self-interaction errors by reducing the local curvature of the energy with respect to electron removal or addition from one localized subshell to the surrounding system. Although it has been suggested that DFT+U should simultaneously alleviate global and local curvature in the atomic limit, no detailed study on real systems has been carried out to probe the validity of this statement. In this work, we show when DFT+U should minimize deviations from linearity and demonstrate that a "+U" correction will never worsen the deviation from linearity of the underlying xc approximation. However, we explain varying degrees of efficiency of the approach over 27 octahedral transition metal complexes with respect to transition metal (Sc-Cu) and ligand strength (CO, NH3, and H2O) and investigate select pathological cases where the delocalization error is invisible to DFT+U within an atomic projection framework. Finally, we demonstrate that the global and local curvatures represent different quantities that show opposing behavior with increasing ligand field strength, and we identify where these two may still coincide.
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Error Estimation for the Linearized Auto-Localization Algorithm
Guevara, Jorge; Jiménez, Antonio R.; Prieto, Jose Carlos; Seco, Fernando
2012-01-01
The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs), using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL), the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method. PMID:22736965
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Cummings, Jorden A; Ballantyne, Elena C; Scallion, Laura M
2015-06-01
Clinical supervision should be a proactive and considered endeavor, not a reactive one. To that end, supervisors should choose supervision processes that are driven by theory, best available research, and clinical experience. These processes should be aimed at helping trainees develop as clinicians. We highlight 3 supervision processes we believe should be used at each supervision meeting: agenda setting, encouraging trainee problem-solving, and formative feedback. Although these are primarily cognitive-behavioral skills, they can be helpful in combination with other supervision models. We provide example dialogue from supervision exchanges, and discuss theoretical and research support for these processes. Using these processes not only encourages trainee development but also models for them how to use the same processes and approaches with clients. (c) 2015 APA, all rights reserved).
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Pitkänen, Salla; Kääriäinen, Maria; Oikarainen, Ashlee; Tuomikoski, Anna-Maria; Elo, Satu; Ruotsalainen, Heidi; Saarikoski, Mikko; Kärsämänoja, Taina; Mikkonen, Kristina
2018-03-01
The purpose of clinical placements and supervision is to promote the development of healthcare students´ professional skills. High-quality clinical learning environments and supervision were shown to have significant influence on healthcare students´ professional development. This study aimed to describe healthcare students` evaluation of the clinical learning environment and supervision, and to identify the factors that affect these. The study was performed as a cross-sectional study. The data (n = 1973) were gathered through an online survey using the Clinical Learning Environment, Supervision and Nurse Teacher scale during the academic year 2015-2016 from all healthcare students (N = 2500) who completed their clinical placement at a certain university hospital in Finland. The data were analysed using descriptive statistics and binary logistic regression analysis. More than half of the healthcare students had a named supervisor and supervision was completed as planned. The students evaluated the clinical learning environment and supervision as 'good'. The students´ readiness to recommend the unit to other students and the frequency of separate private unscheduled sessions with the supervisor were the main factors that affect healthcare students` evaluation of the clinical learning environment and supervision. Individualized and goal-oriented supervision in which the student had a named supervisor and where supervision was completed as planned in a positive environment that supported learning had a significant impact on student's learning. The clinical learning environment and supervision support the development of future healthcare professionals' clinical competence. The supervisory relationship was shown to have a significant effect on the outcomes of students' experiences. We recommend the planning of educational programmes for supervisors of healthcare students for the enhancement of supervisors' pedagogical competencies in supervising students in the clinical practice. Copyright © 2018 Elsevier Ltd. All rights reserved.
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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 understand the effects of supervisory styles on trainee doctors' talent development are contigent on the trainee doctors' clinical learning environment. In summary, supervisors are stakeholders with the responsibility of facilitating learning conditions that hold sufficient structure and support to optimise the trainee doctors learning.
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Locally linear embedding: dimension reduction of massive protostellar spectra
NASA Astrophysics Data System (ADS)
Ward, J. L.; Lumsden, S. L.
2016-09-01
We present the results of the application of locally linear embedding (LLE) to reduce the dimensionality of dereddened and continuum subtracted near-infrared spectra using a combination of models and real spectra of massive protostars selected from the Red MSX Source survey data base. A brief comparison is also made with two other dimension reduction techniques; principal component analysis (PCA) and Isomap using the same set of spectra as well as a more advanced form of LLE, Hessian locally linear embedding. We find that whilst LLE certainly has its limitations, it significantly outperforms both PCA and Isomap in classification of spectra based on the presence/absence of emission lines and provides a valuable tool for classification and analysis of large spectral data sets.
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Counseling Supervision within a Feminist Framework: Guidelines for Intervention
ERIC Educational Resources Information Center
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…
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78 FR 42863 - Rescission of Supervised Investment Bank Holding Company Rules
Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-18
... Rescission of Supervised Investment Bank Holding Company Rules AGENCY: Securities and Exchange Commission... program for supervising investment bank holding companies. The Commission is taking this action pursuant... pertain to the supervised investment bank holding company program rules that are being rescinded. DATES...
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Methods of Feminist Family Therapy Supervision.
ERIC Educational Resources Information Center
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…
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28 CFR 115.113 - Supervision and monitoring.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 28 Judicial Administration 2 2014-07-01 2014-07-01 false Supervision and monitoring. 115.113... NATIONAL STANDARDS Standards for Lockups Prevention Planning § 115.113 Supervision and monitoring. (a) For... heightened protection, to include continuous direct sight and sound supervision, single-cell housing, or...