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

PubMed

Galpert, Deborah; Del Río, Sara; Herrera, Francisco; Ancede-Gallardo, Evys; Antunes, Agostinho; Agüero-Chapin, Guillermin

2015-01-01

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

A targeted change-detection procedure by combining change vector analysis and post-classification approach

NASA Astrophysics Data System (ADS)

Ye, Su; Chen, Dongmei; Yu, Jie

2016-04-01

In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

In-situ trainable intrusion detection system

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

Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob

A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such thatmore » the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.« less

Active Semi-Supervised Community Detection Based on Must-Link and Cannot-Link Constraints

PubMed Central

Cheng, Jianjun; Leng, Mingwei; Li, Longjie; Zhou, Hanhai; Chen, Xiaoyun

2014-01-01

Community structure detection is of great importance because it can help in discovering the relationship between the function and the topology structure of a network. Many community detection algorithms have been proposed, but how to incorporate the prior knowledge in the detection process remains a challenging problem. In this paper, we propose a semi-supervised community detection algorithm, which makes full utilization of the must-link and cannot-link constraints to guide the process of community detection and thereby extracts high-quality community structures from networks. To acquire the high-quality must-link and cannot-link constraints, we also propose a semi-supervised component generation algorithm based on active learning, which actively selects nodes with maximum utility for the proposed semi-supervised community detection algorithm step by step, and then generates the must-link and cannot-link constraints by accessing a noiseless oracle. Extensive experiments were carried out, and the experimental results show that the introduction of active learning into the problem of community detection makes a success. Our proposed method can extract high-quality community structures from networks, and significantly outperforms other comparison methods. PMID:25329660

Detecting Visually Observable Disease Symptoms from Faces.

PubMed

Wang, Kuan; Luo, Jiebo

2016-12-01

Recent years have witnessed an increasing interest in the application of machine learning to clinical informatics and healthcare systems. A significant amount of research has been done on healthcare systems based on supervised learning. In this study, we present a generalized solution to detect visually observable symptoms on faces using semi-supervised anomaly detection combined with machine vision algorithms. We rely on the disease-related statistical facts to detect abnormalities and classify them into multiple categories to narrow down the possible medical reasons of detecting. Our method is in contrast with most existing approaches, which are limited by the availability of labeled training data required for supervised learning, and therefore offers the major advantage of flagging any unusual and visually observable symptoms.

Applications of remote sensing, volume 3

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Of the four change detection techniques (post classification comparison, delta data, spectral/temporal, and layered spectral temporal), the post classification comparison was selected for further development. This was based upon test performances of the four change detection method, straightforwardness of the procedures, and the output products desired. A standardized modified, supervised classification procedure for analyzing the Texas coastal zone data was compiled. This procedure was developed in order that all quadrangles in the study are would be classified using similar analysis techniques to allow for meaningful comparisons and evaluations of the classifications.

FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection.

PubMed

Noto, Keith; Brodley, Carla; Slonim, Donna

2012-01-01

Anomaly detection involves identifying rare data instances (anomalies) that come from a different class or distribution than the majority (which are simply called "normal" instances). Given a training set of only normal data, the semi-supervised anomaly detection task is to identify anomalies in the future. Good solutions to this task have applications in fraud and intrusion detection. The unsupervised anomaly detection task is different: Given unlabeled, mostly-normal data, identify the anomalies among them. Many real-world machine learning tasks, including many fraud and intrusion detection tasks, are unsupervised because it is impractical (or impossible) to verify all of the training data. We recently presented FRaC, a new approach for semi-supervised anomaly detection. FRaC is based on using normal instances to build an ensemble of feature models, and then identifying instances that disagree with those models as anomalous. In this paper, we investigate the behavior of FRaC experimentally and explain why FRaC is so successful. We also show that FRaC is a superior approach for the unsupervised as well as the semi-supervised anomaly detection task, compared to well-known state-of-the-art anomaly detection methods, LOF and one-class support vector machines, and to an existing feature-modeling approach.

FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection

PubMed Central

Brodley, Carla; Slonim, Donna

2011-01-01

Anomaly detection involves identifying rare data instances (anomalies) that come from a different class or distribution than the majority (which are simply called “normal” instances). Given a training set of only normal data, the semi-supervised anomaly detection task is to identify anomalies in the future. Good solutions to this task have applications in fraud and intrusion detection. The unsupervised anomaly detection task is different: Given unlabeled, mostly-normal data, identify the anomalies among them. Many real-world machine learning tasks, including many fraud and intrusion detection tasks, are unsupervised because it is impractical (or impossible) to verify all of the training data. We recently presented FRaC, a new approach for semi-supervised anomaly detection. FRaC is based on using normal instances to build an ensemble of feature models, and then identifying instances that disagree with those models as anomalous. In this paper, we investigate the behavior of FRaC experimentally and explain why FRaC is so successful. We also show that FRaC is a superior approach for the unsupervised as well as the semi-supervised anomaly detection task, compared to well-known state-of-the-art anomaly detection methods, LOF and one-class support vector machines, and to an existing feature-modeling approach. PMID:22639542

Active link selection for efficient semi-supervised community detection

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Active link selection for efficient semi-supervised community detection

PubMed Central

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

2015-01-01

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

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.

Unsupervised active learning based on hierarchical graph-theoretic clustering.

PubMed

Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

2009-10-01

Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

Using Machine Learning for Advanced Anomaly Detection and Classification

NASA Astrophysics Data System (ADS)

Lane, B.; Poole, M.; Camp, M.; Murray-Krezan, J.

2016-09-01

Machine Learning (ML) techniques have successfully been used in a wide variety of applications to automatically detect and potentially classify changes in activity, or a series of activities by utilizing large amounts data, sometimes even seemingly-unrelated data. The amount of data being collected, processed, and stored in the Space Situational Awareness (SSA) domain has grown at an exponential rate and is now better suited for ML. This paper describes development of advanced algorithms to deliver significant improvements in characterization of deep space objects and indication and warning (I&W) using a global network of telescopes that are collecting photometric data on a multitude of space-based objects. The Phase II Air Force Research Laboratory (AFRL) Small Business Innovative Research (SBIR) project Autonomous Characterization Algorithms for Change Detection and Characterization (ACDC), contracted to ExoAnalytic Solutions Inc. is providing the ability to detect and identify photometric signature changes due to potential space object changes (e.g. stability, tumble rate, aspect ratio), and correlate observed changes to potential behavioral changes using a variety of techniques, including supervised learning. Furthermore, these algorithms run in real-time on data being collected and processed by the ExoAnalytic Space Operations Center (EspOC), providing timely alerts and warnings while dynamically creating collection requirements to the EspOC for the algorithms that generate higher fidelity I&W. This paper will discuss the recently implemented ACDC algorithms, including the general design approach and results to date. The usage of supervised algorithms, such as Support Vector Machines, Neural Networks, k-Nearest Neighbors, etc., and unsupervised algorithms, for example k-means, Principle Component Analysis, Hierarchical Clustering, etc., and the implementations of these algorithms is explored. Results of applying these algorithms to EspOC data both in an off-line "pattern of life" analysis as well as using the algorithms on-line in real-time, meaning as data is collected, will be presented. Finally, future work in applying ML for SSA will be discussed.

Unsupervised change detection in a particular vegetation land cover type using spectral angle mapper

NASA Astrophysics Data System (ADS)

Renza, Diego; Martinez, Estibaliz; Molina, Iñigo; Ballesteros L., Dora M.

2017-04-01

This paper presents a new unsupervised change detection methodology for multispectral images applied to specific land covers. The proposed method involves comparing each image against a reference spectrum, where the reference spectrum is obtained from the spectral signature of the type of coverage you want to detect. In this case the method has been tested using multispectral images (SPOT5) of the community of Madrid (Spain), and multispectral images (Quickbird) of an area over Indonesia that was impacted by the December 26, 2004 tsunami; here, the tests have focused on the detection of changes in vegetation. The image comparison is obtained by applying Spectral Angle Mapper between the reference spectrum and each multitemporal image. Then, a threshold to produce a single image of change is applied, which corresponds to the vegetation zones. The results for each multitemporal image are combined through an exclusive or (XOR) operation that selects vegetation zones that have changed over time. Finally, the derived results were compared against a supervised method based on classification with the Support Vector Machine. Furthermore, the NDVI-differencing and the Spectral Angle Mapper techniques were selected as unsupervised methods for comparison purposes. The main novelty of the method consists in the detection of changes in a specific land cover type (vegetation), therefore, for comparison purposes, the best scenario is to compare it with methods that aim to detect changes in a specific land cover type (vegetation). This is the main reason to select NDVI-based method and the post-classification method (SVM implemented in a standard software tool). To evaluate the improvements using a reference spectrum vector, the results are compared with the basic-SAM method. In SPOT5 image, the overall accuracy was 99.36% and the κ index was 90.11%; in Quickbird image, the overall accuracy was 97.5% and the κ index was 82.16%. Finally, the precision results of the method are comparable to those of a supervised method, supported by low detection of false positives and false negatives, along with a high overall accuracy and a high kappa index. On the other hand, the execution times were comparable to those of unsupervised methods of low computational load.

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers.

PubMed

Galpert, Deborah; Fernández, Alberto; Herrera, Francisco; Antunes, Agostinho; Molina-Ruiz, Reinaldo; Agüero-Chapin, Guillermin

2018-05-03

The development of new ortholog detection algorithms and the improvement of existing ones are of major importance in functional genomics. We have previously introduced a successful supervised pairwise ortholog classification approach implemented in a big data platform that considered several pairwise protein features and the low ortholog pair ratios found between two annotated proteomes (Galpert, D et al., BioMed Research International, 2015). The supervised models were built and tested using a Saccharomycete yeast benchmark dataset proposed by Salichos and Rokas (2011). Despite several pairwise protein features being combined in a supervised big data approach; they all, to some extent were alignment-based features and the proposed algorithms were evaluated on a unique test set. Here, we aim to evaluate the impact of alignment-free features on the performance of supervised models implemented in the Spark big data platform for pairwise ortholog detection in several related yeast proteomes. The Spark Random Forest and Decision Trees with oversampling and undersampling techniques, and built with only alignment-based similarity measures or combined with several alignment-free pairwise protein features showed the highest classification performance for ortholog detection in three yeast proteome pairs. Although such supervised approaches outperformed traditional methods, there were no significant differences between the exclusive use of alignment-based similarity measures and their combination with alignment-free features, even within the twilight zone of the studied proteomes. Just when alignment-based and alignment-free features were combined in Spark Decision Trees with imbalance management, a higher success rate (98.71%) within the twilight zone could be achieved for a yeast proteome pair that underwent a whole genome duplication. The feature selection study showed that alignment-based features were top-ranked for the best classifiers while the runners-up were alignment-free features related to amino acid composition. The incorporation of alignment-free features in supervised big data models did not significantly improve ortholog detection in yeast proteomes regarding the classification qualities achieved with just alignment-based similarity measures. However, the similarity of their classification performance to that of traditional ortholog detection methods encourages the evaluation of other alignment-free protein pair descriptors in future research.

Tracking the Effect of Algal Mats on Coral Bleaching Using Remote Sensing

NASA Astrophysics Data System (ADS)

El-Askary, H. M.; Johnson, S. H.; Idris, N.; Qurban, M. A. B.

2014-12-01

Benthic habitats rely on relatively stable environmental conditions for survival. The introduction of algal mats into an ecosystem can have a notable effect on the livelihood of organisms such as coral reefs by causing changes in the biogeochemistry of the surrounding water. Increasing levels of acidity and new competition for sunlight caused by congregations of cyanobacteria essentially starve coral reefs of natural resources. These changes are particularly prevalent in waters near quickly developing population centers, such as the ecologically diverse Arabian Gulf. While ground-truthing studies to determine the extensiveness of coral death proves useful on a microcosmic level, new ventures in remote sensing research allow scientists to utilize satellite data to track these changes on a broader scale. Satellite images acquired from Landsat 5, 1987, Landsat 7, 2000, and Landsat 8, 2013 along with higher resolution IKONOS data are digitally analyzed in order to create spectral libraries for relevant benthic types, which in turn can be used to perform supervised classifications and change detection analyses over a larger area. The supervised classifications performed over the three scenes show five significant marine-related classes, namely coral, mangroves, macro-algae, and seagrass, in different degrees of abundance, yet here we focus only on the algal mats impact on corals bleaching. The change detection analysis is introduced to study see the degree of algal mats impact on coral bleaching over the course of time with possible connection to the local meteorology and current climate scenarios.

Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control.

PubMed

Kawato, Mitsuo; Kuroda, Shinya; Schweighofer, Nicolas

2011-10-01

The biophysical models of spike-timing-dependent plasticity have explored dynamics with molecular basis for such computational concepts as coincidence detection, synaptic eligibility trace, and Hebbian learning. They overall support different learning algorithms in different brain areas, especially supervised learning in the cerebellum. Because a single spine is physically very small, chemical reactions at it are essentially stochastic, and thus sensitivity-longevity dilemma exists in the synaptic memory. Here, the cascade of excitable and bistable dynamics is proposed to overcome this difficulty. All kinds of learning algorithms in different brain regions confront with difficult generalization problems. For resolution of this issue, the control of the degrees-of-freedom can be realized by changing synchronicity of neural firing. Especially, for cerebellar supervised learning, the triangle closed-loop circuit consisting of Purkinje cells, the inferior olive nucleus, and the cerebellar nucleus is proposed as a circuit to optimally control synchronous firing and degrees-of-freedom in learning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Predicting protein complexes using a supervised learning method combined with local structural information.

PubMed

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.

Postgraduate Research Supervision: A Critical Review of Current Practice

ERIC Educational Resources Information Center

McCallin, Antoinette; Nayar, Shoba

2012-01-01

Changes in the funding and delivery of research programmes at the university level have, in recent years, resulted in significant changes to research supervision. This paper critically reviews key influences effecting postgraduate supervision. Analysis draws on literature spanning 2000-2010 to determine the appropriateness of traditional models of…

Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

NASA Astrophysics Data System (ADS)

Kumar, Lalit; Ghosh, Manoj Kumer

2012-01-01

Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.

Just-in-time classifiers for recurrent concepts.

PubMed

Alippi, Cesare; Boracchi, Giacomo; Roveri, Manuel

2013-04-01

Just-in-time (JIT) classifiers operate in evolving environments by classifying instances and reacting to concept drift. In stationary conditions, a JIT classifier improves its accuracy over time by exploiting additional supervised information coming from the field. In nonstationary conditions, however, the classifier reacts as soon as concept drift is detected; the current classification setup is discarded and a suitable one activated to keep the accuracy high. We present a novel generation of JIT classifiers able to deal with recurrent concept drift by means of a practical formalization of the concept representation and the definition of a set of operators working on such representations. The concept-drift detection activity, which is crucial in promptly reacting to changes exactly when needed, is advanced by considering change-detection tests monitoring both inputs and classes distributions.

Diagnostic Imaging of Reproductive Tract Disorders in Reptiles.

PubMed

Gumpenberger, Michaela

2017-05-01

Diagnostic imaging of the reproductive tract in reptiles is used for gender determination, evaluation of breeding status, detection of pathologic changes, and supervising treatment. Whole-body radiographs provide an overview and support detection of mineralized egg shells. Sonography is used to evaluate follicles, nonmineralized eggs, and the salpinx in all reptiles. Computed tomography is able to overcome imaging limitations in chelonian species. This article provides detailed information about the performance of different imaging techniques. Multiple images demonstrate the physiologic appearance of the male and female reproductive tract in various reptile species and pathologic changes. Advantages and disadvantages of radiography, sonography, and computed tomography are described. Copyright © 2016 Elsevier Inc. All rights reserved.

Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients

NASA Technical Reports Server (NTRS)

Thompson, David R.; Majid, Walid A.; Reed, Colorado J.; Wagstaff, Kiri L.

2011-01-01

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.

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,…

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

Deep Learning @15 Petaflops/second: Semi-supervised pattern detection for 15 Terabytes of climate data

NASA Astrophysics Data System (ADS)

Collins, W. D.; Wehner, M. F.; Prabhat, M.; Kurth, T.; Satish, N.; Mitliagkas, I.; Zhang, J.; Racah, E.; Patwary, M.; Sundaram, N.; Dubey, P.

2017-12-01

Anthropogenically-forced climate changes in the number and character of extreme storms have the potential to significantly impact human and natural systems. Current high-performance computing enables multidecadal simulations with global climate models at resolutions of 25km or finer. Such high-resolution simulations are demonstrably superior in simulating extreme storms such as tropical cyclones than the coarser simulations available in the Coupled Model Intercomparison Project (CMIP5) and provide the capability to more credibly project future changes in extreme storm statistics and properties. The identification and tracking of storms in the voluminous model output is very challenging as it is impractical to manually identify storms due to the enormous size of the datasets, and therefore automated procedures are used. Traditionally, these procedures are based on a multi-variate set of physical conditions based on known properties of the class of storms in question. In recent years, we have successfully demonstrated that Deep Learning produces state of the art results for pattern detection in climate data. We have developed supervised and semi-supervised convolutional architectures for detecting and localizing tropical cyclones, extra-tropical cyclones and atmospheric rivers in simulation data. One of the primary challenges in the applicability of Deep Learning to climate data is in the expensive training phase. Typical networks may take days to converge on 10GB-sized datasets, while the climate science community has ready access to O(10 TB)-O(PB) sized datasets. In this work, we present the most scalable implementation of Deep Learning to date. We successfully scale a unified, semi-supervised convolutional architecture on all of the Cori Phase II supercomputer at NERSC. We use IntelCaffe, MKL and MLSL libraries. We have optimized single node MKL libraries to obtain 1-4 TF on single KNL nodes. We have developed a novel hybrid parameter update strategy to improve scaling to 9600 KNL nodes (600,000 cores). We obtain 15PF performance over the course of the training run; setting a new watermark for the HPC and Deep Learning communities. This talk will share insights on how to obtain this extreme level of performance, current gaps/challenges and implications for the climate science community.

A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Sainani, Varsha

The increasing number of network security related incidents have made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). IDSs are expected to analyze a large volume of data while not placing a significantly added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel data mining assisted multiagent-based intrusion detection system (DMAS-IDS) is proposed, particularly with the support of multiclass supervised classification. These agents can detect and take predefined actions against malicious activities, and data mining techniques can help detect them. Our proposed DMAS-IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDS with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on multiagent platform along with a supervised classification technique.

Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification

NASA Astrophysics Data System (ADS)

Charfi, Imen; Miteran, Johel; Dubois, Julien; Atri, Mohamed; Tourki, Rached

2013-10-01

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the features (Fourier transform, wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using support vector machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained by combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol that enables performance to be improved by updating the training in the current location with normal activities records.

Applicability Assessment of Uavsar Data in Wetland Monitoring: a Case Study of Louisiana Wetland

NASA Astrophysics Data System (ADS)

Zhao, J.; Niu, Y.; Lu, Z.; Yang, J.; Li, P.; Liu, W.

2018-04-01

Wetlands are highly productive and support a wide variety of ecosystem goods and services. Monitoring wetland is essential and potential. Because of the repeat-pass nature of satellite orbit and airborne, time-series of remote sensing data can be obtained to monitor wetland. UAVSAR is a NASA L-band synthetic aperture radar (SAR) sensor compact pod-mounted polarimetric instrument for interferometric repeat-track observations. Moreover, UAVSAR images can accurately map crustal deformations associated with natural hazards, such as volcanoes and earthquakes. And its polarization agility facilitates terrain and land-use classification and change detection. In this paper, the multi-temporal UAVSAR data are applied for monitoring the wetland change. Using the multi-temporal polarimetric SAR (PolSAR) data, the change detection maps are obtained by unsupervised and supervised method. And the coherence is extracted from the interfometric SAR (InSAR) data to verify the accuracy of change detection map. The experimental results show that the multi-temporal UAVSAR data is fit for wetland monitor.

An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

PubMed

Lu, Alex Xijie; Moses, Alan M

2016-01-01

Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

Creating an educationally minded schedule: one approach to minimize the impact of duty hour standards on intern continuity clinic experience.

PubMed

DeBlasio, Dominick; Kerrey, M Kathleen; Sucharew, Heidi; Klein, Melissa

2014-11-01

To determine if implementing an educationally minded schedule utilizing consecutive night shifts can moderate the impact of the 2011 duty hour standards on education and patient continuity of care in longitudinal primary care experience (continuity clinic). A 14-month pre-post study was performed in continuity clinic with one supervising physician group and two intern groups. Surveys to assess attitudes and education were distributed to the supervising physicians and interns before and after the changes in duty hour standards. Intern groups' schedules were reviewed for the number of regular and alternative day clinic (i.e. primary care experience on a different weekday) sessions and patient continuity of care. Fifteen supervising physicians and 51 interns participated (25 in 2011, 26 in 2012). Intern groups' comfort when discussing patient issues, educational needs and teamwork perception did not differ. Supervising physicians' understanding of learning needs and provision of feedback did not differ between groups. Supervising physicians indicated a greater ability to provide feedback and understand learning needs during regular continuity clinic sessions compared with alternative day clinics (all p < 0.05). No significant difference was detected between intern groups in the number of regularly scheduled continuity clinics, alternative day clinics or patient continuity of care. The 2011 duty hour standards required significant alterations to intern schedules, but educationally minded scheduling limited impact on education and patient continuity in care.

Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point Clouds.

PubMed

Tran, Thi Huong Giang; Ressl, Camillo; Pfeifer, Norbert

2018-02-03

This paper suggests a new approach for change detection (CD) in 3D point clouds. It combines classification and CD in one step using machine learning. The point cloud data of both epochs are merged for computing features of four types: features describing the point distribution, a feature relating to relative terrain elevation, features specific for the multi-target capability of laser scanning, and features combining the point clouds of both epochs to identify the change. All these features are merged in the points and then training samples are acquired to create the model for supervised classification, which is then applied to the whole study area. The final results reach an overall accuracy of over 90% for both epochs of eight classes: lost tree, new tree, lost building, new building, changed ground, unchanged building, unchanged tree, and unchanged ground.

Detecting event-related changes in organizational networks using optimized neural network models.

PubMed

Li, Ze; Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques.

Detecting event-related changes in organizational networks using optimized neural network models

PubMed Central

Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques. PMID:29190799

To Be or Not to Be: Community Supervision Deja Vu

ERIC Educational Resources Information Center

Taxman, Faye S.

2008-01-01

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

Supervision: A Guide to Instructional Leadership-2nd Edition

ERIC Educational Resources Information Center

Burke, Peter J.; Krey, Robert D.

2005-01-01

The first edition of this book, titled "A Design for Instructional Supervision", provided a structural framework for an effective program of instructional supervision. The basic cognitive thrust of this second edition, "Supervision: A Guide to Instructional Leadership", remains the same as the first. What has changed is the attention to the…

Radar detection with the Neyman-Pearson criterion using supervised-learning-machines trained with the cross-entropy error

NASA Astrophysics Data System (ADS)

Jarabo-Amores, María-Pilar; la Mata-Moya, David de; Gil-Pita, Roberto; Rosa-Zurera, Manuel

2013-12-01

The application of supervised learning machines trained to minimize the Cross-Entropy error to radar detection is explored in this article. The detector is implemented with a learning machine that implements a discriminant function, which output is compared to a threshold selected to fix a desired probability of false alarm. The study is based on the calculation of the function the learning machine approximates to during training, and the application of a sufficient condition for a discriminant function to be used to approximate the optimum Neyman-Pearson (NP) detector. In this article, the function a supervised learning machine approximates to after being trained to minimize the Cross-Entropy error is obtained. This discriminant function can be used to implement the NP detector, which maximizes the probability of detection, maintaining the probability of false alarm below or equal to a predefined value. Some experiments about signal detection using neural networks are also presented to test the validity of the study.

Supervision of Supervisors: On Developing Supervision in Postgraduate Education

ERIC Educational Resources Information Center

Emilsson, Ulla Melin; Johnsson, Eva

2007-01-01

During the 1900s, the path to a PhD degree has seen many changes for both postgraduate students as well as their supervisors. The supervisor's duties have increased in scope and the demands made on PhD candidates have augmented. This paper deals with supervision as pedagogic method. Departing from a project aimed at studying "supervision on…

Change classification in SAR time series: a functional approach

NASA Astrophysics Data System (ADS)

Boldt, Markus; Thiele, Antje; Schulz, Karsten; Hinz, Stefan

2017-10-01

Change detection represents a broad field of research in SAR remote sensing, consisting of many different approaches. Besides the simple recognition of change areas, the analysis of type, category or class of the change areas is at least as important for creating a comprehensive result. Conventional strategies for change classification are based on supervised or unsupervised landuse / landcover classifications. The main drawback of such approaches is that the quality of the classification result directly depends on the selection of training and reference data. Additionally, supervised processing methods require an experienced operator who capably selects the training samples. This training step is not necessary when using unsupervised strategies, but nevertheless meaningful reference data must be available for identifying the resulting classes. Consequently, an experienced operator is indispensable. In this study, an innovative concept for the classification of changes in SAR time series data is proposed. Regarding the drawbacks of traditional strategies given above, it copes without using any training data. Moreover, the method can be applied by an operator, who does not have detailed knowledge about the available scenery yet. This knowledge is provided by the algorithm. The final step of the procedure, which main aspect is given by the iterative optimization of an initial class scheme with respect to the categorized change objects, is represented by the classification of these objects to the finally resulting classes. This assignment step is subject of this paper.

How to create more supportive supervision for primary healthcare: lessons from Ngamiland district of Botswana: co-operative inquiry group.

PubMed

Nkomazana, Oathokwa; Mash, Robert; Wojczewski, Silvia; Kutalek, Ruth; Phaladze, Nthabiseng

2016-01-01

Supportive supervision is a way to foster performance, productivity, motivation, and retention of health workforce. Nevertheless there is a dearth of evidence of the impact and acceptability of supportive supervision in low- and middle-income countries. This article describes a participatory process of transforming the supervisory practice of district health managers to create a supportive environment for primary healthcare workers. The objective of the study was to explore how district health managers can change their practice to create a more supportive environment for primary healthcare providers. A facilitated co-operative inquiry group (CIG) was formed with Ngamiland health district managers. CIG belongs to the participatory action research paradigm and is characterised by a cyclic process of observation, reflection, planning, and action. The CIG went through three cycles between March 2013 and March 2014. Twelve district health managers participated in the inquiry group. The major insights and learning that emerged from the inquiry process included inadequate supervisory practice, perceptions of healthcare workers' experiences, change in the managers' supervision paradigm, recognition of the supervisors' inadequate supervisory skills, and barriers to supportive supervision. Finally, the group developed a 10-point consensus on what they had learnt regarding supportive supervision. Ngamiland health district managers have come to appreciate the value of supportive supervision and changed their management style to be more supportive of their subordinates. They also developed a consensus on supportive supervision that could be adapted for use nationally. Supportive supervision should be prioritised at all levels of the health system, and it should be adequately resourced.

Automatic Building Detection based on Supervised Classification using High Resolution Google Earth Images

NASA Astrophysics Data System (ADS)

Ghaffarian, S.; Ghaffarian, S.

2014-08-01

This paper presents a novel approach to detect the buildings by automization of the training area collecting stage for supervised classification. The method based on the fact that a 3d building structure should cast a shadow under suitable imaging conditions. Therefore, the methodology begins with the detection and masking out the shadow areas using luminance component of the LAB color space, which indicates the lightness of the image, and a novel double thresholding technique. Further, the training areas for supervised classification are selected by automatically determining a buffer zone on each building whose shadow is detected by using the shadow shape and the sun illumination direction. Thereafter, by calculating the statistic values of each buffer zone which is collected from the building areas the Improved Parallelepiped Supervised Classification is executed to detect the buildings. Standard deviation thresholding applied to the Parallelepiped classification method to improve its accuracy. Finally, simple morphological operations conducted for releasing the noises and increasing the accuracy of the results. The experiments were performed on set of high resolution Google Earth images. The performance of the proposed approach was assessed by comparing the results of the proposed approach with the reference data by using well-known quality measurements (Precision, Recall and F1-score) to evaluate the pixel-based and object-based performances of the proposed approach. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.4 % and 853 % overall pixel-based and object-based precision performances, respectively.

Semi-supervised anomaly detection - towards model-independent searches of new physics

NASA Astrophysics Data System (ADS)

Kuusela, Mikael; Vatanen, Tommi; Malmi, Eric; Raiko, Tapani; Aaltonen, Timo; Nagai, Yoshikazu

2012-06-01

Most classification algorithms used in high energy physics fall under the category of supervised machine learning. Such methods require a training set containing both signal and background events and are prone to classification errors should this training data be systematically inaccurate for example due to the assumed MC model. To complement such model-dependent searches, we propose an algorithm based on semi-supervised anomaly detection techniques, which does not require a MC training sample for the signal data. We first model the background using a multivariate Gaussian mixture model. We then search for deviations from this model by fitting to the observations a mixture of the background model and a number of additional Gaussians. This allows us to perform pattern recognition of any anomalous excess over the background. We show by a comparison to neural network classifiers that such an approach is a lot more robust against misspecification of the signal MC than supervised classification. In cases where there is an unexpected signal, a neural network might fail to correctly identify it, while anomaly detection does not suffer from such a limitation. On the other hand, when there are no systematic errors in the training data, both methods perform comparably.

Detecting Parkinsons' symptoms in uncontrolled home environments: a multiple instance learning approach.

PubMed

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.

Application of artificial neural network to fMRI regression analysis.

PubMed

Misaki, Masaya; Miyauchi, Satoru

2006-01-15

We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

Examining clinical supervision as a mechanism for changes in practice: a research protocol.

PubMed

Dilworth, Sophie; Higgins, Isabel; Parker, Vicki; Kelly, Brian; Turner, Jane

2014-02-01

This paper describes the research protocol for a study exploring if and how clinical supervision facilitates change in practice relating to psychosocial aspects of care for Health Professionals, who have been trained to deliver a psychosocial intervention to adults with cancer. There is a recognized need to implement care that is in line with clinical practice guidelines for the psychosocial care of adults with cancer. Clinical supervision is recommended as a means to support Health Professionals in providing the recommended psychosocial care. A qualitative design embedded within an experimental, stepped wedge randomized control trial. The study will use discourse analysis to analyse audio-recorded data collected in clinical supervision sessions that are being delivered as one element of a large randomized control trial. The sessions will be attended primarily by nurses, but including physiotherapists, radiation therapists, occupational therapists. The Health Professionals are participants in a randomized control trial designed to reduce anxiety and depression of distressed adults with cancer. The sessions will be facilitated by psychiatrists experienced in psycho-oncology and the provision of clinical supervision. The proposed research is designed specifically to facilitate exploration of the mechanisms by which clinical supervision enables Health Professionals to deliver a brief, tailored psychosocial intervention in the context of their everyday practice. This is the first study to use discourse analysis embedded within an experimental randomized control trial to explore the mechanisms of change generated within clinical supervision by analysing the discourse within the clinical supervision sessions. © 2013 John Wiley & Sons Ltd.

76 FR 62890 - Self-Regulatory Organizations; Financial Industry Regulatory Authority, Inc.; Notice of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-11

... Rule Change To Adopt Rules Regarding Supervision in the Consolidated FINRA Rulebook October 4, 2011. On... to adopt rules regarding supervision in the consolidated FINRA rulebook. The proposed rule change was...

Crowd macro state detection using entropy model

NASA Astrophysics Data System (ADS)

Zhao, Ying; Yuan, Mengqi; Su, Guofeng; Chen, Tao

2015-08-01

In the crowd security research area a primary concern is to identify the macro state of crowd behaviors to prevent disasters and to supervise the crowd behaviors. The entropy is used to describe the macro state of a self-organization system in physics. The entropy change indicates the system macro state change. This paper provides a method to construct crowd behavior microstates and the corresponded probability distribution using the individuals' velocity information (magnitude and direction). Then an entropy model was built up to describe the crowd behavior macro state. Simulation experiments and video detection experiments were conducted. It was verified that in the disordered state, the crowd behavior entropy is close to the theoretical maximum entropy; while in ordered state, the entropy is much lower than half of the theoretical maximum entropy. The crowd behavior macro state sudden change leads to the entropy change. The proposed entropy model is more applicable than the order parameter model in crowd behavior detection. By recognizing the entropy mutation, it is possible to detect the crowd behavior macro state automatically by utilizing cameras. Results will provide data support on crowd emergency prevention and on emergency manual intervention.

Cases of Coastal Zone Change and Land Use/Land Cover Change: a learning module that goes beyond the "how" of doing image processing and change detection to asking the "why" about what are the "driving forces" of global change.

NASA Astrophysics Data System (ADS)

Ford, R. E.

2006-12-01

In 2006 the Loma Linda University ESSE21 Mesoamerican Project (Earth System Science Education for the 21st Century) along with partners such as the University of Redlands and California State University, Pomona, produced an online learning module that is designed to help students learn critical remote sensing skills-- specifically: ecosystem characterization, i.e. doing a supervised or unsupervised classification of satellite imagery in a tropical coastal environment. And, it would teach how to measure land use / land cover change (LULC) over time and then encourage students to use that data to assess the Human Dimensions of Global Change (HDGC). Specific objectives include: 1. Learn where to find remote sensing data and practice downloading, pre-processing, and "cleaning" the data for image analysis. 2. Use Leica-Geosystems ERDAS Imagine or IDRISI Kilimanjaro to analyze and display the data. 3. Do an unsupervised classification of a LANDSAT image of a protected area in Honduras, i.e. Cuero y Salado, Pico Bonito, or Isla del Tigre. 4. Virtually participate in a ground-validation exercise that would allow one to re-classify the image into a supervised classification using the FAO Global Land Cover Network (GLCN) classification system. 5. Learn more about each protected area's landscape, history, livelihood patterns and "sustainability" issues via virtual online tours that provide ground and space photos of different sites. This will help students in identifying potential "training sites" for doing a supervised classification. 6. Study other global, US, Canadian, and European land use/land cover classification systems and compare their advantages and disadvantages over the FAO/GLCN system. 7. Learn to appreciate the advantages and disadvantages of existing LULC classification schemes and adapt them to local-level user needs. 8. Carry out a change detection exercise that shows how land use and/or land cover has changed over time for the protected area of your choice. The presenter will demonstrate the module, assess the collaborative process which created it, and describe how it has been used so far by users in the US as well as in Honduras and elsewhere via a series joint workshops held in Mesoamerica. Suggestions for improvement will be requested. See the module and related content resources at: http://resweb.llu.edu/rford/ESSE21/LUCCModule/

Vegetation mapping and stress detection in the Santa Monica Mountains, California

NASA Technical Reports Server (NTRS)

Price, Curtis V.; Westman, Walter E.

1987-01-01

Thematic Mapper (TM) simulator data have been used to map coastal sage scrub in the mountains near Los Angeles by means of supervised classification. Changes in TM band radiances and band ratios are examined along an east-west gradient in ozone pollution loads. While the changes noted are interpretable in terms of ozone- and temperature-induced premature leaf drop, and consequent exposure of a dry, grassy understory, TM band and band ratio reflectances are influenced by a variety of independent factors which require that pollution stress interpretations be conducted in the context of the greatest possible ecological system comprehension.

Detection of new-onset choroidal neovascularization using optical coherence tomography: the AMD DOC Study.

PubMed

Do, Diana V; Gower, Emily W; Cassard, Sandra D; Boyer, David; Bressler, Neil M; Bressler, Susan B; Heier, Jeffrey S; Jefferys, Joan L; Singerman, Lawrence J; Solomon, Sharon D

2012-04-01

To determine the sensitivity of time domain optical coherence tomography (OCT) in detecting conversion to neovascular age-related macular degeneration (AMD) in eyes at high risk for choroidal neovascularization (CNV), compared with detection using fluorescein angiography (FA) as the gold standard. Prospective, multicenter, observational study. Individuals aged ≥50 years with nonneovascular AMD at high risk of progressing to CNV in the study eye and evidence of neovascular AMD in the fellow eye. At study entry and every 3 months through 2 years, participants underwent best-corrected visual acuity, supervised Amsler grid testing, preferential hyperacuity perimetry (PHP) testing, stereoscopic digital fundus photographs with FA, and OCT imaging. A central Reading Center graded all images. The sensitivity of OCT in detecting conversion to neovascular AMD by 2 years, using FA as the reference standard. Secondary outcomes included comparison of sensitivity, specificity, positive predictive value, and negative predictive value of OCT, PHP, and supervised Amsler grid relative to FA for detecting incident CNV. A total of 98 participants were enrolled; 87 (89%) of these individuals either completed the 24-month visit or exited the study after developing CNV. Fifteen (17%) study eyes had incident CNV confirmed on FA by the Reading Center. The sensitivity of each modality for detecting CNV was: OCT 0.40 (95% confidence interval [CI], 0.16-0.68), supervised Amsler grid 0.42 (95% CI, 0.15-0.72), and PHP 0.50 (95% CI, 0.23-0.77). Treatment for incident CNV was recommended by the study investigator in 13 study eyes. Sensitivity of the testing modalities for detection of CNV in these 13 eyes was 0.69 (95% CI, 0.39-0.91) for OCT, 0.50 (95% CI, 0.19-0.81) for supervised Amsler grid, and 0.70 (95% CI, 0.35-0.93) for PHP. Specificity of the OCT was higher than that of the Amsler grid and PHP. Time-domain OCT, supervised Amsler grid, and PHP have low to moderate sensitivity for detection of new-onset CNV compared with FA. Optical coherence tomography has greater specificity than Amsler grid or PHP. Among fellow eyes of individuals with unilateral CNV, FA remains the best method to detect new-onset CNV. Copyright © 2012 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

A Longitudinal Study of Adenoma Detection Rate in Gastroenterology Fellowship Training.

PubMed

Gianotti, Robert J; Oza, Sveta Shah; Tapper, Elliot B; Kothari, Darshan; Sheth, Sunil G

2016-10-01

Current guidelines suggest that a gastroenterology fellow in training needs to perform 140 colonoscopies to achieve competency. Data are limited regarding adenoma detection rate (ADR) in fellowship. To assess how fellow ADR correlates with number of colonoscopies performed. We performed a retrospective study examining consecutive colonoscopies performed by gastroenterology fellows. Fellow ADR before and after the 140 procedure benchmark was compared to colonoscopies performed by attending only with whom these fellows trained. A threshold for ideal procedure count was performed using ROC analysis. We analyzed 2021 average-risk colonoscopies performed by 10 gastroenterology fellows under the supervision of an attending physician. When fellows had performed <140 colonoscopies, the ADR was 27 % compared with an ADR of 36 % when fellows had performed >140 colonoscopies under attending supervision (p = 0.02). The ADR of fellows who had performed >140 colonoscopies under attending supervision was greater than that of attending-only colonoscopies (36 vs. 25 %, p < 0.0001). A threshold of >325 (male patients) and 539 (female patients) colonoscopies was determined to be ideal for achieving adequate ADR based on ROC analysis. Our data suggest that ADR increases after fellows perform >140 colonoscopies under attending supervision, and thereafter surpasses the ADR of attending-only colonoscopies. Some of the differences may be driven by detection of small adenomas. The findings of this study suggest that a higher threshold for number of colonoscopies performed under attending supervision may be needed to achieve adequate ADR during fellowship prior to independent practice.

How to create more supportive supervision for primary healthcare: lessons from Ngamiland district of Botswana: co-operative inquiry group

PubMed Central

Nkomazana, Oathokwa; Mash, Robert; Wojczewski, Silvia; Kutalek, Ruth; Phaladze, Nthabiseng

2016-01-01

Background Supportive supervision is a way to foster performance, productivity, motivation, and retention of health workforce. Nevertheless there is a dearth of evidence of the impact and acceptability of supportive supervision in low- and middle-income countries. This article describes a participatory process of transforming the supervisory practice of district health managers to create a supportive environment for primary healthcare workers. Objective The objective of the study was to explore how district health managers can change their practice to create a more supportive environment for primary healthcare providers. Design A facilitated co-operative inquiry group (CIG) was formed with Ngamiland health district managers. CIG belongs to the participatory action research paradigm and is characterised by a cyclic process of observation, reflection, planning, and action. The CIG went through three cycles between March 2013 and March 2014. Results Twelve district health managers participated in the inquiry group. The major insights and learning that emerged from the inquiry process included inadequate supervisory practice, perceptions of healthcare workers’ experiences, change in the managers’ supervision paradigm, recognition of the supervisors’ inadequate supervisory skills, and barriers to supportive supervision. Finally, the group developed a 10-point consensus on what they had learnt regarding supportive supervision. Conclusion Ngamiland health district managers have come to appreciate the value of supportive supervision and changed their management style to be more supportive of their subordinates. They also developed a consensus on supportive supervision that could be adapted for use nationally. Supportive supervision should be prioritised at all levels of the health system, and it should be adequately resourced. PMID:27345024

Remote Sensing Monitoring of Changes in Soil Salinity: A Case Study in Inner Mongolia, China.

PubMed

Wu, Jingwei; Vincent, Bernard; Yang, Jinzhong; Bouarfa, Sami; Vidal, Alain

2008-11-07

This study used archived remote sensing images to depict the history of changes in soil salinity in the Hetao Irrigation District in Inner Mongolia, China, with the purpose of linking these changes with land and water management practices and to draw lessons for salinity control. Most data came from LANDSAT satellite images taken in 1973, 1977, 1988, 1991, 1996, 2001, and 2006. In these years salt-affected areas were detected using a normal supervised classification method. Corresponding cropped areas were detected from NVDI (Normalized Difference Vegetation Index) values using an unsupervised method. Field samples and agricultural statistics were used to estimate the accuracy of the classification. Historical data concerning irrigation/drainage and the groundwater table were used to analyze the relation between changes in soil salinity and land and water management practices. Results showed that: (1) the overall accuracy of remote sensing in detecting soil salinity was 90.2%, and in detecting cropped area, 98%; (2) the installation/innovation of the drainage system did help to control salinity; and (3) a low ratio of cropped land helped control salinity in the Hetao Irrigation District. These findings suggest that remote sensing is a useful tool to detect soil salinity and has potential in evaluating and improving land and water management practices.

How Does Supervision Support Inclusive Teacherhood?

ERIC Educational Resources Information Center

Alila, Sanna; Määttä, Kaarina; Uusiautti, Satu

2016-01-01

Supervision is a multidimensional concept and phenomenon. In this study, the advantages of supervision and its development in inclusive teacherhood was studied. Inclusive teacherhood means a teacher's professional development and the school culture's change toward participatory school for all students. The study analyzed the views of supervisors…

Optimal reinforcement of training datasets in semi-supervised landmark-based segmentation

NASA Astrophysics Data System (ADS)

Ibragimov, Bulat; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

2015-03-01

During the last couple of decades, the development of computerized image segmentation shifted from unsupervised to supervised methods, which made segmentation results more accurate and robust. However, the main disadvantage of supervised segmentation is a need for manual image annotation that is time-consuming and subjected to human error. To reduce the need for manual annotation, we propose a novel learning approach for training dataset reinforcement in the area of landmark-based segmentation, where newly detected landmarks are optimally combined with reference landmarks from the training dataset and therefore enriches the training process. The approach is formulated as a nonlinear optimization problem, where the solution is a vector of weighting factors that measures how reliable are the detected landmarks. The detected landmarks that are found to be more reliable are included into the training procedure with higher weighting factors, whereas the detected landmarks that are found to be less reliable are included with lower weighting factors. The approach is integrated into the landmark-based game-theoretic segmentation framework and validated against the problem of lung field segmentation from chest radiographs.

Supervised detection of exoplanets in high-contrast imaging sequences

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

PubMed

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.

Distributed multi-level supervision to effectively monitor the operations of a fleet of autonomous vehicles in agricultural tasks.

PubMed

Conesa-Muñoz, Jesús; Gonzalez-de-Soto, Mariano; Gonzalez-de-Santos, Pablo; Ribeiro, Angela

2015-03-05

This paper describes a supervisor system for monitoring the operation of automated agricultural vehicles. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a failure or potentially dangerous situation is detected. In some situations, it is even able to execute a neutralising protocol to remedy the failure. The system is based on a distributed and multi-level architecture that divides the supervision into different subsystems, allowing for better management of the detection and repair of failures. The proposed supervision system was developed to perform well in several scenarios, such as spraying canopy treatments against insects and diseases and selective weed treatments, by either spraying herbicide or burning pests with a mechanical-thermal actuator. Results are presented for selective weed treatment by the spraying of herbicide. The system successfully supervised the task; it detected failures such as service disruptions, incorrect working speeds, incorrect implement states, and potential collisions. Moreover, the system was able to prevent collisions between vehicles by taking action to avoid intersecting trajectories. The results show that the proposed system is a highly useful tool for managing fleets of autonomous vehicles. In particular, it can be used to manage agricultural vehicles during treatment operations.

Distributed Multi-Level Supervision to Effectively Monitor the Operations of a Fleet of Autonomous Vehicles in Agricultural Tasks

PubMed Central

Conesa-Muñoz, Jesús; Gonzalez-de-Soto, Mariano; Gonzalez-de-Santos, Pablo; Ribeiro, Angela

2015-01-01

This paper describes a supervisor system for monitoring the operation of automated agricultural vehicles. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a failure or potentially dangerous situation is detected. In some situations, it is even able to execute a neutralising protocol to remedy the failure. The system is based on a distributed and multi-level architecture that divides the supervision into different subsystems, allowing for better management of the detection and repair of failures. The proposed supervision system was developed to perform well in several scenarios, such as spraying canopy treatments against insects and diseases and selective weed treatments, by either spraying herbicide or burning pests with a mechanical-thermal actuator. Results are presented for selective weed treatment by the spraying of herbicide. The system successfully supervised the task; it detected failures such as service disruptions, incorrect working speeds, incorrect implement states, and potential collisions. Moreover, the system was able to prevent collisions between vehicles by taking action to avoid intersecting trajectories. The results show that the proposed system is a highly useful tool for managing fleets of autonomous vehicles. In particular, it can be used to manage agricultural vehicles during treatment operations. PMID:25751079

Redesigning Supervision: Alternative Models for Student Teaching and Field Experiences

ERIC Educational Resources Information Center

Rodgers, Adrian; Jenkins, Deborah Bainer

2010-01-01

In "Redesigning Supervision", active professionals in teacher education and professional development share research-based, alternative models for restructuring the way pre-service teachers are supervised. The authors examine the methods currently used and discuss how teacher educators have striven to change or renew these procedures. They then…

Training Substance Abuse Clinicians in Motivational Interviewing Using Live Supervision via Teleconferencing

ERIC Educational Resources Information Center

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

Objective: Training through traditional workshops is relatively ineffective for changing counseling practices. Teleconferencing supervision (TCS) was developed to provide remote, live supervision for training motivational interviewing (MI). Method: Ninety-seven drug treatment counselors completed a 2-day MI workshop and were randomized to live…

Examining change detection approaches for tropical mangrove monitoring

USGS Publications Warehouse

Myint, Soe W.; Franklin, Janet; Buenemann, Michaela; Kim, Won; Giri, Chandra

2014-01-01

This study evaluated the effectiveness of different band combinations and classifiers (unsupervised, supervised, object-oriented nearest neighbor, and object-oriented decision rule) for quantifying mangrove forest change using multitemporal Landsat data. A discriminant analysis using spectra of different vegetation types determined that bands 2 (0.52 to 0.6 μm), 5 (1.55 to 1.75 μm), and 7 (2.08 to 2.35 μm) were the most effective bands for differentiating mangrove forests from surrounding land cover types. A ranking of thirty-six change maps, produced by comparing the classification accuracy of twelve change detection approaches, was used. The object-based Nearest Neighbor classifier produced the highest mean overall accuracy (84 percent) regardless of band combinations. The automated decision rule-based approach (mean overall accuracy of 88 percent) as well as a composite of bands 2, 5, and 7 used with the unsupervised classifier and the same composite or all band difference with the object-oriented Nearest Neighbor classifier were the most effective approaches.

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... provided a smoke detecting or other suitable type fire detecting system. (c) Enclosed spaces which are “specially suitable for vehicles” shall be fitted with an approved fire or smoke detecting system. [CGFR 66...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... provided a smoke detecting or other suitable type fire detecting system. (c) Enclosed spaces which are “specially suitable for vehicles” shall be fitted with an approved fire or smoke detecting system. [CGFR 66...

Paediatric trainee supervision: management changes and perceived education value.

PubMed

van den Boom, Mirjam; Pinnock, Ralph; Weller, Jennifer; Reed, Peter; Shulruf, Boaz

2012-07-01

Supervision in postgraduate training is an under-researched area. We measured the amount, type and effect of supervision on patient care and perceived education value in a general paediatric service. We designed a structured observation form and questionnaire to document the type, duration and effect of supervision on patient management and perceived education value. Most supervision occurred without the paediatrician confirming the trainee's findings. Direct observation of the trainee was rare. Management was changed in 30% of patients seen on the inpatient ward round and in 42% of the patients discussed during the chart reviews but not seen by the paediatrician. Management was changed in 48% of the cases when the paediatrician saw the patient with the trainee in outpatients but in only 21% of patients when the patient was but not seen. Changes made to patient management, understanding and perceived education value, differed between inpatient and out patient settings. There was more impact when the paediatrician saw the patient with the trainee in outpatients; while for inpatients, the opposite was true. Trainees rated the value of the supervision more highly than their supervisors did. Trainees' comments on what they learnt from their supervisor related almost exclusively to clinical knowledge rather than professional behaviours. We observed little evidence of supervisors directly observing trainees and trainees learning professional behaviours. A review of supervisory practices to promote more effective learning is needed. Communicating to paediatricians the value their trainees place on their input could have a positive effect on their engagement in supervision. © 2012 The Authors. Journal of Paediatrics and Child Health © 2012 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Effects of an off-season conditioning program on the physical characteristics of adolescent rugby union players.

PubMed

Smart, Daniel J; Gill, Nicholas D

2013-03-01

The aims of the study were to determine if a supervised off-season conditioning program enhanced gains in physical characteristics compared with the same program performed in an unsupervised manner and to establish the persistence of the physical changes after a 6-month unsupervised competition period. Forty-four provincial representative adolescent rugby union players (age, mean ± SD, 15.3 ± 1.3 years) participated in a 15-week off-season conditioning program either under supervision from an experienced strength and conditioning coach or unsupervised. Measures of body composition, strength, vertical jump, speed, and anaerobic and aerobic running performance were taken, before, immediately after, and 6 months after the conditioning. Post conditioning program the supervised group had greater improvements in all strength measures than the unsupervised group, with small, moderate and large differences between the groups\\x{2019} changes for chin-ups (9.1%; ± 11.6%), bench-press (16.9%; ± 11.7%) and box-squat (50.4%; ± 20.9%) estimated 1RM respectively. Both groups showed trivial increases in mass; however increases in fat free mass were small and trivial for supervised and unsupervised players respectively. Strength declined in the supervised group while the unsupervised group had small increases during the competition phase, resulting in only a small difference between the long-term changes in box-squat 1RM (15.9%; ± 13.2%). The supervised group had further small increases in fat free mass resulting in a small difference (2.4%; ± 2.7%) in the long-term changes. The postconditioning differences between the 2 groups may have been a result of increased adherence and the attainment of higher training loads during supervised training. The lack of differences in strength after the competition period indicates that supervision should be maintained to reduce substantial decrements in performance.

Supervised walking groups to increase physical activity in type 2 diabetic patients.

PubMed

Negri, Carlo; Bacchi, Elisabetta; Morgante, Susanna; Soave, Diego; Marques, Alessandra; Menghini, Elisabetta; Muggeo, Michele; Bonora, Enzo; Moghetti, Paolo

2010-11-01

To evaluate the impact of an exercise program organized into supervised walking groups in subjects with type 2 diabetes. Fifty-nine diabetic subjects were randomized to a control group receiving standard lifestyle recommendations or an intervention group assigned to three supervised walking sessions per week and counseling. Changes in metabolic features, weight, 6-min walk test, prescription of antidiabetic medications, and overall physical activity were assessed. Functional capacity and overall physical activity were higher in the intervention group, whereas metabolic changes were not different between groups after 4 months. However, in subjects who attended at least 50% of scheduled walking sessions, changes in A1C and fasting glucose were greater than in control subjects. Discontinuation or reduction of antidiabetic drugs occurred in 33% of these patients versus 5% of control subjects (P<0.05). Supervised walking may be beneficial in diabetic subjects, but metabolic improvement requires adequate compliance.

Sensor supervision and multiagent commanding by means of projective virtual reality

NASA Astrophysics Data System (ADS)

Rossmann, Juergen

1998-10-01

When autonomous systems with multiple agents are considered, conventional control- and supervision technologies are often inadequate because the amount of information available is often presented in a way that the user is effectively overwhelmed by the displayed data. New virtual reality (VR) techniques can help to cope with this problem, because VR offers the chance to convey information in an intuitive manner and can combine supervision capabilities and new, intuitive approaches to the control of autonomous systems. In the approach taken, control and supervision issues were equally stressed and finally led to the new ideas and the general framework for Projective Virtual Reality. The key idea of this new approach for an intuitively operable man machine interface for decentrally controlled multi-agent systems is to let the user act in the virtual world, detect the changes and have an action planning component automatically generate task descriptions for the agents involved to project actions that have been carried out by users in the virtual world into the physical world, e.g. with the help of robots. Thus the Projective Virtual Reality approach is to split the job between the task deduction in the VR and the task `projection' onto the physical automation components by the automatic action planning component. Besides describing the realized projective virtual reality system, the paper will also describe in detail the metaphors and visualization aids used to present different types of (e.g. sensor-) information in an intuitively comprehensible manner.

Application of supervised and unsupervised tools to direct effects-based monitoring efforts in the Great Lakes areas of concern: Maumee River, Ohio

EPA Science Inventory

Effects-based approaches that employ molecular and tissue level tools to detect and characterize biological responses to contaminants can be a useful complement to chemical monitoring approaches. When the source/type of contamination is known, a predetermined, or supervised, set...

Teachers' Views on Course Supervision Competencies of Secondary School Managers

ERIC Educational Resources Information Center

Bayram, Arslan

2016-01-01

The definition of supervision in the dictionary is "to look after", "to direct," "to watch over," and "to check." It is usually seen as a tool to manage the teacher. Understanding of supervision in education has shown a change and progress in line with approaches and theories regarding management. The…

Doctoral Student Supervision in a Managerial Climate

ERIC Educational Resources Information Center

Cribb, Alan; Gewirtz, Sharon

2006-01-01

This paper is organized around a single interview with an academic colleague who was asked to reflect on his changing experience of Ph.D. supervision. Material from the interview is used to raise some questions about the nature of responsible supervision in the humanities and social sciences, and the ways in which the possibilities for responsible…

Exploring Organizational Barriers to Strengthening Clinical Supervision of Psychiatric Nursing Staff: A Longitudinal Controlled Intervention Study.

PubMed

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.

Improving the professionalism of post-certification teacher through academic supervision in vocational schools

NASA Astrophysics Data System (ADS)

Satyawati, Sophia Tri; Widyanto, I. Putu; Suemy

2017-03-01

This paper examines the principal's efforts in improving the professionalism of post-certification teachers through academic supervision in vocational school. The certification of educators is expected to improve the professionalism of teachers, there are significant changes between the before and after receiving the certificate of educators. One of the efforts made by the principal on increasing the professionalism of teachers is to carry out academic supervision completely and continuously. This paper examines about how principals at vocational schools carry out the programmed academic supervision, and continuing through mentoring, evaluation and coaching. Academic supervision is performed by individual supervision techniques which includes: classroom or practical visit, classroom or practical observation, individual meetings, inter-class or practical places visit, and self-assessment.

Theory-Based Predictors of Follow-Up Exercise Behavior After A Supervised Exercise Intervention in Older Breast Cancer Survivors

PubMed Central

Loprinzi, Paul D.; Cardinal, Bradley J.; Si, Qi; Bennett, Jill A.; Winters-Stone, Kerri

2014-01-01

Purpose Supervised exercise interventions can elicit numerous positive health outcomes in older breast cancer survivors. However, to maintain these benefits, regular exercise needs to be maintained long after the supervised program. This may be difficult, as in this transitional period (i.e., time period immediately following a supervised exercise program), breast cancer survivors are in the absence of on-site direct supervision from a trained exercise specialist. The purpose of the present study was to identify key determinants of regular exercise participation during a 6-month follow-up period after a 12-month supervised exercise program among women aged 65+ years who had completed adjuvant treatment for breast cancer. Methods At the conclusion of a supervised exercise program, and 6-months later, 69 breast cancer survivors completed surveys examining their exercise behavior and key constructs from the Transtheoretical Model. Results After adjusting for weight status and physical activity at the transition point, breast cancer survivors with higher self-efficacy at the point of transition were more likely to be active 6-months after leaving the supervised exercise program (OR [95% CI]: 1.10 [1.01–1.18]). Similarly, breast cancer survivors with higher behavioral processes of change use at the point of transition were more likely to be active (OR [95% CI]: 1.13 [1.02–1.26]). Conclusion These findings suggest that self-efficacy and the behavioral processes of change, in particular, play an important role in exercise participation during the transition from a supervised to a home-based program among older breast cancer survivors. PMID:22252545

Changing over a Project Changing over: A Project-Research Supervision as a Conversation

ERIC Educational Resources Information Center

Clarke, Helen; Ryan, Charly

2006-01-01

Extracts from the written conversation between research student and supervisor show the nature of educative research supervision. The authors argue that researcher-supervisor relationships are methodological in nature as they shape and influence the people, the project and the field. Such relationships, which construct meanings, are complex. A…

Improved Anomaly Detection using Integrated Supervised and Unsupervised Processing

NASA Astrophysics Data System (ADS)

Hunt, B.; Sheppard, D. G.; Wetterer, C. J.

There are two broad technologies of signal processing applicable to space object feature identification using nonresolved imagery: supervised processing analyzes a large set of data for common characteristics that can be then used to identify, transform, and extract information from new data taken of the same given class (e.g. support vector machine); unsupervised processing utilizes detailed physics-based models that generate comparison data that can then be used to estimate parameters presumed to be governed by the same models (e.g. estimation filters). Both processes have been used in non-resolved space object identification and yield similar results yet arrived at using vastly different processes. The goal of integrating the results of the two is to seek to achieve an even greater performance by building on the process diversity. Specifically, both supervised processing and unsupervised processing will jointly operate on the analysis of brightness (radiometric flux intensity) measurements reflected by space objects and observed by a ground station to determine whether a particular day conforms to a nominal operating mode (as determined from a training set) or exhibits anomalous behavior where a particular parameter (e.g. attitude, solar panel articulation angle) has changed in some way. It is demonstrated in a variety of different scenarios that the integrated process achieves a greater performance than each of the separate processes alone.

Attending Physician Remote Access of the Electronic Health Record and Implications for Resident Supervision: A Mixed Methods Study.

PubMed

Martin, Shannon K; Tulla, Kiara; Meltzer, David O; Arora, Vineet M; Farnan, Jeanne M

2017-12-01

Advances in information technology have increased remote access to the electronic health record (EHR). Concurrently, standards defining appropriate resident supervision have evolved. How often and under what circumstances inpatient attending physicians remotely access the EHR for resident supervision is unknown. We described a model of attending remote EHR use for resident supervision, and quantified the frequency and magnitude of use. Using a mixed methods approach, general medicine inpatient attendings were surveyed and interviewed about their remote EHR use. Frequency of use and supervisory actions were quantitatively examined via survey. Transcripts from semistructured interviews were analyzed using grounded theory to identify codes and themes. A total of 83% (59 of 71) of attendings participated. Fifty-seven (97%) reported using the EHR remotely, with 54 (92%) reporting they discovered new clinical information not relayed by residents via remote EHR use. A majority (93%, 55 of 59) reported that this resulted in management changes, and 54% (32 of 59) reported making immediate changes by contacting cross-covering teams. Six major factors around remote EHR use emerged: resident, clinical, educational, personal, technical, and administrative. Attendings described resident and clinical factors as facilitating "backstage" supervision via remote EHR use. In our study to assess attending remote EHR use for resident supervision, attendings reported frequent remote use with resulting supervisory actions, describing a previously uncharacterized form of "backstage" oversight supervision. Future work should explore best practices in remote EHR use to provide effective supervision and ultimately improve patient safety.

Supervised Walking Groups to Increase Physical Activity in Type 2 Diabetic Patients

PubMed Central

Negri, Carlo; Bacchi, Elisabetta; Morgante, Susanna; Soave, Diego; Marques, Alessandra; Menghini, Elisabetta; Muggeo, Michele; Bonora, Enzo; Moghetti, Paolo

2010-01-01

OBJECTIVE To evaluate the impact of an exercise program organized into supervised walking groups in subjects with type 2 diabetes. RESEARCH DESIGN AND METHODS Fifty-nine diabetic subjects were randomized to a control group receiving standard lifestyle recommendations or an intervention group assigned to three supervised walking sessions per week and counseling. Changes in metabolic features, weight, 6-min walk test, prescription of antidiabetic medications, and overall physical activity were assessed. RESULTS Functional capacity and overall physical activity were higher in the intervention group, whereas metabolic changes were not different between groups after 4 months. However, in subjects who attended at least 50% of scheduled walking sessions, changes in A1C and fasting glucose were greater than in control subjects. Discontinuation or reduction of antidiabetic drugs occurred in 33% of these patients versus 5% of control subjects (P < 0.05). CONCLUSIONS Supervised walking may be beneficial in diabetic subjects, but metabolic improvement requires adequate compliance. PMID:20980426

Dual Low-Rank Pursuit: Learning Salient Features for Saliency Detection.

PubMed

Lang, Congyan; Feng, Jiashi; Feng, Songhe; Wang, Jingdong; Yan, Shuicheng

2016-06-01

Saliency detection is an important procedure for machines to understand visual world as humans do. In this paper, we consider a specific saliency detection problem of predicting human eye fixations when they freely view natural images, and propose a novel dual low-rank pursuit (DLRP) method. DLRP learns saliency-aware feature transformations by utilizing available supervision information and constructs discriminative bases for effectively detecting human fixation points under the popular low-rank and sparsity-pursuit framework. Benefiting from the embedded high-level information in the supervised learning process, DLRP is able to predict fixations accurately without performing the expensive object segmentation as in the previous works. Comprehensive experiments clearly show the superiority of the proposed DLRP method over the established state-of-the-art methods. We also empirically demonstrate that DLRP provides stronger generalization performance across different data sets and inherits the advantages of both the bottom-up- and top-down-based saliency detection methods.

LANDSAT data for coastal zone management. [New Jersey

NASA Technical Reports Server (NTRS)

Mckenzie, S.

1981-01-01

The lack of adequate, current data on land and water surface conditions in New Jersey led to the search for better data collections and analysis techniques. Four-channel MSS data of Cape May County and access to the OSER computer interpretation system were provided by NASA. The spectral resolution of the data was tested and a surface cover map was produced by going through the steps of supervised classification. Topics covered include classification; change detection and improvement of spectral and spatial resolution; merging LANDSAT and map data; and potential applications for New Jersey.

Video mining using combinations of unsupervised and supervised learning techniques

NASA Astrophysics Data System (ADS)

Divakaran, Ajay; Miyahara, Koji; Peker, Kadir A.; Radhakrishnan, Regunathan; Xiong, Ziyou

2003-12-01

We discuss the meaning and significance of the video mining problem, and present our work on some aspects of video mining. A simple definition of video mining is unsupervised discovery of patterns in audio-visual content. Such purely unsupervised discovery is readily applicable to video surveillance as well as to consumer video browsing applications. We interpret video mining as content-adaptive or "blind" content processing, in which the first stage is content characterization and the second stage is event discovery based on the characterization obtained in stage 1. We discuss the target applications and find that using a purely unsupervised approach are too computationally complex to be implemented on our product platform. We then describe various combinations of unsupervised and supervised learning techniques that help discover patterns that are useful to the end-user of the application. We target consumer video browsing applications such as commercial message detection, sports highlights extraction etc. We employ both audio and video features. We find that supervised audio classification combined with unsupervised unusual event discovery enables accurate supervised detection of desired events. Our techniques are computationally simple and robust to common variations in production styles etc.

Lidar Cloud Detection with Fully Convolutional Networks

NASA Astrophysics Data System (ADS)

Cromwell, E.; Flynn, D.

2017-12-01

The vertical distribution of clouds from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of clouds can be expressed as a binary cloud mask and is a primary input for climate modeling efforts and cloud formation studies. Current cloud detection algorithms producing these masks do not accurately identify the cloud boundaries and tend to oversample or over-represent the cloud. This translates as uncertainty for assessing the radiative impact of clouds and tracking changes in cloud climatologies. The Atmospheric Radiation Measurement (ARM) program has over 20 years of micro-pulse lidar (MPL) and High Spectral Resolution Lidar (HSRL) instrument data and companion automated cloud mask product at the mid-latitude Southern Great Plains (SGP) and the polar North Slope of Alaska (NSA) atmospheric observatory. Using this data, we train a fully convolutional network (FCN) with semi-supervised learning to segment lidar imagery into geometric time-height cloud locations for the SGP site and MPL instrument. We then use transfer learning to train a FCN for (1) the MPL instrument at the NSA site and (2) for the HSRL. In our semi-supervised approach, we pre-train the classification layers of the FCN with weakly labeled lidar data. Then, we facilitate end-to-end unsupervised pre-training and transition to fully supervised learning with ground truth labeled data. Our goal is to improve the cloud mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current cloud mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a cloud mask accuracy of 90% and a precision of 80%.

Supervised Learning for Detection of Duplicates in Genomic Sequence Databases.

PubMed

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

2016-01-01

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

Monitoring urban growth and detection of land use with GIS and remote sensing: a case study of the Kyrenia region

NASA Astrophysics Data System (ADS)

Kara, Can; Akçit, Nuhcan

2016-08-01

Land-cover change is considered one of the central components in current strategies for managing natural resources and monitoring environmental changes. It is important to manage land resources in a sustainable manner which targets at compacting and consolidating urban development. From 2005 to 2015,urban growth in Kyrenia has been quite dramatic, showing a wide and scattered pattern, lacking proper plan. As a result of this unplanned/unorganized expansion, agricultural areas, vegetation and water bodies have been lost in the region. Therefore, it has become a necessity to analyze the results of this urban growth and compare the losses between land-cover changes. With this goal in mind, a case study of Kyrenia region has been carried out using a supervised image classification method and Landsat TM images acquired in 2005 and 2015 to map and extract land-cover changes. This paper tries to assess urban-growth changes detected in the region by using Remote Sensing and GIS. The study monitors the changes between different land cover types. Also, it shows the urban occupation of primary soil loss and the losses in forest areas, open areas, etc.

An efficient semi-supervised community detection framework in social networks.

PubMed

Li, Zhen; Gong, Yong; Pan, Zhisong; Hu, Guyu

2017-01-01

Community detection is an important tasks across a number of research fields including social science, biology, and physics. In the real world, topology information alone is often inadequate to accurately find out community structure due to its sparsity and noise. The potential useful prior information such as pairwise constraints which contain must-link and cannot-link constraints can be obtained from domain knowledge in many applications. Thus, combining network topology with prior information to improve the community detection accuracy is promising. Previous methods mainly utilize the must-link constraints while cannot make full use of cannot-link constraints. In this paper, we propose a semi-supervised community detection framework which can effectively incorporate two types of pairwise constraints into the detection process. Particularly, must-link and cannot-link constraints are represented as positive and negative links, and we encode them by adding different graph regularization terms to penalize closeness of the nodes. Experiments on multiple real-world datasets show that the proposed framework significantly improves the accuracy of community detection.

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

PubMed

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

2018-04-01

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

Effects of Supervised vs. Unsupervised Training Programs on Balance and Muscle Strength in Older Adults: A Systematic Review and Meta-Analysis.

PubMed

Lacroix, André; Hortobágyi, Tibor; Beurskens, Rainer; Granacher, Urs

2017-11-01

Balance and resistance training can improve healthy older adults' balance and muscle strength. Delivering such exercise programs at home without supervision may facilitate participation for older adults because they do not have to leave their homes. To date, no systematic literature analysis has been conducted to determine if supervision affects the effectiveness of these programs to improve healthy older adults' balance and muscle strength/power. The objective of this systematic review and meta-analysis was to quantify the effectiveness of supervised vs. unsupervised balance and/or resistance training programs on measures of balance and muscle strength/power in healthy older adults. In addition, the impact of supervision on training-induced adaptive processes was evaluated in the form of dose-response relationships by analyzing randomized controlled trials that compared supervised with unsupervised trials. A computerized systematic literature search was performed in the electronic databases PubMed, Web of Science, and SportDiscus to detect articles examining the role of supervision in balance and/or resistance training in older adults. The initially identified 6041 articles were systematically screened. Studies were included if they examined balance and/or resistance training in adults aged ≥65 years with no relevant diseases and registered at least one behavioral balance (e.g., time during single leg stance) and/or muscle strength/power outcome (e.g., time for 5-Times-Chair-Rise-Test). Finally, 11 studies were eligible for inclusion in this meta-analysis. Weighted mean standardized mean differences between subjects (SMD bs ) of supervised vs. unsupervised balance/resistance training studies were calculated. The included studies were coded for the following variables: number of participants, sex, age, number and type of interventions, type of balance/strength tests, and change (%) from pre- to post-intervention values. Additionally, we coded training according to the following modalities: period, frequency, volume, modalities of supervision (i.e., number of supervised/unsupervised sessions within the supervised or unsupervised training groups, respectively). Heterogeneity was computed using I 2 and χ 2 statistics. The methodological quality of the included studies was evaluated using the Physiotherapy Evidence Database scale. Our analyses revealed that in older adults, supervised balance/resistance training was superior compared with unsupervised balance/resistance training in improving measures of static steady-state balance (mean SMD bs  = 0.28, p = 0.39), dynamic steady-state balance (mean SMD bs  = 0.35, p = 0.02), proactive balance (mean SMD bs  = 0.24, p = 0.05), balance test batteries (mean SMD bs  = 0.53, p = 0.02), and measures of muscle strength/power (mean SMD bs  = 0.51, p = 0.04). Regarding the examined dose-response relationships, our analyses showed that a number of 10-29 additional supervised sessions in the supervised training groups compared with the unsupervised training groups resulted in the largest effects for static steady-state balance (mean SMD bs  = 0.35), dynamic steady-state balance (mean SMD bs  = 0.37), and muscle strength/power (mean SMD bs  = 1.12). Further, ≥30 additional supervised sessions in the supervised training groups were needed to produce the largest effects on proactive balance (mean SMD bs  = 0.30) and balance test batteries (mean SMD bs  = 0.77). Effects in favor of supervised programs were larger for studies that did not include any supervised sessions in their unsupervised programs (mean SMD bs : 0.28-1.24) compared with studies that implemented a few supervised sessions in their unsupervised programs (e.g., three supervised sessions throughout the entire intervention program; SMD bs : -0.06 to 0.41). The present findings have to be interpreted with caution because of the low number of eligible studies and the moderate methodological quality of the included studies, which is indicated by a median Physiotherapy Evidence Database scale score of 5. Furthermore, we indirectly compared dose-response relationships across studies and not from single controlled studies. Our analyses suggest that supervised balance and/or resistance training improved measures of balance and muscle strength/power to a greater extent than unsupervised programs in older adults. Owing to the small number of available studies, we were unable to establish a clear dose-response relationship with regard to the impact of supervision. However, the positive effects of supervised training are particularly prominent when compared with completely unsupervised training programs. It is therefore recommended to include supervised sessions (i.e., two out of three sessions/week) in balance/resistance training programs to effectively improve balance and muscle strength/power in older adults.

Automated Health Alerts Using In-Home Sensor Data for Embedded Health Assessment

PubMed Central

Guevara, Rainer Dane; Rantz, Marilyn

2015-01-01

We present an example of unobtrusive, continuous monitoring in the home for the purpose of assessing early health changes. Sensors embedded in the environment capture behavior and activity patterns. Changes in patterns are detected as potential signs of changing health. We first present results of a preliminary study investigating 22 features extracted from in-home sensor data. A 1-D alert algorithm was then implemented to generate health alerts to clinicians in a senior housing facility. Clinicians analyze each alert and provide a rating on the clinical relevance. These ratings are then used as ground truth for training and testing classifiers. Here, we present the methodology for four classification approaches that fuse multisensor data. Results are shown using embedded sensor data and health alert ratings collected on 21 seniors over nine months. The best results show similar performance for two techniques, where one approach uses only domain knowledge and the second uses supervised learning for training. Finally, we propose a health change detection model based on these results and clinical expertise. The system of in-home sensors and algorithms for automated health alerts provides a method for detecting health problems very early so that early treatment is possible. This method of passive in-home sensing alleviates compliance issues. PMID:27170900

District nurses' experience of supervising nursing students in primary health care: A pre- and post-implementation questionnaire study.

PubMed

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.

A Re-Examination of Hebbian-Covariance Rules and Spike Timing-Dependent Plasticity in Cat Visual Cortex in vivo

PubMed Central

Frégnac, Yves; Pananceau, Marc; René, Alice; Huguet, Nazyed; Marre, Olivier; Levy, Manuel; Shulz, Daniel E.

2010-01-01

Spike timing-dependent plasticity (STDP) is considered as an ubiquitous rule for associative plasticity in cortical networks in vitro. However, limited supporting evidence for its functional role has been provided in vivo. In particular, there are very few studies demonstrating the co-occurrence of synaptic efficiency changes and alteration of sensory responses in adult cortex during Hebbian or STDP protocols. We addressed this issue by reviewing and comparing the functional effects of two types of cellular conditioning in cat visual cortex. The first one, referred to as the “covariance” protocol, obeys a generalized Hebbian framework, by imposing, for different stimuli, supervised positive and negative changes in covariance between postsynaptic and presynaptic activity rates. The second protocol, based on intracellular recordings, replicated in vivo variants of the theta-burst paradigm (TBS), proven successful in inducing long-term potentiation in vitro. Since it was shown to impose a precise correlation delay between the electrically activated thalamic input and the TBS-induced postsynaptic spike, this protocol can be seen as a probe of causal (“pre-before-post”) STDP. By choosing a thalamic region where the visual field representation was in retinotopic overlap with the intracellularly recorded cortical receptive field as the afferent site for supervised electrical stimulation, this protocol allowed to look for possible correlates between STDP and functional reorganization of the conditioned cortical receptive field. The rate-based “covariance protocol” induced significant and large amplitude changes in receptive field properties, in both kitten and adult V1 cortex. The TBS STDP-like protocol produced in the adult significant changes in the synaptic gain of the electrically activated thalamic pathway, but the statistical significance of the functional correlates was detectable mostly at the population level. Comparison of our observations with the literature leads us to re-examine the experimental status of spike timing-dependent potentiation in adult cortex. We propose the existence of a correlation-based threshold in vivo, limiting the expression of STDP-induced changes outside the critical period, and which accounts for the stability of synaptic weights during sensory cortical processing in the absence of attention or reward-gated supervision. PMID:21423533

A deep learning and novelty detection framework for rapid phenotyping in high-content screening

PubMed Central

Sommer, Christoph; Hoefler, Rudolf; Samwer, Matthias; Gerlich, Daniel W.

2017-01-01

Supervised machine learning is a powerful and widely used method for analyzing high-content screening data. Despite its accuracy, efficiency, and versatility, supervised machine learning has drawbacks, most notably its dependence on a priori knowledge of expected phenotypes and time-consuming classifier training. We provide a solution to these limitations with CellCognition Explorer, a generic novelty detection and deep learning framework. Application to several large-scale screening data sets on nuclear and mitotic cell morphologies demonstrates that CellCognition Explorer enables discovery of rare phenotypes without user training, which has broad implications for improved assay development in high-content screening. PMID:28954863

Using simulation pedagogy to teach clinical education skills: A randomized trial.

PubMed

Holdsworth, Clare; Skinner, Elizabeth H; Delany, Clare M

2016-05-01

Supervision of students is a key role of senior physiotherapy clinicians in teaching hospitals. The objective of this study was to test the effect of simulated learning environments (SLE) on educators' self-efficacy in student supervision skills. A pilot prospective randomized controlled trial with concealed allocation was conducted. Clinical educators were randomized to intervention (SLE) or control groups. SLE participants completed two 3-hour workshops, which included simulated clinical teaching scenarios, and facilitated debrief. Standard Education (StEd) participants completed two online learning modules. Change in educator clinical supervision self-efficacy (SE) and student perceptions of supervisor skill were calculated. Between-group comparisons of SE change scores were analyzed with independent t-tests to account for potential baseline differences in education experience. Eighteen educators (n = 18) were recruited (SLE [n = 10], StEd [n = 8]). Significant improvements in SE change scores were seen in SLE participants compared to control participants in three domains of self-efficacy: (1) talking to students about supervision and learning styles (p = 0.01); (2) adapting teaching styles for students' individual needs (p = 0.02); and (3) identifying strategies for future practice while supervising students (p = 0.02). This is the first study investigating SLE for teaching skills of clinical education. SLE improved educators' self-efficacy in three domains of clinical education. Sample size limited the interpretation of student ratings of educator supervision skills. Future studies using SLE would benefit from future large multicenter trials evaluating its effect on educators' teaching skills, student learning outcomes, and subsequent effects on patient care and health outcomes.

A semi-supervised classification algorithm using the TAD-derived background as training data

NASA Astrophysics Data System (ADS)

Fan, Lei; Ambeau, Brittany; Messinger, David W.

2013-05-01

In general, spectral image classification algorithms fall into one of two categories: supervised and unsupervised. In unsupervised approaches, the algorithm automatically identifies clusters in the data without a priori information about those clusters (except perhaps the expected number of them). Supervised approaches require an analyst to identify training data to learn the characteristics of the clusters such that they can then classify all other pixels into one of the pre-defined groups. The classification algorithm presented here is a semi-supervised approach based on the Topological Anomaly Detection (TAD) algorithm. The TAD algorithm defines background components based on a mutual k-Nearest Neighbor graph model of the data, along with a spectral connected components analysis. Here, the largest components produced by TAD are used as regions of interest (ROI's),or training data for a supervised classification scheme. By combining those ROI's with a Gaussian Maximum Likelihood (GML) or a Minimum Distance to the Mean (MDM) algorithm, we are able to achieve a semi supervised classification method. We test this classification algorithm against data collected by the HyMAP sensor over the Cooke City, MT area and University of Pavia scene.

Segmentation of retinal blood vessels using artificial neural networks for early detection of diabetic retinopathy

NASA Astrophysics Data System (ADS)

Mann, Kulwinder S.; Kaur, Sukhpreet

2017-06-01

There are various eye diseases in the patients suffering from the diabetes which includes Diabetic Retinopathy, Glaucoma, Hypertension etc. These all are the most common sight threatening eye diseases due to the changes in the blood vessel structure. The proposed method using supervised methods concluded that the segmentation of the retinal blood vessels can be performed accurately using neural networks training. It uses features which include Gray level features; Moment Invariant based features, Gabor filtering, Intensity feature, Vesselness feature for feature vector computation. Then the feature vector is calculated using only the prominent features.

Clinical supervision for nurses in administrative and leadership positions: a systematic literature review of the studies focusing on administrative clinical supervision.

PubMed

Sirola-Karvinen, Pirjo; Hyrkäs, Kristiina

2006-11-01

The aim of this systematic literature review was to describe administrative clinical supervision from the nursing leaders', directors' and administrators' perspective. Administrative clinical supervision is a timely and important topic as organizational structures in health care and nursing leadership are changing in addition to the increasing number of complex challenges present in health care. The material in this review was drawn from national and international databases including doctoral dissertations, distinguished thesis and peer-reviewed articles. The material was analysed by means of content analysis. The theoretical framework for the analysis was based on the three main functions of clinical supervision: administrative, educational and supportive. The findings demonstrated that the experiences of the administrative clinical supervision and its supportiveness were varying. The intervention was seen to provide versatility of learning experiences and support in challenging work experiences. Administrative clinical supervision effects and assures the quality of care. The effects as a means of development were explained through its resemblance to a leading specialist community. The findings support earlier perceptions concerning the importance and significance of administrative clinical supervision for nursing managers and administrators. However, more research is needed to develop administrative clinical supervision and to increase understanding of theoretical assumptions and relationships of the concepts on the background.

The effectiveness of clinical supervision for a group of ward managers based in a district general hospital: an evaluative study.

PubMed

Davis, Cynthia; Burke, Linda

2012-09-01

To present an evaluative audit assessing the effectiveness of clinical supervision for ward managers. A year-long project to introduce clinical supervision to ward managers was implemented and evaluated. The objectives were to evaluate staff perceptions of implementing clinical supervision and determine its outcomes. An audit evaluation process was used. Findings are presented against perceptions, implementation and reported outcomes of clinical supervision. Insights were gained into its relevance and importance to nurses and the organisation. Findings show that clinical supervision was perceived to be effective and helped improve patient care, but some feared it becoming a form of managerial control. Ward managers perceived advantages for personal and professional development from adopting this process. There is a need for greater understanding of clinical supervision before Trusts implement it. The introduction of a resource pack for clinical areas would also be of value. Finally, there needs to be a named person who has a special knowledge of clinical supervision to act as a champion and change agent in effecting implementation at both the executive level and within each clinical area. © 2011 Blackwell Publishing Ltd.

Supervising for Home Safety Program: A Randomized Controlled Trial (RCT) Testing Community-Based Group Delivery.

PubMed

Morrongiello, Barbara A; Hou, Sharon; Bell, Melissa; Walton, Kathryn; Filion, A Jordan; Haines, Jess

2017-08-01

The individually delivered Supervising for Home Safety (SHS) program improves caregivers' injury-related beliefs and supervision practices. The current randomized controlled trial used a group delivery in a community setting and assessed program impact, feasibility, and acceptance. Caregivers of 2-5-year-olds were randomized to receive either the SHS or an attention-matched control program. In the SHS group only, there were increases from baseline to postintervention in the following: beliefs about children's vulnerability to injury, caregiver preventability of injuries, and self-efficacy to do so; readiness for change in supervision; and watchful supervision. Face-to-face recruitment by staff at community organizations proved most successful. Caregivers' satisfaction ratings were high, as was caregiver engagement (95% completed at least seven of the nine sessions). The SHS program can be delivered to groups of caregivers in community settings, is positively received by caregivers, and produces desirable changes that can be expected to improve caregivers' home safety practices. © The Author 2016. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Operating Room Anesthesia Subspecialization Is Not Associated With Significantly Greater Quality of Supervision of Anesthesia Residents and Nurse Anesthetists.

PubMed

Dexter, Franklin; Ledolter, Johannes; Epstein, Richard H; Hindman, Bradley J

2017-04-01

Supervision of anesthesia residents and nurse anesthetists is a major responsibility of faculty anesthesiologists. The quality of their supervision can be assessed quantitatively by the anesthesia residents and nurse anesthetists. Supervision scores are an independent measure of the contribution of the anesthesiologist to patient care. We evaluated the association between quality of supervision and level of specialization of anesthesiologists. We used two 6-month periods, one with no feedback to anesthesiologists of the residents' and nurse anesthetists' evaluations, and the other with feedback. Supervision scores provided by residents and nurse anesthetists were considered separately. Sample sizes among the 4 combinations ranged from n = 51 to n = 62 University of Iowa faculty. For each supervising anesthesiologist and 6-month period, we calculated the proportion of anesthetic cases attributable to each anesthesia Current Procedural Terminology code. The sum of the square of the proportions, a measurement of diversity, is known as the Herfindahl index. The inverse of this index represents the effective number of common procedures. The diversity (degree of specialization) of each faculty anesthesiologist was measured attributing each case to: (1) the anesthesiologist who supervised for the longest total period of time, (2) the anesthesiologist who started the case, or (3) the anesthesiologist who started the case, limited to cases started during "regular hours" (defined as nonholiday Monday to Friday, 07:00 AM to 02:59 PM). Inferential analysis was performed using bivariate-weighted least-squares regression. The point estimates of all 12 slopes were in the direction of greater specialization of practice of the evaluated faculty anesthesiologist being associated with significantly lower supervision scores. Among supervision scores provided by nurse anesthetists, the association was statistically significant for the third of the 6-month periods under the first and second ways of attributing the cases (uncorrected P < .0001). However, the slopes of the relationships were all small (eg, 0.109 ± 0.025 [SE] units on the 4-point supervision scale for a change of 10 common procedures). Among supervision scores provided by anesthesia residents, the association was statistically significant during the first period for all 3 ways of attributing the case (uncorrected P < .0001). However, again, the slopes were small (eg, 0.127 ± 0.027 units for a change of 10 common procedures). Greater clinical specialization of faculty anesthesiologists was not associated with meaningful improvements in quality of clinical supervision.

Effects of increased overnight supervision on resident education, decision-making, and autonomy.

PubMed

Haber, Lawrence A; Lau, Catherine Y; Sharpe, Bradley A; Arora, Vineet M; Farnan, Jeanne M; Ranji, Sumant R

2012-10-01

New supervisory regulations highlight the challenge of balancing housestaff supervision and autonomy. To better understand the impact of increased supervision on residency training, we investigated housestaff perceptions of education, autonomy, and clinical decision-making before and after implementation of an in-hospital, overnight attending physician (nocturnist). We established a nocturnist program in July 2010 at our academic, tertiary care medical center. We administered pre-surveys and post-surveys of internal medicine residents on night float rotation during the 2010-2011 academic year. We surveyed residents before and after experiencing the nocturnist program. Housestaff reported an increase in the clinical value of the night float rotation (3.95 vs 4.27, P = 0.01) and the adequacy of overnight supervision (3.65 vs 4.30, P < 0.0001) without a change in decision-making autonomy (4.35 vs 4.45, P = 0.44). Trainees agreed that nocturnist supervision positively impacted patient outcomes (3.79 vs 4.30, P = 0.002). Housestaff contacted attendings more frequently for transfers from outside facilities (2.00 vs 3.20, P = 0.006), during adverse events (2.51 vs 3.25, P = 0.04), prior to ordering invasive diagnostics (1.75 vs 2.76, P = 0.004), and prior to vasopressor use (1.52 vs 2.40, P = 0.004). Residents' fear of revealing knowledge gaps and desire to make decisions independently did not change. Increased overnight supervision enhanced the clinical value of the night float rotation, increased rates of attending contact during critical clinical decision-making, and improved perception of patient care. These changes occurred without a decrease in housestaff's perceived decision-making autonomy. Copyright © 2012 Society of Hospital Medicine.

Can clinical supervision sustain our workforce in the current healthcare landscape? Findings from a Queensland study of allied health professionals.

PubMed

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.

PROBLEMS OF RADIOLOGICAL PROTECTION IN FLAW DETECTION (in Polish)

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

Domanus, J.; Wolski, M.

1962-01-01

All industrial flaw detection laboratories are covered, with respect to their radiological protection, by the supervision of the Inst. of Electrotechnics. A discussion is given of the results of this action, especially the cases of exceeding the admissible doses. The analysis of endangerment by radiation of employees of flaw detection laboratories is given. (auth)

From Google Maps to a fine-grained catalog of street trees

NASA Astrophysics Data System (ADS)

Branson, Steve; Wegner, Jan Dirk; Hall, David; Lang, Nico; Schindler, Konrad; Perona, Pietro

2018-01-01

Up-to-date catalogs of the urban tree population are of importance for municipalities to monitor and improve quality of life in cities. Despite much research on automation of tree mapping, mainly relying on dedicated airborne LiDAR or hyperspectral campaigns, tree detection and species recognition is still mostly done manually in practice. We present a fully automated tree detection and species recognition pipeline that can process thousands of trees within a few hours using publicly available aerial and street view images of Google MapsTM. These data provide rich information from different viewpoints and at different scales from global tree shapes to bark textures. Our work-flow is built around a supervised classification that automatically learns the most discriminative features from thousands of trees and corresponding, publicly available tree inventory data. In addition, we introduce a change tracker that recognizes changes of individual trees at city-scale, which is essential to keep an urban tree inventory up-to-date. The system takes street-level images of the same tree location at two different times and classifies the type of change (e.g., tree has been removed). Drawing on recent advances in computer vision and machine learning, we apply convolutional neural networks (CNN) for all classification tasks. We propose the following pipeline: download all available panoramas and overhead images of an area of interest, detect trees per image and combine multi-view detections in a probabilistic framework, adding prior knowledge; recognize fine-grained species of detected trees. In a later, separate module, track trees over time, detect significant changes and classify the type of change. We believe this is the first work to exploit publicly available image data for city-scale street tree detection, species recognition and change tracking, exhaustively over several square kilometers, respectively many thousands of trees. Experiments in the city of Pasadena, California, USA show that we can detect >70% of the street trees, assign correct species to >80% for 40 different species, and correctly detect and classify changes in >90% of the cases.

Registrar sleep patterns and supervision during two different rosters in a tertiary Australasian intensive care unit.

PubMed

Poynter, Chris J; Garden, Alexander; Young, Paul J

2012-03-01

To compare registrar sleep and supervision hours before and after a change in roster to accommodate more senior registrar (SR) positions, and to identify risky patterns of sleep on night shifts. Prospective study of 21 registrars on two different roster templates from September 2010 to May 2011 in the intensive care unit of Wellington Regional Hospital, Wellington, New Zealand. Roster change from 13 registrars and one SR to 10 registrars and four SRs. Mean sleep and supervision hours by shift; episodes of sleep ≤ 5 hours, wakefulness ≥17 hours, sleep during shift, waking before 16:00 before night shifts. 990 sleep surveys were analysed. There was no significant difference between groups in mean sleep or supervision hours for any shift. Two hundred and thirty-six night shifts were analysed. Registrars slept ≤5 hours before 19/236 (8.1%) night shifts; had ≥17 hours wakefulness before 79/236 night shifts (33.5%); woke by 16:00 107/ 236 (45.3%) times; and slept during 86/236 (36.4%) night shifts. Registrars arrived at work having either woken before 16:00 or had ≤5 hours of sleep on 114/236 (48.3%) night shifts. Changing the registrar roster to meet the training demands of our senior trainees did not adversely affect registrar sleep or supervision. Registrars may be taking on unnecessary risk due to poor sleep hygiene around night shifts. We suggest sleep education and scheduled sleep time during night shifts.

Supervised Classification Processes for the Characterization of Heritage Elements, Case Study: Cuenca-Ecuador

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.

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.

A systematic review of evidence relating to clinical supervision for nurses, midwives and allied health professionals.

PubMed

Pollock, Alex; Campbell, Pauline; Deery, Ruth; Fleming, Mick; Rankin, Jean; Sloan, Graham; Cheyne, Helen

2017-08-01

The aim of this study was to systematically review evidence relating to clinical supervision for nurses, midwives and allied health professionals. Since 1902 statutory supervision has been a requirement for UK midwives, but this is due to change. Evidence relating to clinical supervision for nurses and allied health professions could inform a new model of clinical supervision for midwives. A systematic review with a contingent design, comprising a broad map of research relating to clinical supervision and two focussed syntheses answering specific review questions. Electronic databases were searched from 2005 - September 2015, limited to English-language peer-reviewed publications. Systematic reviews evaluating the effectiveness of clinical supervision were included in Synthesis 1. Primary research studies including a description of a clinical supervision intervention were included in Synthesis 2. Quality of reviews were judged using a risk of bias tool and review results summarized in tables. Data describing the key components of clinical supervision interventions were extracted from studies included in Synthesis 2, categorized using a reporting framework and a narrative account provided. Ten reviews were included in Synthesis 1; these demonstrated an absence of convincing empirical evidence and lack of agreement over the nature of clinical supervision. Nineteen primary studies were included in Synthesis 2; these highlighted a lack of consistency and large variations between delivered interventions. Despite insufficient evidence to directly inform the selection and implementation of a framework, the limited available evidence can inform the design of a new model of clinical supervision for UK-based midwives. © 2017 John Wiley & Sons Ltd.

Temporal assessment on land use land cover of Somalia after the effect of the civil war using remote sensing

NASA Astrophysics Data System (ADS)

Abdulle, Abdinur; Tan, Adhwa Amir; Pradhan, Biswajeet; Abdullahi, Saleh

2016-06-01

The aim of this study is to analyse land use and cover changes for the studied area during 1992-2015 and particularly evaluate the effect of civil war on these changes. Three Landsat images were used; Landsat 4 (1992), Landsat 7 (2000) and Landsat 8 (2015). Assessment of changes has been applied through three supervised classification algorithms, support vector machine, minimum classifier, and mahalanobis classifier. The result shows that SVM is providing highest overall accuracy of 98.5% for the years 2000 and 2015 with kappa coefficient of 0.9803 in year 2015. The change detection result show that the higher changes is between year 1992-2000 where vegetation land cover has dropped down to 11.1% and undeveloped area has increased to 11.4%. Whereas for year 2000-2015, higher changes belongs to build up area by 3.30% while undeveloped area and vegetation land cover keep decreasing by 2.64% and 1.93% respectively.

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

PubMed

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.

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

The UK Postgraduate Masters Dissertation: An "Elusive Chameleon"?

ERIC Educational Resources Information Center

Pilcher, Nick

2011-01-01

Many studies into the process of producing and supervising dissertations exist, yet little research into the "product" of the Masters dissertation, or into how Masters supervision changes over time exist. Drawing on 62 semi-structured interviews with 31 Maths and Computer Science supervisors over a two-year period, this paper explores…

The Principal and Supervision. Elementary Principal Series No. 4.

ERIC Educational Resources Information Center

Luehe, Bill

The fourth of six volumes in the "Elementary Principal Series," this booklet offers new principals a set of ideas, procedures, and examples associated with effective teacher supervision. The principal-teacher supervisory relationship has changed dramatically over recent years. The principal is no longer an inspector, but a colleague…

The effects of therapeutic exercises on pain, muscle strength, functional capacity, balance and hemodynamic parameters in knee osteoarthritis patients: a randomized controlled study of supervised versus home exercises.

PubMed

Kuru Çolak, Tuğba; Kavlak, Bahar; Aydoğdu, Onur; Şahin, Emir; Acar, Gönül; Demirbüken, İlkşan; Sarı, Zübeyir; Çolak, İlker; Bulut, Güven; Polat, M Gülden

2017-03-01

The aim of the study was to compare the effects of low-intensity exercise programs for lower extremities, either supervised or at home, on pain, muscle strength, balance and the hemodynamic parameters of knee osteoarthritis (OA) patients. This randomized study included 78 patients with knee OA in 2 groups of supervised and home-based exercise program. Exercises were applied to the first group in the clinic as a group exercise program and were demonstrated to the second group to be performed at home. Before and after the 6-week exercise program, assessment was made of pain, quadriceps and hamstring muscle strengths, 6-min walk test (6MWT), and non-invasive hemodynamic parameters. Results of the 78 patients, 56 completed the study. Pain, muscle strength, and 6MWT scores showed significant improvements in both groups. There were also significant differences in the amount of change in pain and muscle strength (pain: p = 0.041, Rqdc: 0.009, Lqdc: 0.013, Rhms: 0.04) which indicated greater improvements in the supervised group. The balance scores of supervised group showed a significant improvement (p = 0.009). No significant change was determined in hemodynamic parameters of either group. Conclusion according to the results of this study showed that low-intensity lower extremity exercises conducted in a clinic under the supervision of a physiotherapist were more effective than home-based exercises in reducing post-activity pain levels and improving quadriceps and right hamstring muscle strength. Both the supervised and home exercise programs were seen to be effective in reducing rest pain and increasing 6 MW distance in knee osteoarthritis patients.

The cost-effectiveness of three interventions for providing preventive services to low-income children.

PubMed

Johnson, Ben; Serban, Nicoleta; Griffin, Paul M; Tomar, Scott L

2017-12-01

We evaluated the impact of loan repayment programmes, revising Medicaid fee-for-service rates, and changing dental hygienist supervision requirements on access to preventive dental care for children in Georgia. We estimated cost savings from the three interventions of preventive care for young children after netting out the intervention cost. We used a regression model to evaluate the impact of changing the Medicaid reimbursement rates. The impact of supervision was evaluated by comparing general and direct supervision in school-based dental sealant programmes. Federal loan repayments to dentists and school-based sealant programmes (SBSPs) had lower intervention costs (with higher potential cost savings) than raising the Medicaid reimbursement rate. General supervision had costs 56% lower than direct supervision of dental hygienists for implementing a SBSP. Raising the Medicaid reimbursement rate by 10 percentage points would improve utilization by <1% and cost over $38 million. Given one parameter set, SBSPs could serve over 27 000 children with an intervention cost between $500 000 and $1.3 million with a potential cost saving of $1.1 million. Loan repayment could serve almost 13 000 children for a cost of $400 000 and a potential cost saving of $176 000. The three interventions all improved met need for preventive dental care. Raising the reimbursement rate alone would marginally affect utilization of Medicaid services but would not substantially increase acceptance of Medicaid by providers. Both loan repayment programmes and amending supervision requirements are potentially cost-saving interventions. Loan repayment programmes provide complete care to targeted areas, while amending supervision requirements of dental hygienists could provide preventive care across the state. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

PubMed

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

2015-01-01

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

76 FR 48949 - Office of Thrift Supervision Integration Pursuant to the Dodd-Frank Wall Street Reform and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-09

...Pursuant to Title III of the Dodd-Frank Wall Street Reform and Consumer Protection Act, all functions of the Office of Thrift Supervision (OTS) relating to Federal savings associations and the rulemaking authority of the OTS relating to all savings associations are transferred to the Office of the Comptroller of the Currency (OCC) on July 21, 2011 (transfer date). In order to facilitate the OCC's enforcement and administration of former OTS rules and to make appropriate changes to these rules to reflect OCC supervision of Federal savings associations as of the transfer date, the OCC is republishing, with nomenclature and other technical changes, the OTS regulations currently found in Chapter V of Title 12 of the Code of Federal Regulations. The republished regulations will be recodified with the OCC's regulations in Chapter I at parts 100 through 197 (Republished Regulations), effective on July 21, 2011. The Republished Regulations will supersede the OTS regulations in Chapter V for purposes of OCC supervision and regulation of Federal savings associations, and certain of the Republished Rules will supersede the OTS regulations in Chapter V for purposes of the FDIC's supervision of state savings associations. Chapter V of Title 12 of the Code of Federal Regulations will be vacated at a later date.

A Kalman filtering framework for physiological detection of anxiety-related arousal in children with autism spectrum disorder.

PubMed

Kushki, Azadeh; Khan, Ajmal; Brian, Jessica; Anagnostou, Evdokia

2015-03-01

Anxiety is associated with physiological changes that can be noninvasively measured using inexpensive and wearable sensors. These changes provide an objective and language-free measure of arousal associated with anxiety, which can complement treatment programs for clinical populations who have difficulty with introspection, communication, and emotion recognition. This motivates the development of automatic methods for detection of anxiety-related arousal using physiology signals. While several supervised learning methods have been proposed for this purpose, these methods require regular collection and updating of training data and are, therefore, not suitable for clinical populations, where obtaining labelled data may be challenging due to impairments in communication and introspection. In this context, the objective of this paper is to develop an unsupervised and real-time arousal detection algorithm. We propose a learning framework based on the Kalman filtering theory for detection of physiological arousal based on cardiac activity. The performance of the system was evaluated on data obtained from a sample of children with autism spectrum disorder. The results indicate that the system can detect anxiety-related arousal in these children with sensitivity and specificity of 99% and 92%, respectively. Our results show that the proposed method can detect physiological arousal associated with anxiety with high accuracy, providing support for technical feasibility of augmenting anxiety treatments with automatic detection techniques. This approach can ultimately lead to more effective anxiety treatment for a larger and more diverse population.

Parental supervision for their children's toothbrushing: Mediating effects of planning, self-efficacy, and action control.

PubMed

Hamilton, Kyra; Cornish, Stephen; Kirkpatrick, Aaron; Kroon, Jeroen; Schwarzer, Ralf

2018-05-01

With 60-90% of children worldwide reportedly experiencing dental caries, poor oral health in the younger years is a major public health issue. As parents are important to children's oral hygiene practices, we examined the key self-regulatory behaviours of parents for supervising their children's toothbrushing using the health action process approach. Participants (N = 281, 197 mothers) comprised Australian parents of 2- to 5-year-olds. A longitudinal design was used to investigate the sequential mediation chain for the effect of intention (Time 1) on parental supervision for their youngest child's toothbrushing (Time 3), via self-efficacy and planning (Time 2), and action control (Time 3). A latent-variable structural equation model, controlling for baseline behaviour and habit, revealed significant indirect effects from intention via self-efficacy and action control and intention via planning and action control, on parental supervision behaviour. The model was a good fit to the data, explaining 74% of the variance in parents' supervising behaviour for their children's toothbrushing. While national recommendations are provided to guide parents in promoting good oral hygiene practices with their children, current results show the importance of going beyond simple knowledge transmission to support parents' intentions to supervise their children's toothbrushing actually materialize. Current findings make a significant contribution to the cumulative empirical evidence regarding self-regulatory components in health behaviour change and can inform intervention development to increase parents' participation in childhood oral hygiene practices, thus helping to curb rising oral health conditions and diseases. Statement of contribution What is already known on this subject? Self-regulatory skills are important to translate intentions into behaviour. Self-efficacy, planning, and action control are key self-regulatory skills for behaviour change. What does this study add? Self-regulatory skills are needed for parents to supervise their children's toothbrushings. Self-efficacy, planning, and action control are important self-regulatory skills in this context. Future interventions should map these self-regulatory predictors onto behaviour change techniques. © 2018 The British Psychological Society.

Spatio-Temporal Assessment of Margalla Hills Forest by Using Landsat Imagery for Year 2000 and 2018

NASA Astrophysics Data System (ADS)

Batool, R.; Javaid, K.

2018-04-01

Environmental imbalance due to human activities has shown serious threat to ecosystem and produced negative impacts. The main goal of this study is to identify, monitor and classify temporal changes of forest cover, build up and open spaces in Margalla Hills National Park, Islamabad. Geographic Information Sciences (GISc) and Remote Sensing (RS) techniques has been used for the assessment of analysis. LANDSAT-7 Enhanced Thematic Mapper (ETM+) and LANDSAT-8 Operational Land Imager (OLI) were utilized for obtaining data of year 2000 and 2018. Temporal changes were evaluated after applying supervised classification and discrimination was analyzed by Per-Pixel based change detection. Results depicts forest cover decrease from 87 % to 74 % whereas build up has increased from 5 % to 7 % over the span. Consequences also justify the presence of open land in study area that has been increased from 2 % to 7 % respectively.

Calibration model maintenance in melamine resin production: Integrating drift detection, smart sample selection and model adaptation.

PubMed

Nikzad-Langerodi, Ramin; Lughofer, Edwin; Cernuda, Carlos; Reischer, Thomas; Kantner, Wolfgang; Pawliczek, Marcin; Brandstetter, Markus

2018-07-12

The physico-chemical properties of Melamine Formaldehyde (MF) based thermosets are largely influenced by the degree of polymerization (DP) in the underlying resin. On-line supervision of the turbidity point by means of vibrational spectroscopy has recently emerged as a promising technique to monitor the DP of MF resins. However, spectroscopic determination of the DP relies on chemometric models, which are usually sensitive to drifts caused by instrumental and/or sample-associated changes occurring over time. In order to detect the time point when drifts start causing prediction bias, we here explore a universal drift detector based on a faded version of the Page-Hinkley (PH) statistic, which we test in three data streams from an industrial MF resin production process. We employ committee disagreement (CD), computed as the variance of model predictions from an ensemble of partial least squares (PLS) models, as a measure for sample-wise prediction uncertainty and use the PH statistic to detect changes in this quantity. We further explore supervised and unsupervised strategies for (semi-)automatic model adaptation upon detection of a drift. For the former, manual reference measurements are requested whenever statistical thresholds on Hotelling's T 2 and/or Q-Residuals are violated. Models are subsequently re-calibrated using weighted partial least squares in order to increase the influence of newer samples, which increases the flexibility when adapting to new (drifted) states. Unsupervised model adaptation is carried out exploiting the dual antecedent-consequent structure of a recently developed fuzzy systems variant of PLS termed FLEXFIS-PLS. In particular, antecedent parts are updated while maintaining the internal structure of the local linear predictors (i.e. the consequents). We found improved drift detection capability of the CD compared to Hotelling's T 2 and Q-Residuals when used in combination with the proposed PH test. Furthermore, we found that active selection of samples by active learning (AL) used for subsequent model adaptation is advantageous compared to passive (random) selection in case that a drift leads to persistent prediction bias allowing more rapid adaptation at lower reference measurement rates. Fully unsupervised adaptation using FLEXFIS-PLS could improve predictive accuracy significantly for light drifts but was not able to fully compensate for prediction bias in case of significant lack of fit w.r.t. the latent variable space. Copyright © 2018 Elsevier B.V. All rights reserved.

A robust multi-kernel change detection framework for detecting leaf beetle defoliation using Landsat 7 ETM+ data

NASA Astrophysics Data System (ADS)

Anees, Asim; Aryal, Jagannath; O'Reilly, Małgorzata M.; Gale, Timothy J.; Wardlaw, Tim

2016-12-01

A robust non-parametric framework, based on multiple Radial Basic Function (RBF) kernels, is proposed in this study, for detecting land/forest cover changes using Landsat 7 ETM+ images. One of the widely used frameworks is to find change vectors (difference image) and use a supervised classifier to differentiate between change and no-change. The Bayesian Classifiers e.g. Maximum Likelihood Classifier (MLC), Naive Bayes (NB), are widely used probabilistic classifiers which assume parametric models, e.g. Gaussian function, for the class conditional distributions. However, their performance can be limited if the data set deviates from the assumed model. The proposed framework exploits the useful properties of Least Squares Probabilistic Classifier (LSPC) formulation i.e. non-parametric and probabilistic nature, to model class posterior probabilities of the difference image using a linear combination of a large number of Gaussian kernels. To this end, a simple technique, based on 10-fold cross-validation is also proposed for tuning model parameters automatically instead of selecting a (possibly) suboptimal combination from pre-specified lists of values. The proposed framework has been tested and compared with Support Vector Machine (SVM) and NB for detection of defoliation, caused by leaf beetles (Paropsisterna spp.) in Eucalyptus nitens and Eucalyptus globulus plantations of two test areas, in Tasmania, Australia, using raw bands and band combination indices of Landsat 7 ETM+. It was observed that due to multi-kernel non-parametric formulation and probabilistic nature, the LSPC outperforms parametric NB with Gaussian assumption in change detection framework, with Overall Accuracy (OA) ranging from 93.6% (κ = 0.87) to 97.4% (κ = 0.94) against 85.3% (κ = 0.69) to 93.4% (κ = 0.85), and is more robust to changing data distributions. Its performance was comparable to SVM, with added advantages of being probabilistic and capable of handling multi-class problems naturally with its original formulation.

Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979-2009) in China.

PubMed

Yin, Jie; Yin, Zhane; Zhong, Haidong; Xu, Shiyuan; Hu, Xiaomeng; Wang, Jun; Wu, Jianping

2011-06-01

This study explored the spatio-temporal dynamics and evolution of land use/cover changes and urban expansion in Shanghai metropolitan area, China, during the transitional economy period (1979-2009) using multi-temporal satellite images and geographic information systems (GIS). A maximum likelihood supervised classification algorithm was employed to extract information from four landsat images, with the post-classification change detection technique and GIS-based spatial analysis methods used to detect land-use and land-cover (LULC) changes. The overall Kappa indices of land use/cover change maps ranged from 0.79 to 0.89. Results indicated that urbanization has accelerated at an unprecedented scale and rate during the study period, leading to a considerable reduction in the area of farmland and green land. Findings further revealed that water bodies and bare land increased, obviously due to large-scale coastal development after 2000. The direction of urban expansion was along a north-south axis from 1979 to 2000, but after 2000 this growth changed to spread from both the existing urban area and along transport routes in all directions. Urban expansion and subsequent LULC changes in Shanghai have largely been driven by policy reform, population growth, and economic development. Rapid urban expansion through clearing of vegetation has led to a wide range of eco-environmental degradation.

Cognitive Dissonance, Supervision, and Administrative Team Conflict

ERIC Educational Resources Information Center

Zepeda, Sally J.

2006-01-01

Purpose: The purpose of this paper is to record and summarize the tensions and problems experienced by a high school administrative team as they attempted to change supervision alongside instruction in a transition to a new block schedule. Design/methodology/approach: A case study method was used. As a case study, the research is contextual in…

Successful Supervision from the Student-Teachers' Perspective: An Analysis of Supervisory Talk

ERIC Educational Resources Information Center

Gulden, Ilin; Julide, Inozu; Rana, Yildirim

2007-01-01

This study aims at analyzing supervisory talk and student- teachers' interpretations of it in order to find out the qualities that characterize successful supervision which leads to a change in student- teachers' beliefs. To achieve this, supervisory feedback sessions with four supervisors were recorded, transcribed and then analyzed for…

New Technology, Changing Pedagogies? Exploring the Concept of Remote Teaching Placement Supervision

ERIC Educational Resources Information Center

Chilton, Helen; McCracken, Wendy

2017-01-01

Mobile technologies continue to have a growing influence on contemporary society, are becoming more commonplace within tertiary educational settings and hold the potential to impact on the learning process. This project evaluation considers the perspectives of participants who trialled the use of new technology to enable remote supervision and…

The Principles and Practices of Supervision That Supports the Development of Inclusive Teacherhood

ERIC Educational Resources Information Center

Alila, Sanna; Uusiautti, Satu; Määttä, Kaarina

2016-01-01

In this study, the purpose was to study what kind of supervision supports inclusive teacherhood the best. Inclusive teacherhood means a teacher's professional development and the school culture's change toward participatory school for all students. The study investigated the perceptions of supervisors with a teaching background. This was a…

"What's So Special About HIV and AIDS?": Stresses and Strains for Clients and Counsellors.

ERIC Educational Resources Information Center

Kiemle, Gundi

1994-01-01

Discusses supervision and counseling of people with AIDS. Addresses the impact upon the client and the counselor against the background of stigmatization. Conflicts and losses arising at different stages are explored. Discusses implications for the need for supervision to facilitate changes necessary to cope with clients' and counselors' feelings…

Self-Help for Teachers: Collegial Supervision in an Urban School.

ERIC Educational Resources Information Center

Mattaliano, A. Peter

Teachers in inner city schools today are usually unprepared for dealing effectively with a mobile, rapidly changing, culturally varied population. A program to provide such training, based upon the concept of staff self help through collegial supervision, was implemented in the Francis M. Leahy Elementary School in Lawrence, Massachusetts. Over a…

Fighting Fires in Early Intervention Supervision: Trading the Axe for Mr. Rogers's Slippers

ERIC Educational Resources Information Center

Alexander, Laura; Gallen, Robert T.; Salazar, Ruby; Shahmoon-Shanok, Rebecca

2012-01-01

When Pennsylvania's Early Intervention system implemented an early intervention-reflective supervision project, modest expectations for change were anticipated, given the limited amount of time and funding for the project. In this article, one participant tells the story of her professional development, which enabled her to augment her skills as…

Managing severe mental illness in the community using the Mental Health Act 1983: a comparison of Supervised Discharge and Guardianship in England.

PubMed

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.

Supervising away from home: clinical, cultural and professional challenges.

PubMed

Abramovitch, Henry; Wiener, Jan

2017-02-01

This paper explores some challenges of supervising clinical work of trainees, known as 'routers', who live in countries with diverse cultural, social and political traditions, and the analysts who travel to supervise them. It is written as an evolving dialogue between the authors, who explore together the effects of their own culture of origin, and in particular the legacy and values of their own training institutes on the styles and models of analytic supervision. Their dialogue is framed around the meaning of home and experiences of homesickness for analysts working away from home in an interactive field of strangeness in countries where analytical psychology is a relatively new discipline. The authors outline the findings from their own qualitative survey, where other supervisors working abroad, and those they have supervised, describe their experiences and their encounters with difference. The dialogue ends with both authors discussing what they have learned about teaching and supervising abroad, the implications for more flexible use of Jungian concepts, and how such visits have changed their clinical practice in their home countries. © 2017, The Society of Analytical Psychology.

Physical isolation with virtual support: Registrars' learning via remote supervision.

PubMed

Wearne, Susan M; Teunissen, Pim W; Dornan, Tim; Skinner, Timothy

2014-08-26

Abstract Purpose: Changing the current geographical maldistribution of the medical workforce is important for global health. Research regarding programs that train doctors for work with disadvantaged, rural populations is needed. This paper explores one approach of remote supervision of registrars in isolated rural practice. Researching how learning occurs without on-site supervision may also reveal other key elements of postgraduate education. Methods: Thematic analysis of in-depth interviews exploring 11 respondents' experiences of learning via remote supervision. Results: Remote supervision created distinctive learning environments. Respondents' attributes interacted with external supports to influence whether and how their learning was promoted or impeded. Registrars with clinical and/or life experience, who were insightful and motivated to direct their learning, turned the challenges of isolated practice into opportunities that accelerated their professional development. Discussion: Remote supervision was not necessarily problematic but instead provided rich learning for doctors training in and for the context where they were needed. Registrars learnt through clinical responsibility for defined populations and longitudinal, supportive supervisory relationships. Responsibility and continuity may be as important as supervisory proximity for experienced registrars.

Measuring the Effectiveness of a Genetic Counseling Supervision Training Conference.

PubMed

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.

Improving practice in community-based settings: a randomized trial of supervision - study protocol.

PubMed

Dorsey, Shannon; Pullmann, Michael D; Deblinger, Esther; Berliner, Lucy; Kerns, Suzanne E; Thompson, Kelly; Unützer, Jürgen; Weisz, John R; Garland, Ann F

2013-08-10

Evidence-based treatments for child mental health problems are not consistently available in public mental health settings. Expanding availability requires workforce training. However, research has demonstrated that training alone is not sufficient for changing provider behavior, suggesting that ongoing intervention-specific supervision or consultation is required. Supervision is notably under-investigated, particularly as provided in public mental health. The degree to which supervision in this setting includes 'gold standard' supervision elements from efficacy trials (e.g., session review, model fidelity, outcome monitoring, skill-building) is unknown. The current federally-funded investigation leverages the Washington State Trauma-focused Cognitive Behavioral Therapy Initiative to describe usual supervision practices and test the impact of systematic implementation of gold standard supervision strategies on treatment fidelity and clinical outcomes. The study has two phases. We will conduct an initial descriptive study (Phase I) of supervision practices within public mental health in Washington State followed by a randomized controlled trial of gold standard supervision strategies (Phase II), with randomization at the clinician level (i.e., supervisors provide both conditions). Study participants will be 35 supervisors and 130 clinicians in community mental health centers. We will enroll one child per clinician in Phase I (N = 130) and three children per clinician in Phase II (N = 390). We use a multi-level mixed within- and between-subjects longitudinal design. Audio recordings of supervision and therapy sessions will be collected and coded throughout both phases. Child outcome data will be collected at the beginning of treatment and at three and six months into treatment. This study will provide insight into how supervisors can optimally support clinicians delivering evidence-based treatments. Phase I will provide descriptive information, currently unavailable in the literature, about commonly used supervision strategies in community mental health. The Phase II randomized controlled trial of gold standard supervision strategies is, to our knowledge, the first experimental study of gold standard supervision strategies in community mental health and will yield needed information about how to leverage supervision to improve clinician fidelity and client outcomes. ClinicalTrials.gov NCT01800266.

Improving practice in community-based settings: a randomized trial of supervision – study protocol

PubMed Central

2013-01-01

Background Evidence-based treatments for child mental health problems are not consistently available in public mental health settings. Expanding availability requires workforce training. However, research has demonstrated that training alone is not sufficient for changing provider behavior, suggesting that ongoing intervention-specific supervision or consultation is required. Supervision is notably under-investigated, particularly as provided in public mental health. The degree to which supervision in this setting includes ‘gold standard’ supervision elements from efficacy trials (e.g., session review, model fidelity, outcome monitoring, skill-building) is unknown. The current federally-funded investigation leverages the Washington State Trauma-focused Cognitive Behavioral Therapy Initiative to describe usual supervision practices and test the impact of systematic implementation of gold standard supervision strategies on treatment fidelity and clinical outcomes. Methods/Design The study has two phases. We will conduct an initial descriptive study (Phase I) of supervision practices within public mental health in Washington State followed by a randomized controlled trial of gold standard supervision strategies (Phase II), with randomization at the clinician level (i.e., supervisors provide both conditions). Study participants will be 35 supervisors and 130 clinicians in community mental health centers. We will enroll one child per clinician in Phase I (N = 130) and three children per clinician in Phase II (N = 390). We use a multi-level mixed within- and between-subjects longitudinal design. Audio recordings of supervision and therapy sessions will be collected and coded throughout both phases. Child outcome data will be collected at the beginning of treatment and at three and six months into treatment. Discussion This study will provide insight into how supervisors can optimally support clinicians delivering evidence-based treatments. Phase I will provide descriptive information, currently unavailable in the literature, about commonly used supervision strategies in community mental health. The Phase II randomized controlled trial of gold standard supervision strategies is, to our knowledge, the first experimental study of gold standard supervision strategies in community mental health and will yield needed information about how to leverage supervision to improve clinician fidelity and client outcomes. Trial registration ClinicalTrials.gov NCT01800266 PMID:23937766

Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960-2005.

PubMed

Dewan, Ashraf M; Yamaguchi, Yasushi

2009-03-01

This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.

Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters.

PubMed

Feng, Jianyuan; Turksoy, Kamuran; Samadi, Sediqeh; Hajizadeh, Iman; Littlejohn, Elizabeth; Cinar, Ali

2017-12-01

Supervision and control systems rely on signals from sensors to receive information to monitor the operation of a system and adjust manipulated variables to achieve the control objective. However, sensor performance is often limited by their working conditions and sensors may also be subjected to interference by other devices. Many different types of sensor errors such as outliers, missing values, drifts and corruption with noise may occur during process operation. A hybrid online sensor error detection and functional redundancy system is developed to detect errors in online signals, and replace erroneous or missing values detected with model-based estimates. The proposed hybrid system relies on two techniques, an outlier-robust Kalman filter (ORKF) and a locally-weighted partial least squares (LW-PLS) regression model, which leverage the advantages of automatic measurement error elimination with ORKF and data-driven prediction with LW-PLS. The system includes a nominal angle analysis (NAA) method to distinguish between signal faults and large changes in sensor values caused by real dynamic changes in process operation. The performance of the system is illustrated with clinical data continuous glucose monitoring (CGM) sensors from people with type 1 diabetes. More than 50,000 CGM sensor errors were added to original CGM signals from 25 clinical experiments, then the performance of error detection and functional redundancy algorithms were analyzed. The results indicate that the proposed system can successfully detect most of the erroneous signals and substitute them with reasonable estimated values computed by functional redundancy system.

Patients' and therapists' experiences of general change mechanisms during bug-in-the-eye and delayed video-based supervised cognitive-behavioral therapy. A randomized controlled trial.

PubMed

Probst, Thomas; Jakob, Marion; Kaufmann, Yvonne M; Müller-Neng, Julia M B; Bohus, Martin; Weck, Florian

2018-04-01

This secondary analysis of a randomized controlled trial investigated whether bug-in-the-eye (BITE) supervision (live computer-based supervision during a psychotherapy session) affects the manner in which patients and therapists experience general change mechanisms (GCMs) during cognitive-behavioral therapy (CBT). A total of 23 therapists were randomized either to the BITE condition or the control condition (delayed video-based [DVB] supervision). After each session, both patients (BITE: n = 19; DVB: n = 23) and therapists (BITE: n = 11; DVB: n = 12) completed the Helping Alliance Questionnaire (HAQ) and the Bernese Post Session Report (BPSR). The HAQ total score and the 3 secondary factors of the BPSR (interpersonal experiences, intrapersonal experiences, problem actuation) functioned as GCMs. Multilevel models were performed. For patients, GCMs did not develop differently between BITE and DVB during CBT. Therapists rated the alliance as well as interpersonal and intrapersonal experiences not significantly different between BITE and DVB during CBT, but they perceived problem actuation to increase significantly more in BITE than in DVB (p < .05). BITE supervision might be helpful in encouraging CBT therapists to apply interventions, which focus on the activation of relevant problems and related emotions. © 2017 Wiley Periodicals, Inc.

[Learning and supervision in Danish clerkships--a qualitative study].

PubMed

Wichmann-Hansen, Gitte; Mørcke, Anne Mette; Eika, Berit

2007-10-15

The medical profession and hospital practice have changed over the last decades without a concomitant change in Danish clerkships. Therefore, the aim of this study was to analyze learning and supervision in clerkships and to discuss how traditional clerkship learning matches a modern effective hospital environment. A qualitative field study based on 38 days of observations ( asymptotically equal to 135 hours) with 6 students in 8th Semester in 2 internal medical and 3 surgical wards at 2 teaching hospitals in Aarhus County during 2003. The 6 students were interviewed prior to and following clerkship. Data were coded using Ethnograph and analyzed qualitatively. The students typically participated in 6 learning activities: morning reports, ward rounds, out-patient clinics, on call, clerking, and operating theatres. A common feature for the first 3 activities was the students' observational role in contrast to their more active role in the latter 3 activities. Supervision was primarily indirect as the doctors worked and thereby served as tacit role models. When direct, the supervision was didactic and characterized by information transfer. A clerkship offers important learning opportunities for students. They are exposed to many patients and faced with various clinical problems. However, the benefit of students learning in authentic environments is not fully utilized, and the didactic supervision used by doctors hardly matches the learning conditions in a busy hospital. Consequently, we need to reassess the students' roles and doctors' supervisory methods.

Microcrack Quantification in Composite Materials by a Neural Network Analysis of Ultrasound Spectral Data

NASA Technical Reports Server (NTRS)

Walker, James L.; Russell, Samuel S.; Suits, Michael W.

2003-01-01

Intra-ply microcracking in unlined composite pressure vessels can be very troublesome to detect and when linked through the thickness can provide leak paths that may hinder mission success. The leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping into air pockets within the laminate. Ultrasonic techniques have been shown capable of detecting the presence of microcracking and in this work they are used to quantify the level of microcracking. Resonance ultrasound methods are utilized with artificial neural networks to build a microcrack prediction/measurement tool. Two networks are presented, one unsupervised to provide a qualitative measure of microcracking and one supervised which provides a quantitative assessment of the level of microcracking. The resonant ultrasound spectroscopic method is made sensitive to microcracking by tuning the input spectrum to the higher frequency (shorter wavelength) components allowing more significant interaction with the defects. This interaction causes the spectral characteristics to shift toward lower amplitudes at the higher frequencies. As the density of the defects increases more interactions occur and more drastic amplitude changes are observed. Preliminary experiments to quantify the level of microcracking induced in graphite/epoxy composite samples through a combination of tensile loading and cryogenic temperatures are presented. Both unsupervised (Kohonen) and supervised (radial basis function) artificial neural networks are presented to determine the measurable effect on the resonance spectrum of the ultrasonic data taken from the samples.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.

PubMed

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.

Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification

PubMed Central

Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried

2017-01-01

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows. PMID:28125723

Comparison of remote sensing image processing techniques to identify tornado damage areas from Landsat TM data

USGS Publications Warehouse

Myint, S.W.; Yuan, M.; Cerveny, R.S.; Giri, C.P.

2008-01-01

Remote sensing techniques have been shown effective for large-scale damage surveys after a hazardous event in both near real-time or post-event analyses. The paper aims to compare accuracy of common imaging processing techniques to detect tornado damage tracks from Landsat TM data. We employed the direct change detection approach using two sets of images acquired before and after the tornado event to produce a principal component composite images and a set of image difference bands. Techniques in the comparison include supervised classification, unsupervised classification, and objectoriented classification approach with a nearest neighbor classifier. Accuracy assessment is based on Kappa coefficient calculated from error matrices which cross tabulate correctly identified cells on the TM image and commission and omission errors in the result. Overall, the Object-oriented Approach exhibits the highest degree of accuracy in tornado damage detection. PCA and Image Differencing methods show comparable outcomes. While selected PCs can improve detection accuracy 5 to 10%, the Object-oriented Approach performs significantly better with 15-20% higher accuracy than the other two techniques. ?? 2008 by MDPI.

Comparison of Remote Sensing Image Processing Techniques to Identify Tornado Damage Areas from Landsat TM Data

PubMed Central

Myint, Soe W.; Yuan, May; Cerveny, Randall S.; Giri, Chandra P.

2008-01-01

Remote sensing techniques have been shown effective for large-scale damage surveys after a hazardous event in both near real-time or post-event analyses. The paper aims to compare accuracy of common imaging processing techniques to detect tornado damage tracks from Landsat TM data. We employed the direct change detection approach using two sets of images acquired before and after the tornado event to produce a principal component composite images and a set of image difference bands. Techniques in the comparison include supervised classification, unsupervised classification, and object-oriented classification approach with a nearest neighbor classifier. Accuracy assessment is based on Kappa coefficient calculated from error matrices which cross tabulate correctly identified cells on the TM image and commission and omission errors in the result. Overall, the Object-oriented Approach exhibits the highest degree of accuracy in tornado damage detection. PCA and Image Differencing methods show comparable outcomes. While selected PCs can improve detection accuracy 5 to 10%, the Object-oriented Approach performs significantly better with 15-20% higher accuracy than the other two techniques. PMID:27879757

Towards a Theoretical Framework for the Use of ICT Strategies for Teaching Practicum Supervision

ERIC Educational Resources Information Center

Mabunda, P. L.

2013-01-01

Teaching Practice is a core component of pre-service or initial teacher education programmes worldwide. The requirements set by the South African Committee on Higher Education effected changes to the coordination and supervision of Teaching Practice. The purpose of this conceptual study was to review and gain insight into the use of various…

77 FR 21603 - Self-Regulatory Organizations; NASDAQ OMX BX, Inc.; Notice of Filing of Proposed Rule Change...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-10

... monitoring of proprietary trading, market-making or brokerage activities and/or that is engaged in the supervision or training of those engaged in proprietary trading, market-making or brokerage activities will be... behalf of a broker-dealer account, supervises or monitors proprietary trading, market-making or brokerage...

A Bourdieusian Perspective on Becoming and Being a Postgraduate Supervisor: The Role of Capital

ERIC Educational Resources Information Center

Maritz, Jeanette; Prinsloo, Paul

2015-01-01

The objective of this paper is to map the role of capital in the process of learning to become a postgraduate supervisor. Economic, technological and geopolitical changes in higher education call into question previous assumptions about supervision. Supervision is no longer primarily seen as an intellectual and social enterprise but is…

Using Insider Research in MEd Final Projects to Bridge the Theory/Practice Gap

ERIC Educational Resources Information Center

Arar, Khalid

2018-01-01

This paper aims to identify key issues involved in MEd final project supervision and to highlight the potential of supervision from an academic institution to change educational reality through the postgraduate student-teachers' work-based final project as insider researchers in Israeli schools. It draws on analysis of case-study data from two…

An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

PubMed

Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

2017-08-01

Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

PubMed

Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

2017-05-01

This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

Nondestructive detection of chilling injury in cucumber fruit using hyperspectral imaging with feature selection and supervised classification

USDA-ARS?s Scientific Manuscript database

Chilling injury, as a physiological disorder in cucumbers, occurs after the fruit has been subjected to low temperatures. It is thus desirable to detect chilling injury at early stages and/or remove chilling injured cucumbers during sorting and grading. This research was aimed to apply hyperspectral...

Detection and Evaluation of Cheating on College Exams Using Supervised Classification

ERIC Educational Resources Information Center

Cavalcanti, Elmano Ramalho; Pires, Carlos Eduardo; Cavalcanti, Elmano Pontes; Pires, Vládia Freire

2012-01-01

Text mining has been used for various purposes, such as document classification and extraction of domain-specific information from text. In this paper we present a study in which text mining methodology and algorithms were properly employed for academic dishonesty (cheating) detection and evaluation on open-ended college exams, based on document…

12 CFR 571.90 - Duties regarding the detection, prevention, and mitigation of identity theft.

Code of Federal Regulations, 2011 CFR

2011-01-01

... mitigation of identity theft. 571.90 Section 571.90 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FAIR CREDIT REPORTING Identity Theft Red Flags § 571.90 Duties regarding the detection, prevention, and mitigation of identity theft. (a) Scope. This section applies to a financial...

12 CFR 571.90 - Duties regarding the detection, prevention, and mitigation of identity theft.

Code of Federal Regulations, 2013 CFR

2013-01-01

... mitigation of identity theft. 571.90 Section 571.90 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FAIR CREDIT REPORTING Identity Theft Red Flags § 571.90 Duties regarding the detection, prevention, and mitigation of identity theft. (a) Scope. This section applies to a financial...

12 CFR 571.90 - Duties regarding the detection, prevention, and mitigation of identity theft.

Code of Federal Regulations, 2014 CFR

2014-01-01

... mitigation of identity theft. 571.90 Section 571.90 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FAIR CREDIT REPORTING Identity Theft Red Flags § 571.90 Duties regarding the detection, prevention, and mitigation of identity theft. (a) Scope. This section applies to a financial...

12 CFR 571.90 - Duties regarding the detection, prevention, and mitigation of identity theft.

Code of Federal Regulations, 2012 CFR

2012-01-01

... mitigation of identity theft. 571.90 Section 571.90 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FAIR CREDIT REPORTING Identity Theft Red Flags § 571.90 Duties regarding the detection, prevention, and mitigation of identity theft. (a) Scope. This section applies to a financial...

Automated detection of microaneurysms using scale-adapted blob analysis and semi-supervised learning.

PubMed

Adal, Kedir M; Sidibé, Désiré; Ali, Sharib; Chaum, Edward; Karnowski, Thomas P; Mériaudeau, Fabrice

2014-04-01

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 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 which can detect true MAs. The developed system is built using only 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. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Time-of-flight-assisted Kinect camera-based people detection for intuitive human robot cooperation in the surgical operating room.

PubMed

Beyl, Tim; Nicolai, Philip; Comparetti, Mirko D; Raczkowsky, Jörg; De Momi, Elena; Wörn, Heinz

2016-07-01

Scene supervision is a major tool to make medical robots safer and more intuitive. The paper shows an approach to efficiently use 3D cameras within the surgical operating room to enable for safe human robot interaction and action perception. Additionally the presented approach aims to make 3D camera-based scene supervision more reliable and accurate. A camera system composed of multiple Kinect and time-of-flight cameras has been designed, implemented and calibrated. Calibration and object detection as well as people tracking methods have been designed and evaluated. The camera system shows a good registration accuracy of 0.05 m. The tracking of humans is reliable and accurate and has been evaluated in an experimental setup using operating clothing. The robot detection shows an error of around 0.04 m. The robustness and accuracy of the approach allow for an integration into modern operating room. The data output can be used directly for situation and workflow detection as well as collision avoidance.

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.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data.

PubMed

Song, Hongchao; Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k -nearest neighbor graphs- ( K -NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

PubMed Central

Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k-nearest neighbor graphs- (K-NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity. PMID:29270197

Exploring supervised and unsupervised methods to detect topics in biomedical text

PubMed Central

Lee, Minsuk; Wang, Weiqing; Yu, Hong

2006-01-01

Background Topic detection is a task that automatically identifies topics (e.g., "biochemistry" and "protein structure") in scientific articles based on information content. Topic detection will benefit many other natural language processing tasks including information retrieval, text summarization and question answering; and is a necessary step towards the building of an information system that provides an efficient way for biologists to seek information from an ocean of literature. Results We have explored the methods of Topic Spotting, a task of text categorization that applies the supervised machine-learning technique naïve Bayes to assign automatically a document into one or more predefined topics; and Topic Clustering, which apply unsupervised hierarchical clustering algorithms to aggregate documents into clusters such that each cluster represents a topic. We have applied our methods to detect topics of more than fifteen thousand of articles that represent over sixteen thousand entries in the Online Mendelian Inheritance in Man (OMIM) database. We have explored bag of words as the features. Additionally, we have explored semantic features; namely, the Medical Subject Headings (MeSH) that are assigned to the MEDLINE records, and the Unified Medical Language System (UMLS) semantic types that correspond to the MeSH terms, in addition to bag of words, to facilitate the tasks of topic detection. Our results indicate that incorporating the MeSH terms and the UMLS semantic types as additional features enhances the performance of topic detection and the naïve Bayes has the highest accuracy, 66.4%, for predicting the topic of an OMIM article as one of the total twenty-five topics. Conclusion Our results indicate that the supervised topic spotting methods outperformed the unsupervised topic clustering; on the other hand, the unsupervised topic clustering methods have the advantages of being robust and applicable in real world settings. PMID:16539745

Videosensor for the Detection of Unsafe Driving Behavior in the Proximity of Black Spots

PubMed Central

Fuentes, Andres; Fuentes, Ricardo; Cabello, Enrique; Conde, Cristina; Martin, Isaac

2014-01-01

This paper discusses the overall design and implementation of a video sensor for the detection of risky behaviors of car drivers near previously identified and georeferenced black spots. The main goal is to provide the driver with a visual audio alert that informs of the proximity of an area of high incidence of highway accidents only if their driving behavior could result in a risky situation. It proposes a video sensor for detecting and supervising driver behavior, its main objective being manual distractions, so hand driver supervision is performed. A GPS signal is also considered, the GPS information is compared with a database of global positioning Black Spots to determine the relative proximity of a risky area. The outputs of the video sensor and GPS sensor are combined to evaluate a possible risky behavior. The results are promising in terms of risk analysis in order to be validated for use in the context of the automotive industry as future work. PMID:25347580

Videosensor for the detection of unsafe driving behavior in the proximity of black spots.

PubMed

Fuentes, Andres; Fuentes, Ricardo; Cabello, Enrique; Conde, Cristina; Martin, Isaac

2014-10-24

This paper discusses the overall design and implementation of a video sensor for the detection of risky behaviors of car drivers near previously identified and georeferenced black spots. The main goal is to provide the driver with a visual audio alert that informs of the proximity of an area of high incidence of highway accidents only if their driving behavior could result in a risky situation. It proposes a video sensor for detecting and supervising driver behavior, its main objective being manual distractions, so hand driver supervision is performed. A GPS signal is also considered, the GPS information is compared with a database of global positioning Black Spots to determine the relative proximity of a risky area. The outputs of the video sensor and GPS sensor are combined to evaluate a possible risky behavior. The results are promising in terms of risk analysis in order to be validated for use in the context of the automotive industry as future work.

Biophysical control of intertidal benthic macroalgae revealed by high-frequency multispectral camera images

NASA Astrophysics Data System (ADS)

van der Wal, Daphne; van Dalen, Jeroen; Wielemaker-van den Dool, Annette; Dijkstra, Jasper T.; Ysebaert, Tom

2014-07-01

Intertidal benthic macroalgae are a biological quality indicator in estuaries and coasts. While remote sensing has been applied to quantify the spatial distribution of such macroalgae, it is generally not used for their monitoring. We examined the day-to-day and seasonal dynamics of macroalgal cover on a sandy intertidal flat using visible and near-infrared images from a time-lapse camera mounted on a tower. Benthic algae were identified using supervised, semi-supervised and unsupervised classification techniques, validated with monthly ground-truthing over one year. A supervised classification (based on maximum likelihood, using training areas identified in the field) performed best in discriminating between sediment, benthic diatom films and macroalgae, with highest spectral separability between macroalgae and diatoms in spring/summer. An automated unsupervised classification (based on the Normalised Differential Vegetation Index NDVI) allowed detection of daily changes in macroalgal coverage without the need for calibration. This method showed a bloom of macroalgae (filamentous green algae, Ulva sp.) in summer with > 60% cover, but with pronounced superimposed day-to-day variation in cover. Waves were a major factor in regulating macroalgal cover, but regrowth of the thalli after a summer storm was fast (2 weeks). Images and in situ data demonstrated that the protruding tubes of the polychaete Lanice conchilega facilitated both settlement (anchorage) and survival (resistance to waves) of the macroalgae. Thus, high-frequency, high resolution images revealed the mechanisms for regulating the dynamics in cover of the macroalgae and for their spatial structuring. Ramifications for the mode, timing, frequency and evaluation of monitoring macroalgae by field and remote sensing surveys are discussed.

PhD Students' Experiences of Thesis Supervision in Malaysia: Managing Relationships in the Midst of Institutional Change

ERIC Educational Resources Information Center

Krauss, Steven Eric; Ismail, Ismi Arif

2010-01-01

Despite the plethora of studies that have been conducted on PhD supervision, little qualitative investigation has been conducted with a diverse, non-Western sample of doctoral students in an attempt to understand how the supervisory relationship is experienced. In response, eighteen students from diverse, non-Western backgrounds studying at one…

Seeing Is Believing: Innovating the Clinical Practice Experience for Education Specialist Teacher Candidates with Video-Based Remote Supervision

ERIC Educational Resources Information Center

Van Boxtel, Joanne M.

2017-01-01

A call to implement 21st-century change drivers within teacher preparation is evidenced within policy and research. The use of technology-enhanced methods of supervision where virtual observations of pre-service or in-service teachers are performed by university supervisors or mentors has an established and growing research base that demonstrates…

Changing the Response of Vocational Students to Supervision: The Use of Motion Pictures and Group Discussion. Final Report. Research Series No. 44.

ERIC Educational Resources Information Center

Stogdill, Ralph M.; Bailey, Walter R.

This study was designed to determine whether viewing and discussing five movies, each depicting a different pattern of supervisory behavior, would enable maladjusted students to react more favorably to supervision. Patterns of behavior were: (1) consideration of employees, (2) structuring expectations, (3) tolerance of freedom of action, (4)…

On supervised graph Laplacian embedding CA model & kernel construction and its application

NASA Astrophysics Data System (ADS)

Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

2017-01-01

There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

Weakly supervised image semantic segmentation based on clustering superpixels

NASA Astrophysics Data System (ADS)

Yan, Xiong; Liu, Xiaohua

2018-04-01

In this paper, we propose an image semantic segmentation model which is trained from image-level labeled images. The proposed model starts with superpixel segmenting, and features of the superpixels are extracted by trained CNN. We introduce a superpixel-based graph followed by applying the graph partition method to group correlated superpixels into clusters. For the acquisition of inter-label correlations between the image-level labels in dataset, we not only utilize label co-occurrence statistics but also exploit visual contextual cues simultaneously. At last, we formulate the task of mapping appropriate image-level labels to the detected clusters as a problem of convex minimization. Experimental results on MSRC-21 dataset and LableMe dataset show that the proposed method has a better performance than most of the weakly supervised methods and is even comparable to fully supervised methods.

Dissociation between exercise-induced reduction in liver fat and changes in hepatic and peripheral glucose homoeostasis in obese patients with non-alcoholic fatty liver disease.

PubMed

Cuthbertson, Daniel J; Shojaee-Moradie, Fariba; Sprung, Victoria S; Jones, Helen; Pugh, Christopher J A; Richardson, Paul; Kemp, Graham J; Barrett, Mark; Jackson, Nicola C; Thomas, E Louise; Bell, Jimmy D; Umpleby, A Margot

2016-01-01

Non-alcoholic fatty liver disease (NAFLD) is associated with multi-organ (hepatic, skeletal muscle, adipose tissue) insulin resistance (IR). Exercise is an effective treatment for lowering liver fat but its effect on IR in NAFLD is unknown. We aimed to determine whether supervised exercise in NAFLD would reduce liver fat and improve hepatic and peripheral (skeletal muscle and adipose tissue) insulin sensitivity. Sixty nine NAFLD patients were randomized to 16 weeks exercise supervision (n=38) or counselling (n=31) without dietary modification. All participants underwent MRI/spectroscopy to assess changes in body fat and in liver and skeletal muscle triglyceride, before and following exercise/counselling. To quantify changes in hepatic and peripheral insulin sensitivity, a pre-determined subset (n=12 per group) underwent a two-stage hyperinsulinaemic euglycaemic clamp pre- and post-intervention. Results are shown as mean [95% confidence interval (CI)]. Fifty participants (30 exercise, 20 counselling), 51 years (IQR 40, 56), body mass index (BMI) 31 kg/m(2) (IQR 29, 35) with baseline liver fat/water % of 18.8% (IQR 10.7, 34.6) completed the study (12/12 exercise and 7/12 counselling completed the clamp studies). Supervised exercise mediated a greater reduction in liver fat/water percentage than counselling [Δ mean change 4.7% (0.01, 9.4); P<0.05], which correlated with the change in cardiorespiratory fitness (r=-0.34, P=0.0173). With exercise, peripheral insulin sensitivity significantly increased (following high-dose insulin) despite no significant change in hepatic glucose production (HGP; following low-dose insulin); no changes were observed in the control group. Although supervised exercise effectively reduced liver fat, improving peripheral IR in NAFLD, the reduction in liver fat was insufficient to improve hepatic IR. © 2016 Authors; published by Portland Press Limited.

Improving the Efficiency and Effectiveness of Community Detection via Prior-Induced Equivalent Super-Network.

PubMed

Yang, Liang; Jin, Di; He, Dongxiao; Fu, Huazhu; Cao, Xiaochun; Fogelman-Soulie, Francoise

2017-03-29

Due to the importance of community structure in understanding network and a surge of interest aroused on community detectability, how to improve the community identification performance with pairwise prior information becomes a hot topic. However, most existing semi-supervised community detection algorithms only focus on improving the accuracy but ignore the impacts of priors on speeding detection. Besides, they always require to tune additional parameters and cannot guarantee pairwise constraints. To address these drawbacks, we propose a general, high-speed, effective and parameter-free semi-supervised community detection framework. By constructing the indivisible super-nodes according to the connected subgraph of the must-link constraints and by forming the weighted super-edge based on network topology and cannot-link constraints, our new framework transforms the original network into an equivalent but much smaller Super-Network. Super-Network perfectly ensures the must-link constraints and effectively encodes cannot-link constraints. Furthermore, the time complexity of super-network construction process is linear in the original network size, which makes it efficient. Meanwhile, since the constructed super-network is much smaller than the original one, any existing community detection algorithm is much faster when using our framework. Besides, the overall process will not introduce any additional parameters, making it more practical.

Satellite monitoring of vegetation and geology in semi-arid environments. [Tanzania

NASA Technical Reports Server (NTRS)

Kihlblom, U.; Johansson, D. (Principal Investigator)

1980-01-01

The possibility of mapping various characteristics of the natural environment of Tanzania by various LANDSAT techniques was assessed. Interpretation and mapping were carried out using black and white as well as color infrared images on the scale of 1:250,000. The advantages of several computer techniques were also assessed, including contrast-stretched rationing, differential edge enhancement; supervised classification; multitemporal classification; and change detection. Results Show the most useful image for interpretation comes from band 5, with additional information being obtained from either band 6 or band 7. The advantages of using color infrared images for interpreting vegetation and geology are so great that black and white should be used only to supplement the colored images.

Network Supervision of Adult Experience and Learning Dependent Sensory Cortical Plasticity.

PubMed

Blake, David T

2017-06-18

The brain is capable of remodeling throughout life. The sensory cortices provide a useful preparation for studying neuroplasticity both during development and thereafter. In adulthood, sensory cortices change in the cortical area activated by behaviorally relevant stimuli, by the strength of response within that activated area, and by the temporal profiles of those responses. Evidence supports forms of unsupervised, reinforcement, and fully supervised network learning rules. Studies on experience-dependent plasticity have mostly not controlled for learning, and they find support for unsupervised learning mechanisms. Changes occur with greatest ease in neurons containing α-CamKII, which are pyramidal neurons in layers II/III and layers V/VI. These changes use synaptic mechanisms including long term depression. Synaptic strengthening at NMDA-containing synapses does occur, but its weak association with activity suggests other factors also initiate changes. Studies that control learning find support of reinforcement learning rules and limited evidence of other forms of supervised learning. Behaviorally associating a stimulus with reinforcement leads to a strengthening of cortical response strength and enlarging of response area with poor selectivity. Associating a stimulus with omission of reinforcement leads to a selective weakening of responses. In some preparations in which these associations are not as clearly made, neurons with the most informative discharges are relatively stronger after training. Studies analyzing the temporal profile of responses associated with omission of reward, or of plasticity in studies with different discriminanda but statistically matched stimuli, support the existence of limited supervised network learning. © 2017 American Physiological Society. Compr Physiol 7:977-1008, 2017. Copyright © 2017 John Wiley & Sons, Inc.

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

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

Jiang, S; Dolly, S; Cai, B

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deepmore » modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.« less

Training Substance Abuse Clinicians in Motivational Interviewing Using Live Supervision via Tele-conferencing

PubMed Central

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

Nurse managers' conceptions of quality management as promoted by peer supervision.

PubMed

Hyrkäs, Kristiina; Koivula, Meeri; Lehti, Kristiina; Paunonen-Ilmonen, Marita

2003-01-01

The aim of the study was to describe nurse managers' conceptions of quality management in their work as promoted by peer supervision. Quality management is one of the topical issues in a nurse manager's demanding and changing work. As first-line managers, they have a key role in quality management which is seen to create the system and environment for high quality services and quality improvement. Despite the official recommendations and definitions of quality management, several published reports have shown that there is no single solution for quality management. Peer supervision or the support provided by it to nursing managers have rarely been a subject of study. This study was carried out at Tampere University Hospital between 1996 and 1998. The peer supervision intervention was organized once a month, 2 hours at a time and in closed supervisor-led groups of nine nurse managers. Data were collected by themed interviews. Fifteen nurse managers participated in the study. The data were analysed using the phenomenographic method. Two main categories were formed of nurse managers' conceptions. The first described supportive and reflective characteristics of peer supervision. This main category was described by horizontal, hierarchical categories of support from peer group and reflection. The second main category described nurse managers' conceptions of individual development of leadership during peer supervision. This main category was also described by three horizontal categories: personal growth, finding psychological resources and internalization of leadership. The finding of this study show that peer supervision benefited nurse managers in quality management through reflection and support. The reflective and supportive characteristics of peer supervision promoted the nurse managers' individual development, but also that of leadership. It can be concluded that peer supervision promotes quality management in nurse managers' work.

Group supervision for healthcare professionals within primary care for patients with psychosomatic health problems: a pilot intervention study.

PubMed

Bullington, Jennifer; Cronqvist, Agneta

2018-03-01

In primary health care, efficacious treatment strategies are lacking for these patients, although the most prominent symptoms accounting for consultation in primary care often cannot be related to any biological causes. The aim was to explore whether group supervision from a specific phenomenological theory of psychosomatics could provide healthcare professionals treating patients with psychosomatic health issues within primary care a deeper understanding of these conditions and stimulate profession-specific treatment strategies. Our research questions were as follows: (i) What is the healthcare professionals' understanding of psychosomatics before and after the intervention? (ii) What are the treatment strategies for this group of patients before and after the intervention? The study was an explorative qualitative intervention pilot study. The six participants from a primary healthcare setting in a medium-sized city in Sweden participated in the study. A supervision group was formed, based on a mix of professions, age, gender and years of clinical experience. Supervision consisted of one 75-minutes meeting every month during the course of 6 months. Participants were interviewed before and after the supervision intervention. The study showed two distinct categories emerged from the data. One category of healthcare professionals espoused a psycho-educative approach, while the other lacked a cohesive approach. The supervision improved the second category of healthcare professionals' understanding of psychosomatics. The psycho-educative group did not change their understanding of psychosomatics, although they felt strengthened in their approach by the supervision. Profession-specific strategies were not developed. This pilot study indicates that a relatively short supervision intervention can aid clinicians in their clinical encounters with these patients; however, further research is necessary to ascertain the value of the specific phenomenologically based supervision intervention. © 2017 Nordic College of Caring Science.

[The Quality Analysis of National Supervising Sampling for Rubella Virus IgM Diagnostic Kits in 2014].

PubMed

Yu, Tina; Qu, Shoufang; Zhang, Xiaoyan; Sun, Nan; Gao, Shangxian; Li, Haining; Huang, Jie

2015-07-01

To evaluate the quality status of rubella virus IgM diagnostic kits by national supervising sampling. Using legal inspection combining with exploratory study, the positive and negative coincidence rate, detection limit and repeatability of kits were verified. The results showed that 15 of 16 batches of kits were qualified using legal inspection, and the passing rate was 93.8%. The unqualified item was negative coincidence rate. In exploratory study, only 11 batches (68.8%) complied with industry standard. The unqualified items were negative coincidence rate, detection limit and repeatability. At present, rubella virus IgM diagnostic Kits have some quality problems in the market. It is recommended that we adopt industry standard and national reference panel in the registration inspection for the future, which will prompt enterprises to improve quality.

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

PubMed Central

Goerner-Potvin, Patricia; Morin, Andreanne; Shao, Xiaojian; Pastinen, Tomi

2017-01-01

Motivation: Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose a supervised machine learning approach for ChIP-seq data analysis, using labels that encode qualitative judgments about which genomic regions contain or do not contain peaks. The main idea is to manually label a small subset of the genome, and then learn a model that makes consistent peak predictions on the rest of the genome. Results: We created 7 new histone mark datasets with 12 826 visually determined labels, and analyzed 3 existing transcription factor datasets. We observed that default peak detection parameters yield high false positive rates, which can be reduced by learning parameters using a relatively small training set of labeled data from the same experiment type. We also observed that labels from different people are highly consistent. Overall, these data indicate that our supervised labeling method is useful for quantitatively training and testing peak detection algorithms. Availability and Implementation: Labeled histone mark data http://cbio.ensmp.fr/~thocking/chip-seq-chunk-db/, R package to compute the label error of predicted peaks https://github.com/tdhock/PeakError Contacts: toby.hocking@mail.mcgill.ca or guil.bourque@mcgill.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27797775

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

PubMed

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

2017-02-15

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

Measurement of faculty anesthesiologists' quality of clinical supervision has greater reliability when controlling for the leniency of the rating anesthesia resident: a retrospective cohort study.

PubMed

Dexter, Franklin; Ledolter, Johannes; Hindman, Bradley J

2017-06-01

Our department monitors the quality of anesthesiologists' clinical supervision and provides each anesthesiologist with periodic feedback. We hypothesized that greater differentiation among anesthesiologists' supervision scores could be obtained by adjusting for leniency of the rating resident. From July 1, 2013 to December 31, 2015, our department has utilized the de Oliveira Filho unidimensional nine-item supervision scale to assess the quality of clinical supervision provided by faculty as rated by residents. We examined all 13,664 ratings of the 97 anesthesiologists (ratees) by the 65 residents (raters). Testing for internal consistency among answers to questions (large Cronbach's alpha > 0.90) was performed to rule out that one or two questions accounted for leniency. Mixed-effects logistic regression was used to compare ratees while controlling for rater leniency vs using Student t tests without rater leniency. The mean supervision scale score was calculated for each combination of the 65 raters and nine questions. The Cronbach's alpha was very large (0.977). The mean score was calculated for each of the 3,421 observed combinations of resident and anesthesiologist. The logits of the percentage of scores equal to the maximum value of 4.00 were normally distributed (residents, P = 0.24; anesthesiologists, P = 0.50). There were 20/97 anesthesiologists identified as significant outliers (13 with below average supervision scores and seven with better than average) using the mixed-effects logistic regression with rater leniency entered as a fixed effect but not by Student's t test. In contrast, there were three of 97 anesthesiologists identified as outliers (all three above average) using Student's t tests but not by logistic regression with leniency. The 20 vs 3 was significant (P < 0.001). Use of logistic regression with leniency results in greater detection of anesthesiologists with significantly better (or worse) clinical supervision scores than use of Student's t tests (i.e., without adjustment for rater leniency).

Investigating the Potential Contribution of Patient Rating Sites to Hospital Supervision: Exploratory Results From an Interview Study in the Netherlands.

PubMed

Kleefstra, Sophia Martine; Zandbelt, Linda C; Borghans, Ine; de Haes, Hanneke J C J M; Kool, Rudolf B

2016-07-20

Over the last decades, the patient perspective on health care quality has been unconditionally integrated into quality management. For several years now, patient rating sites have been rapidly gaining attention. These offer a new approach toward hearing the patient's perspective on the quality of health care. The aim of our study was to explore whether and how patient reviews of hospitals, as reported on rating sites, have the potential to contribute to health care inspector's daily supervision of hospital care. Given the unexplored nature of the topic, an interview study among hospital inspectors was designed in the Netherlands. We performed 2 rounds of interviews with 10 senior inspectors, addressing their use and their judgment on the relevance of review data from a rating site. All 10 Dutch senior hospital inspectors participated in this research. The inspectors initially showed some reluctance to use the major patient rating site in their daily supervision. This was mainly because of objections such as worries about how representative they are, subjectivity, and doubts about the relevance of patient reviews for supervision. However, confrontation with, and assessment of, negative reviews by the inspectors resulted in 23% of the reviews being deemed relevant for risk identification. Most inspectors were cautiously positive about the contribution of the reviews to their risk identification. Patient rating sites may be of value to the risk-based supervision of hospital care carried out by the Health Care Inspectorate. Health care inspectors do have several objections against the use of patient rating sites for daily supervision. However, when they are presented with texts of negative reviews from a hospital under their supervision, it appears that most inspectors consider it as an additional source of information to detect poor quality of care. Still, it should always be accompanied and verified by other quality and safety indicators. More research on the value and usability of patient rating sites in daily hospital supervision and other health settings is needed.

Genetic Classification of Populations Using Supervised Learning

PubMed Central

Bridges, Michael; Heron, Elizabeth A.; O'Dushlaine, Colm; Segurado, Ricardo; Morris, Derek; Corvin, Aiden; Gill, Michael; Pinto, Carlos

2011-01-01

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case–control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed unsupervised. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available. In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies. PMID:21589856

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones †

PubMed Central

Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E

2016-01-01

As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy. PMID:27556461

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones.

PubMed

Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E

2016-08-20

As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user's daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy.

Developing Discourses of Knowledge and Understanding: Longitudinal Studies of Ph.D. Supervision

ERIC Educational Resources Information Center

Kandiko, Camille B.; Kinchin, Ian M.

2013-01-01

Competing notions of what a Ph.D. has been, is and should be are undercurrents in doctoral education. A longitudinal study of Ph.D. supervision based on interviews and concept mapping was used to surface understandings of the purpose of a Ph.D. This research tracks change over time for both the student and the supervisor. The data were analysed…

The Changing Nature of the Role of the University Supervisor and Function of Preservice Teacher Supervision in an Era of Clinically-Rich Practice

ERIC Educational Resources Information Center

Burns, Rebecca West; Jacobs, Jennifer; Yendol-Hoppey, Diane

2016-01-01

Given the movement to enhanced clinical experiences and school-university collaboration emphasized in the NCATE Blue Ribbon Report, the field of teacher preparation would benefit from an understanding of the research related to preservice teacher (PST) supervision. This article uses qualitative meta-analysis to generate new knowledge about PST…

Supporting self and others: from staff nurse to nurse consultant. Part 5: clinical supervision.

PubMed

Fowler, John

This series of articles explores various ways of supporting staff who work in the fast-moving and ever-changing health service. In previous articles, John Fowler an experienced nursing lecturer, author and consultant examined the importance of developing a supportive working culture and the role of preceptorship and mentoring. This article examines the use of clinical supervision within nursing.

A rapid detection method for policy-sensitive amines real-time supervision.

PubMed

Zhang, Haixu; Shu, Jinian; Yang, Bo; Zhang, Peng; Ma, Pengkun

2018-02-01

Many organic amines that comprise a benzene ring are policy-sensitive because of their toxicity and links to social harm. However, to date, detection of such compounds mainly relies on offline methods. This study proposes an online pptv (parts per trillion by volume) level of detection method for amines, using the recently-built vacuum ultraviolet photoionization mass spectrometer (VUV-PIMS) combined with a new doping technique. Thus, the dichloromethane doping-assisted photoionization mass spectra of aniline, benzylamine, phenethylamine, amphetamine, and their structural isomers were recorded. The dominant characteristic mass peaks for all amines are those afforded by protonated amines and the amino radical-loss. The signal intensities of the amines were enhanced by 60-130 times compared to those recorded without doping assistance. Under 10s detection time, the sensitivities of aniline and benzylamine in the gas phase were determined as 4.0 and 2.7 countspptv -1 , with limits of detection (LODs) of 36 and 22 pptv, respectively. Notably, the detection efficiency of this method can be tenfold better in future applications since the ion transmission efficiency of the mass spectrometer was intentionally reduced to ~ 10% in this study. Therefore, dichloromethane doping-assisted photoionization mass spectrometry has proven to be a highly promising on-line approach to amine detection in environmental and judicial supervision and shows great potential for application in the biological field. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical supervision of allied health professionals in country South Australia: A mixed methods pilot study.

PubMed

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.

Enforcer, manager or leader? The judicial role in family violence courts.

PubMed

King, Michael; Batagol, Becky

2010-01-01

Judicial supervision of offenders is an important component of many family violence courts. Skepticism concerning the ability of offenders to reform and a desire to protect victims has led to some judges to use supervision as a form of deterrence. Supervision is also used to hold offenders accountable for following court orders. Some family violence courts apply processes used in drug courts, such as rewards and sanctions, to promote offender rehabilitation. This article suggests that while protection and support of victims should be the prime concern of family violence courts, a form of judging that engages offenders in the development and implementation of solutions for their problems and supports their implementation is more likely to promote their positive behavioral change than other approaches to judicial supervision. The approach to judging proposed in this article draws from therapeutic jurisprudence, feminist theory, transformational leadership and solution-focused brief therapy principles. Copyright © 2010 Elsevier Ltd. All rights reserved.

Automated attribution of remotely-sensed ecological disturbances using spatial and temporal characteristics of common disturbance classes.

NASA Astrophysics Data System (ADS)

Cooper, L. A.; Ballantyne, A.

2017-12-01

Forest disturbances are critical components of ecosystems. Knowledge of their prevalence and impacts is necessary to accurately describe forest health and ecosystem services through time. While there are currently several methods available to identify and describe forest disturbances, especially those which occur in North America, the process remains inefficient and inaccessible in many parts of the world. Here, we introduce a preliminary approach to streamline and automate both the detection and attribution of forest disturbances. We use a combination of the Breaks for Additive Season and Trend (BFAST) detection algorithm to detect disturbances in combination with supervised and unsupervised classification algorithms to attribute the detections to disturbance classes. Both spatial and temporal disturbance characteristics are derived and utilized for the goal of automating the disturbance attribution process. The resulting preliminary algorithm is applied to up-scaled (100m) Landsat data for several different ecosystems in North America, with varying success. Our results indicate that supervised classification is more reliable than unsupervised classification, but that limited training data are required for a region. Future work will improve the algorithm through refining and validating at sites within North America before applying this approach globally.

Comparing experts and novices in Martian surface feature change detection and identification

NASA Astrophysics Data System (ADS)

Wardlaw, Jessica; Sprinks, James; Houghton, Robert; Muller, Jan-Peter; Sidiropoulos, Panagiotis; Bamford, Steven; Marsh, Stuart

2018-02-01

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided ;expert; data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who want to use crowd-sourcing for similar scientific purposes, particularly for the supervised training of computer algorithms, and inform the scope and design of future projects.

Blinking supervision in a working environment

NASA Astrophysics Data System (ADS)

Morcego, Bernardo; Argilés, Marc; Cabrerizo, Marc; Cardona, Genís; Pérez, Ramon; Pérez-Cabré, Elisabet; Gispets, Joan

2016-02-01

The health of the ocular surface requires blinks of the eye to be frequent in order to provide moisture and to renew the tear film. However, blinking frequency has been shown to decrease in certain conditions such as when subjects are conducting tasks with high cognitive and visual demands. These conditions are becoming more common as people work or spend their leisure time in front of video display terminals. Supervision of blinking frequency in such environments is possible, thanks to the availability of computer-integrated cameras. Therefore, the aim of the present study is to develop an algorithm for the detection of eye blinks and to test it, in a number of videos captured, while subjects are conducting a variety of tasks in front of the computer. The sensitivity of the algorithm for blink detection was found to be of 87.54% (range 30% to 100%), with a mean false-positive rate of 0.19% (range 0% to 1.7%), depending on the illumination conditions during which the image was captured and other computer-user spatial configurations. The current automatic process is based on a partly modified pre-existing eye detection and image processing algorithms and consists of four stages that are aimed at eye detection, eye tracking, iris detection and segmentation, and iris height/width ratio assessment.

Internet and video technology in psychotherapy supervision and training.

PubMed

Wolf, Abraham W

2011-06-01

The seven articles in this special section on the use of Internet and video technology represent the latest growth on one branch of the increasingly prolific and differentiated work in the technology of psychotherapy. In addition to the work presented here on video and the Internet applications to supervision and training, information technology is changing the field of psychotherapy through computer assisted therapies and virtual reality interventions.

[Study on the optimization of monitoring indicators of drinking water quality during health supervision].

PubMed

Ye, Bixiong; E, Xueli; Zhang, Lan

2015-01-01

To optimize non-regular drinking water quality indices (except Giardia and Cryptosporidium) of urban drinking water. Several methods including drinking water quality exceed the standard, the risk of exceeding standard, the frequency of detecting concentrations below the detection limit, water quality comprehensive index evaluation method, and attribute reduction algorithm of rough set theory were applied, redundancy factor of water quality indicators were eliminated, control factors that play a leading role in drinking water safety were found. Optimization results showed in 62 unconventional water quality monitoring indicators of urban drinking water, 42 water quality indicators could be optimized reduction by comprehensively evaluation combined with attribute reduction of rough set. Optimization of the water quality monitoring indicators and reduction of monitoring indicators and monitoring frequency could ensure the safety of drinking water quality while lowering monitoring costs and reducing monitoring pressure of the sanitation supervision departments.

Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media

PubMed Central

Yazdavar, Amir Hossein; Al-Olimat, Hussein S.; Ebrahimi, Monireh; Bajaj, Goonmeet; Banerjee, Tanvi; Thirunarayan, Krishnaprasad; Pathak, Jyotishman; Sheth, Amit

2017-01-01

With the rise of social media, millions of people are routinely expressing their moods, feelings, and daily struggles with mental health issues on social media platforms like Twitter. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of clinical depression from tweets obtained unobtrusively. Based on the analysis of tweets crawled from users with self-reported depressive symptoms in their Twitter profiles, we demonstrate the potential for detecting clinical depression symptoms which emulate the PHQ-9 questionnaire clinicians use today. Our study uses a semi-supervised statistical model to evaluate how the duration of these symptoms and their expression on Twitter (in terms of word usage patterns and topical preferences) align with the medical findings reported via the PHQ-9. Our proactive and automatic screening tool is able to identify clinical depressive symptoms with an accuracy of 68% and precision of 72%. PMID:29707701

Transfer of communication skills training from workshop to workplace: the impact of clinical supervision.

PubMed

Heaven, Cathy; Clegg, Jenny; Maguire, Peter

2006-03-01

Recent studies have recognised that the communication skills learned in the training environment are not always transferred back into the clinical setting. This paper reports a study which investigated the potential of clinical supervision in enhancing the transfer process. A randomised controlled trial was conducted involving 61 clinical nurse specialists. All attended a 3-day communication skills training workshop. Twenty-nine were then randomised to 4 weeks of clinical supervision, aimed at facilitating transfer of newly acquired skills into practice. Assessments, using real and simulated patients, were carried out before the course, immediately after the supervision period and 3 months later. Interviews were rated objectively using the Medical Interview Aural Rating Scale (MIARS) to assess nurses' ability to use key skills, respond to patient cues and identify patient concerns. Assessments with simulated patients showed that the training programme was extremely effective in changing competence in all three key areas. However, only those who experienced supervision showed any evidence of transfer. Improvements were found in the supervised groups' use of open questions, negotiation and psychological exploration. Whilst neither group facilitated more disclosure of cues or concerns, those in the experimental group responded more effectively to the cues disclosed, reduced their distancing behaviour and increasing their exploration of cues. The study has shown that whilst training enhances skills, without intervention, it may have little effect on clinical practice. The potential role of clinical supervision as one way of enhancing the clinical effectiveness of communication skills training programmes has been demonstrated. PRACTISE IMPLICATIONS: This study raises questions about the effectiveness of training programmes which do not incorporate a transfer element, and provides evidence to support the need for clinical supervision for clinical nurse specialist.

Supervision of care networks for frail community dwelling adults aged 75 years and older: protocol of a mixed methods study

PubMed Central

Verver, Didi; Merten, Hanneke; Robben, Paul; Wagner, Cordula

2015-01-01

Introduction The Dutch healthcare inspectorate (IGZ) supervises the quality and safety of healthcare in the Netherlands. Owing to the growing population of (community dwelling) older adults and changes in the Dutch healthcare system, the IGZ is exploring new methods to effectively supervise care networks that exist around frail older adults. The composition of these networks, where formal and informal care takes place, and the lack of guidelines and quality and risk indicators make supervision complicated in the current situation. Methods and analysis This study consists of four phases. The first phase identifies risks for community dwelling frail older adults in the existing literature. In the second phase, a qualitative pilot study will be conducted to assess the needs and wishes of the frail older adults concerning care and well-being, perception of risks, and the composition of their networks, collaboration and coordination between care providers involved in the network. In the third phase, questionnaires based on the results of phase II will be sent to a larger group of frail older adults (n=200) and their care providers. The results will describe the composition of their care networks and prioritise risks concerning community dwelling older adults. Also, it will provide input for the development of a new supervision framework by the IGZ. During phase IV, a second questionnaire will be sent to the participants of phase III to establish changes of perception in risks and possible changes in the care networks. The framework will be tested by the IGZ in pilots, and the researchers will evaluate these pilots and provide feedback to the IGZ. Ethics and dissemination The study protocol was approved by the Scientific Committee of the EMGO+institute and the Medical Ethical review committee of the VU University Medical Centre. Results will be presented in scientific articles and reports and at meetings. PMID:26307619

Investigation on changes in complex vegetation coverage using multi-temporal landsat data of Western Black Sea region--a case study.

PubMed

Coban, Huseyin Oguz; Koc, Ayhan; Eker, Mehmet

2010-01-01

Previous studies have been able to successfully detect changes in gently-sloping forested areas with low-diversity and homogeneous vegetation cover using medium-resolution satellite data such as landsat. The aim of the present study is to examine the capacity of multi-temporal landsat data to identify changes in forested areas with mixed vegetation and generally located on steep slopes or non-uniform topography landsat thematic mapper (TM) and landsat enhanced thematic mapperplus (ETM+) data for the years 1987-2000 was used to detect changes within a 19,500 ha forested area in the Western Black sea region of Turkey. The data comply with the forest cover type maps previously created for forest management plans of the research area. The methods used to detect changes were: post-classification comparison, image differencing, image rationing and NDVI (Normalized Difference Vegetation Index) differencing methods. Following the supervised classification process, error matrices were used to evaluate the accuracy of classified images obtained. The overall accuracy has been calculated as 87.59% for 1987 image and as 91.81% for 2000 image. General kappa statistics have been calculated as 0.8543 and 0.9038 for 1987 and 2000, respectively. The changes identified via the post-classification comparison method were compared with other change detetion methods. Maximum coherence was found to be 74.95% at 4/3 band rate. The NDVI difference and 3rd band difference methods achieved the same coherence with slight variations. The results suggest that landsat satellite data accurately conveys the temporal changes which occur on steeply-sloping forested areas with a mixed structure, providing a limited amount of detail but with a high level of accuracy. Moreover it has been decided that the post-classification comparison method can meet the needs of forestry activities better than other methods as it provides information about the direction of these changes.

Sensor fault detection and isolation via high-gain observers: application to a double-pipe heat exchanger.

PubMed

Escobar, R F; Astorga-Zaragoza, C M; Téllez-Anguiano, A C; Juárez-Romero, D; Hernández, J A; Guerrero-Ramírez, G V

2011-07-01

This paper deals with fault detection and isolation (FDI) in sensors applied to a concentric-pipe counter-flow heat exchanger. The proposed FDI is based on the analytical redundancy implementing nonlinear high-gain observers which are used to generate residuals when a sensor fault is presented (as software sensors). By evaluating the generated residual, it is possible to switch between the sensor and the observer when a failure is detected. Experiments in a heat exchanger pilot validate the effectiveness of the approach. The FDI technique is easy to implement allowing the industries to have an excellent alternative tool to keep their heat transfer process under supervision. The main contribution of this work is based on a dynamic model with heat transfer coefficients which depend on temperature and flow used to estimate the output temperatures of a heat exchanger. This model provides a satisfactory approximation of the states of the heat exchanger in order to allow its implementation in a FDI system used to perform supervision tasks. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Visualization techniques for computer network defense

NASA Astrophysics Data System (ADS)

Beaver, Justin M.; Steed, Chad A.; Patton, Robert M.; Cui, Xiaohui; Schultz, Matthew

2011-06-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operator to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.

Improving Non-Linear Approaches to Anomaly Detection, Class Separation, and Visualization

DTIC Science & Technology

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

Credit Card Fraud Detection: A Realistic Modeling and a Novel Learning Strategy.

PubMed

Dal Pozzolo, Andrea; Boracchi, Giacomo; Caelen, Olivier; Alippi, Cesare; Bontempi, Gianluca

2017-09-14

Detecting frauds in credit card transactions is perhaps one of the best testbeds for computational intelligence algorithms. In fact, this problem involves a number of relevant challenges, namely: concept drift (customers' habits evolve and fraudsters change their strategies over time), class imbalance (genuine transactions far outnumber frauds), and verification latency (only a small set of transactions are timely checked by investigators). However, the vast majority of learning algorithms that have been proposed for fraud detection rely on assumptions that hardly hold in a real-world fraud-detection system (FDS). This lack of realism concerns two main aspects: 1) the way and timing with which supervised information is provided and 2) the measures used to assess fraud-detection performance. This paper has three major contributions. First, we propose, with the help of our industrial partner, a formalization of the fraud-detection problem that realistically describes the operating conditions of FDSs that everyday analyze massive streams of credit card transactions. We also illustrate the most appropriate performance measures to be used for fraud-detection purposes. Second, we design and assess a novel learning strategy that effectively addresses class imbalance, concept drift, and verification latency. Third, in our experiments, we demonstrate the impact of class unbalance and concept drift in a real-world data stream containing more than 75 million transactions, authorized over a time window of three years.

Using Bi-Seasonal WorldView-2 Multi-Spectral Data and Supervised Random Forest Classification to Map Coastal Plant Communities in Everglades National Park.

PubMed

Wendelberger, Kristie S; Gann, Daniel; Richards, Jennifer H

2018-03-09

Coastal plant communities are being transformed or lost because of sea level rise (SLR) and land-use change. In conjunction with SLR, the Florida Everglades ecosystem has undergone large-scale drainage and restoration, altering coastal vegetation throughout south Florida. To understand how coastal plant communities are changing over time, accurate mapping techniques are needed that can define plant communities at a fine-enough resolution to detect fine-scale changes. We explored using bi-seasonal versus single-season WorldView-2 satellite data to map three mangrove and four adjacent plant communities, including the buttonwood/glycophyte community that harbors the federally-endangered plant Chromolaena frustrata . Bi-seasonal data were more effective than single-season to differentiate all communities of interest. Bi-seasonal data combined with Light Detection and Ranging (LiDAR) elevation data were used to map coastal plant communities of a coastal stretch within Everglades National Park (ENP). Overall map accuracy was 86%. Black and red mangroves were the dominant communities and covered 50% of the study site. All the remaining communities had ≤10% cover, including the buttonwood/glycophyte community. ENP harbors 21 rare coastal species threatened by SLR. The spatially explicit, quantitative data provided by our map provides a fine-scale baseline for monitoring future change in these species' habitats. Our results also offer a method to monitor vegetation change in other threatened habitats.

Using Bi-Seasonal WorldView-2 Multi-Spectral Data and Supervised Random Forest Classification to Map Coastal Plant Communities in Everglades National Park

PubMed Central

Richards, Jennifer H.

2018-01-01

Coastal plant communities are being transformed or lost because of sea level rise (SLR) and land-use change. In conjunction with SLR, the Florida Everglades ecosystem has undergone large-scale drainage and restoration, altering coastal vegetation throughout south Florida. To understand how coastal plant communities are changing over time, accurate mapping techniques are needed that can define plant communities at a fine-enough resolution to detect fine-scale changes. We explored using bi-seasonal versus single-season WorldView-2 satellite data to map three mangrove and four adjacent plant communities, including the buttonwood/glycophyte community that harbors the federally-endangered plant Chromolaena frustrata. Bi-seasonal data were more effective than single-season to differentiate all communities of interest. Bi-seasonal data combined with Light Detection and Ranging (LiDAR) elevation data were used to map coastal plant communities of a coastal stretch within Everglades National Park (ENP). Overall map accuracy was 86%. Black and red mangroves were the dominant communities and covered 50% of the study site. All the remaining communities had ≤10% cover, including the buttonwood/glycophyte community. ENP harbors 21 rare coastal species threatened by SLR. The spatially explicit, quantitative data provided by our map provides a fine-scale baseline for monitoring future change in these species’ habitats. Our results also offer a method to monitor vegetation change in other threatened habitats. PMID:29522476

Changing Supervision for Changing Times.

ERIC Educational Resources Information Center

Leeper, Robert R., Ed.

This collection of four addresses considers some important issues for educational supervisors in a society undergoing rapid social changes. Jacqueline Grennan Wexler suggests that open communication in a climate of mutual independence and responsibility among educational administrators, students, teachers, and taxpayers is a possible solution to…

The Role of Adult Perceptions and Supervision Behavior in Preventing Child Injury.

PubMed

Huynh, Ha T; Demeter, Natalie E; Burke, Rita V; Upperman, Jeffrey S

2017-08-01

Supervision is an important factor in reducing injury risk. There are multiple factors that can affect the appropriate level of supervision including risk perception, anticipation of injury, and distracted behaviors. This study examined the perceived risks of child injury among parents and child caregivers and their supervision behavior among adults in an urban playground. Participant data from 25 individuals were collected through observations and anonymous self-reported surveys. More than half of the participants indicated practice of appropriate supervisory behavior, including attentiveness to their child's behavior and proximity to their child during play. Caregivers were more likely to report more careful levels of supervision. One-fourth of participants reported a change in the supervisory behavior during periods of distraction, specifically with phone use. Of the variables tested, there was a significant association between the variable 'talking to other adults' during supervision and 'prior injury' (P value = 0.04, 95% CI 0.03-0.91). Parents were more likely to report that they would leave their child unattended if they believed that the playground was a safe environment for play. There was a difference between self-reported behaviors and actual observed behavior, which is likely due to varying perspectives regarding child safety and injury prevention. In regards to injury risk, findings highlight the important role of appropriate supervisory behaviors and risk perceptions in preventing child injuries.

CREATING A "NEST" OF EMOTIONAL SAFETY: REFLECTIVE SUPERVISION IN A CHILD-PARENT PSYCHOTHERAPY CASE.

PubMed

Many, Michele M; Kronenberg, Mindy E; Dickson, Amy B

2016-11-01

Reflective supervision is considered a key practice component for any infant mental health provider to work effectively with young children and their families. This article will provide a brief history and discussion of reflective supervision followed by a case study demonstrating the importance of reflective supervision in the context of child-parent psychotherapy (CPP; A.F. Lieberman, C. Ghosh Ippen, & P. Van Horn, ; A.F. Lieberman & P. Van Horn, , 2008). Given that CPP leverages the caregiver-child relationship as the mechanism for change in young children who have been impacted by stressors and traumas, primary objectives of CPP include assisting caregivers as they understand the meaning of their child's distress and improving the caregiver-child relationship to make it a safe and supportive space in which the child can heal. As this case will demonstrate, when a clinician is emotionally triggered by a family's negative intergenerational patterns of relating, reflective supervision supports a parallel process in which the psychotherapist feels understood and contained by the supervisor so that she or he is able to support the caregiver's efforts to understand and contain the child. © 2016 Michigan Association for Infant Mental Health.

Pediatric Anesthesiology Fellows' Perception of Quality of Attending Supervision and Medical Errors.

PubMed

Benzon, Hubert A; Hajduk, John; De Oliveira, Gildasio; Suresh, Santhanam; Nizamuddin, Sarah L; McCarthy, Robert; Jagannathan, Narasimhan

2018-02-01

Appropriate supervision has been shown to reduce medical errors in anesthesiology residents and other trainees across various specialties. Nonetheless, supervision of pediatric anesthesiology fellows has yet to be evaluated. The main objective of this survey investigation was to evaluate supervision of pediatric anesthesiology fellows in the United States. We hypothesized that there was an indirect association between perceived quality of faculty supervision of pediatric anesthesiology fellow trainees and the frequency of medical errors reported. A survey of pediatric fellows from 53 pediatric anesthesiology fellowship programs in the United States was performed. The primary outcome was the frequency of self-reported errors by fellows, and the primary independent variable was supervision scores. Questions also assessed barriers for effective faculty supervision. One hundred seventy-six pediatric anesthesiology fellows were invited to participate, and 104 (59%) responded to the survey. Nine of 103 (9%, 95% confidence interval [CI], 4%-16%) respondents reported performing procedures, on >1 occasion, for which they were not properly trained for. Thirteen of 101 (13%, 95% CI, 7%-21%) reported making >1 mistake with negative consequence to patients, and 23 of 104 (22%, 95% CI, 15%-31%) reported >1 medication error in the last year. There were no differences in median (interquartile range) supervision scores between fellows who reported >1 medication error compared to those reporting ≤1 errors (3.4 [3.0-3.7] vs 3.4 [3.1-3.7]; median difference, 0; 99% CI, -0.3 to 0.3; P = .96). Similarly, there were no differences in those who reported >1 mistake with negative patient consequences, 3.3 (3.0-3.7), compared with those who did not report mistakes with negative patient consequences (3.4 [3.3-3.7]; median difference, 0.1; 99% CI, -0.2 to 0.6; P = .35). We detected a high rate of self-reported medication errors in pediatric anesthesiology fellows in the United States. Interestingly, fellows' perception of quality of faculty supervision was not associated with the frequency of reported errors. The current results with a narrow CI suggest the need to evaluate other potential factors that can be associated with the high frequency of reported errors by pediatric fellows (eg, fatigue, burnout). The identification of factors that lead to medical errors by pediatric anesthesiology fellows should be a main research priority to improve both trainee education and best practices of pediatric anesthesia.

[ORGANIZATION OF THE QUALITY CONTROL OF PLACEMENT AND ACCOMMODATION OF PARTICIPANTS ATTENDANTS AND GUESTS OF THE XXII OLYMPIC WINTER GAMES AND XI PARALYMPIC WINTER GAMES OF 2014 IN THE RESORT CITY OF SOCHI].

PubMed

Gorskiĭ, A A; Gus'kov, A S; Pochtareva, E S; Klindukhov, V P; Nikolaevich, P N; Grechanaia, T V; Vechemyaia, E A; Biriukov, V A; Bozhko, I I; Kulichenko, A N; Taran, T V; Zaĭtsev, A A; Tushina, O V

2015-01-01

There is presented the analysis of activities of the Federal Service for Supervision of Consumer Rights protection and Human Welfare to ensure adequate conditions of accommodation of the participants, attendants and guests of the XXII Olympic Winter Games and XI Paralympic Winter Games of 2014 in the Resort city of Sochi according to regulated requirements. There were detected ways of the strengthening the supervision for the quality of the accommodation during mass sports activities for the assurance of the rights for consumers.

Semi supervised Learning of Feature Hierarchies for Object Detection in a Video (Open Access)

DTIC Science & Technology

2013-10-03

dataset: PETS2009 Dataset, Oxford Town Center dataset [3], PNNL Parking Lot datasets [25] and CAVIAR cols1 dataset [1] for human detection. Be- sides, we...level features from TownCen- ter, ParkingLot, PETS09 and CAVIAR . As we can see that, the four set of features are visually very different from each other...information is more distinguished for detecting a person in the TownCen- ter than CAVIAR . Comparing figure 5(a) with 6(a), interest- ingly, the color

In-training assessment: qualitative study of effects on supervision and feedback in an undergraduate clinical rotation.

PubMed

Daelmans, H E M; Overmeer, R M; van der Hem-Stokroos, H H; Scherpbier, A J J A; Stehouwer, C D A; van der Vleuten, C P M

2006-01-01

Supervision and feedback are essential factors that contribute to the learning environment in the context of workplace learning and their frequency and quality can be improved. Assessment is a powerful tool with which to influence students' learning and supervisors' teaching and thus the learning environment. To investigate an in-training assessment (ITA) programme in action and to explore its effects on supervision and feedback. A qualitative study using individual, semistructured interviews. Eight students and 17 assessors (9 members of staff and 8 residents) in the internal medicine undergraduate clerkship at Vrije Universiteit Medical Centre, Amsterdam, the Netherlands. The ITA programme in action differed from the intended programme. Assessors provided hardly any follow-up on supervision and feedback given during assessments. Although students wanted more supervision and feedback, they rarely asked for it. Students and assessors failed to integrate the whole range of competencies included in the ITA programme into their respective learning and supervision and feedback. When giving feedback, assessors rarely gave borderline or fail judgements. If an ITA programme in action is to be congruent with the intended programme, the implementation of the programme must be monitored. It is also necessary to provide full information about the programme and to ensure this information is given repeatedly. Introducing an ITA programme that includes the assessment of several competencies does not automatically lead to more attention being paid to these competencies in terms of supervision and feedback. Measures that facilitate change in the learning environment seem to be a prerequisite for enabling the assessment programme to steer the learning environment.

Pelvic floor muscle exercises utilizing trunk stabilization for treating postpartum urinary incontinence: randomized controlled pilot trial of supervised versus unsupervised training.

PubMed

Kim, Eun-Young; Kim, Suhn-Yeop; Oh, Duck-Won

2012-02-01

To investigate the effect of supervised and unsupervised pelvic floor muscle exercises utilizing trunk stabilization for treating postpartum urinary incontinence and to compare the outcomes. Randomized, single-blind controlled study. Outpatient rehabilitation hospital. Eighteen subjects with postpartum urinary incontinence. Subjects were randomized to either a supervised training group with verbal instruction from a physiotherapist, or an unsupervised training group after undergoing a supervised demonstration session. Bristol Female Lower Urinary Tract Symptom questionnaire (urinary symptoms and quality of life) and vaginal function test (maximal vaginal squeeze pressure and holding time) using a perineometer. The change values for urinary symptoms (-27.22 ± 6.20 versus -18.22 ± 5.49), quality of life (-5.33 ± 2.96 versus -1.78 ± 3.93), total score (-32.56 ± 8.17 versus -20.00 ± 6.67), maximal vaginal squeeze pressure (18.96 ± 9.08 versus 2.67 ± 3.64 mmHg), and holding time (11.32 ± 3.17 versus 5.72 ± 2.29 seconds) were more improved in the supervised group than in the unsupervised group (P < 0.05). In the supervised group, significant differences were found for all variables between pre- and post-test values (P < 0.01), whereas the unsupervised group showed significant differences for urinary symptom score, total score and holding time between the pre- and post-test results (P < 0.05). These findings suggest that exercising the pelvic floor muscles by utilizing trunk stabilization under physiotherapist supervision may be beneficial for the management of postpartum urinary incontinence.

Towards harmonized seismic analysis across Europe using supervised machine learning approaches

NASA Astrophysics Data System (ADS)

Zaccarelli, Riccardo; Bindi, Dino; Cotton, Fabrice; Strollo, Angelo

2017-04-01

In the framework of the Thematic Core Services for Seismology of EPOS-IP (European Plate Observing System-Implementation Phase), a service for disseminating a regionalized logic-tree of ground motions models for Europe is under development. While for the Mediterranean area the large availability of strong motion data qualified and disseminated through the Engineering Strong Motion database (ESM-EPOS), supports the development of both selection criteria and ground motion models, for the low-to-moderate seismic regions of continental Europe the development of ad-hoc models using weak motion recordings of moderate earthquakes is unavoidable. Aim of this work is to present a platform for creating application-oriented earthquake databases by retrieving information from EIDA (European Integrated Data Archive) and applying supervised learning models for earthquake records selection and processing suitable for any specific application of interest. Supervised learning models, i.e. the task of inferring a function from labelled training data, have been extensively used in several fields such as spam detection, speech and image recognition and in general pattern recognition. Their suitability to detect anomalies and perform a semi- to fully- automated filtering on large waveform data set easing the effort of (or replacing) human expertise is therefore straightforward. Being supervised learning algorithms capable of learning from a relatively small training set to predict and categorize unseen data, its advantage when processing large amount of data is crucial. Moreover, their intrinsic ability to make data driven predictions makes them suitable (and preferable) in those cases where explicit algorithms for detection might be unfeasible or too heuristic. In this study, we consider relatively simple statistical classifiers (e.g., Naive Bayes, Logistic Regression, Random Forest, SVMs) where label are assigned to waveform data based on "recognized classes" needed for our use case. These classes might be a simply binary case (e.g., "good for analysis" vs "bad") or more complex one (e.g., "good for analysis" vs "low SNR", "multi-event", "bad coda envelope"). It is important to stress the fact that our approach can be generalized to any use case providing, as in any supervised approach, an adequate training set of labelled data, a feature-set, a statistical classifier, and finally model validation and evaluation. Examples of use cases considered to develop the system prototype are the characterization of the ground motion in low seismic areas; harmonized spectral analysis across Europe for source and attenuation studies; magnitude calibration; coda analysis for attenuation studies.

Label-free image-based detection of drug resistance with optofluidic time-stretch microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kobayashi, Hirofumi; Lei, Cheng; Mao, Ailin; Jiang, Yiyue; Guo, Baoshan; Ozeki, Yasuyuki; Goda, Keisuke

2017-02-01

Acquired drug resistance is a fundamental predicament in cancer therapy. Early detection of drug-resistant cancer cells during or after treatment is expected to benefit patients from unnecessary drug administration and thus play a significant role in the development of a therapeutic strategy. However, the development of an effective method of detecting drug-resistant cancer cells is still in its infancy due to their complex mechanism in drug resistance. To address this problem, we propose and experimentally demonstrate label-free image-based drug resistance detection with optofluidic time-stretch microscopy using leukemia cells (K562 and K562/ADM). By adding adriamycin (ADM) to both K562 and K562/ADM (ADM-resistant K562 cells) cells, both types of cells express unique morphological changes, which are subsequently captured by an optofluidic time-stretch microscope. These unique morphological changes are extracted as image features and are subjected to supervised machine learning for cell classification. We hereby have successfully differentiated K562 and K562/ADM solely with label-free images, which suggests that our technique is capable of detecting drug-resistant cancer cells. Our optofluidic time-stretch microscope consists of a time-stretch microscope with a high spatial resolution of 780 nm at a 1D frame rate of 75 MHz and a microfluidic device that focuses and orders cells. We compare various machine learning algorithms as well as various concentrations of ADM for cell classification. Owing to its unprecedented versatility of using label-free image and its independency from specific molecules, our technique holds great promise for detecting drug resistance of cancer cells for which its underlying mechanism is still unknown or chemical probes are still unavailable.

Fingerprint Liveness Detection in the Presence of Capable Intruders.

PubMed

Sequeira, Ana F; Cardoso, Jaime S

2015-06-19

Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the use of a previously known material. This assumption has led to the use of supervised techniques to estimate the performance of the methods, using both live and spoof samples to train the predictive models and evaluate each type of fake samples individually. Additionally, the background was often included in the sample representation, completely distorting the decision process. Therefore, we propose that an automatic segmentation step should be performed to isolate the fingerprint from the background and truly decide on the liveness of the fingerprint and not on the characteristics of the background. Also, we argue that one cannot aim to model the fake samples completely since the material used by the intruder is unknown beforehand. We approach the design by modeling the distribution of the live samples and predicting as fake the samples very unlikely according to that model. Our experiments compare the performance of the supervised approaches with the semi-supervised ones that rely solely on the live samples. The results obtained differ from the ones obtained by the more standard approaches which reinforces our conviction that the results in the literature are misleadingly estimating the true vulnerability of the biometric system.

Adaptive maritime video surveillance

NASA Astrophysics Data System (ADS)

Gupta, Kalyan Moy; Aha, David W.; Hartley, Ralph; Moore, Philip G.

2009-05-01

Maritime assets such as ports, harbors, and vessels are vulnerable to a variety of near-shore threats such as small-boat attacks. Currently, such vulnerabilities are addressed predominantly by watchstanders and manual video surveillance, which is manpower intensive. Automatic maritime video surveillance techniques are being introduced to reduce manpower costs, but they have limited functionality and performance. For example, they only detect simple events such as perimeter breaches and cannot predict emerging threats. They also generate too many false alerts and cannot explain their reasoning. To overcome these limitations, we are developing the Maritime Activity Analysis Workbench (MAAW), which will be a mixed-initiative real-time maritime video surveillance tool that uses an integrated supervised machine learning approach to label independent and coordinated maritime activities. It uses the same information to predict anomalous behavior and explain its reasoning; this is an important capability for watchstander training and for collecting performance feedback. In this paper, we describe MAAW's functional architecture, which includes the following pipeline of components: (1) a video acquisition and preprocessing component that detects and tracks vessels in video images, (2) a vessel categorization and activity labeling component that uses standard and relational supervised machine learning methods to label maritime activities, and (3) an ontology-guided vessel and maritime activity annotator to enable subject matter experts (e.g., watchstanders) to provide feedback and supervision to the system. We report our findings from a preliminary system evaluation on river traffic video.

Fingerprint Liveness Detection in the Presence of Capable Intruders

PubMed Central

Sequeira, Ana F.; Cardoso, Jaime S.

2015-01-01

Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the use of a previously known material. This assumption has led to the use of supervised techniques to estimate the performance of the methods, using both live and spoof samples to train the predictive models and evaluate each type of fake samples individually. Additionally, the background was often included in the sample representation, completely distorting the decision process. Therefore, we propose that an automatic segmentation step should be performed to isolate the fingerprint from the background and truly decide on the liveness of the fingerprint and not on the characteristics of the background. Also, we argue that one cannot aim to model the fake samples completely since the material used by the intruder is unknown beforehand. We approach the design by modeling the distribution of the live samples and predicting as fake the samples very unlikely according to that model. Our experiments compare the performance of the supervised approaches with the semi-supervised ones that rely solely on the live samples. The results obtained differ from the ones obtained by the more standard approaches which reinforces our conviction that the results in the literature are misleadingly estimating the true vulnerability of the biometric system. PMID:26102491

[Supervised administration of Alzheimer's patients using information communication technology].

PubMed

Noda, Yasuha; Sakata, Yoshifumi; Kubota, Masakazu; Uemura, Kengo; Kihara, Takeshi; Kimura, Toru; Ino, Masashi; Tsuji, Teruyuki; Hayashi, Michiyuki; Kinoshita, Ayae

2014-12-01

Drug adherence is central to the treatment of dementia, which might reduce compliance due to memory loss, particularly among home-based patients with dementia. In order to improve drug adherence, we suggest the efficient and effective supervised administration by use of information communication technology(ICT). ICT makes face-to-face real-time communication possible, and it also enables picture sharing. Therefore, it might be useful to apply ICT to controlling and supervising medication for patients with dementia to improve drug adherence. Accordingly, we enrolled patients who were supposed to take a newly prescribed anti-dementia patch containing the choline esterase inhibitor rivastigmine(Rivastach®)and investigated the effect of ICT-based intervention for drug adherence, emotional change, and cognitive change, utilizing Skype, a free communication software program. Scheduled Skype interventions increased drug adherence ratio, levels of subjective satisfaction, and instrumental activities of daily living(IADL). Furthermore, we can provide patients and their caregivers with a feeling of safety through regular bidirectional communication, as patients can easily consult medical staff regarding the adverse effects of newly prescribed drugs. Instead of frequent visits to their primary physicians, ICT-based communications can be used as a substitute for supervision of medication, given the availability of the telecommunication system. By directly connecting the medical institution to the home, we expect that this ICT-based system will expand into the geriatric care field, including the care of elderly individuals living alone.

Supervised Time Series Event Detector for Building Data

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

2016-04-13

A machine learning based approach is developed to detect events that have rarely been seen in the historical data. The data can include building energy consumption, sensor data, environmental data and any data that may affect the building's energy consumption. The algorithm is a modified nonlinear Bayesian support vector machine, which examines daily energy consumption profile, detect the days with abnormal events, and diagnose the cause of the events.

Detection of food intake from swallowing sequences by supervised and unsupervised methods.

PubMed

Lopez-Meyer, Paulo; Makeyev, Oleksandr; Schuckers, Stephanie; Melanson, Edward L; Neuman, Michael R; Sazonov, Edward

2010-08-01

Studies of food intake and ingestive behavior in free-living conditions most often rely on self-reporting-based methods that can be highly inaccurate. Methods of Monitoring of Ingestive Behavior (MIB) rely on objective measures derived from chewing and swallowing sequences and thus can be used for unbiased study of food intake with free-living conditions. Our previous study demonstrated accurate detection of food intake in simple models relying on observation of both chewing and swallowing. This article investigates methods that achieve comparable accuracy of food intake detection using only the time series of swallows and thus eliminating the need for the chewing sensor. The classification is performed for each individual swallow rather than for previously used time slices and thus will lead to higher accuracy in mass prediction models relying on counts of swallows. Performance of a group model based on a supervised method (SVM) is compared to performance of individual models based on an unsupervised method (K-means) with results indicating better performance of the unsupervised, self-adapting method. Overall, the results demonstrate that highly accurate detection of intake of foods with substantially different physical properties is possible by an unsupervised system that relies on the information provided by the swallowing alone.

Detection of Food Intake from Swallowing Sequences by Supervised and Unsupervised Methods

PubMed Central

Lopez-Meyer, Paulo; Makeyev, Oleksandr; Schuckers, Stephanie; Melanson, Edward L.; Neuman, Michael R.; Sazonov, Edward

2010-01-01

Studies of food intake and ingestive behavior in free-living conditions most often rely on self-reporting-based methods that can be highly inaccurate. Methods of Monitoring of Ingestive Behavior (MIB) rely on objective measures derived from chewing and swallowing sequences and thus can be used for unbiased study of food intake with free-living conditions. Our previous study demonstrated accurate detection of food intake in simple models relying on observation of both chewing and swallowing. This article investigates methods that achieve comparable accuracy of food intake detection using only the time series of swallows and thus eliminating the need for the chewing sensor. The classification is performed for each individual swallow rather than for previously used time slices and thus will lead to higher accuracy in mass prediction models relying on counts of swallows. Performance of a group model based on a supervised method (SVM) is compared to performance of individual models based on an unsupervised method (K-means) with results indicating better performance of the unsupervised, self-adapting method. Overall, the results demonstrate that highly accurate detection of intake of foods with substantially different physical properties is possible by an unsupervised system that relies on the information provided by the swallowing alone. PMID:20352335

The dynamics of human-induced land cover change in miombo ecosystems of southern Africa

NASA Astrophysics Data System (ADS)

Jaiteh, Malanding Sambou

Understanding human-induced land cover change in the miombo require the consistent, geographically-referenced, data on temporal land cover characteristics as well as biophysical and socioeconomic drivers of land use, the major cause of land cover change. The overall goal of this research to examine the applications of high-resolution satellite remote sensing data in studying the dynamics of human-induced land cover change in the miombo. Specific objectives are to: (1) evaluate the applications of computer-assisted classification of Landsat Thematic Mapper (TM) data for land cover mapping in the miombo and (2) analyze spatial and temporal patterns of landscape change locations in the miombo. Stepwise Thematic Classification, STC (a hybrid supervised-unsupervised classification) procedure for classifying Landsat TM data was developed and tested using Landsat TM data. Classification accuracy results were compared to those from supervised and unsupervised classification. The STC provided the highest classification accuracy i.e., 83.9% correspondence between classified and referenced data compared to 44.2% and 34.5% for unsupervised and supervised classification respectively. Improvements in the classification process can be attributed to thematic stratification of the image data into spectrally homogenous (thematic) groups and step-by-step classification of the groups using supervised or unsupervised classification techniques. Supervised classification failed to classify 18% of the scene evidence that training data used did not adequately represent all of the variability in the data. Application of the procedure in drier miombo produced overall classification accuracy of 63%. This is much lower than that of wetter miombo. The results clearly demonstrate that digital classification of Landsat TM can be successfully implemented in the miombo without intensive fieldwork. Spatial characteristics of land cover change in agricultural and forested landscapes in central Malawi were analyzed for the period 1984 to 1995 spatial pattern analysis methods. Shifting cultivation areas, Agriculture in forested landscape, experienced highest rate of woodland cover fragmentation with mean patch size of closed woodland cover decreasing from 20ha to 7.5ha. Permanent bare (cropland and settlement) in intensive agricultural matrix landscapes increased 52% largely through the conversion of fallow areas. Protected National Park area remained fairly unchanged although closed woodland area increased by 4%, mainly from regeneration of open woodland. This study provided evidence that changes in spatial characteristics in the miombo differ with landscape. Land use change (i.e. conversion to cropland) is the primary driving force behind changes in landscape spatial patterns. Also, results revealed that exclusion of intense human use (i.e. cultivation and woodcutting) through regulations and/or fencing increased both closed woodland area (through regeneration of open woodland) and overall connectivity in the landscape. Spatial characteristics of land cover change were analyzed at locations in Malawi (wetter miombo) and Zimbabwe (drier miombo). Results indicate land cover dynamics differ both between and within case study sites. In communal areas in the Kasungu scene, land cover change is dominated by woodland fragmentation to open vegetation. Change in private commercial lands was dominantly expansion of bare (settlement and cropland) areas primarily at the expense of open vegetation (fallow land).

Detecting Seismic Events Using a Supervised Hidden Markov Model

NASA Astrophysics Data System (ADS)

Burks, L.; Forrest, R.; Ray, J.; Young, C.

2017-12-01

We explore the use of supervised hidden Markov models (HMMs) to detect seismic events in streaming seismogram data. Current methods for seismic event detection include simple triggering algorithms, such as STA/LTA and the Z-statistic, which can lead to large numbers of false positives that must be investigated by an analyst. The hypothesis of this study is that more advanced detection methods, such as HMMs, may decreases false positives while maintaining accuracy similar to current methods. We train a binary HMM classifier using 2 weeks of 3-component waveform data from the International Monitoring System (IMS) that was carefully reviewed by an expert analyst to pick all seismic events. Using an ensemble of simple and discrete features, such as the triggering of STA/LTA, the HMM predicts the time at which transition occurs from noise to signal. Compared to the STA/LTA detection algorithm, the HMM detects more true events, but the false positive rate remains unacceptably high. Future work to potentially decrease the false positive rate may include using continuous features, a Gaussian HMM, and multi-class HMMs to distinguish between types of seismic waves (e.g., P-waves and S-waves). Acknowledgement: Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.SAND No: SAND2017-8154 A

Comparing minimally supervised home-based and closely supervised gym-based exercise programs in weight reduction and insulin resistance after bariatric surgery: A randomized clinical trial.

PubMed

Kaviani, Sara; Dadgostar, Haleh; Mazaherinezhad, Ali; Adib, Hanie; Solaymani-Dodaran, Masoud; Soheilipour, Fahimeh; Hakiminezhad, Mahdi

2017-01-01

Background: Effectiveness of various exercise protocols in weight reduction after bariatric surgery has not been sufficiently explored in the literature. Thus, in the present study, we aimed at comparing the effect of minimally supervised home-based and closely supervised gym-based exercise programs on weight reduction and insulin resistance after bariatric surgery. Methods: Females undergoing gastric bypass surgery were invited to participate in an exercise program and were randomly allocated into 2 groups using a random number generator in Excel. They were either offered a minimally supervised home-based (MSHB) or closely supervised gym-based (CSGB) exercise program. The CSGB protocol constitutes 2 weekly training sessions under ACSM guidelines. In the MSHB protocol, the participants received a notebook containing a list of recommended aerobic and resistance exercises, a log to record their activity, and a schedule of follow-up phone calls and clinic visits. Both groups received a pedometer. We measured their weight, BMI, lipid profile, FBS, and insulin level at baseline and at 20 weeks after the exercises, the results of which were compared using t test or Mann-Whitney U test at the end of the study. All the processes were observed by 1 senior resident in sport medicine. Results: A total of 80 patients were recruited who were all able to complete our study (MSHB= 38 and CSGB= 42). The baseline comparison revealed that the 2 groups were similar. The mean change (reduction) in BMI was slightly better in CSGB (8.61 95% CI 7.76-9.45) compared with the MSHB (5.18 95% CI 3.91-6.46); p< 0.01. However, the 2 groups did not have a statistically significant difference in the amount of change in the other factors including FBS and Homa.ir. Conclusion: As we expected a non-inferiority result, our results showed that both MSHB and CSGB exercise methods are somewhat equally effective in improving lipid profile and insulin resistance in the 2 groups, but a slightly better effect on BMI was observed in CSGB group. With considerably lower costs of minimally supervised home- based exercise programs, both methods should be considered when there is lack of adequate funding.

Supervised Injectable Heroin: A Clinical Perspective.

PubMed

Bell, James; Waal, Rob van der; Strang, John

2017-07-01

Six recent randomised control trials (RCTs) have suggested that supervised injectable heroin (SIH) can be effective in patients who persist in street heroin use during methadone treatment. However, short-term randomised control trials have limitations in assessing the effectiveness of treatments for addictive disorders, which are chronic and relapsing disorders of motivation. These RCTs particularly fail to capture the process of the SIH treatment and the diversity of influence and change over time. This narrative review is based on the analysis of published data. Conclusions are drawn from a process of reflection informed by experience in delivering one of the published trials, subsequent experiences in varying the way SIH is delivered, and through consideration of possible mechanisms of action of SIH. Many long-term, socially marginalised and demoralised people who are addicted to heroin experience few rewards from the stability afforded by methadone treatment. Supervised injected heroin is sufficiently reinforcing for many of these individuals to attend daily and participate in highly structured treatment. With an adequate daily dose of supervised methadone to avoid withdrawal dysphoria, occasional diamorphine injections-not necessarily twice daily, or even every day-is enough to hold people in treatment. Participation was associated with reduced amounts of non-prescribed drug use, a gradual change in self-image and attitude, and for some subjects, a movement towards social reintegration and eventual withdrawal from SIH. Prescribed heroin is sufficiently motivating to hold a proportion of recidivist addicts in long-term treatment. Participation in structured treatment provides respite from compulsive drug use, and a proportion of subjects develop sufficient rewards from social reintegration to successfully withdraw from treatment. Such change, when it occurs, is slow and stuttering.

Improved semi-supervised online boosting for object tracking

NASA Astrophysics Data System (ADS)

Li, Yicui; Qi, Lin; Tan, Shukun

2016-10-01

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.

The efficacy of a supervised and a home-based core strengthening programme in adults with poor core stability: a three-arm randomised controlled trial.

PubMed

Chuter, V H; de Jonge, X A K Janse; Thompson, B M; Callister, R

2015-03-01

Poor core stability is linked to a range of musculoskeletal pathologies and core-strengthening programmes are widely used as treatment. Treatment outcomes, however, are highly variable, which may be related to the method of delivery of core strengthening programmes. We investigated the effect of identical 8 week core strengthening programmes delivered as either supervised or home-based on measures of core stability. Participants with poor core stability were randomised into three groups: supervised (n=26), home-based (n=26) or control (n=26). Primary outcomes were the Sahrmann test and the Star Excursion Balance Test (SEBT) for dynamic core stability and three endurance tests (side-bridge, flexor and Sorensen) for static core stability. The exercise programme was devised and supervised by an exercise physiologist. Analysis of covariance on the change from baseline over the 8 weeks showed that the supervised group performed significantly better on all core stability measures than both the home-based and control group. The home-based group produced significant improvements compared to the control group in all static core stability tests, but not in most of the dynamic core stability tests (Sahrmann test and two out of three directions of the SEBT). Our results support the use of a supervised core-strengthening programme over a home-based programme to maximise improvements in core stability, especially in its dynamic aspects. Based on our findings in healthy individuals with low core stability, further research is recommended on potential therapeutic benefits of supervised core-strengthening programmes for pathologies associated with low core stability. ACTRN12613000233729. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Does training frequency and supervision affect compliance, performance and muscular health? A cluster randomized controlled trial.

PubMed

Dalager, Tina; Bredahl, Thomas G V; Pedersen, Mogens T; Boyle, Eleanor; Andersen, Lars L; Sjøgaard, Gisela

2015-10-01

The aim was to determine the effect of one weekly hour of specific strength training within working hours, performed with the same total training volume but with different training frequencies and durations, or with different levels of supervision, on compliance, muscle health and performance, behavior and work performance. In total, 573 office workers were cluster-randomized to: 1 WS: one 60-min supervised session/week, 3 WS: three 20-min supervised sessions/week, 9 WS: nine 7-min supervised sessions/week, 3 MS: three 20-min sessions/week with minimal supervision, or REF: a reference group without training. Outcomes were diary-based compliance, total training volume, muscle performance and questionnaire-based health, behavior and work performance. Comparisons were made among the WS training groups and between 3 WS and 3 MS. If no difference, training groups were collapsed (TG) and compared with REF. Results demonstrated similar degrees of compliance, mean(range) of 39(33-44)%, and total training volume, 13.266(11.977-15.096)kg. Musculoskeletal pain in neck and shoulders were reduced with approx. 50% in TG, which was significant compared with REF. Only the training groups improved significantly their muscle strength 8(4-13)% and endurance 27(12-37)%, both being significant compared with REF. No change in workability, productivity or self-rated health was demonstrated. Secondary analysis showed exercise self-efficacy to be a significant predictor of compliance. Regardless of training schedule and supervision, similar degrees of compliance were shown together with reduced musculoskeletal pain and improved muscle performance. These findings provide evidence that a great degree of flexibility is legitimate for companies in planning future implementation of physical exercise programs at the workplace. ClinicalTrials.gov, number NCT01027390. Copyright © 2015 Elsevier Ltd. All rights reserved.

Supervisory Behaviors That Reflect Reality: A Diversified Supervision Model.

ERIC Educational Resources Information Center

Uzat, Rodney R. J.

This paper clarifies exactly what "culture" and "change" mean to the educational system and why these terms are so important to the health, survival, and instructional improvement of educational organizations. Educational leaders must accept the fact that crafting a change-friendly, change-embracing organizational culture for continuous…

Synthesis of actual knowledge on machine-tool monitoring methods and equipment

NASA Astrophysics Data System (ADS)

Tanguy, J. C.

1988-06-01

Problems connected with the automatic supervision of production were studied. Many different automatic control devices are now able to identify defects in the tools, but the solutions proposed to detect optimal limits in the utilization of a tool are not satisfactory.

Learning the ideal observer for SKE detection tasks by use of convolutional neural networks (Cum Laude Poster Award)

NASA Astrophysics Data System (ADS)

Zhou, Weimin; Anastasio, Mark A.

2018-03-01

It has been advocated that task-based measures of image quality (IQ) should be employed to evaluate and optimize imaging systems. Task-based measures of IQ quantify the performance of an observer on a medically relevant task. The Bayesian Ideal Observer (IO), which employs complete statistical information of the object and noise, achieves the upper limit of the performance for a binary signal classification task. However, computing the IO performance is generally analytically intractable and can be computationally burdensome when Markov-chain Monte Carlo (MCMC) techniques are employed. In this paper, supervised learning with convolutional neural networks (CNNs) is employed to approximate the IO test statistics for a signal-known-exactly and background-known-exactly (SKE/BKE) binary detection task. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are compared to those produced by the analytically computed IO. The advantages of the proposed supervised learning approach for approximating the IO are demonstrated.

"SmartMonitor"--an intelligent security system for the protection of individuals and small properties with the possibility of home automation.

PubMed

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.

Change Detection Analysis of Costal Habitat Using Remote Sensing Technologies in the Western Arabian Gulf (Saudi Arabian Coast) over a Thirty-Year Period.

NASA Astrophysics Data System (ADS)

El-Askary, H. M.; Idris, N.; Johnson, S. H.; Qurban, M. A. B.

2014-12-01

Many factors can severely affect the growth and abundance of the marine ecosystems. For example, due to anthropogenic and natural forces, benthic habitats including but not limited to mangroves, sea grass, salt marshes, macro algae, and coral reefs have been experiencing high levels of declination. Furthermore, aerosols and their propellants are suspected contributors to marine habitat degradation. Although several studies reveal that the Arabian Gulf habitats have suffered deleterious impacts after the Gulf War and the following six month off-shore oil spill, limited research exists to track the changes in benthic habitats over the past three decades using remote sensing. Document changes in costal habitats over the past thirty years were better observed with the use of multispectral remote sensors such as Landsat-5, Landsat-7, and Landsat8 (OLI). Change detection analysis was performed on the three Landsat images (Landsat-5 for the 1987 image, Landsat-7 for the 2000, and Landsat-8 for the 2013 image). The images were then modified, masked off from open water and land. An unsupervised classification was performed which cluster similar classes together. The supervised classification displayed the seven following classes: coral reefs, macro algae, sea grass, salt marshes, mangroves, water, and land. Compared to 1987 image to 2000 scene, there was a noticeable increase in the extensiveness of salt marsh and macro algae habitats. However, a significant decrease in salt marsh habitats were apparent in the 2013 scene.

Older siblings as potential supervisors of younger siblings: sibling supervisors' recognition of injury-risk behaviours and beliefs about supervisee risk taking and potential injury outcomes.

PubMed

Morrongiello, B A; Schell, S L; Stewart, J

2015-07-01

Past research has shown that increased injury risk for supervisees during sibling supervision is in part due to the supervision practices of older siblings. The current study used a photo sorting task to examine older siblings' recognition of injury-risk behaviours, their perceived likelihood of supervisees engaging in, or being injured while engaging in, these behaviours, and awareness of past risk-taking behaviours of supervisees. Mothers completed the same measures and an interview about sibling supervision in the home. Mothers reported that sibling supervision occurred most frequently in the kitchen, living room, and children's bedrooms, for approximately 39 min/day, and that the more time the children spent together in a room, the more frequently the older sibling supervised the younger one. The most common reasons mothers gave for why sibling supervision was allowed included beliefs that the older child knows about hazards and unsafe behaviours and that the child could provide adequate supervision. Photo sort results revealed that older siblings were able to correctly identify about 98% of risk behaviours, with these scores significantly higher than what mothers expected (79%). However, compared with mothers, older siblings were less aware of risk behaviours that their younger siblings had engaged in previously. In addition, mothers rated supervisees as 'fairly likely' both to engage in risk behaviours and to experience an injury if they tried these behaviours, whereas sibling supervisors rated both supervisee risk behaviour and injury outcomes as 'not likely' to occur. Older siblings showed good knowledge of hazards but failed to realize that younger children often engage in injury-risk behaviours. Efforts to improve the supervision practices of sibling supervisors need to include changing their perception of supervisees' injury vulnerability and potential injury severity, rather than targeting to increase knowledge of injury-risk behaviours per se. © 2014 John Wiley & Sons Ltd.

Evaluation of the clinical supervision and professional development of student nurses.

PubMed

Severinsson, Elisabeth; Sand, Ase

2010-09-01

The aim of the present study was to evaluate the clinical supervision and professional development of student nurses during their undergraduate education. Nursing education has undergone radical changes as a result of improvements in the academic-based clinical education required for the Bachelor's degree. The sample consisted of student nurses (n = 147) and data were collected by means of questionnaires. The results demonstrated that the frequency of sessions and the supervision model employed influence the student nurses' professional development. Several significant correlations were found, most of which were related to the development of the student nurses' professional relationships with their supervisors and reflection on the development of their skills. From the patients' perspective, a high correlation was found between the factors 'preserving integrity' and 'protecting participation by patients and family members'. Clinical supervision strongly influences the student nurses' development of a professional identity, enhancing decision-making ability and personal growth. However, development of documentation skills should include a greater level of user involvement. The findings highlight the need for management and staff nurses to engage in on-going professional development. Transformative leadership, which is value driven, can facilitate and enhance the supervision and development of student nurses. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

Performance Monitoring Applied to System Supervision

PubMed Central

Somon, Bertille; Campagne, Aurélie; Delorme, Arnaud; Berberian, Bruno

2017-01-01

Nowadays, automation is present in every aspect of our daily life and has some benefits. Nonetheless, empirical data suggest that traditional automation has many negative performance and safety consequences as it changed task performers into task supervisors. In this context, we propose to use recent insights into the anatomical and neurophysiological substrates of action monitoring in humans, to help further characterize performance monitoring during system supervision. Error monitoring is critical for humans to learn from the consequences of their actions. A wide variety of studies have shown that the error monitoring system is involved not only in our own errors, but also in the errors of others. We hypothesize that the neurobiological correlates of the self-performance monitoring activity can be applied to system supervision. At a larger scale, a better understanding of system supervision may allow its negative effects to be anticipated or even countered. This review is divided into three main parts. First, we assess the neurophysiological correlates of self-performance monitoring and their characteristics during error execution. Then, we extend these results to include performance monitoring and error observation of others or of systems. Finally, we provide further directions in the study of system supervision and assess the limits preventing us from studying a well-known phenomenon: the Out-Of-the-Loop (OOL) performance problem. PMID:28744209

Visualization Techniques for Computer Network Defense

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

Beaver, Justin M; Steed, Chad A; Patton, Robert M

2011-01-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operatormore » to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.« less

Inline inspection of textured plastics surfaces

NASA Astrophysics Data System (ADS)

Michaeli, Walter; Berdel, Klaus

2011-02-01

This article focuses on the inspection of plastics web materials exhibiting irregular textures such as imitation wood or leather. They are produced in a continuous process at high speed. In this process, various defects occur sporadically. However, current inspection systems for plastics surfaces are able to inspect unstructured products or products with regular, i.e., highly periodic, textures, only. The proposed inspection algorithm uses the local binary pattern operator for texture feature extraction. For classification, semisupervised as well as supervised approaches are used. A simple concept for semisupervised classification is presented and applied for defect detection. The resulting defect-maps are presented to the operator. He assigns class labels that are used to train the supervised classifier in order to distinguish between different defect types. A concept for parallelization is presented allowing the efficient use of standard multicore processor PC hardware. Experiments with images of a typical product acquired in an industrial setting show a detection rate of 97% while achieving a false alarm rate below 1%. Real-time tests show that defects can be reliably detected even at haul-off speeds of 30 m/min. Further applications of the presented concept can be found in the inspection of other materials.

FDI and Accommodation Using NN Based Techniques

NASA Astrophysics Data System (ADS)

Garcia, Ramon Ferreiro; de Miguel Catoira, Alberto; Sanz, Beatriz Ferreiro

Massive application of dynamic backpropagation neural networks is used on closed loop control FDI (fault detection and isolation) tasks. The process dynamics is mapped by means of a trained backpropagation NN to be applied on residual generation. Process supervision is then applied to discriminate faults on process sensors, and process plant parameters. A rule based expert system is used to implement the decision making task and the corresponding solution in terms of faults accommodation and/or reconfiguration. Results show an efficient and robust FDI system which could be used as the core of an SCADA or alternatively as a complement supervision tool operating in parallel with the SCADA when applied on a heat exchanger.

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

PubMed

Kelly, Damian; McLoone, Sean; Farrell, Ronan

2010-01-01

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

Embedded security system for multi-modal surveillance in a railway carriage

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Audigier, Romaric; Ambellouis, Sébastien; Capman, François; Benhadda, Hamid; Joudrier, Stéphanie; Sodoyer, David; Lamarque, Thierry

2015-10-01

Public transport security is one of the main priorities of the public authorities when fighting against crime and terrorism. In this context, there is a great demand for autonomous systems able to detect abnormal events such as violent acts aboard passenger cars and intrusions when the train is parked at the depot. To this end, we present an innovative approach which aims at providing efficient automatic event detection by fusing video and audio analytics and reducing the false alarm rate compared to classical stand-alone video detection. The multi-modal system is composed of two microphones and one camera and integrates onboard video and audio analytics and fusion capabilities. On the one hand, for detecting intrusion, the system relies on the fusion of "unusual" audio events detection with intrusion detections from video processing. The audio analysis consists in modeling the normal ambience and detecting deviation from the trained models during testing. This unsupervised approach is based on clustering of automatically extracted segments of acoustic features and statistical Gaussian Mixture Model (GMM) modeling of each cluster. The intrusion detection is based on the three-dimensional (3D) detection and tracking of individuals in the videos. On the other hand, for violent events detection, the system fuses unsupervised and supervised audio algorithms with video event detection. The supervised audio technique detects specific events such as shouts. A GMM is used to catch the formant structure of a shout signal. Video analytics use an original approach for detecting aggressive motion by focusing on erratic motion patterns specific to violent events. As data with violent events is not easily available, a normality model with structured motions from non-violent videos is learned for one-class classification. A fusion algorithm based on Dempster-Shafer's theory analyses the asynchronous detection outputs and computes the degree of belief of each probable event.

System Biology Approach: Gene Network Analysis for Muscular Dystrophy.

PubMed

Censi, Federica; Calcagnini, Giovanni; Mattei, Eugenio; Giuliani, Alessandro

2018-01-01

Phenotypic changes at different organization levels from cell to entire organism are associated to changes in the pattern of gene expression. These changes involve the entire genome expression pattern and heavily rely upon correlation patterns among genes. The classical approach used to analyze gene expression data builds upon the application of supervised statistical techniques to detect genes differentially expressed among two or more phenotypes (e.g., normal vs. disease). The use of an a posteriori, unsupervised approach based on principal component analysis (PCA) and the subsequent construction of gene correlation networks can shed a light on unexpected behaviour of gene regulation system while maintaining a more naturalistic view on the studied system.In this chapter we applied an unsupervised method to discriminate DMD patient and controls. The genes having the highest absolute scores in the discrimination between the groups were then analyzed in terms of gene expression networks, on the basis of their mutual correlation in the two groups. The correlation network structures suggest two different modes of gene regulation in the two groups, reminiscent of important aspects of DMD pathogenesis.

Shadow detection and removal in RGB VHR images for land use unsupervised classification

NASA Astrophysics Data System (ADS)

Movia, A.; Beinat, A.; Crosilla, F.

2016-09-01

Nowadays, high resolution aerial images are widely available thanks to the diffusion of advanced technologies such as UAVs (Unmanned Aerial Vehicles) and new satellite missions. Although these developments offer new opportunities for accurate land use analysis and change detection, cloud and terrain shadows actually limit benefits and possibilities of modern sensors. Focusing on the problem of shadow detection and removal in VHR color images, the paper proposes new solutions and analyses how they can enhance common unsupervised classification procedures for identifying land use classes related to the CO2 absorption. To this aim, an improved fully automatic procedure has been developed for detecting image shadows using exclusively RGB color information, and avoiding user interaction. Results show a significant accuracy enhancement with respect to similar methods using RGB based indexes. Furthermore, novel solutions derived from Procrustes analysis have been applied to remove shadows and restore brightness in the images. In particular, two methods implementing the so called "anisotropic Procrustes" and the "not-centered oblique Procrustes" algorithms have been developed and compared with the linear correlation correction method based on the Cholesky decomposition. To assess how shadow removal can enhance unsupervised classifications, results obtained with classical methods such as k-means, maximum likelihood, and self-organizing maps, have been compared to each other and with a supervised clustering procedure.

[Myositis-specific antibodies associated with juvenile dermatomyositis].

PubMed

Eising, K; Peitz, J; Unterwalder, N; Meisel, C; Horneff, G

2018-02-06

Juvenile dermatomyositis (JDM) is a rare autoimmune disease associated with typical skin changes and muscle weakness. Within the framework of the diagnostics, myositis-associated (MAA) and myositis-specific antibodies (MSA) can be detected. These are important for the assessment of the course of the disease and the prognosis. In this study we searched for MAA and MSA by means of a line immunoassay in 12 currently supervised JDM patients in the Rheumatism Center Sankt Augustin. In 10 of the 12 patients a total of 15 myositis antibodies were detected where 3 patients each had Mi2, SRP or NXP2 antibodies, 2 had TIF-1γ antibodies and Jo1 or Mi2β antibodies were found in 1 patient each. Of the patients two had additional PM-Scl antibodies. In the 10 patients with detected antibodies, a good phenotype-serotype correlation was found with deviation from the phenotypes described in the literature in only 3 patients. The frequent detection of certain antibodies and the good correlation with those phenotypes described in the literature, show that the determination of MSA is an important diagnostic tool to assess the course, complications and outcome and to initiate adequate therapy at an early stage.

Dissecting modes of action of non-genotoxic carcinogens in primary mouse hepatocytes.

PubMed

Schaap, Mirjam M; Zwart, Edwin P; Wackers, Paul F K; Huijskens, Ilse; van de Water, Bob; Breit, Timo M; van Steeg, Harry; Jonker, Martijs J; Luijten, Mirjam

2012-11-01

Under REACH, the European Community Regulation on chemicals, the testing strategy for carcinogenicity is based on in vitro and in vivo genotoxicity assays. Given that non-genotoxic carcinogens are negative for genotoxicity and chronic bioassays are no longer regularly performed, this class of carcinogens will go undetected. Therefore, test systems detecting non-genotoxic carcinogens, or even better their modes of action, are required. Here, we investigated whether gene expression profiling in primary hepatocytes can be used to distinguish different modes of action of non-genotoxic carcinogens. For this, primary mouse hepatocytes were exposed to 16 non-genotoxic carcinogens with diverse modes of action. Upon profiling, pathway analysis was performed to obtain insight into the biological relevance of the observed changes in gene expression. Subsequently, both a supervised and an unsupervised comparison approach were applied to recognize the modes of action at the transcriptomic level. These analyses resulted in the detection of three of eight compound classes, that is, peroxisome proliferators, metalloids and skin tumor promotors. In conclusion, gene expression profiles in primary hepatocytes, at least in rodent hepatocytes, appear to be useful to detect some, certainly not all, modes of action of non-genotoxic carcinogens.

Behavior of fluopyram and tebuconazole and some selected pesticides in ripe apples and consumer exposure assessment in the applied crop protection framework.

PubMed

Podbielska, Magdalena; Szpyrka, Ewa; Piechowicz, Bartosz; Zwolak, Aneta; Sadło, Stanisław

2017-07-01

The supervised field trials were conducted in a commercial apple orchard in 2016. The trials were an attempt to determine a model for dissipation and toxicological evaluation of fluopyram, tebuconazole, captan, tetrahydrophthalimide (THPI), pirimicarb, spirodiclofen, and boscalid residues detected in fruit of Red Jonaprince, Lobo, and Gala varieties immediately before harvest. The analysis also covered amounts of pesticides still present in remnants of calyx in Lobo and Gala varieties immediately before harvest. Laboratory samples of ripe apples were collected within 14 days of the treatment. Levels of pesticide residues detected in the samples changed at a constant exponential rate, and the residue levels found in ripe apples of Red Jonaprince, Gala, and Lobo varieties immediately before harvest were below maximum residue levels (MRL). Overall, captan residues in remnants of calyx were at a level of 22.3% for the Gala variety and 9.3% for the Lobo variety. Likewise, the long-term daily intake of the detected substances by a Polish adult consumer was low, ranging from 0.02% ADI for pirimicarb to 0.72% ADI for captan.

DNA and RNA Synthesis in Animal Cells in Culture--Methods for Use in Schools

ERIC Educational Resources Information Center

Godsell, P. M.; Balls, M.

1973-01-01

Describes the experimental procedures used for detecting DNA and RNA synthesis in xenopus cells by autoradiography. The method described is suitable for senior high school laboratory classes or biology projects, if supervised by a teacher qualified to handle radioisotopes. (JR)

Vicarious Traumatization, Trauma-Sensitive Supervision, and Counselor Preparation

ERIC Educational Resources Information Center

Sommer, Carol A.

2008-01-01

Counselor educators have an ethical responsibility to prepare counselors and supervisors to detect and resolve vicarious traumatization in themselves and their supervisees. This article reviews relevant literature on vicarious traumatization and strategies to mitigate it. Also included is a review of the American Counseling Association's (2005)…

Author Detection on a Mobile Phone

DTIC Science & Technology

2011-03-01

handwriting , and to mine sales data for profitable trends. Two broad categories of machine learning are supervised learn- ing and unsupervised learning...evaluation,” AI 2006: Advances in Artificial Intelligence, p. 1015–1021, 2006. [23] “Gartner says worldwide mobile phone sales grew 17 per cent in first

Establishment of a chick embryo shell-less culture system and its use to observe change in behavior caused by nicotine and substances from cigarette smoke.

PubMed

Hamamichi, S; Nishigori, H

2001-02-28

Early detection and removal of harmful factors are essential to the proper physical and psychological development of the fetus, presumably showing the effects during the prenatal period and after birth. As one procedure to aid in understanding such factors, we have established a shell-less culture system for video monitoring to observe change in behavior of 7-day-old chick embryos. Nicotine and aqueous cigarette smoke extract (ACSE) were selected for the present experiments, and the results showed a complete stoppage of swing-like movements by administrations of 10 microg nicotine and 1xACSE, possibly displaying paralytic symptoms. Quantitative analysis of nicotine in 1xACSE indicated that more than 10 microg of nicotine were contained in 100 microl of the extract. The present system, although in initial stage of development, may be a useful preliminary screening procedure for perhaps supervision and warning about the environment surrounding pregnant women.

Land mine detection using multispectral image fusion

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

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-03-29

Our system fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a varietymore » of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts. We use a supervised learning pattern recognition approach to detecting the metal and plastic land mines. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the spectral bands add value to the detection system. The most important features from the various sensors are fused using a supervised learning pattern classifier (the probabilistic neural network). We present results of experiments to detect land mines from real data collected from an airborne platform, and evaluate the usefulness of fusing feature information from multiple spectral bands.« less

Unsupervised detection and removal of muscle artifacts from scalp EEG recordings using canonical correlation analysis, wavelets and random forests.

PubMed

Anastasiadou, Maria N; Christodoulakis, Manolis; Papathanasiou, Eleftherios S; Papacostas, Savvas S; Mitsis, Georgios D

2017-09-01

This paper proposes supervised and unsupervised algorithms for automatic muscle artifact detection and removal from long-term EEG recordings, which combine canonical correlation analysis (CCA) and wavelets with random forests (RF). The proposed algorithms first perform CCA and continuous wavelet transform of the canonical components to generate a number of features which include component autocorrelation values and wavelet coefficient magnitude values. A subset of the most important features is subsequently selected using RF and labelled observations (supervised case) or synthetic data constructed from the original observations (unsupervised case). The proposed algorithms are evaluated using realistic simulation data as well as 30min epochs of non-invasive EEG recordings obtained from ten patients with epilepsy. We assessed the performance of the proposed algorithms using classification performance and goodness-of-fit values for noisy and noise-free signal windows. In the simulation study, where the ground truth was known, the proposed algorithms yielded almost perfect performance. In the case of experimental data, where expert marking was performed, the results suggest that both the supervised and unsupervised algorithm versions were able to remove artifacts without affecting noise-free channels considerably, outperforming standard CCA, independent component analysis (ICA) and Lagged Auto-Mutual Information Clustering (LAMIC). The proposed algorithms achieved excellent performance for both simulation and experimental data. Importantly, for the first time to our knowledge, we were able to perform entirely unsupervised artifact removal, i.e. without using already marked noisy data segments, achieving performance that is comparable to the supervised case. Overall, the results suggest that the proposed algorithms yield significant future potential for improving EEG signal quality in research or clinical settings without the need for marking by expert neurophysiologists, EMG signal recording and user visual inspection. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Mapping decadal land cover changes in the woodlands of north eastern Namibia using the Landsat satellite archive (1975-2014)

NASA Astrophysics Data System (ADS)

Wingate, Vladimir; Phinn, Stuart; Kuhn, Nikolaus

2016-04-01

Woodland savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to intensive land uses. This study investigates the land cover changes over 108,038 km2 in NE Namibia using multi-sensor Landsat imagery, at decadal intervals from 1975 to 2014, with a post-classification change detection method and supervised Regression Tree classifiers. We discuss likely impacts of land tenure and reforms over the past four decades on changes in land use and land cover. These included losses, gains and exchanges between predominant land cover classes. Exchanges comprised logical conversions between woodland and agricultural classes, implying woodland clearing for arable farming, cropland abandonment and vegetation succession. The dominant change was a reduction in the area of the woodland class due to the expansion of the agricultural class, specifically, small-scale cereal and pastoral production. Woodland area decreased from 90% of the study area in 1975 to 83% in 2014, while cleared land increased from 9% to 14%. We found that the main land cover changes are conversion from woodland to agricultural and urban land uses, driven by urban expansion and woodland clearing for subsistence-based agriculture and pastoralism.

The Thai anesthesia incident monitoring study (Thai AIMS): an analysis of perioperative myocardial ischemia/infarction.

PubMed

Ngamprasertwong, Pornswan; Kositanurit, Inthiporn; Yokanit, Preechayuth; Wattanavinit, Rhuthai; Atichat, Sunida; Lapisatepun, Worawut

2008-11-01

To analyze the clinical course, outcome, contributing factors and factors minimizing the incidents of perioperative myocardial ischemia or infarction (PMI) from Thai AIMS study. The present study was a prospective multicenter study. Data was collected from 51 hospitals in Thailand during a six-month period. The participating anesthesia provider completed the standardized incident report form of the Thai AIMS as soon as they found the PMI incident. Each incident was reviewed by three peer reviewers for clinical courses, contributing factors, outcome and minimizing factors of PMI. From the Thai AIMS incident report, the authors found 25 suspected PMI cases which was 0.9% of the 2,669 incidents reported in the present study. Most of the PMI occurred in elective cases (84%) and orthopedic procedures (56%). The majority of PMI was reported from the patients undergoing general anesthesia (72%). Suspected PMI occurred mostly during operations (56%). New ST-T segment change was detected in 92% of these patients. The most common immediate outcome of PMI was major physiological change (88%). The most common management effect of PMI was unplanned ICU admission (64%); the others were prolonged ventilatory support (12%) and prolonged hospital stay (16%). Four patients (16%) died after the suspected PMI. Most of the events occurred spontaneously and were unpreventable (80%). Patient factors (100%), anesthesia factors (72%), surgical factors (32%) and system factors (8%) were all judged as a precipitating factor for PMI. Human factors were the most common contributing factors which included poor preoperative evaluation, inexperience and improper decision. The three most common factors minimizing the adverse incidents included prior experienced, high awareness and experienced assistance. The recommended corrective strategies were guideline practice, quality assurance activity, improvement of supervision and additional training. Perioperative myocardial ischemia/infarction was infrequent but may be lethal. Patient factors were the most common precipitating cause. The morbidity and mortality could be reduced by high quality preoperative evaluation and preparation, early detection and appropriate treatment. Guideline practice, quality assurance activity, improvement of supervision and additional training were suggested corrective strategies.

Compliance with 14-day primaquine therapy for radical cure of vivax malaria--a randomized placebo-controlled trial comparing unsupervised with supervised treatment.

PubMed

Leslie, Toby; Rab, Mohammad Abdur; Ahmadzai, Hayat; Durrani, Naeem; Fayaz, Mohammad; Kolaczinski, Jan; Rowland, Mark

2004-03-01

The only available treatment that can eliminate the latent hypnozoite reservoir of vivax malaria is a 14 d course of primaquine (PQ). A potential problem with long-course chemotherapy is the issue of compliance after clinical symptoms have subsided. The present study, carried out at an Afghan refugee camp in Pakistan, between June 2000 and August 2001, compared 14 d treatment in supervised and unsupervised groups in which compliance was monitored by comparison of relapse rates. Clinical cases recruited by passive case detection were randomised by family to placebo, supervised, or unsupervised groups, and treated with chloroquine (25 mg/kg) over 3 days to eliminate erythrocytic stages. Individuals with glucose-6-phosphate dehydrogenase (G6PD) deficiency were excluded from the trial. Cases allocated to supervision were given directly observed treatment (0.25 mg PQ/kg body weight) once per day for 14 days. Cases allocated to the unsupervised group were provided with 14 PQ doses upon enrollment and strongly advised to complete the course. A total of 595 cases were enrolled. After 9 months of follow up PQ proved equally protective against further episodes of P. vivax in supervised (odds ratio 0.35, 95% CI 0.21-0.57) and unsupervised (odds ratio 0.37, 95% CI 0.23-0.59) groups as compared to placebo. All age groups on supervised or unsupervised treatment showed a similar degree of protection even though the risk of relapse decreased with age. The study showed that a presumed problem of poor compliance may be overcome with simple health messages even when the majority of individuals are illiterate and without formal education. Unsupervised treatment with 14-day PQ when combined with simple instruction can avert a significant amount of the morbidity associated with relapse in populations where G6PD deficiency is either absent or readily diagnosable.

Detecting Virus Exposure During the Pre Symptomatic Incubation Period Using Physiological Data (with Supplementary Materials)

DTIC Science & Technology

2016-06-30

processed the data to reduce short-term variability and normalize diurnal variations , then provided these to a supervised random forest...complementary hypothesis concerning the pathogenesis of multiple organ dysfunction syndrome. Crit Care Med 24: 1107-1116. 61. Goldberger AL, Peng CK

Effectiveness of workplace exercise supervised by a physical therapist among nurses conducting shift work: A randomized controlled trial

PubMed Central

Matsugaki, Ryutaro; Kuhara, Satoshi; Saeki, Satoru; Jiang, Ying; Michishita, Ryoma; Ohta, Masanori; Yamato, Hiroshi

2017-01-01

Objectives: This study aimed to evaluate the effectiveness of supervised exercise among nurses conducting shift work for health promotion. Methods: A total of 30 healthy female nurses conducting shift work participated in this study and they were randomly assigned to one of the following 2 groups: The supervised exercise group (SG; participants exercised under the supervision of a physical therapist (PT)) and the voluntary exercise group (VG; participants exercised without supervision). The study participants were asked to exercise twice/week for 12 weeks for 24 sessions. The primary outcome was aerobic fitness, and the secondary outcomes were muscle strength, anthropometric data, biochemical parameters, and mental health. We compared all the outcomes before and after the intervention within each group and between both groups at follow-up. Results: Aerobic fitness increased in the SG whereas it decreased in the VG, but these changes were not statistically significant (p=0.053 and 0.073, respectively). However, the between-group difference was significant in the intervention effect (p=0.010). Muscle strength, high-density lipoprotein cholesterol and metabolic profile (high-molecular weight adiponectin), and depressive symptom significantly improved in the SG over time, even though the SG exercised less as compared with the VG. Moreover, significant differences in muscle strength, and low-density lipoprotein cholesterol and reactive oxygen metabolite levels were observed between both groups, and these parameters were better in the SG than in the VG. Conclusions: Our data-suggest the effectiveness of exercise supervised by a PT at the workplace of nurses conducting shift work for health promotion. PMID:28638000

Claims to the benefits of clinical supervision: A critique of the policy development process and outcomes in New South Wales, Australia.

PubMed

White, Edward

2017-02-01

The historical development of clinical supervision has been variously interpreted in the international literature. Creditable evidence has accumulated, particularly over the past two decades, to show that clinical supervision has a positive demonstrable effect on supervisees. However, comparatively little research evidence has entered the public domain on any effect that clinical supervision might have on other nominated outcomes. In Australia, developments in clinical supervision were recently prompted by initiatives at national and state levels. Since 2010, lead agencies for these have sought feedback from professional bodies and organizations on a number of inter-related draft policy documents. The present article tracked changes over time between the draft and final versions of these documents in New South Wales, and reviewed the original sources of literature cited within them. The strength of evidence upon which the final published versions were reportedly predicated was scrutinized. Upon examination, claims to the wider benefits of clinical supervision were found to be unconvincingly supported, not least because the examples selected by the agencies from the international literature and cited in their respective documents were either silent, parsimonious, or contradictory. Many claims remain at the level of folklore/hypothetical propositions, therefore, and stay worthy of rigorous empirical testing and faithful public reporting. Such investigations have been acknowledged as notoriously difficult to conduct. The present article identified noteworthy examples in the contemporary literature that signpost robust ways forward for empirical outcomes-orientated research, the findings from which might strengthen the evidence base of future policy documents. © 2017 Australian College of Mental Health Nurses Inc.

Machine learning and next-generation asteroid surveys

NASA Astrophysics Data System (ADS)

Nugent, Carrie R.; Dailey, John; Cutri, Roc M.; Masci, Frank J.; Mainzer, Amy K.

2017-10-01

Next-generation surveys such as NEOCam (Mainzer et al., 2016) will sift through tens of millions of point source detections daily to detect and discover asteroids. This requires new, more efficient techniques to distinguish between solar system objects, background stars and galaxies, and artifacts such as cosmic rays, scattered light and diffraction spikes.Supervised machine learning is a set of algorithms that allows computers to classify data on a training set, and then apply that classification to make predictions on new datasets. It has been employed by a broad range of fields, including computer vision, medical diagnoses, economics, and natural language processing. It has also been applied to astronomical datasets, including transient identification in the Palomar Transient Factory pipeline (Masci et al., 2016), and in the Pan-STARRS1 difference imaging (D. E. Wright et al., 2015).As part of the NEOCam extended phase A work we apply machine learning techniques to the problem of asteroid detection. Asteroid detection is an ideal application of supervised learning, as there is a wealth of metrics associated with each extracted source, and suitable training sets are easily created. Using the vetted NEOWISE dataset (E. L. Wright et al., 2010, Mainzer et al., 2011) as a proof-of-concept of this technique, we applied the python package sklearn. We report on reliability, feature set selection, and the suitability of various algorithms.

SIMPLE MEASURES ARE AS EFFECTIVE AS INVASIVE TECHNIQUES IN THE DIAGNOSIS OF PULMONARY TUBERCULOSIS IN MALAWI

PubMed Central

Bell, David J; Dacombe, Russell; Graham, Stephen M; Hicks, Alexander; Cohen, Danielle; Chikaonda, Tarsizio; French, Neil; Molyneux, Malcolm E; Zijlstra, Ed E; Squire, S Bertel; Gordon, Stephen B

2010-01-01

Setting Detection of smear-positive pulmonary tuberculosis (PTB) cases is vital for tuberculosis control. Methods to augment sputum collection are available but their additional benefit is uncertain in resource-limited settings. Objective To compare the diagnostic yields using five methods to obtain sputum from adults diagnosed with smear-negative PTB in Malawi. Design Self-expectorated sputum was collected under supervision for microscopy and mycobacterial culture in the study laboratory. Confirmed smear-negative patients, provided physiotherapy-assisted sputum and induced sputum followed, the next morning, by gastric washing and bronchoalveolar-lavage samples. Results 150 patients, diagnosed with smear-negative PTB by the hospital service, were screened. 39 (26%) were smear-positive from supervised self-expectorated sputum examined in the study laboratory. The remaining 111 confirmed smear-negative patients were enrolled; 89% were HIV positive. Seven additional smear-positive cases were diagnosed using the augmented sputum collection techniques. No differences were observed in the numbers of cases detected using the different methods. 44 (95.6%) of the 46 smear-positive cases could be detected from self-expectorated and physiotherapy-assisted samples Conclusions For countries like Malawi, the best use of limited resources to detect smear-positive PTB cases would be to improve the quality of self-expectorated sputum collection and microscopy. The additional diagnostic yield using bronchoalveolar-lavage after induced sputum is limited. PMID:19105886

Tacit Knowledge in Military Leadership: Some Research Products and Their Applications to Leadership Development.

DTIC Science & Technology

1998-05-01

credibility Directing and supervising others Managing organizational change Managing the self Cooperating with others Indirect communication and... managing organizational change was unique to our battalion commanders’ stories. We also found that the composition of tacit knowledge about

Molecular imprinted opal closest-packing photonic crystals for the detection of trace 17β-estradiol in aqueous solution.

PubMed

Sai, Na; Wu, Yuntang; Sun, Zhong; Huang, Guowei; Gao, Zhixian

2015-11-01

A novel opal closest-packing (OCP) photonic crystal (PC) was prepared by the introduction of molecular imprinting technique into the OCP PC. This molecular imprinted (MI)-OCP PC was fabricated via a vertical convective self-assembly method using 17β-estradiol (E2) as template molecules for monitoring E2 in aqueous solution. Morphology characterization showed that the MI-OCP PC possessed a highly ordered three-dimensional (3D) periodically-ordered structure, showing the desired structural color. The proposed PC material displayed a reduced reflection intensity when detecting E2 in water environment, because the molecular imprinting recognition events make the optical characteristics of PC change. The Bragg diffraction intensity decreased by 19.864 a.u. with the increase of E2 concentration from 1.5 ng mL(-1) to 364.5 ng mL(-1) within 6 min, whereas there were no obvious peak intensity changes for estriol, estrone, cholesterol, testosterone and diethylstilbestrol, indicating that the MI-OCP PC had selective and rapid response for E2 molecules. The adsorption results showed that the OCP structure and homogeneous layers were created in the MI-OCP PC with higher adsorption capacity. Thus, it was learned the MI-OCP PC is a simple prepared, sensitive, selective, and easy operative material, which shows promising use in routine supervision for residue detection in food and environment. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of an Indicator to Monitor Mediterranean Wetlands

PubMed Central

Sanchez, Antonio; Abdul Malak, Dania; Guelmami, Anis; Perennou, Christian

2015-01-01

Wetlands are sensitive ecosystems that are increasingly subjected to threats from anthropogenic factors. In the last decades, coastal Mediterranean wetlands have been suffering considerable pressures from land use change, intensification of urban growth, increasing tourism infrastructure and intensification of agricultural practices. Remote sensing (RS) and Geographic Information Systems (GIS) techniques are efficient tools that can support monitoring Mediterranean coastal wetlands on large scales and over long periods of time. The study aims at developing a wetland indicator to support monitoring Mediterranean coastal wetlands using these techniques. The indicator makes use of multi-temporal Landsat images, land use reference layers, a 50m numerical model of the territory (NMT) and Corine Land Cover (CLC) for the identification and mapping of wetlands. The approach combines supervised image classification techniques making use of vegetation indices and decision tree analysis to identify the surface covered by wetlands at a given date. A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability. The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas. The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered. PMID:25826210

Development of an indicator to monitor mediterranean wetlands.

PubMed

Sanchez, Antonio; Abdul Malak, Dania; Guelmami, Anis; Perennou, Christian

2015-01-01

Wetlands are sensitive ecosystems that are increasingly subjected to threats from anthropogenic factors. In the last decades, coastal Mediterranean wetlands have been suffering considerable pressures from land use change, intensification of urban growth, increasing tourism infrastructure and intensification of agricultural practices. Remote sensing (RS) and Geographic Information Systems (GIS) techniques are efficient tools that can support monitoring Mediterranean coastal wetlands on large scales and over long periods of time. The study aims at developing a wetland indicator to support monitoring Mediterranean coastal wetlands using these techniques. The indicator makes use of multi-temporal Landsat images, land use reference layers, a 50m numerical model of the territory (NMT) and Corine Land Cover (CLC) for the identification and mapping of wetlands. The approach combines supervised image classification techniques making use of vegetation indices and decision tree analysis to identify the surface covered by wetlands at a given date. A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability. The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas. The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered.

Learned filters for object detection in multi-object visual tracking

NASA Astrophysics Data System (ADS)

Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

2016-05-01

We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

Arthroscopic surgery compared with supervised exercises in patients with rotator cuff disease (stage II impingement syndrome)

PubMed Central

Brox, J I; Staff, P H; Ljunggren, A E; Brevik, J I

1993-01-01

OBJECTIVE--To compare the effectiveness of arthroscopic surgery, a supervised exercise regimen, and placebo soft laser treatment in patients with rotator cuff disease (stage II impingement syndrome). DESIGN--Randomised clinical trial. SETTING--Hospital departments of orthopaedics and of physical medicine and rehabilitation. PATIENTS--125 patients aged 18-66 who had had rotator cuff disease for at least three months and whose condition was resistant to treatment. INTERVENTIONS--Arthroscopic subacromial decompression performed by two experienced surgeons; exercise regimen over three to six months supervised by one experienced physiotherapist; or 12 sessions of detuned soft laser treatment over six weeks. MAIN OUTCOME MEASURES--Change in the overall Neer shoulder score (pain during previous week and blinded evaluation of function and range of movement by one clinician) after six months. RESULTS--No differences were found between the three groups in duration of sick leave and daily intake of analgesics. After six months the difference in improvement in overall Neer score between surgery and supervised exercises was 4.0 (95% confidence interval -2 to 11) and 2.0 (-1.4 to 5.4) after adjustment for sex. The condition improved significantly compared with placebo in both groups given the active treatments. Treatment costs were higher for those given surgery (720 pounds v 390 pounds). CONCLUSIONS--Surgery or a supervised exercise regimen significantly, and equally, improved rotator cuff disease compared with placebo. PMID:8241852

Improving quality of reproductive health care in Senegal through formative supervision: results from four districts.

PubMed

Suh, Siri; Moreira, Philippe; Ly, Moussa

2007-11-29

In Senegal, traditional supervision often focuses more on collection of service statistics than on evaluation of service quality. This approach yields limited information on quality of care and does little to improve providers' competence. In response to this challenge, Management Sciences for Health (MSH) has implemented a program of formative supervision. This multifaceted, problem-solving approach collects data on quality of care, improves technical competence, and engages the community in improving reproductive health care. This study evaluated changes in service quality and community involvement after two rounds of supervision in 45 health facilities in four districts of Senegal. We used checklists to assess quality in four areas of service delivery: infrastructure, staff and services management, record-keeping, and technical competence. We also measured community involvement in improving service quality using the completion rates of action plans. The most notable improvement across regions was in infection prevention.Management of staff, services, and logistics also consistently improved across the four districts. Record-keeping skills showed variable but lower improvement by region. The completion rates of action plans suggest that communities are engaged in improving service quality in all four districts. Formative supervision can improve the quality of reproductive health services, especially in areas where there is on-site skill building and refresher training. This approach can also mobilize communities to participate in improving service quality.

Improving quality of reproductive health care in Senegal through formative supervision: results from four districts

PubMed Central

Suh, Siri; Moreira, Philippe; Ly, Moussa

2007-01-01

Background In Senegal, traditional supervision often focuses more on collection of service statistics than on evaluation of service quality. This approach yields limited information on quality of care and does little to improve providers' competence. In response to this challenge, Management Sciences for Health (MSH) has implemented a program of formative supervision. This multifaceted, problem-solving approach collects data on quality of care, improves technical competence, and engages the community in improving reproductive health care. Methods This study evaluated changes in service quality and community involvement after two rounds of supervision in 45 health facilities in four districts of Senegal. We used checklists to assess quality in four areas of service delivery: infrastructure, staff and services management, record-keeping, and technical competence. We also measured community involvement in improving service quality using the completion rates of action plans. Results The most notable improvement across regions was in infection prevention. Management of staff, services, and logistics also consistently improved across the four districts. Record-keeping skills showed variable but lower improvement by region. The completion rates of action plans suggest that communities are engaged in improving service quality in all four districts. Conclusion Formative supervision can improve the quality of reproductive health services, especially in areas where there is on-site skill building and refresher training. This approach can also mobilize communities to participate in improving service quality. PMID:18047678

Influence of regular exercise on body fat and eating patterns of patients with intermittent claudication.

PubMed

Leicht, Anthony; Crowther, Robert; Golledge, Jonathan

2015-05-18

This study examined the impact of regular supervised exercise on body fat, assessed via anthropometry, and eating patterns of peripheral arterial disease patients with intermittent claudication (IC). Body fat, eating patterns and walking ability were assessed in 11 healthy adults (Control) and age- and mass-matched IC patients undertaking usual care (n = 10; IC-Con) or supervised exercise (12-months; n = 10; IC-Ex). At entry, all groups exhibited similar body fat and eating patterns. Maximal walking ability was greatest for Control participants and similar for IC-Ex and IC-Con patients. Supervised exercise resulted in significantly greater improvements in maximal walking ability (IC-Ex 148%-170% vs. IC-Con 29%-52%) and smaller increases in body fat (IC-Ex -2.1%-1.4% vs. IC-Con 8.4%-10%). IC-Con patients exhibited significantly greater increases in body fat compared with Control at follow-up (8.4%-10% vs. -0.6%-1.4%). Eating patterns were similar for all groups at follow-up. The current study demonstrated that regular, supervised exercise significantly improved maximal walking ability and minimised increase in body fat amongst IC patients without changes in eating patterns. The study supports the use of supervised exercise to minimize cardiovascular risk amongst IC patients. Further studies are needed to examine the additional value of other lifestyle interventions such as diet modification.

Staff supervision in residential care.

PubMed

Myers, Peter G; Bibbs, Tonya; Orozco, Candy

2004-04-01

Residential care workers must be offered opportunities for formalized and systematic supervision in individual and group formats to provide the highest possible level of care to children and adolescents whom they serve. Effective supervision with residential care staff should be open to exploring issues at all levels of their experience and in relation to each component of the broader organizational structure within which they work. Systems theory offers a useful lens through which to view supervising staff in residential treatment. Systems theory proposes that human behavior is shaped by interactional processes and internal factors. Although the development of the individual occurs within intrinsic cognitive and emotional spheres, it also is believed to be related to several other elements. These additional variables include the point at which the family and system function in their own life cycle, the historical and current emotional context, the current and changing structure of the system, narratives, and the cultural context. This article discussed how methods of training and supervision would be most effective if they were designed specifically for the developmental level of the participants. Some literature reviews have concluded that youth care workers, like all professionals, pass through developmental stages and progress through them in their work. To assist youth care workers in their jobs, supervisors must understand these stages and the ways in which they may be enacted in the workplace.

Nursing leadership from the perspective of clinical group supervision: a paradoxical practice.

PubMed

Bondas, Terese

2010-05-01

Increase understanding of nursing leadership in group clinical supervision (CS). Leadership in CS has received little interest besides the theories in use and administrative CS. Hermeneutic interpretation of written narratives of 24 clinical nurse supervisors. Continuity in structuring, story and mission and reflection in group and leadership processes and theories of nursing and caring characterize leadership in CS. Leadership by inhibiting and creating fear, inapproachability and indistinctiveness were patterns in content brought to CS. Supervision when leadership was involved illuminated a reflexive change in focus from leadership to nursing care, from particular experiences to nursing and caring science, and from the unfamiliar to the well known and the well known to the unknown. Continuity and reflective changes using nursing and caring theories seem to be core ideas of nursing leadership from the perspective of CS. The poles of separation and communion show opposites of nursing leadership as it is illuminated in CS. The findings add knowledge to Bondas' theory of caritative leadership. CS is a reflexive practice of support and guidance that seems to have an impact on the trajectory of nursing care and staff development using nursing and caring theories.

Is there a doctor in the house? : The presence of physicians in the direct-to-consumer genetic testing context.

PubMed

Howard, Heidi Carmen; Borry, Pascal

2012-04-01

Over the last couple of years, many commercial companies, the majority of which are based in the USA, have been advertising and offering direct-to-consumer (DTC) genetic testing services outside of the established health care system, and often without any involvement from a health care professional. In the last year, however, a number of DTC genetic testing companies have changed their provision model such that consumers must now contact a health care professional before being able to order the genetic testing service. In discussing the advent of this new model of service provision, this article also reviews the ethical and social issues surrounding DTC genetic testing and addresses the potential motivations for change, some barriers to achieving truly appropriate medical supervision and the present reality of DTC genetic testing for some psychiatric and neurological disorders. Since the advent of these commercial activities, critics have pointed a finger at the lack of medical supervision surrounding these services. The discussion herein, however, reveals how difficult it may be, despite the addition of a physician, to actually achieve adequate medical supervision within the present context of DTC genetic testing.

Changes in Perceived Supervision Quality After Introduction of Competency-Based Orthopedic Residency Training: A National 6-Year Follow-Up Study.

PubMed

van Vendeloo, Stefan N; Brand, Paul L P; Kollen, Boudewijn J; Verheyen, Cees C P M

2018-04-27

To evaluate the perceived quality of the learning environment, before and after introduction of competency-based postgraduate orthopedic education. From 2009 to 2014, we conducted annual surveys among Dutch orthopedic residents. The validated Dutch Residency Educational Climate Test (D-RECT, 50 items on 11 subscales) was used to assess the quality of the learning environment. Scores range from 1 (poor) to 5 (excellent). Dynamic cohort follow-up study. All Dutch orthopedic residents were surveyed during annual compulsory courses. Over the 6-year period, 641 responses were obtained (response rate 92%). Scores for "supervision" (95% CI for difference 0.06-0.28, p = 0.002) and "coaching and assessment" (95% CI 0.11-0.35, p < 0.001) improved significantly after introduction of competency-based training. There was no significant change in score on the other subscales of the D-RECT. After the introduction of some of the core components of competency-based postgraduate orthopedic education the perceived quality of "supervision" and "coaching and assessment" improved significantly. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Moving Away from Social Work and Half Way Back Again: New Research on Skills in Probation

PubMed Central

Raynor, Peter; Vanstone, Maurice

2016-01-01

Research on social work in the criminal justice system was well represented in the social work literature until the 1990s. Since then, changes in the organisation, training and research base of probation practice, particularly in England and Wales, have all contributed to a separation between probation research and the mainstream social work research literature. However, recent probation research, by focusing on individual practice skills and on the quality of relationships, is producing findings which resonate with traditional social work concerns. The study presented here, based on analysis of videotaped interviews between probation staff and the people they are supervising, shows what skills are used and the effects of skilled supervision. People supervised by more skilled staff were significantly less likely to be reconvicted over a two-year follow-up, and the most effective supervisors combined good relationship skills with a range of ‘structuring’ or change-promoting skills. In effect, this can be regarded as a test of the impact of social work skills used by probation staff and suggests that a closer relationship between mainstream social work research and probation research could be productive for both. PMID:27559218

Sensor feature fusion for detecting buried objects

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-04-01

Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in amore » two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.« less

Medically supervised water-only fasting in the treatment of borderline hypertension.

PubMed

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.

76 FR 7629 - Interagency Notice of Change in Control

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-10

... DEPARTMENT OF THE TREASURY Office of Thrift Supervision Interagency Notice of Change in Control... information collection displays a currently valid OMB control number. As part of the approval process, we... in Control. OMB Number: 1550-0032. Form Number: 1622. Description: The Regional Office must review...

STRATEGIES FOR INSTRUCTIONAL CHANGE--PROMISING IDEAS AND PERPLEXING PROBLEMS.

ERIC Educational Resources Information Center

HARRIS, BEN M.

SUPERVISION, BECAUSE IT COVERS A MULTIPLICITY OF TASKS PERFORMED IN NO FIXED LOCUS, ITS ALMOST IMMUNE TO SYSTEMATIC EVALUATION. ELABORATE DESCRIPTIVE STUDIES ARE NEEDED (POSSIBLY REPLICATIONS OF EDUCATIONAL ADMINISTRATION STUDIES) ON SUCH TOPICS AS RESISTANCE TO CHANGE AND SUPERVISOR-SUPERVISOR RELATIONSHIPS. THEORETICAL MODELS AND CONCEPTS WHICH…

Observing Change in the Family Therapy Supervisory Relationship.

ERIC Educational Resources Information Center

Moy, Caryl T.; Goodman, Earl O.

A common assumption in family therapy supervision is that the relationship between supervisor and supervisee changes over time, following a developmental continuum from the tentative competency of the supervisee as a therapist to relative competency. In particular, Ard (1973) theorizes that supervisees and supervisors move steadily together…

12 CFR 571.91 - Duties of card issuers regarding changes of address.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 5 2011-01-01 2011-01-01 false Duties of card issuers regarding changes of address. 571.91 Section 571.91 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FAIR CREDIT REPORTING Identity Theft Red Flags § 571.91 Duties of card issuers regarding changes of...

Effectiveness of additional supervised exercises compared with conventional treatment alone in patients with acute lateral ankle sprains: systematic review

PubMed Central

van Ochten, John; Luijsterburg, Pim A J; van Middelkoop, Marienke; Koes, Bart W; Bierma-Zeinstra, Sita M A

2010-01-01

Objective To summarise the effectiveness of adding supervised exercises to conventional treatment compared with conventional treatment alone in patients with acute lateral ankle sprains. Design Systematic review. Data sources Medline, Embase, Cochrane Central Register of Controlled Trials, Cinahl, and reference screening. Study selection Included studies were randomised controlled trials, quasi-randomised controlled trials, or clinical trials. Patients were adolescents or adults with an acute lateral ankle sprain. The treatment options were conventional treatment alone or conventional treatment combined with supervised exercises. Two reviewers independently assessed the risk of bias, and one reviewer extracted data. Because of clinical heterogeneity we analysed the data using a best evidence synthesis. Follow-up was classified as short term (up to two weeks), intermediate (two weeks to three months), and long term (more than three months). Results 11 studies were included. There was limited to moderate evidence to suggest that the addition of supervised exercises to conventional treatment leads to faster and better recovery and a faster return to sport at short term follow-up than conventional treatment alone. In specific populations (athletes, soldiers, and patients with severe injuries) this evidence was restricted to a faster return to work and sport only. There was no strong evidence of effectiveness for any of the outcome measures. Most of the included studies had a high risk of bias, with few having adequate statistical power to detect clinically relevant differences. Conclusion Additional supervised exercises compared with conventional treatment alone have some benefit for recovery and return to sport in patients with ankle sprain, though the evidence is limited or moderate and many studies are subject to bias. PMID:20978065

Evolution of Controllability in Interbank Networks

NASA Astrophysics Data System (ADS)

Delpini, Danilo; Battiston, Stefano; Riccaboni, Massimo; Gabbi, Giampaolo; Pammolli, Fabio; Caldarelli, Guido

2013-04-01

The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected ``hub'' institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies.

Detecting brain tumor in pathological slides using hyperspectral imaging

PubMed Central

Ortega, Samuel; Fabelo, Himar; Camacho, Rafael; de la Luz Plaza, María; Callicó, Gustavo M.; Sarmiento, Roberto

2018-01-01

Hyperspectral imaging (HSI) is an emerging technology for medical diagnosis. This research work presents a proof-of-concept on the use of HSI data to automatically detect human brain tumor tissue in pathological slides. The samples, consisting of hyperspectral cubes collected from 400 nm to 1000 nm, were acquired from ten different patients diagnosed with high-grade glioma. Based on the diagnosis provided by pathologists, a spectral library of normal and tumor tissues was created and processed using three different supervised classification algorithms. Results prove that HSI is a suitable technique to automatically detect high-grade tumors from pathological slides. PMID:29552415

Detecting brain tumor in pathological slides using hyperspectral imaging.

PubMed

Ortega, Samuel; Fabelo, Himar; Camacho, Rafael; de la Luz Plaza, María; Callicó, Gustavo M; Sarmiento, Roberto

2018-02-01

Hyperspectral imaging (HSI) is an emerging technology for medical diagnosis. This research work presents a proof-of-concept on the use of HSI data to automatically detect human brain tumor tissue in pathological slides. The samples, consisting of hyperspectral cubes collected from 400 nm to 1000 nm, were acquired from ten different patients diagnosed with high-grade glioma. Based on the diagnosis provided by pathologists, a spectral library of normal and tumor tissues was created and processed using three different supervised classification algorithms. Results prove that HSI is a suitable technique to automatically detect high-grade tumors from pathological slides.

A blended supervision model in Australian general practice training.

PubMed

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.

Involvement of surgical trainees in surgery for colorectal cancer and their effect on outcome.

PubMed

Borowski, D W; Ratcliffe, A A; Bharathan, B; Gunn, A; Bradburn, D M; Mills, S J; Wilson, R G; Kelly, S B

2008-10-01

Surgical training in the UK is undergoing substantial changes. This study assessed: 1) the training opportunities available to trainees in operations for colorectal cancer, 2) the effect of colorectal specialization on training, and 3) the effect of consultant supervision on anastomotic complications, postoperative stay, operative mortality and 5-year survival. Unadjusted and adjusted comparisons of outcomes were made for unsupervised trainees, supervised trainees and consultants as the primary surgeon in 7411 operated patients included in the Northern Region Colorectal Cancer Audit between 1998 and 2002. Surgery was performed in 656 (8.8%) patients by unsupervised trainees and in 1578 (21.3%) patients by supervised trainees. Unsupervised operations reduced from 182 (12.4%) in 1998 to 82 (6.1%) in 2002 (P < 0.001). Consultants with a colorectal specialist interest were more likely than nonspecialists to be present at surgical resections (OR 1.35, 1.12-1.63, P = 0.001) and to provide supervised training (OR 1.34, 1.17-1.53, P < 0.001). Patients operated on by unsupervised trainees were more often high-risk patients, however, consultant presence was not significantly associated with operative mortality (OR 0.83, 0.63-1.09, P = 0.186) or survival (HR 1.02, 0.92-1.13, P = 0.735) in risk-adjusted analysis. Supervised trainees had a case-mix similar to consultants, with shorter length of hospital stay (11.4 vs 12.4 days, P < 0.001), but similar mortality (OR 0.90, 0.71-1.16, 0.418) and survival (HR 0.96, 0.89-1.05, P = 0.378). One third of patients were operated on by trainees, who were more likely to perform supervised resections in colorectal teams. There was no difference in anastomotic leaks rates, operative mortality or survival between unsupervised trainees, supervised trainees and consultants when case-mix adjustment was applied. This study would suggest that there is considerable underused training capacity available.

[Professional Development Processes of Trainee and Experienced Psychotherapists in Turkey].

PubMed

Bilican, F Işıl; Soygüt, Gonca

2015-01-01

This study explored professional characteristics of psychotherapists in Turkey, examined the changes in their professional developmental processes, and compared the professional characteristics of the trainees and experienced therapists. The participants were 88 psychotherapists, including trainee (N=37) and experienced (N=51) psychotherapists in Turkey. They completed the Development of Psychotherapists International Study-Common Core Questionnaire (DPCCQ), developed by the Collaborative Research Network. The participants identified with the cognitive theoretical orientation most often. 30% of the participants had more than two salient orientations. The most prevalent therapy modality was individual, followed by couples, family, and group psychotherapy. Ongoing supervision rate was 44%. Trainees scored lower on effectiveness in engaging patients in a working alliance, feeling natural while working with patients, effectiveness in communicating their understanding and concern to their patients, and feeling confident in their role as a therapist. Experienced therapists made changes in the therapeutic contract and invited collaboration from families more compared to the trainees. 63% of the variance in Healing Involvement was explained by Overall Career Development, Currently Experienced Growth, being influenced by the humanistic approach, and the impact of the main therapeutic environment; 26% of the variance in Stressful Involvement was explained by the length of official supervision received and having control over the length of therapy sessions. Therapists were more cognitively oriented, less eclectic, and had less supervision compared to their international counterparts. Experienced therapists were more flexible, natural, and confident than the trainees. Supervision, a supportive work environment, the humanistic approach, and investing in career development were essential to providing a healing experience.

If training data appears to be mislabeled, should we relabel it? Improving supervised learning algorithms for threat detection in ground penetrating radar data

NASA Astrophysics Data System (ADS)

Reichman, Daniël.; Collins, Leslie M.; Malof, Jordan M.

2018-04-01

This work focuses on the development of automatic buried threat detection (BTD) algorithms using ground penetrating radar (GPR) data. Buried threats tend to exhibit unique characteristics in GPR imagery, such as high energy hyperbolic shapes, which can be leveraged for detection. Many recent BTD algorithms are supervised, and therefore they require training with exemplars of GPR data collected over non-threat locations and threat locations, respectively. Frequently, data from non-threat GPR examples will exhibit high energy hyperbolic patterns, similar to those observed from a buried threat. Is it still useful therefore, to include such examples during algorithm training, and encourage an algorithm to label such data as a non-threat? Similarly, some true buried threat examples exhibit very little distinctive threat-like patterns. We investigate whether it is beneficial to treat such GPR data examples as mislabeled, and either (i) relabel them, or (ii) remove them from training. We study this problem using two algorithms to automatically identify mislabeled examples, if they are present, and examine the impact of removing or relabeling them for training. We conduct these experiments on a large collection of GPR data with several state-of-the-art GPR-based BTD algorithms.

Extracting and summarizing white matter hyperintensities using supervised segmentation methods in Alzheimer's disease risk and aging studies.

PubMed

Ithapu, Vamsi; Singh, Vikas; Lindner, Christopher; Austin, Benjamin P; Hinrichs, Chris; Carlsson, Cynthia M; Bendlin, Barbara B; Johnson, Sterling C

2014-08-01

Precise detection and quantification of white matter hyperintensities (WMH) observed in T2-weighted Fluid Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Images (MRI) is of substantial interest in aging, and age-related neurological disorders such as Alzheimer's disease (AD). This is mainly because WMH may reflect co-morbid neural injury or cerebral vascular disease burden. WMH in the older population may be small, diffuse, and irregular in shape, and sufficiently heterogeneous within and across subjects. Here, we pose hyperintensity detection as a supervised inference problem and adapt two learning models, specifically, Support Vector Machines and Random Forests, for this task. Using texture features engineered by texton filter banks, we provide a suite of effective segmentation methods for this problem. Through extensive evaluations on healthy middle-aged and older adults who vary in AD risk, we show that our methods are reliable and robust in segmenting hyperintense regions. A measure of hyperintensity accumulation, referred to as normalized effective WMH volume, is shown to be associated with dementia in older adults and parental family history in cognitively normal subjects. We provide an open source library for hyperintensity detection and accumulation (interfaced with existing neuroimaging tools), that can be adapted for segmentation problems in other neuroimaging studies. Copyright © 2014 Wiley Periodicals, Inc.

Supervised resistance training results in changes in postural control in patients with multiple sclerosis.

PubMed

Huisinga, Jessie M; Filipi, Mary L; Stergiou, Nicholas

2012-01-01

Postural disturbances are one of the first reported symptoms in patients with Multiple Sclerosis (MS). The purpose of this study was to investigate the effect of supervised resistance training on postural control in MS patients. Postural control was assessed using amount of sway variability [Root Mean Square (RMS)] and temporal structure of sway variability [Lyapunov Exponent (LyE)] from 15 MS patients. Posture was evaluated before and after completion of three months of resistance training. There were significant differences between MS patients pretraining and healthy controls for both LyE (p = .000) and RMS (p = .002), but no differences between groups after training. There was a significant decrease in RMS (p = .025) and a significant increase in LyE (p = .049) for MS patients pre- to posttraining. The findings suggested that postural control of MS patients could be affected by a supervised resistance training intervention.

25 CFR 173.11 - Supervision of permittees' rates.

Code of Federal Regulations, 2013 CFR

2013-04-01

... Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER CONCESSIONS, PERMITS AND... two conspicuous places on the premises. Approved rates may not be changed without first obtaining in the same manner a change in the rate schedule. The Secretary shall have the right to readjust rates...

Elementary Administrators' Mathematics Supervision and Self-Efficacy Development

ERIC Educational Resources Information Center

Johnson, Kelly M. Gomez

2017-01-01

Mathematics curriculum reform is changing the content and resources in today's elementary classrooms as well as the culture of mathematics teaching and learning. Administrators face the challenge of leading large-scale curricular change efforts with limited prior knowledge or experiences with reform curricula structures. Administrators, as the…

Supervising Doctoral Students: Variation in Purpose and Pedagogy

ERIC Educational Resources Information Center

Åkerlind, Gerlese; McAlpine, Lynn

2017-01-01

International policy changes that have prioritised increasing growth in the numbers of doctoral students have led to wide-ranging debate about the changing purpose of the doctorate. However, there has been little research aimed at investigating doctoral supervisors' views of the purpose of the doctorate, despite the significant role supervisors…

Detecting Targeted Malicious Email through Supervised Classification of Persistent Threat and Recipient Oriented Features

ERIC Educational Resources Information Center

Amin, Rohan Mahesh

2010-01-01

Targeted email attacks to enable computer network exploitation have become more prevalent, more insidious, and more widely documented in recent years. Beyond nuisance spam or phishing designed to trick users into revealing personal information, targeted malicious email (TME) facilitates computer network exploitation and the gathering of sensitive…

Understanding Discourse on Work and Job-Related Well-Being in Public Social Media

PubMed Central

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

Considering Alternate Futures to Classify Off-Task Behavior as Emotion Self-Regulation: A Supervised Learning Approach

ERIC Educational Resources Information Center

Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C.

2013-01-01

Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…

“SmartMonitor” — An Intelligent Security System for the Protection of Individuals and Small Properties with the Possibility of Home Automation

PubMed Central

Frejlichowski, Dariusz; Gościewska, Katarzyna; Forczmański, Paweł; Hofman, Radosław

2014-01-01

“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. PMID:24905854

Comparing automated classification and digitization approaches to detect change in eelgrass bed extent during restoration of a large river delta

USGS Publications Warehouse

Davenport, Anna Elizabeth; Davis, Jerry D.; Woo, Isa; Grossman, Eric; Barham, Jesse B.; Ellings, Christopher S.; Takekawa, John Y.

2017-01-01

Native eelgrass (Zostera marina) is an important contributor to ecosystem services that supplies cover for juvenile fish, supports a variety of invertebrate prey resources for fish and waterbirds, provides substrate for herring roe consumed by numerous fish and birds, helps stabilize sediment, and sequesters organic carbon. Seagrasses are in decline globally, and monitoring changes in their growth and extent is increasingly valuable to determine impacts from large-scale estuarine restoration and inform blue carbon mapping initiatives. Thus, we examined the efficacy of two remote sensing mapping methods with high-resolution (0.5 m pixel size) color near infrared imagery with ground validation to assess change following major tidal marsh restoration. Automated classification of false color aerial imagery and digitized polygons documented a slight decline in eelgrass area directly after restoration followed by an increase two years later. Classification of sparse and low to medium density eelgrass was confounded in areas with algal cover, however large dense patches of eelgrass were well delineated. Automated classification of aerial imagery from unsupervised and supervised methods provided reasonable accuracies of 73% and hand-digitizing polygons from the same imagery yielded similar results. Visual clues for hand digitizing from the high-resolution imagery provided as reliable a map of dense eelgrass extent as automated image classification. We found that automated classification had no advantages over manual digitization particularly because of the limitations of detecting eelgrass with only three bands of imagery and near infrared.

Exercise training for intermittent claudication.

PubMed

McDermott, Mary M

2017-11-01

The objective of this study was to provide an overview of evidence regarding exercise therapies for patients with lower extremity peripheral artery disease (PAD). This manuscript summarizes the content of a lecture delivered as part of the 2016 Crawford Critical Issues Symposium. Multiple randomized clinical trials demonstrate that supervised treadmill exercise significantly improves treadmill walking performance in people with PAD and intermittent claudication symptoms. A meta-analysis of 25 randomized trials demonstrated a 180-meter increase in treadmill walking distance in response to supervised exercise interventions compared with a nonexercising control group. Supervised treadmill exercise has been inaccessible to many patients with PAD because of lack of medical insurance coverage. However, in 2017, the Centers for Medicare and Medicaid Services issued a decision memorandum to support health insurance coverage of 12 weeks of supervised treadmill exercise for patients with walking impairment due to PAD. Recent evidence also supports home-based walking exercise to improve walking performance in people with PAD. Effective home-exercise programs incorporate behavioral change interventions such as a remote coach, goal setting, and self-monitoring. Supervised treadmill exercise programs preferentially improve treadmill walking performance, whereas home-based walking exercise programs preferentially improve corridor walking, such as the 6-minute walk test. Clinical trial evidence also supports arm or leg ergometry exercise to improve walking endurance in people with PAD. Treadmill walking exercise appears superior to resistance training alone for improving walking endurance. Supervised treadmill exercise significantly improves treadmill walking performance in people with PAD by approximately 180 meters compared with no exercise. Recent evidence suggests that home-based exercise is also effective and preferentially improves over-ground walking performance, such as the 6-minute walk test. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Supervised multimedia categorization

NASA Astrophysics Data System (ADS)

Aldershoff, Frank; Salden, Alfons H.; Iacob, Sorin M.; Kempen, Masja

2003-01-01

Static multimedia on the Web can already be hardly structured manually. Although unavoidable and necessary, manual annotation of dynamic multimedia becomes even less feasible when multimedia quickly changes in complexity, i.e. in volume, modality, and usage context. The latter context could be set by learning or other purposes of the multimedia material. This multimedia dynamics calls for categorisation systems that index, query and retrieve multimedia objects on the fly in a similar way as a human expert would. We present and demonstrate such a supervised dynamic multimedia object categorisation system. Our categorisation system comes about by continuously gauging it to a group of human experts who annotate raw multimedia for a certain domain ontology given a usage context. Thus effectively our system learns the categorisation behaviour of human experts. By inducing supervised multi-modal content and context-dependent potentials our categorisation system associates field strengths of raw dynamic multimedia object categorisations with those human experts would assign. After a sufficient long period of supervised machine learning we arrive at automated robust and discriminative multimedia categorisation. We demonstrate the usefulness and effectiveness of our multimedia categorisation system in retrieving semantically meaningful soccer-video fragments, in particular by taking advantage of multimodal and domain specific information and knowledge supplied by human experts.

Neutral face classification using personalized appearance models for fast and robust emotion detection.

PubMed

Chiranjeevi, Pojala; Gopalakrishnan, Viswanath; Moogi, Pratibha

2015-09-01

Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning-based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, and so on, in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as user stays neutral for majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this paper, we propose a light-weight neutral versus emotion classification engine, which acts as a pre-processer to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at key emotion (KE) points using a statistical texture model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a statistical texture model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves emotion recognition (ER) accuracy and simultaneously reduces computational complexity of the ER system, as validated on multiple databases.

Infrared small target detection with kernel Fukunaga Koontz transform

NASA Astrophysics Data System (ADS)

Liu, Rui-ming; Liu, Er-qi; Yang, Jie; Zhang, Tian-hao; Wang, Fang-lin

2007-09-01

The Fukunaga-Koontz transform (FKT) has been proposed for many years. It can be used to solve two-pattern classification problems successfully. However, there are few researchers who have definitely extended FKT to kernel FKT (KFKT). In this paper, we first complete this task. Then a method based on KFKT is developed to detect infrared small targets. KFKT is a supervised learning algorithm. How to construct training sets is very important. For automatically detecting targets, the synthetic target images and real background images are used to train KFKT. Because KFKT can represent the higher order statistical properties of images, we expect better detection performance of KFKT than that of FKT. The well-devised experiments verify that KFKT outperforms FKT in detecting infrared small targets.

Detection of gear cracks in a complex gearbox of wind turbines using supervised bounded component analysis of vibration signals collected from multi-channel sensors

NASA Astrophysics Data System (ADS)

Li, Zhixiong; Yan, Xinping; Wang, Xuping; Peng, Zhongxiao

2016-06-01

In the complex gear transmission systems, in wind turbines a crack is one of the most common failure modes and can be fatal to the wind turbine power systems. A single sensor may suffer with issues relating to its installation position and direction, resulting in the collection of weak dynamic responses of the cracked gear. A multi-channel sensor system is hence applied in the signal acquisition and the blind source separation (BSS) technologies are employed to optimally process the information collected from multiple sensors. However, literature review finds that most of the BSS based fault detectors did not address the dependence/correlation between different moving components in the gear systems; particularly, the popular used independent component analysis (ICA) assumes mutual independence of different vibration sources. The fault detection performance may be significantly influenced by the dependence/correlation between vibration sources. In order to address this issue, this paper presents a new method based on the supervised order tracking bounded component analysis (SOTBCA) for gear crack detection in wind turbines. The bounded component analysis (BCA) is a state of art technology for dependent source separation and is applied limitedly to communication signals. To make it applicable for vibration analysis, in this work, the order tracking has been appropriately incorporated into the BCA framework to eliminate the noise and disturbance signal components. Then an autoregressive (AR) model built with prior knowledge about the crack fault is employed to supervise the reconstruction of the crack vibration source signature. The SOTBCA only outputs one source signal that has the closest distance with the AR model. Owing to the dependence tolerance ability of the BCA framework, interfering vibration sources that are dependent/correlated with the crack vibration source could be recognized by the SOTBCA, and hence, only useful fault information could be preserved in the reconstructed signal. The crack failure thus could be precisely identified by the cyclic spectral correlation analysis. A series of numerical simulations and experimental tests have been conducted to illustrate the advantages of the proposed SOTBCA method for fatigue crack detection. Comparisons to three representative techniques, i.e. Erdogan's BCA (E-BCA), joint approximate diagonalization of eigen-matrices (JADE), and FastICA, have demonstrated the effectiveness of the SOTBCA. Hence the proposed approach is suitable for accurate gear crack detection in practical applications.

Colorectal cancer detection by hyperspectral imaging using fluorescence excitation scanning

NASA Astrophysics Data System (ADS)

Leavesley, Silas J.; Deal, Joshua; Hill, Shante; Martin, Will A.; Lall, Malvika; Lopez, Carmen; Rider, Paul F.; Rich, Thomas C.; Boudreaux, Carole W.

2018-02-01

Hyperspectral imaging technologies have shown great promise for biomedical applications. These techniques have been especially useful for detection of molecular events and characterization of cell, tissue, and biomaterial composition. Unfortunately, hyperspectral imaging technologies have been slow to translate to clinical devices - likely due to increased cost and complexity of the technology as well as long acquisition times often required to sample a spectral image. We have demonstrated that hyperspectral imaging approaches which scan the fluorescence excitation spectrum can provide increased signal strength and faster imaging, compared to traditional emission-scanning approaches. We have also demonstrated that excitation-scanning approaches may be able to detect spectral differences between colonic adenomas and adenocarcinomas and normal mucosa in flash-frozen tissues. Here, we report feasibility results from using excitation-scanning hyperspectral imaging to screen pairs of fresh tumoral and nontumoral colorectal tissues. Tissues were imaged using a novel hyperspectral imaging fluorescence excitation scanning microscope, sampling a wavelength range of 360-550 nm, at 5 nm increments. Image data were corrected to achieve a NIST-traceable flat spectral response. Image data were then analyzed using a range of supervised and unsupervised classification approaches within ENVI software (Harris Geospatial Solutions). Supervised classification resulted in >99% accuracy for single-patient image data, but only 64% accuracy for multi-patient classification (n=9 to date), with the drop in accuracy due to increased false-positive detection rates. Hence, initial data indicate that this approach may be a viable detection approach, but that larger patient sample sizes need to be evaluated and the effects of inter-patient variability studied.

Supervision in neuropsychological assessment: a survey of training, practices, and perspectives of supervisors.

PubMed

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.

On-line Machine Learning and Event Detection in Petascale Data Streams

NASA Astrophysics Data System (ADS)

Thompson, David R.; Wagstaff, K. L.

2012-01-01

Traditional statistical data mining involves off-line analysis in which all data are available and equally accessible. However, petascale datasets have challenged this premise since it is often impossible to store, let alone analyze, the relevant observations. This has led the machine learning community to investigate adaptive processing chains where data mining is a continuous process. Here pattern recognition permits triage and followup decisions at multiple stages of a processing pipeline. Such techniques can also benefit new astronomical instruments such as the Large Synoptic Survey Telescope (LSST) and Square Kilometre Array (SKA) that will generate petascale data volumes. We summarize some machine learning perspectives on real time data mining, with representative cases of astronomical applications and event detection in high volume datastreams. The first is a "supervised classification" approach currently used for transient event detection at the Very Long Baseline Array (VLBA). It injects known signals of interest - faint single-pulse anomalies - and tunes system parameters to recover these events. This permits meaningful event detection for diverse instrument configurations and observing conditions whose noise cannot be well-characterized in advance. Second, "semi-supervised novelty detection" finds novel events based on statistical deviations from previous patterns. It detects outlier signals of interest while considering known examples of false alarm interference. Applied to data from the Parkes pulsar survey, the approach identifies anomalous "peryton" phenomena that do not match previous event models. Finally, we consider online light curve classification that can trigger adaptive followup measurements of candidate events. Classifier performance analyses suggest optimal survey strategies, and permit principled followup decisions from incomplete data. These examples trace a broad range of algorithm possibilities available for online astronomical data mining. This talk describes research performed at the Jet Propulsion Laboratory, California Institute of Technology. Copyright 2012, All Rights Reserved. U.S. Government support acknowledged.

Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.

PubMed

Wang, Zhiwei; Liu, Chaoyue; Cheng, Danpeng; Wang, Liang; Yang, Xin; Cheng, Kwang-Ting

2018-05-01

Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter magnetic resonance images (mp-MRI) are of high demand. Existing methods typically employ several separate steps, each of which is optimized individually without considering the error tolerance of other steps. As a result, they could either involve unnecessary computational cost or suffer from errors accumulated over steps. In this paper, we present an automated CS PCa detection system, where all steps are optimized jointly in an end-to-end trainable deep neural network. The proposed neural network consists of concatenated subnets: 1) a novel tissue deformation network (TDN) for automated prostate detection and multimodal registration and 2) a dual-path convolutional neural network (CNN) for CS PCa detection. Three types of loss functions, i.e., classification loss, inconsistency loss, and overlap loss, are employed for optimizing all parameters of the proposed TDN and CNN. In the training phase, the two nets mutually affect each other and effectively guide registration and extraction of representative CS PCa-relevant features to achieve results with sufficient accuracy. The entire network is trained in a weakly supervised manner by providing only image-level annotations (i.e., presence/absence of PCa) without exact priors of lesions' locations. Compared with most existing systems which require supervised labels, e.g., manual delineation of PCa lesions, it is much more convenient for clinical usage. Comprehensive evaluation based on fivefold cross validation using 360 patient data demonstrates that our system achieves a high accuracy for CS PCa detection, i.e., a sensitivity of 0.6374 and 0.8978 at 0.1 and 1 false positives per normal/benign patient.

Detecting opinion spams through supervised boosting approach.

PubMed

Hazim, Mohamad; Anuar, Nor Badrul; Ab Razak, Mohd Faizal; Abdullah, Nor Aniza

2018-01-01

Product reviews are the individual's opinions, judgement or belief about a certain product or service provided by certain companies. Such reviews serve as guides for these companies to plan and monitor their business ventures in terms of increasing productivity or enhancing their product/service qualities. Product reviews can also increase business profits by convincing future customers about the products which they have interest in. In the mobile application marketplace such as Google Playstore, reviews and star ratings are used as indicators of the application quality. However, among all these reviews, hereby also known as opinions, spams also exist, to disrupt the online business balance. Previous studies used the time series and neural network approach (which require a lot of computational power) to detect these opinion spams. However, the detection performance can be restricted in terms of accuracy because the approach focusses on basic, discrete and document level features only thereby, projecting little statistical relationships. Aiming to improve the detection of opinion spams in mobile application marketplace, this study proposes using statistical based features that are modelled through the supervised boosting approach such as the Extreme Gradient Boost (XGBoost) and the Generalized Boosted Regression Model (GBM) to evaluate two multilingual datasets (i.e. English and Malay language). From the evaluation done, it was found that the XGBoost is most suitable for detecting opinion spams in the English dataset while the GBM Gaussian is most suitable for the Malay dataset. The comparative analysis also indicates that the implementation of the proposed statistical based features had achieved a detection accuracy rate of 87.43 per cent on the English dataset and 86.13 per cent on the Malay dataset.

Abnormality detection of mammograms by discriminative dictionary learning on DSIFT descriptors.

PubMed

Tavakoli, Nasrin; Karimi, Maryam; Nejati, Mansour; Karimi, Nader; Reza Soroushmehr, S M; Samavi, Shadrokh; Najarian, Kayvan

2017-07-01

Detection and classification of breast lesions using mammographic images are one of the most difficult studies in medical image processing. A number of learning and non-learning methods have been proposed for detecting and classifying these lesions. However, the accuracy of the detection/classification still needs improvement. In this paper we propose a powerful classification method based on sparse learning to diagnose breast cancer in mammograms. For this purpose, a supervised discriminative dictionary learning approach is applied on dense scale invariant feature transform (DSIFT) features. A linear classifier is also simultaneously learned with the dictionary which can effectively classify the sparse representations. Our experimental results show the superior performance of our method compared to existing approaches.

13 CFR 120.464 - Reports to SBA.

Code of Federal Regulations, 2010 CFR

2010-01-01

... submit to SBA a summary of any changes in the SBA Supervised Lender's organization or financing (within... reasons and documentation. The waiver decision of the appropriate Office of Capital Access official in...

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...

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...

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...

Label-free electrochemical aptasensor for detection of alpha-fetoprotein based on AFP-aptamer and thionin/reduced graphene oxide/gold nanoparticles.

PubMed

Li, Guiyin; Li, Shanshan; Wang, Zhihong; Xue, Yewei; Dong, Chenyang; Zeng, Junxiang; Huang, Yong; Liang, Jintao; Zhou, Zhide

2018-04-15

Sensitive and accurate detection of tumor markers is critical to early diagnosis, point-of-care and portable medical supervision. Alpha fetoprotein (AFP) is an important clinical tumor marker for hepatocellular carcinoma (HCC), and the concentration of AFP in human serum is related to the stage of HCC. In this paper, a label-free electrochemical aptasensor for AFP detection was fabricated using AFP-aptamer as the recognition molecule and thionin/reduced graphene oxide/gold nanoparticles (TH/RGO/Au NPs) as the sensor platform. With high electrocatalytic property and large specific surface area, RGO and Au NPs were employed on the screen-printed carbon electrode to load TH molecules. The TH not only acted as a bridging molecule to effectively capture and immobilize AFP-aptamer, but as the electron transfer mediator to provide the electrochemical signal. The AFP detection was based on the monitoring of the electrochemical current response change of TH by the differential pulse voltammetry. Under optimal conditions, the electrochemical responses were proportional to the AFP concentration in the range of 0.1-100.0 μg/mL. The limit of detection was 0.050 μg/mL at a signal-to-noise ratio of 3. The proposed method may provide a promising application of aptamer with the properties of facile procedure, low cost, high selectivity in clinic. Copyright © 2018. Published by Elsevier Inc.

Skeletal muscle adaptation in response to supervised exercise training for intermittent claudication.

PubMed

Beckitt, T A; Day, J; Morgan, M; Lamont, P M

2012-09-01

There is evidence that the improvement following supervised exercise for claudication results from skeletal muscle adaptation. The myosin heavy chain (MHC) determines muscle fibre type and therefore efficiency. Immunohistochemical analysis has failed to take account of hybrid MHC expression within myofibres. This study sought evidence of differential MHC protein expression following supervised exercise for claudication. 38 claudicants were recruited. Subjects undertook a three-month supervised exercise programme. Controls were patients awaiting angioplasty for claudication. Subjects underwent paired gastrocnemius biopsy. Relative expression of MHC proteins was determined by SDS-PAGE electrophoresis. Non-parametric data is presented as median with the inter-quartile range and parametric as the mean ± standard deviation. Upon completion of the exercise programme there was a 94% increase (124 (106-145) to 241 (193-265) metres, p = 0.002) in maximum walking distance, which was not evident in the control group. An 11.1% (p = 0.02) increase in MHC I expression was observed in the exercise but not the control group (34.3% ± 6.8 to 45.4% ± 4.4). There was a positive correlation between the change in MHC I expression and the improvement in claudication distance (r = 0.69, p < 0.05). Supervised exercise training for claudication results in an increase in the proportion of MHC type I expression within the symptomatic gastrocnemius muscle. Copyright © 2012 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

An exudate detection method for diagnosis risk of diabetic macular edema in retinal images using feature-based and supervised classification.

PubMed

Marin, D; Gegundez-Arias, M E; Ponte, B; Alvarez, F; Garrido, J; Ortega, C; Vasallo, M J; Bravo, J M

2018-01-10

The present paper aims at presenting the methodology and first results of a detection system of risk of diabetic macular edema (DME) in fundus images. The system is based on the detection of retinal exudates (Ex), whose presence in the image is clinically used for an early diagnosis of the disease. To do so, the system applies digital image processing algorithms to the retinal image in order to obtain a set of candidate regions to be Ex, which are validated by means of feature extraction and supervised classification techniques. The diagnoses provided by the system on 1058 retinographies of 529 diabetic patients at risk of having DME show that the system can operate at a level of sensitivity comparable to that of ophthalmological specialists: it achieved 0.9000 sensitivity per patient against 0.7733, 0.9133 and 0.9000 of several specialists, where the false negatives were mild clinical cases of the disease. In addition, the level of specificity reached by the system was 0.6939, high enough to screen about 70% of the patients with no evidence of DME. These values show that the system fulfils the requirements for its possible integration into a complete diabetic retinopathy pre-screening tool for the automated management of patients within a screening programme. Graphical Abstract Diagnosis system of risk of diabetic macular edema (DME) based on exudate (Ex) detection in fundus images.

JointMMCC: Joint Maximum-Margin Classification and Clustering of Imaging Data

PubMed Central

Filipovych, Roman; Resnick, Susan M.; Davatzikos, Christos

2012-01-01

A number of conditions are characterized by pathologies that form continuous or nearly-continuous spectra spanning from the absence of pathology to very pronounced pathological changes (e.g., normal aging, Mild Cognitive Impairment, Alzheimer's). Moreover, diseases are often highly heterogeneous with a number of diagnostic subcategories or subconditions lying within the spectra (e.g., Autism Spectrum Disorder, schizophrenia). Discovering coherent subpopulations of subjects within the spectrum of pathological changes may further our understanding of diseases, and potentially identify subconditions that require alternative or modified treatment options. In this paper, we propose an approach that aims at identifying coherent subpopulations with respect to the underlying MRI in the scenario where the condition is heterogeneous and pathological changes form a continuous spectrum. We describe a Joint Maximum-Margin Classification and Clustering (JointMMCC) approach that jointly detects the pathologic population via semi-supervised classification, as well as disentangles heterogeneity of the pathological cohort by solving a clustering subproblem. We propose an efficient solution to the non-convex optimization problem associated with JointMMCC. We apply our proposed approach to an MRI study of aging, and identify coherent subpopulations (i.e., clusters) of cognitively less stable adults. PMID:22328179

Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

PubMed

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.

Using aerial photography and image analysis to measure changes in giant reed populations

USDA-ARS?s Scientific Manuscript database

A study was conducted along the Rio Grande in southwest Texas to evaluate color-infrared aerial photography combined with supervised image analysis to quantify changes in giant reed (Arundo donax L.) populations over a 6-year period. Aerial photographs from 2002 and 2008 of the same seven study site...

Is Parenting the Mediator of Change in Behavioral Parent Training for Externalizing Problems of Youth?

PubMed Central

Forehand, Rex; Lafko, Nicole; Parent, Justin; Burt, Keith

2014-01-01

Change in parenting behavior is theorized to be the mediator accounting for change in child and adolescent externalizing problems in behavioral parent training (BPT). The purpose of this review is to examine this assumption in BPT prevention and intervention programs. Eight intervention and 17 prevention studies were identified as meeting all criteria or all but one criterion for testing mediation. Parenting behaviors were classified as positive, negative, discipline, monitoring/supervision, or a composite measure. Forty-five percent of the tests performed across studies to test mediation supported parenting as a mediator. A composite measure of parenting and discipline received the most support, whereas monitoring/supervision was rarely examined. More support for the mediating role of parenting emerged for prevention than intervention studies and when meeting all criteria for testing mediation was not required. Although the findings do not call BPT into question as an efficacious treatment, they do suggest more attention should be focused on examining parenting as a putative mediator in BPT. PMID:25455625

Recent forest cover changes (2002-2015) in the Southern Carpathians: A case study of the Iezer Mountains, Romania.

PubMed

Mihai, Bogdan; Săvulescu, Ionuț; Rujoiu-Mare, Marina; Nistor, Constantin

2017-12-01

The paper explores the dynamics of the forest cover change in the Iezer Mountains, part of Southern Carpathians, in the context of the forest ownership recovery and deforestation processes, combined with the effects of biotic and abiotic disturbances. The aim of the study is to map and evaluate the typology and the spatial extension of changes in the montane forest cover between 700 and 2462m a.s.l., sampling all the representative Carpathian ecosystems, from the European beech zone up to the spruce-fir zone and the subalpine-alpine pastures. The methodology uses a change detection analysis of satellite imagery with Landsat ETM+/OLI and Sentinel-2 MSI data. The workflow started with a complete calibration of multispectral data from 2002, before the massive forest restitution to private owners, after the Law 247/2005 empowerment, and 2015, the intensification of deforestation process. For the data classification, a Maximum Likelihood supervised classification algorithm was utilized. The forest change map was developed after combining the classifications in a unitary formula using image difference. The principal outcome of the research identifies the type of forest cover change using a quantitative formula. This information can be integrated in the future decision-making strategies for forest stand management and sustainable development. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in fMRI activation in anterior hippocampus and motor cortex during memory retrieval after an intense exercise intervention.

PubMed

Wagner, Gerd; Herbsleb, Marco; de la Cruz, Feliberto; Schumann, Andy; Köhler, Stefanie; Puta, Christian; Gabriel, Holger W; Reichenbach, Jürgen R; Bär, Karl-Jürgen

2017-03-01

Strong evidence indicates that regular aerobic training induces beneficial effects on cognitive functions. The present controlled fMRI study was designed to investigate the impact of a short-term intense aerobic exercise on the pattern of functional activation during the retrieval of learned pair-associates in 17 young and healthy male adults compared to 17 matched control subjects. We further aimed to relate putative changes in hippocampal activation to postulated changes in the exercised-induced brain derived neurotrophic factor (BDNF). The supervised exercise program was performed on a bicycle ergometer and lasted six weeks, with three aerobic sessions per week. We found profound improvement of physical fitness in most subjects indicated by the target parameter 'individual anaerobic threshold'. Significant improvements in the cognitive performance were detected in the exercise group, but also in the control group. We observed significant differences in the activation pattern of the left anterior hippocampus during the pair-associates task after the intervention. We could also show a significant positive correlation between changes in exercise-induced BDNF and left anterior hippocampal activation. Moreover, we observed the brain's motor network to be significantly stronger activated after the exercise intervention. Thus, our results suggest BDNF dependent activation changes of the hippocampus in addition to previously described structural changes after exercise. Copyright © 2017 Elsevier B.V. All rights reserved.

Promising Practices in E-Supervision: Exploring Graduate Speech-Language Pathology Interns’ Perceptions

PubMed Central

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

The experience of clinical supervision for nurses and healthcare assistants in a secure adolescent service: Affecting service improvement.

PubMed

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.

46 CFR 161.002-10 - Automatic fire detecting system control unit.

Code of Federal Regulations, 2012 CFR

2012-10-01

... that part of the supply circuit on the load side of the battery transfer switch and fuses. On a system supplied by a branch circuit the “normal source” shall be construed to mean the load side of any... fire alarm shall be electrically supervised. (d) Power failure alarms—(1) Loss of potential. The loss...

A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

PubMed Central

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions. PMID:24717283

A practical and automated approach to large area forest disturbance mapping with remote sensing.

PubMed

Ozdogan, Mutlu

2014-01-01

In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover change analysis over very large regions.

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.…

The impact of a human resource management intervention on the capacity of supervisors to support and supervise their staff at health facility level.

PubMed

Uduma, Ogenna; Galligan, Marie; Mollel, Henry; Masanja, Honorati; Bradley, Susan; McAuliffe, Eilish

2017-08-30

A systematic and structured approach to the support and supervision of health workers can strengthen the human resource management function at the district and health facility levels and may help address the current crisis in human resources for health in sub-Saharan Africa by improving health workers' motivation and retention. A supportive supervision programme including (a) a workshop, (b) intensive training and (c) action learning sets was designed to improve human resource management in districts and health facilities in Tanzania. We conducted a randomised experimental design to evaluate the impact of the intervention. Data on the same measures were collected pre and post the intervention in order to identify any changes that occurred (between baseline and end of project) in the capacity of supervisors in intervention a + b and intervention a + b + c to support and supervise their staff. These were compared to supervisors in a control group in each of Tanga, Iringa and Tabora regions (n = 9). A quantitative survey of 95 and 108 supervisors and 196 and 187 health workers sampled at baseline and end-line, respectively, also contained open-ended responses which were analysed separately. Supervisors assessed their own competency levels pre- and post-intervention. End-line samples generally scored higher compared to the corresponding baseline in both intervention groups for competence activities. Significant differences between baseline and end-line were observed in the total scores on 'maintaining high levels of performance', 'dealing with performance problems', 'counselling a troubled employee' and 'time management' in intervention a + b. In contrast, for intervention a + b + c, a significant difference in distribution of scores was only found on 'counselling a troubled employee', although the end-line mean scores were higher than their corresponding baseline mean scores in all cases. Similar trends to those in the supervisors' reports are seen in health workers data in terms of more efficient supervision processes, although the increases are not as marked. A number of different indicators were measured to assess the impact of the supportive supervision intervention on the a + b and a + b + c intervention sites. The average frequency of supervision visits and the supervisors' competency levels across the facilities increased in both intervention types. This would suggest that the intervention proved effective in raising awareness of the importance of supervision and this understanding led to action in the form of more supportive supervision.

Evolution of Controllability in Interbank Networks

PubMed Central

Delpini, Danilo; Battiston, Stefano; Riccaboni, Massimo; Gabbi, Giampaolo; Pammolli, Fabio; Caldarelli, Guido

2013-01-01

The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected “hub” institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies. PMID:23568033

Reproducible diagnostic metabolites in plasma from typhoid fever patients in Asia and Africa.

PubMed

Näsström, Elin; Parry, Christopher M; Vu Thieu, Nga Tran; Maude, Rapeephan R; de Jong, Hanna K; Fukushima, Masako; Rzhepishevska, Olena; Marks, Florian; Panzner, Ursula; Im, Justin; Jeon, Hyonjin; Park, Seeun; Chaudhury, Zabeen; Ghose, Aniruddha; Samad, Rasheda; Van, Tan Trinh; Johansson, Anders; Dondorp, Arjen M; Thwaites, Guy E; Faiz, Abul; Antti, Henrik; Baker, Stephen

2017-05-09

Salmonella Typhi is the causative agent of typhoid. Typhoid is diagnosed by blood culture, a method that lacks sensitivity, portability and speed. We have previously shown that specific metabolomic profiles can be detected in the blood of typhoid patients from Nepal (Näsström et al., 2014). Here, we performed mass spectrometry on plasma from Bangladeshi and Senegalese patients with culture confirmed typhoid fever, clinically suspected typhoid, and other febrile diseases including malaria. After applying supervised pattern recognition modelling, we could significantly distinguish metabolite profiles in plasma from the culture confirmed typhoid patients. After comparing the direction of change and degree of multivariate significance, we identified 24 metabolites that were consistently up- or down regulated in a further Bangladeshi/Senegalese validation cohort, and the Nepali cohort from our previous work. We have identified and validated a metabolite panel that can distinguish typhoid from other febrile diseases, providing a new approach for typhoid diagnostics.

An FPGA-Based WASN for Remote Real-Time Monitoring of Endangered Species: A Case Study on the Birdsong Recognition of Botaurus stellaris.

PubMed

Hervás, Marcos; Alsina-Pagès, Rosa Ma; Alías, Francesc; Salvador, Martí

2017-06-08

Fast environmental variations due to climate change can cause mass decline or even extinctions of species, having a dramatic impact on the future of biodiversity. During the last decade, different approaches have been proposed to track and monitor endangered species, generally based on costly semi-automatic systems that require human supervision adding limitations in coverage and time. However, the recent emergence of Wireless Acoustic Sensor Networks (WASN) has allowed non-intrusive remote monitoring of endangered species in real time through the automatic identification of the sound they emit. In this work, an FPGA-based WASN centralized architecture is proposed and validated on a simulated operation environment. The feasibility of the architecture is evaluated in a case study designed to detect the threatened Botaurus stellaris among other 19 cohabiting birds species in The Parc Natural dels Aiguamolls de l'Empord.

Intelligent Rover Execution for Detecting Life in the Atacama Desert

NASA Technical Reports Server (NTRS)

Baskaran, Vijayakumar; Muscettola, Nicola; Rijsman, David; Plaunt, Chris; Fry, Chuck

2006-01-01

On-board supervisory execution is crucial for the deployment of more capable and autonomous remote explorers. Planetary science is considering robotic explorers operating for long periods of time without ground supervision while interacting with a changing and often hostile environment. Effective and robust operations require on-board supervisory control with a high level of awareness of the principles of functioning of the environment and of the numerous internal subsystems that need to be coordinated. We describe an on-board rover executive that was deployed on a rover as past of the "Limits of Life in the Atacama Desert (LITA)" field campaign sponsored by the NASA ASTEP program. The executive was built using the Intelligent Distributed Execution Architecture (IDEA), an execution framework that uses model-based and plan-based supervisory control of its fundamental computational paradigm. We present the results of the third field experiment conducted in the Atacama desert (Chile) in August - October 2005.

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

PubMed

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.

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…

Supervising community health workers in low-income countries – a review of impact and implementation issues

PubMed Central

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

Exploring the roles of cannot-link constraint in community detection via Multi-variance Mixed Gaussian Generative Model.

PubMed

Yang, Liang; Ge, Meng; Jin, Di; He, Dongxiao; Fu, Huazhu; Wang, Jing; Cao, Xiaochun

2017-01-01

Due to the demand for performance improvement and the existence of prior information, semi-supervised community detection with pairwise constraints becomes a hot topic. Most existing methods have been successfully encoding the must-link constraints, but neglect the opposite ones, i.e., the cannot-link constraints, which can force the exclusion between nodes. In this paper, we are interested in understanding the role of cannot-link constraints and effectively encoding pairwise constraints. Towards these goals, we define an integral generative process jointly considering the network topology, must-link and cannot-link constraints. We propose to characterize this process as a Multi-variance Mixed Gaussian Generative (MMGG) Model to address diverse degrees of confidences that exist in network topology and pairwise constraints and formulate it as a weighted nonnegative matrix factorization problem. The experiments on artificial and real-world networks not only illustrate the superiority of our proposed MMGG, but also, most importantly, reveal the roles of pairwise constraints. That is, though the must-link is more important than cannot-link when either of them is available, both must-link and cannot-link are equally important when both of them are available. To the best of our knowledge, this is the first work on discovering and exploring the importance of cannot-link constraints in semi-supervised community detection.

Exploring the roles of cannot-link constraint in community detection via Multi-variance Mixed Gaussian Generative Model

PubMed Central

Ge, Meng; Jin, Di; He, Dongxiao; Fu, Huazhu; Wang, Jing; Cao, Xiaochun

2017-01-01

Due to the demand for performance improvement and the existence of prior information, semi-supervised community detection with pairwise constraints becomes a hot topic. Most existing methods have been successfully encoding the must-link constraints, but neglect the opposite ones, i.e., the cannot-link constraints, which can force the exclusion between nodes. In this paper, we are interested in understanding the role of cannot-link constraints and effectively encoding pairwise constraints. Towards these goals, we define an integral generative process jointly considering the network topology, must-link and cannot-link constraints. We propose to characterize this process as a Multi-variance Mixed Gaussian Generative (MMGG) Model to address diverse degrees of confidences that exist in network topology and pairwise constraints and formulate it as a weighted nonnegative matrix factorization problem. The experiments on artificial and real-world networks not only illustrate the superiority of our proposed MMGG, but also, most importantly, reveal the roles of pairwise constraints. That is, though the must-link is more important than cannot-link when either of them is available, both must-link and cannot-link are equally important when both of them are available. To the best of our knowledge, this is the first work on discovering and exploring the importance of cannot-link constraints in semi-supervised community detection. PMID:28678864

Semi-Supervised Geographical Feature Detection

NASA Astrophysics Data System (ADS)

Yu, H.; Yu, L.; Kuo, K. S.

2016-12-01

Extraction and tracking geographical features is a fundamental requirement in many geoscience fields. However, this operation has become an increasingly challenging task for domain scientists when tackling a large amount of geoscience data. Although domain scientists may have a relatively clear definition of features, it is difficult to capture the presence of features in an accurate and efficient fashion. We propose a semi-supervised approach to address large geographical feature detection. Our approach has two main components. First, we represent a heterogeneous geoscience data in a unified high-dimensional space, which can facilitate us to evaluate the similarity of data points with respect to geolocation, time, and variable values. We characterize the data from these measures, and use a set of hash functions to parameterize the initial knowledge of the data. Second, for any user query, our approach can automatically extract the initial results based on the hash functions. To improve the accuracy of querying, our approach provides a visualization interface to display the querying results and allow users to interactively explore and refine them. The user feedback will be used to enhance our knowledge base in an iterative manner. In our implementation, we use high-performance computing techniques to accelerate the construction of hash functions. Our design facilitates a parallelization scheme for feature detection and extraction, which is a traditionally challenging problem for large-scale data. We evaluate our approach and demonstrate the effectiveness using both synthetic and real world datasets.

Marine Targets Detection in Pol-SAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong

2016-08-01

In this poster, we present a new method of marine target detection in Pol-SAR data. One band SAR image, like HH, VV or VH, can be used to find marine target using a Contant False Alarm Ratio (CFAR) algorithm. But some false detection may happen, as the sidelobe of antenna, Azimuth ambiguity, strong speckle noise and so on in the single band SAR image. Pol-SAR image can get more information of targets. After decomposition and false color composite, the sidelobe of antenna and Azimuth ambiguity could be deleted. So, the method presented include three steps, decomposion, false color composite and supervised classification. The result of Radarsat-2 SAR image test indicates a good accuracy. The detection results are compared with Automatic Indentify Sistem (AIS) data, the accuracy of right detection is above 95% and false detection ratio is below 5%.

Training, supervision and quality of care in selected integrated community case management (iCCM) programmes: A scoping review of programmatic evidence.

PubMed

Bosch-Capblanch, Xavier; Marceau, Claudine

2014-12-01

To describe the training, supervision and quality of care components of integrated Community Case Management (iCCM) programmes and to draw lessons learned from existing evaluations of those programmes. Scoping review of reports from 29 selected iCCM programmes purposively provided by stakeholders containing any information relevant to understand quality of care issues. The number of people reached by iCCM programmes varied from the tens of thousands to more than a million. All programmes aimed at improving access of vulnerable populations to health care, focusing on the main childhood illnesses, managed by Community Health Workers (CHW), often selected bycommunities. Training and supervision were widely implemented, in different ways and intensities, and often complemented with tools (eg, guides, job aids), supplies, equipment and incentives. Quality of care was measured using many outcomes (eg, access or appropriate treatment). Overall, there seemed to be positive effects for those strategies that involved policy change, organisational change, standardisation of clinical practices and alignment with other programmes. Positive effects were mostly achieved in large multi-component programmes. Mild or no effects have been described on mortality reduction amongst the few programmes for which data on this outcome was available to us. Promising strategies included teaming-up of CHW, micro-franchising or social franchising. On-site training and supervision of CHW have been shown to improve clinical practices. Effects on caregivers seemed positive, with increases in knowledge, care seeking behaviour, or caregivers' basic disease management. Evidence on iCCM is often of low quality, cannot relate specific interventions or the ways they are implemented with outcomes and lacks standardisation; this limits the capacity to identify promising strategies to improve quality of care. Large, multi-faceted, iCCM programmes, with strong components of training, supervision, which included additional support of equipment and supplies, seemed to improve selected quality of care outcomes. However, current evaluation and reporting practices need to be revised in a new research agenda to address the methodological challenges of iCCM evaluations.

Training, supervision and quality of care in selected integrated community case management (iCCM) programmes: A scoping review of programmatic evidence

PubMed Central

Bosch–Capblanch, Xavier; Marceau, Claudine

2014-01-01

Aim To describe the training, supervision and quality of care components of integrated Community Case Management (iCCM) programmes and to draw lessons learned from existing evaluations of those programmes. Methods Scoping review of reports from 29 selected iCCM programmes purposively provided by stakeholders containing any information relevant to understand quality of care issues. Results The number of people reached by iCCM programmes varied from the tens of thousands to more than a million. All programmes aimed at improving access of vulnerable populations to health care, focusing on the main childhood illnesses, managed by Community Health Workers (CHW), often selected bycommunities. Training and supervision were widely implemented, in different ways and intensities, and often complemented with tools (eg, guides, job aids), supplies, equipment and incentives. Quality of care was measured using many outcomes (eg, access or appropriate treatment). Overall, there seemed to be positive effects for those strategies that involved policy change, organisational change, standardisation of clinical practices and alignment with other programmes. Positive effects were mostly achieved in large multi–component programmes. Mild or no effects have been described on mortality reduction amongst the few programmes for which data on this outcome was available to us. Promising strategies included teaming–up of CHW, micro–franchising or social franchising. On–site training and supervision of CHW have been shown to improve clinical practices. Effects on caregivers seemed positive, with increases in knowledge, care seeking behaviour, or caregivers’ basic disease management. Evidence on iCCM is often of low quality, cannot relate specific interventions or the ways they are implemented with outcomes and lacks standardisation; this limits the capacity to identify promising strategies to improve quality of care. Conclusion Large, multi–faceted, iCCM programmes, with strong components of training, supervision, which included additional support of equipment and supplies, seemed to improve selected quality of care outcomes. However, current evaluation and reporting practices need to be revised in a new research agenda to address the methodological challenges of iCCM evaluations. PMID:25520793

Inquiring Minds Want To Know: Does the Clinical Supervision Course Improve Cooperating Teachers' Supervisory Performance?

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…

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)

Direct Supervision in Outpatient Psychiatric Graduate Medical Education.

PubMed

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.

a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

A Mobile App to Stabilize Daily Functional Activity of Breast Cancer Patients in Collaboration With the Physician: A Randomized Controlled Clinical Trial.

PubMed

Egbring, Marco; Far, Elmira; Roos, Malgorzata; Dietrich, Michael; Brauchbar, Mathis; Kullak-Ublick, Gerd A; Trojan, Andreas

2016-09-06

The well-being of breast cancer patients and reporting of adverse events require close monitoring. Mobile apps allow continuous recording of disease- and medication-related symptoms in patients undergoing chemotherapy. The aim of the study was to evaluate the effects of a mobile app on patient-reported daily functional activity in a supervised and unsupervised setting. We conducted a randomized controlled study of 139 breast cancer patients undergoing chemotherapy. Patient status was self-measured using Eastern Cooperative Oncology Group scoring and Common Terminology Criteria for Adverse Events. Participants were randomly assigned to a control group, an unsupervised group that used a mobile app to record data, or a supervised group that used the app and reviewed data with a physician. Primary outcome variables were change in daily functional activity and symptoms over three outpatient visits. Functional activity scores declined in all groups from the first to second visit. However, from the second to third visit, only the supervised group improved, whereas the others continued to decline. Overall, the supervised group showed no significant difference from the first (median 90.85, IQR 30.67) to third visit (median 84.76, IQR 18.29, P=.72). Both app-using groups reported more distinct adverse events in the app than in the questionnaire (supervised: n=1033 vs n=656; unsupervised: n=852 vs n=823), although the unsupervised group reported more symptoms overall (n=4808) in the app than the supervised group (n=4463). The mobile app was associated with stabilized daily functional activity when used under collaborative review. App-using participants could more frequently report adverse events, and those under supervision made fewer and more precise entries than unsupervised participants. Our findings suggest that patient well-being and awareness of chemotherapy adverse effects can be improved by using a mobile app in collaboration with the treating physician. ClinicalTrials.gov NCT02004496; https://clinicaltrials.gov/ct2/show/NCT02004496 (Archived by WebCite at http://www.webcitation.org/6k68FZHo2).

A Mobile App to Stabilize Daily Functional Activity of Breast Cancer Patients in Collaboration With the Physician: A Randomized Controlled Clinical Trial

PubMed Central

Egbring, Marco; Far, Elmira; Roos, Malgorzata; Dietrich, Michael; Brauchbar, Mathis; Kullak-Ublick, Gerd A

2016-01-01

Background The well-being of breast cancer patients and reporting of adverse events require close monitoring. Mobile apps allow continuous recording of disease- and medication-related symptoms in patients undergoing chemotherapy. Objective The aim of the study was to evaluate the effects of a mobile app on patient-reported daily functional activity in a supervised and unsupervised setting. Methods We conducted a randomized controlled study of 139 breast cancer patients undergoing chemotherapy. Patient status was self-measured using Eastern Cooperative Oncology Group scoring and Common Terminology Criteria for Adverse Events. Participants were randomly assigned to a control group, an unsupervised group that used a mobile app to record data, or a supervised group that used the app and reviewed data with a physician. Primary outcome variables were change in daily functional activity and symptoms over three outpatient visits. Results Functional activity scores declined in all groups from the first to second visit. However, from the second to third visit, only the supervised group improved, whereas the others continued to decline. Overall, the supervised group showed no significant difference from the first (median 90.85, IQR 30.67) to third visit (median 84.76, IQR 18.29, P=.72). Both app-using groups reported more distinct adverse events in the app than in the questionnaire (supervised: n=1033 vs n=656; unsupervised: n=852 vs n=823), although the unsupervised group reported more symptoms overall (n=4808) in the app than the supervised group (n=4463). Conclusions The mobile app was associated with stabilized daily functional activity when used under collaborative review. App-using participants could more frequently report adverse events, and those under supervision made fewer and more precise entries than unsupervised participants. Our findings suggest that patient well-being and awareness of chemotherapy adverse effects can be improved by using a mobile app in collaboration with the treating physician. ClinicalTrial ClinicalTrials.gov NCT02004496; https://clinicaltrials.gov/ct2/show/NCT02004496 (Archived by WebCite at http://www.webcitation.org/6k68FZHo2) PMID:27601354

Project Evidence: Responding to the Changing Professional Learning Needs of Mentors in Initial Teacher Education

ERIC Educational Resources Information Center

Allen, Jeanne Maree; White, Simone; Sim, Cheryl

2017-01-01

This positioning paper seeks to contribute to the knowledge base of the changing professional learning needs of supervising or mentor teachers in initial teacher education. To do so, we draw from the work of "Project Evidence," an Australian Office of Learning and Teaching funded project, designed to support teacher education through the…

Preceptor Recruitment, Training, and Retention--A Nation-Wide Survey of Colleges of Pharmacy

ERIC Educational Resources Information Center

Johanson, Erin L.

2013-01-01

Recent changes surrounding the profession of pharmacy resulted in a growing number of new pharmacy programs as well as expansion of existing class sizes. This extreme growth, coupled with changes to accreditation standards which require volunteer licensed pharmacists to supervise student interns for a minimum of thirty percent of the Doctor of…

Examining Behavioral Change among Supervision and Management Undergraduates in a Selected College

ERIC Educational Resources Information Center

Litt, Sheri Diamond

2010-01-01

A baccalaureate education was once limited to an elite population of high school graduates in pursuit of guaranteed career success. Today, more than 70% of high school graduates opt to attend college to earn a baccalaureate degree, due to economic, global, and technological changes. While this percent has significantly risen, employers are…

75 FR 66410 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-28

... Effectiveness of Proposed Rule Change Relating to the Sales Value Fee October 22, 2010. Pursuant to Section 19(b... Terms of Substance of the Proposed Rule Change The Exchange proposes to adopt ISE Rule 212 (Sales Value... supervision and regulation of the securities markets and securities professionals. To offset this obligation...

Using Registered Dental Hygienists to Promote a School-Based Approach to Dental Public Health

PubMed Central

Wellever, Anthony; Kelly, Patricia

2017-01-01

We examine a strategy for improving oral health in the United States by focusing on low-income children in school-based settings. Vulnerable children often experience cultural, social, economic, structural, and geographic barriers when trying to access dental services in traditional dental office settings. These disparities have been discussed for more than a decade in multiple US Department of Health and Human Services publications. One solution is to revise dental practice acts to allow registered dental hygienists increased scope of services, expanded public health delivery opportunities, and decreased dentist supervision. We provide examples of how federally qualified health centers have implemented successful school-based dental models within the parameters of two state policies that allow registered dental hygienists varying levels of dentist supervision. Changes to dental practice acts at the state level allowing registered dental hygienists to practice with limited supervision in community settings, such as schools, may provide vulnerable populations greater access to screening and preventive services. We derive our recommendations from expert opinion. PMID:28661808

Supervised extensions of chemography approaches: case studies of chemical liabilities assessment

PubMed Central

2014-01-01

Chemical liabilities, such as adverse effects and toxicity, play a significant role in modern drug discovery process. In silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Herein, we propose an approach combining several classification and chemography methods to be able to predict chemical liabilities and to interpret obtained results in the context of impact of structural changes of compounds on their pharmacological profile. To our knowledge for the first time, the supervised extension of Generative Topographic Mapping is proposed as an effective new chemography method. New approach for mapping new data using supervised Isomap without re-building models from the scratch has been proposed. Two approaches for estimation of model’s applicability domain are used in our study to our knowledge for the first time in chemoinformatics. The structural alerts responsible for the negative characteristics of pharmacological profile of chemical compounds has been found as a result of model interpretation. PMID:24868246

The Need for Data-Informed Clinical Supervision in Substance Use Disorder Treatment

PubMed Central

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

The need for data-informed clinical supervision in substance use disorder treatment.

PubMed

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.

Delivering colonoscopy screening for low-income populations in Suffolk County: strategies, outcomes, and benchmarks.

PubMed

Lane, Dorothy S; Messina, Catherine R; Cavanagh, Mary F; Anderson, Joseph C

2013-08-01

Current and pending legislation provides colorectal cancer screening reimbursement for previously uninsured populations. Colonoscopy is currently the screening method most frequently recommended by physicians for insured patients. The experience of the SCOPE (Suffolk County Preventive Endoscopy) demonstration project (Project SCOPE) at Stony Brook University Medical Center provides a model for delivering colonoscopy screening to low-income populations to meet anticipated increasing demands. Project SCOPE, based in the Department of Preventive Medicine, featured internal collaboration with the academic medical center's large gastroenterology practice and external collaboration with the Suffolk County Department of Health Services' network of community health centers. Colonoscopies were performed by faculty gastroenterologists or supervised fellows. Measures of colonoscopy performance were compared with quality indicators and differences between faculty and supervised fellows were identified. During a 40-month screening period, 800 initial colonoscopies were performed. Approximately 21% of women screened were found to have adenomatous polyps compared with 36% of men. Five cancers were detected. The majority of the population screened (70%) were members of minority populations. African American individuals had a higher percentage of proximally located adenomas (78%) compared with white individuals (65%) and Hispanics (49%), based on the location of the most advanced lesion. Hispanic individuals had a 36% lower risk of adenomas compared with white individuals. Performance measures including the percentage of procedures with adequate bowel preparation, cecum reached, scope withdrawal time, and adenoma detection rate met quality benchmarks when performed by either faculty or supervised fellows. Project SCOPE's operational strategies demonstrated a feasible method for an academic medical center to provide high-quality screening colonoscopy for low-income populations. © 2013 American Cancer Society.

Guidelines for community supervision of DWI offenders

DOT National Transportation Integrated Search

2008-03-01

To protect the public and provide DWI offenders with adequate interventions to help promote behavior change, it is important for community corrections agencies to assess their practices and programs for this population. The guidelines presented in th...

Chronic disease self-management and exercise in COPD as pulmonary rehabilitation: a randomized controlled trial.

PubMed

Cameron-Tucker, Helen L; Wood-Baker, Richard; Owen, Christine; Joseph, Lyn; Walters, E Haydn

2014-01-01

Both exercise and self-management are advocated in pulmonary rehabilitation for people with chronic obstructive pulmonary disease (COPD). The widely used 6-week, group-based Chronic Disease Self-Management Program (CDSMP) increases self-reported exercise, despite supervised exercise not being a program component. This has been little explored in COPD. Whether adding supervised exercise to the CDSMP would add benefit is unknown. We investigated the CDSMP in COPD, with and without a formal supervised exercise component, to address this question. Adult outpatients with COPD were randomized to the CDSMP with or without one hour of weekly supervised exercise over 6 weeks. The primary outcome measure was 6-minute walk test distance (6MWD). Secondary outcomes included self-reported exercise, exercise stage of change, exercise self-efficacy, breathlessness, quality of life, and self-management behaviors. Within- and between-group differences were analyzed on an intention-to-treat basis. Of 84 subjects recruited, 15 withdrew. 6MWD increased similarly in both groups: CDSMP-plus-exercise (intervention group) by 18.6±46.2 m; CDSMP-alone (control group) by 20.0±46.2 m. There was no significant difference for any secondary outcome. The CDSMP produced à small statistically significant increase in 6MWD. The addition of a single supervised exercise session did not further increase exercise capacity. Our findings confirm the efficacy of a behaviorally based intervention in COPD, but this would seem to be less than expected from conventional exercise-based pulmonary rehabilitation, raising the question of how, if at all, the small gains observed in this study may be augmented.

Is it possible to strengthen psychiatric nursing staff's clinical supervision? RCT of a meta-supervision intervention.

PubMed

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.

Treatments for the prevention of Sudden Unexpected Death in Epilepsy (SUDEP).

PubMed

Maguire, Melissa J; Jackson, Cerian F; Marson, Anthony G; Nolan, Sarah J

2016-07-19

Sudden Unexpected Death in Epilepsy (SUDEP) is defined as sudden, unexpected, witnessed or unwitnessed, non-traumatic or non-drowning death of people with epilepsy, with or without evidence of a seizure, excluding documented status epilepticus and in whom postmortem examination does not reveal a structural or toxicological cause for death. SUDEP has a reported incidence of 1 to 2 per 1000 patient years and represents the most common epilepsy-related cause of death. The presence and frequency of generalised tonic-clonic seizures (GTCS), male sex, early age of seizure onset, duration of epilepsy, and polytherapy are all predictors of risk of SUDEP. The exact pathophysiology of SUDEP is currently unknown, although GTCS-induced cardiac, respiratory, and brainstem dysfunction appears likely. Appropriately chosen antiepileptic drug treatment can render around 70% of patients free of all seizures. However, around one-third will remain drug refractory despite polytherapy. Continuing seizures place patients at risk of SUDEP, depression, and reduced quality of life. Preventative strategies for SUDEP include reducing the occurrence of GTCS by timely referral for presurgical evaluation in people with lesional epilepsy and advice on lifestyle measures; detecting cardiorespiratory distress through clinical observation and seizure, respiratory, and heart rate monitoring devices; preventing airway obstruction through nocturnal supervision and safety pillows; reducing central hypoventilation through physical stimulation and enhancing serotonergic mechanisms of respiratory regulation using selective serotonin reuptake inhibitors (SSRIs); reducing adenosine and endogenous opioid-induced brain and brainstem depression. To assess the effectiveness of interventions in preventing SUDEP in people with epilepsy by synthesising evidence from randomised controlled trials of interventions and cohort and case-control non-randomised studies. We searched the following databases: Cochrane Epilepsy Group Specialized Register; Cochrane Central Register of Controlled Trials (CENTRAL, Issue 11, 2015) via the Cochrane Register of Studies Online (CRSO); MEDLINE (Ovid, 1946 onwards); SCOPUS (1823 onwards); PsycINFO (EBSCOhost, 1887 onwards); CINAHL Plus (EBSCOhost, 1937 onwards); ClinicalTrials.gov; and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP). We used no language restrictions. The date of the last search was 12 November 2015. We checked the reference lists of retrieved studies for additional reports of relevant studies and contacted lead study authors for any relevant unpublished material. We identified duplicate studies by screening reports according to title, authors' names, location, and medical institute, omitting any duplicated studies. We identified any grey literature studies published in the last five years by searching: Zetoc database; ISI Proceedings; International Bureau for Epilepsy (IBE) congress proceedings database; International League Against Epilepsy (ILAE) congress proceedings database; abstract books of symposia and congresses, meeting abstracts, and research reports. We aimed to include randomised controlled trials (RCTs), quasi-RCTs, and cluster-RCTs; prospective non-randomised cohort controlled and uncontrolled studies; and case-control studies of adults and children with epilepsy receiving an intervention for the prevention of SUDEP. Types of interventions included: early versus delayed pre-surgical evaluation for lesional epilepsy; educational programmes; seizure-monitoring devices; safety pillows; nocturnal supervision; selective serotonin reuptake inhibitors (SSRIs); opiate antagonists; and adenosine antagonists. We aimed to collect data on study design factors and participant demographics for included studies. The primary outcome of interest was the number of deaths from SUDEP. Secondary outcomes included: number of other deaths (unrelated to SUDEP); change in mean depression and anxiety scores (as defined within the study); clinically important change in quality of life, that is any change in quality of life score (average and endpoint) according to validated quality of life scales; and number of hospital attendances for seizures. We identified 582 records from the databases and search strategies. We found 10 further records by searching other resources (handsearching). We removed 211 duplicate records and screened 381 records (title and abstract) for inclusion in the review. We excluded 364 records based on the title and abstract and assessed 17 full-text articles. We excluded 15 studies: eight studies did not assess interventions to prevent SUDEP; five studies measured sensitivity of devices to detect GTCS but did not directly measure SUDEP; and two studies assessed risk factors for SUDEP but not interventions for preventing SUDEP. One listed study is awaiting classification.We included one case-control study at serious risk of bias within a qualitative analysis in this review. This study of 154 cases of SUDEP and 616 controls ascertained a protective effect for the presence of nocturnal supervision (unadjusted odds ratio (OR) 0.34, 95% confidence interval (CI) 0.22 to 0.53) and when a supervising person shared the same bedroom or when special precautions, for example a listening device, were used (unadjusted OR 0.41, 95% CI 0.20 to 0.82). This effect was independent of seizure control. Non-SUDEP deaths; changes to anxiety, depression, and quality of life; and number of hospital attendances were not reported. We found very low-quality evidence of a preventative effect for nocturnal supervision against SUDEP. Further research is required to identify the effectiveness of other current interventions, for example seizure detection devices, safety pillows, SSRIs, early surgical evaluation, educational programmes, and opiate and adenosine antagonists in preventing SUDEP in people with epilepsy.

Toward a Real-Time (Day) Dreamcatcher: Sensor-Free Detection of Mind Wandering during Online Reading

ERIC Educational Resources Information Center

Mills, Caitlin; D'Mello, Sidney

2015-01-01

This paper reports the results from a sensor-free detector of mind wandering during an online reading task. Features consisted of reading behaviors (e.g., reading time) and textual features (e.g., level of difficulty) extracted from self-paced reading log files. Supervised machine learning was applied to two datasets in order to predict if…

Human Expert Labeling Process (HELP): Towards a Reliable Higher-Order User State Labeling Process and Tool to Assess Student Engagement

ERIC Educational Resources Information Center

Aslan, Sinem; Mete, Sinem Emine; Okur, Eda; Oktay, Ece; Alyuz, Nese; Genc, Utku Ergin; Stanhill, David; Esme, Asli Arslan

2017-01-01

In a series of longitudinal research studies, researchers at Intel Corporation in Turkey have been working towards an adaptive learning system automatically detecting student engagement as a higher-order user state in real-time. The labeled data necessary for supervised learning can be obtained through labeling conducted by human experts. Using…

Detection and Mapping of the Geomorphic Effects of Flooding Using UAV Photogrammetry

NASA Astrophysics Data System (ADS)

Langhammer, Jakub; Vacková, Tereza

2018-04-01

In this paper, we present a novel technique for the objective detection of the geomorphological effects of flooding in riverbeds and floodplains using imagery acquired by unmanned aerial vehicles (UAVs, also known as drones) equipped with an panchromatic camera. The proposed method is based on the fusion of the two key data products of UAV photogrammetry, the digital elevation model (DEM), and the orthoimage, as well as derived qualitative information, which together serve as the basis for object-based segmentation and the supervised classification of fluvial forms. The orthoimage is used to calculate textural features, enabling detection of the structural properties of the image area and supporting the differentiation of features with similar spectral responses but different surface structures. The DEM is used to derive a flood depth model and the terrain ruggedness index, supporting the detection of bank erosion. All the newly derived information layers are merged with the orthoimage to form a multi-band data set, which is used for object-based segmentation and the supervised classification of key fluvial forms resulting from flooding, i.e., fresh and old gravel accumulations, sand accumulations, and bank erosion. The method was tested on the effects of a snowmelt flood that occurred in December 2015 in a montane stream in the Sumava Mountains, Czech Republic, Central Europe. A multi-rotor UAV was used to collect images of a 1-km-long and 200-m-wide stretch of meandering stream with fresh traces of fluvial activity. The performed segmentation and classification proved that the fusion of 2D and 3D data with the derived qualitative layers significantly enhanced the reliability of the fluvial form detection process. The assessment accuracy for all of the detected classes exceeded 90%. The proposed technique proved its potential for application in rapid mapping and detection of the geomorphological effects of flooding.

Adequate supervision for children and adolescents.

PubMed

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.

[Physicians and nurses subjected to disciplinary actions because of substance abuse. Ten years of experience with supervision in Copenhagen].

PubMed

Hansen, Elisabet Tornberg; Fouchard, Jan R; Hoffmeyer, Jane H; Rosdahl, Nils

2002-11-18

Medical Health Officers supervise medical staff on behalf of the Danish National Board of Health. The Board can impose disciplinary action on registered providers of health care. This retrospective investigation was based on case reports from 1 January 1989 to 31 December 1995 on medical staff under individual supervision because of alcohol or drug abuse, with a 3-year follow-up to 31 December 1998 in Greater Copenhagen (about 1.25 million inhabitants). Altogether 173 health personnel were identified. Of these, 47 physicians and 91 nurses had disciplinary actions imposed on them because of abuse. In well over a third the abuse had lasted less than two years, whereas in a third it had lasted more than five years before admission to individual supervision. Half of both physicians and nurses had undergone psychiatric treatment before that time. Frequent disciplinary actions imposed were examination of urine passed without prior warning and controlled treatment of alcohol abuse. Difficulties in adhering to these conditions were found in one third to half of the cases. The Medical Health Officers notified the National Board of Health of breaches in 64%, often several times for each person. At the end of the follow-up period, 49% were still working. There was a statistically significant excess mortality in the group. Of the 26 dead, four had committed suicide and in a further 12 cases poisoning or abuse was a contributory cause of death. Earlier detection, a tightening of sanctions, and improved treatment are recommended.

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy.

PubMed

Salvatore, C; Cerasa, A; Castiglioni, I; Gallivanone, F; Augimeri, A; Lopez, M; Arabia, G; Morelli, M; Gilardi, M C; Quattrone, A

2014-01-30

Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feasibility of a supervised machine learning algorithm for the assisted diagnosis of patients with clinically diagnosed Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP). Morphological T1-weighted Magnetic Resonance Images (MRIs) of PD patients (28), PSP patients (28) and healthy control subjects (28) were used by a supervised machine learning algorithm based on the combination of Principal Components Analysis as feature extraction technique and on Support Vector Machines as classification algorithm. The algorithm was able to obtain voxel-based morphological biomarkers of PD and PSP. The algorithm allowed individual diagnosis of PD versus controls, PSP versus controls and PSP versus PD with an Accuracy, Specificity and Sensitivity>90%. Voxels influencing classification between PD and PSP patients involved midbrain, pons, corpus callosum and thalamus, four critical regions known to be strongly involved in the pathophysiological mechanisms of PSP. Classification accuracy of individual PSP patients was consistent with previous manual morphological metrics and with other supervised machine learning application to MRI data, whereas accuracy in the detection of individual PD patients was significantly higher with our classification method. The algorithm provides excellent discrimination of PD patients from PSP patients at an individual level, thus encouraging the application of computer-based diagnosis in clinical practice. Copyright © 2013 Elsevier B.V. All rights reserved.

Short- and long-term effects of imprisonment on future felony convictions and prison admissions.

PubMed

Harding, David J; Morenoff, Jeffrey D; Nguyen, Anh P; Bushway, Shawn D

2017-10-17

A substantial contributor to prison admissions is the return of individuals recently released from prison, which has come to be known as prison's "revolving door." However, it is unclear whether being sentenced to prison itself has a causal effect on the probability of a subsequent return to prison or on criminal behavior. To examine the causal effect of being sentenced to prison on subsequent offending and reimprisonment, we leverage a natural experiment using the random assignment of judges with different propensities for sentencing offenders to prison. Drawing on data on all individuals sentenced for a felony in Michigan between 2003 and 2006, we compare individuals sentenced to prison to those sentenced to probation, taking into account sentence lengths and stratifying our analysis by race. Results show that being sentenced to prison rather than probation increases the probability of imprisonment in the first 3 years after release from prison by 18 percentage points among nonwhites and 19 percentage points among whites. Further results show that such effects are driven primarily by imprisonment for technical violations of community supervision rather than new felony convictions. This suggests that more stringent postprison parole supervision (relative to probation supervision) increases imprisonment through the detection and punishment of low-level offending or violation behavior. Such behavior would not otherwise result in imprisonment for someone who had not already been to prison or who was not on parole. These results demonstrate that the revolving door of prison is in part an effect of the nature of postprison supervision.

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

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…

High degree of supervision improves adherence to inhaled corticosteroids in children with asthma

PubMed Central

Park, Geun Mi; Han, Hye Won; Kim, Hee Se; Kim, Jae Youn; Lee, Eun; Cho, Hyun-Ju; Yang, Song-I; Jung, Young-Ho; Hong, Soo-Jong; Kim, Hyung Young; Seo, Ju-Hee

2015-01-01

Purpose Adherence to treatment with inhaled corticosteroids (ICS) is a critical determinant of asthma control. The objective of this study was to assess factors that determine adherence to ICS therapy in children with asthma. Methods Fifty-eight children with asthma, aged 5 to 16 years, used ICS with or without a spacer for 3 months. Adherence rates as measured from questionnaires and canisters, asthma symptom scores, and inhalation technique scores were assessed every 30 days. The degree of supervision by caregivers was assessed at day 30. Results Adherence rates measured using canisters were lower at day 60 than at day 30 (P=0.044) and did not change thereafter (74.4%±17.4% at day 30, 66.5%±18.4% at day 60, and 67.4%±22.2% at day 90). Adherence rates at days 60 and 90 and during the total study period were significantly different when measured by using questionnaires versus canisters (P<0.001, P=0.022, and P=0.001, respectively). In the comparison of adherence rates repeatedly measured at days 30, 60, and 90 and adherence rates during the total study period among the 3 groups, adherence rates in the high-degree supervision group were significantly higher than those in the low-degree supervision group (82.0±16.0 vs. 66.1±14.5, 75.4±14.4 vs. 56.2±18.4, 75.0±18.3 vs. 55.0±19.7 [P=0.027]; 77.9±12.2 vs. 59.1±11.4 [P=0.021]) after adjustment for sex and age. Conclusion The level of caregiver supervision is an important factor affecting adherence to ICS therapy in children with asthma. Therefore, a high degree of supervision may be required to increase adherence to ICS therapy in children with asthma. PMID:26770222

Application of learning to rank to protein remote homology detection.

PubMed

Liu, Bin; Chen, Junjie; Wang, Xiaolong

2015-11-01

Protein remote homology detection is one of the fundamental problems in computational biology, aiming to find protein sequences in a database of known structures that are evolutionarily related to a given query protein. Some computational methods treat this problem as a ranking problem and achieve the state-of-the-art performance, such as PSI-BLAST, HHblits and ProtEmbed. This raises the possibility to combine these methods to improve the predictive performance. In this regard, we are to propose a new computational method called ProtDec-LTR for protein remote homology detection, which is able to combine various ranking methods in a supervised manner via using the Learning to Rank (LTR) algorithm derived from natural language processing. Experimental results on a widely used benchmark dataset showed that ProtDec-LTR can achieve an ROC1 score of 0.8442 and an ROC50 score of 0.9023 outperforming all the individual predictors and some state-of-the-art methods. These results indicate that it is correct to treat protein remote homology detection as a ranking problem, and predictive performance improvement can be achieved by combining different ranking approaches in a supervised manner via using LTR. For users' convenience, the software tools of three basic ranking predictors and Learning to Rank algorithm were provided at http://bioinformatics.hitsz.edu.cn/ProtDec-LTR/home/ bliu@insun.hit.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The effects of clinical supervision on supervisees and patients in cognitive behavioral therapy: a systematic review.

PubMed

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.

Supervision of Facilitators in a Multisite Study: Goals, Process, and Outcomes

PubMed Central

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

Guidelines for clinical supervision in health service psychology.

PubMed

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.

Unsupervised EEG analysis for automated epileptic seizure detection

NASA Astrophysics Data System (ADS)

Birjandtalab, Javad; Pouyan, Maziyar Baran; Nourani, Mehrdad

2016-07-01

Epilepsy is a neurological disorder which can, if not controlled, potentially cause unexpected death. It is extremely crucial to have accurate automatic pattern recognition and data mining techniques to detect the onset of seizures and inform care-givers to help the patients. EEG signals are the preferred biosignals for diagnosis of epileptic patients. Most of the existing pattern recognition techniques used in EEG analysis leverage the notion of supervised machine learning algorithms. Since seizure data are heavily under-represented, such techniques are not always practical particularly when the labeled data is not sufficiently available or when disease progression is rapid and the corresponding EEG footprint pattern will not be robust. Furthermore, EEG pattern change is highly individual dependent and requires experienced specialists to annotate the seizure and non-seizure events. In this work, we present an unsupervised technique to discriminate seizures and non-seizures events. We employ power spectral density of EEG signals in different frequency bands that are informative features to accurately cluster seizure and non-seizure events. The experimental results tried so far indicate achieving more than 90% accuracy in clustering seizure and non-seizure events without having any prior knowledge on patient's history.

The Show Must Go On.

ERIC Educational Resources Information Center

Faust, Debra Dion

1995-01-01

Discusses the challenges of sponsoring extracurricular drama activities from the planning of a theatre season to the supervision of acting. Suggests changes to make the job more manageable. Makes a case for why dramatic productions are especially effective vehicles of education. (TB)

17 CFR 240.17i-3 - Withdrawal from supervision by the Commission as a supervised investment bank holding company.

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...

Building an Evidence Base for Effective Supervision Practices: An Analogue Experiment of Supervision to Increase EBT Fidelity.

PubMed

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.

The Juggling Act of Supervision in Community Mental Health: Implications for Supporting Evidence-Based Treatment.

PubMed

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.

Factors influencing the perceived quality of clinical supervision of occupational therapists in a large Australian state.

PubMed

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.

Safety of Aerobic Exercise in People With Diabetic Peripheral Neuropathy: Single-Group Clinical Trial

PubMed Central

Pasnoor, Mamatha; Singh, Rupali; D'Silva, Linda J.; Yoo, Min; Billinger, Sandra A.; LeMaster, Joseph W.; Dimachkie, Mazen M.; Herbelin, Laura; Wright, Douglas E.

2015-01-01

Background Exercise is recommended for people with diabetes, but little is known about exercise in people with diabetic peripheral neuropathy (DPN). Objective The primary purpose of this preliminary study was to examine adverse events (AEs) during moderate-intensity, supervised aerobic exercise in people with DPN. The secondary purpose was to examine changes in fatigue, aerobic fitness, and other outcomes after intervention. Design This was a single-group preliminary study. Setting The setting was an academic medical center. Participants Participants were 18 people who were sedentary and had type 2 diabetes and peripheral neuropathy (mean age=58.1 years, SD=5). Intervention The intervention was a supervised 16-week aerobic exercise program (3 times per week at 50% to >70% oxygen uptake reserve). Measurements Adverse events were categorized as related or unrelated to the study, anticipated or unanticipated, and serious or not serious. Outcomes included fatigue (Multidimensional Fatigue Inventory), cardiovascular fitness (peak oxygen uptake), body composition (dual-energy x-ray absorptiometry), sleep quality, plasma metabolic markers, and peripheral vascular function. Results During the study, 57 nonserious AEs occurred. Improvements were found in general fatigue (mean change=−3.5; 95% confidence interval [95% CI]=−1.3, −5.3), physical fatigue (mean change=−3.1; 95% CI=−1.2, −5.0), peak oxygen uptake (mean change=1.1 mL·kg−1·min−1; 95% CI=0.2, 1.9), total body fat (mean change=−1%; 95% CI=−0.3, −1.7), fat mass (mean change=−1,780 g; 95% CI=−616.2, −2,938.7), and peripheral blood flow (mean change=2.27%; 95% CI=0.6, 4.0). Limitations This was a small-scale, uncontrolled study. A future randomized controlled trial is needed to fully assess the effects of exercise on the outcomes. Conclusions This study provides new support for supervised aerobic exercise in people with DPN. However, it is important for physical therapists to carefully prescribe initial exercise intensity and provide close monitoring and education to address the anticipated AEs as people who are sedentary and have DPN begin an exercise program. PMID:25278335

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.

Preschool Education in Portugal: Development, Innovation and Changes. A True Mobilising Contract.

ERIC Educational Resources Information Center

Vasconcelos, Teresa

Changes in the preschool education system are provided for by a new federal law in Portugal, Law 5/97, Law for Preschool Education. This law calls for a new role for the State that involves fewer direct services, less bureaucracy, more efficient supervision, and a greater regulating and compensating role. The law requires parents to participate in…

Using Self-Study to Develop a Third Space for Collaborative Supervision of Master's Projects in Teacher Education

ERIC Educational Resources Information Center

Jónsdóttir, Svanborg R.; Gísladóttir, Karen Rut; Guðjónsdóttir, Hafdís

2015-01-01

Teacher education is constantly being renewed in response to continuous social, economic and technological changes. In 2008, teacher education in Iceland was extended from a three-year to a five-year master's degree program and this significantly increased the number of students at the master's level. To respond to these changes, 3…

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...

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...

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...

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...

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...

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...

Field-deployable sniffer for 2,4-dinitrotoluene detection.

PubMed

Albert, K J; Myrick, M L; Brown, S B; James, D L; Milanovich, F P; Walt, D R

2001-08-01

A field-deployable instrument has been developed to detect low-level 2,4-dinitrotoluene (2,4-DNT) vapors. The system is based on previously developed artificial nose technology and employs an array of sensory materials attached to the distal tips of an optical fiber bundle. Both semiselective and nonspecific, cross-reactive sensors were employed. Each sensor within the array responds differentially to vapor exposure so the array's fluorescence response patterns are unique for each analyte. The instrument is computationally "trained" to discriminate target response patterns from nontarget and background environments. This detection system has been applied to detect 2,4-DNT, an analyte commonly detected on the soil surface above buried 2,4,6-trinitrotoluene (TNT) land mines, in spiked soil and aqueous and ground samples. The system has been characterized and demonstrated the ability to detect 120 ppb 2,4-DNT vapor in blind (unknown) humidified samples during a supervised field test.

Eavesdropping on the Arctic: Automated Bioacoustics Promise to Untangle Climate-Induced Shifts in Songbird Migration

NASA Astrophysics Data System (ADS)

Oliver, R.; Ellis, D.; Gough, L.; Chmura, H.; Sweet, S. K.; Boelman, N.; Krause, J.; Perez, J.; Wingfield, J.

2017-12-01

Climate change is altering the seasonality of environmental conditions and the phenology of vegetation, particularly at high northern latitudes. Yet changes in the phenology of wildlife that rely on northern ecosystems is significantly understudied. In much the same way that remote sensing enables global-scale observations of climate and vegetation, ground-based bioacoustic recording networks have the potential to vastly expand the spatial and temporal coverage of wildlife monitoring. However, the enormous datasets that autonomous recorders typically generate demand automated analyses that remain largely undeveloped. To unleash the potential for global-scale bioacoustic monitoring, we developed automated signal processing and machine learning algorithms to generate seasonal times series of breeding songbird vocal activity from 1200 hours of landscape-level recordings in northern Alaska. The calendar dates on which songbird communities arrived to their breeding grounds in five springs (2010-2014) were automatically extracted from the time series, and agreed within 3 days to those determined via traditional avian surveys (RMSE = 1.88 - 3.02). Relative to other years, our bioacoustic approach identified a 1-9 day delay in the arrival of long distance migratory songbird communities to their breeding grounds in 2013 - a spring characterized by persistent snow cover and cold temperatures. Differences in arrival timing among sites were strongly related to the date on which the landscape surrounding the microphone became snow-free, particularly in the supervised approach (supervised: R2 = 0.59, p < 0.01 and unsupervised: R2 = 0.13, p = 0.15). We found daily variation in vocal activity was heavily influenced by environmental conditions - primarily snow cover and temperature, and especially prior to egg laying (R2 = 0.61 +/- 0.07 vs. 0.23 +/- 0.07, p < 0.1) - suggesting that extending bioacoustics analysis beyond arrival date estimation requires coupling recordings with meteorological networks and information on community breeding phenology. The success of our novel analytical approach demonstrates that shifts in avian migratory behavior could be detected autonomously, which would provide the coverage necessary to determine and project the influence of climate on rapidly changing ecosystems.

Detection of new-onset choroidal neovascularization.

PubMed

Do, Diana V

2013-05-01

To highlight the most common methods that are used to detect new-onset choroidal neovascularization (CNV) as a result of age-related macular degeneration (AMD). Numerous modalities are available to try to detect CNV. Amsler grid testing, preferential hyperacuity perimetry (PHP), optical coherence tomography (OCT), and fluorescein angiography are tools that may be used to detect CNV. The Age-Related Macular Degeneration: Detection of Onset of new Choroidal neovascularization Study (AMD DOC Study) evaluated the sensitivity of time domain OCT, relative to fluorescein angiography, in detecting new-onset neovascular AMD within a 2-year period. The sensitivity of each modality for detecting CNV was OCT 0.40 [(95% confidence interval (95% CI) (0.16-0.68), supervised Amsler grid 0.42 (95% CI 0.15-0.72), and PHP 0.50 (95% CI 0.23-0.77)]. Numerous modalities are available to try to detect CNV. The prospective AMD DOC Study demonstrated that fluorescein angiography still remains the best method to detect new-onset CNV.

Developing a Peer Mentorship Program to Increase Competence in Clinical Supervision in Clinical Psychology Doctoral Training Programs.

PubMed

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.

Is parenting the mediator of change in behavioral parent training for externalizing problems of youth?

PubMed

Forehand, Rex; Lafko, Nicole; Parent, Justin; Burt, Keith B

2014-12-01

Change in parenting behavior is theorized to be the mediator accounting for change in child and adolescent externalizing problems in behavioral parent training (BPT). The purpose of this review is to examine this assumption in BPT prevention and intervention programs. Eight intervention and 17 prevention studies were identified as meeting all criteria or all but one criterion for testing mediation. Parenting behaviors were classified as positive, negative, discipline, monitoring/supervision, or a composite measure. Forty-five percent of the tests performed across studies to test mediation supported parenting as a mediator. A composite measure of parenting and discipline received the most support, whereas monitoring/supervision was rarely examined. More support for the mediating role of parenting emerged for prevention than intervention studies and when meeting all criteria for testing mediation was not required. Although the findings do not call BPT into question as an efficacious treatment, they do suggest more attention should be focused on examining parenting as a putative mediator in BPT. Copyright © 2014 Elsevier Ltd. All rights reserved.

Effect of Supervised Pelvic Floor Biofeedback and Electrical Stimulation in Women With Mixed and Stress Urinary Incontinence.

PubMed

Richmond, Cherrilyn F; Martin, Deanna K; Yip, Sallis O; Dick, Madeline A; Erekson, Elisabeth A

2016-01-01

The aim of this study was to compare the symptomatic change in urinary symptom distress before and after treatment with pelvic floor biofeedback and electrical stimulation in women with mixed urinary incontinence (MUI) and stress urinary incontinence (SUI). We conducted a retrospective cohort study of women who underwent supervised pelvic floor biofeedback therapy and electrostimulation for the treatment of MUI and SUI. Our primary outcome was change in the Urinary Distress Inventory-6 (UDI-6) score before and after therapy. Overall, a significant drop in UDI-6 score was seen in women with MUI (mean decrease, 29.1 [27.5]; P < 0.001), and a nonsignificant drop was seen in women with SUI (mean decrease, 6.8 [20.3]; P = 0.07) after treatment. Significantly greater change in UDI-6 score from baseline to follow-up was noted in women with MUI compared with those with SUI (P = 0.002). Women with MUI have greater urinary distress symptoms than women with SUI. Both women with MUI and SUI experienced significant improvement in their urinary distress symptoms after pelvic floor biofeedback and electrostimulation.

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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…

Preparation of a Manuscript on Leadership Dynamics.

DTIC Science & Technology

1977-11-01

Sciences Division, Office of Naval Research IB- KEY WORDS (Confirm* en feverae »Id» II rfc*,,mr, and Identity fey Meek number,) Leadership ... Management , Supervision Leader-Follower Relations Leadership Effectiveness, 3roup and Organizational Performance, Planned Change j 20. ABSTRACT

A Pilot Study Examining Factors Influencing Readiness to Progress to Indirect Supervision Among First Year Residents in a General Psychiatry Training Program.

PubMed

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.

Analysis of land cover change and its driving forces in a desert oasis landscape of southern Xinjiang, China

NASA Astrophysics Data System (ADS)

Amuti, T.; Luo, G.

2014-07-01

The combined effects of drought, warming and the changes in land cover have caused severe land degradation for several decades in the extremely arid desert oases of Southern Xinjiang, Northwest China. This study examined land cover changes during 1990-2008 to characterize and quantify the transformations in the typical oasis of Hotan. Land cover classifications of these images were performed based on the supervised classification scheme integrated with conventional vegetation and soil indexes. Change-detection techniques in remote sensing (RS) and a geographic information system (GIS) were applied to quantify temporal and spatial dynamics of land cover changes. The overall accuracies, Kappa coefficients, and average annual increase rate or decrease rate of land cover classes were calculated to assess classification results and changing rate of land cover. The analysis revealed that major trends of the land cover changes were the notable growth of the oasis and the reduction of the desert-oasis ecotone, which led to accelerated soil salinization and plant deterioration within the oasis. These changes were mainly attributed to the intensified human activities. The results indicated that the newly created agricultural land along the margins of the Hotan oasis could result in more potential areas of land degradation. If no effective measures are taken against the deterioration of the oasis environment, soil erosion caused by land cover change may proceed. The trend of desert moving further inward and the shrinking of the ecotone may lead to potential risks to the eco-environment of the Hotan oasis over the next decades.

Geospatial analysis of land use change in the Savannah River Basin using Google Earth Engine

NASA Astrophysics Data System (ADS)

Zurqani, Hamdi A.; Post, Christopher J.; Mikhailova, Elena A.; Schlautman, Mark A.; Sharp, Julia L.

2018-07-01

Climate and land use/cover change are among the most pervasive issues facing the Southeastern United States, including the Savannah River basin in South Carolina and Georgia. Land use directly affects the natural environment across the Savannah River basin and it is important to analyze these impacts. The objectives of this study are to: 1) determine the classes and the distribution of land cover in the Savannah River basin; 2) identify the spatial and the temporal change of the land cover that occurs as a consequence of land use change in the area; and 3) discuss the potential effects of land use change in the Savannah River basin. The land cover maps were produced using random forest supervised classification at four time periods for a total of thirteen common land cover classes with overall accuracy assessments of 79.18% (1999), 79.41% (2005), 76.04% (2009), and 76.11% (2015). The major land use change observed was due to the deforestation and reforestation of forest areas during the entire study period. The change detection results using the normalized difference vegetation index (NDVI) indicated that the proportion areas of the deforestation were 5.93% (1999-2005), 4.63% (2005-2009), and 3.76% (2009-2015), while the proportion areas of the reforestation were 1.57% (1999-2005), 0.44% (2005-2009), and 1.53% (2009-2015). These results not only indicate land use change, but also demonstrate the advantage of utilizing Google Earth Engine and the public archive database in its platform to track and monitor this change over time.

Resistance to group clinical supervision: A semistructured interview study of non-participating mental health nursing staff members.

PubMed

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.

Supervised guiding long-short term memory for image caption generation based on object classes

NASA Astrophysics Data System (ADS)

Wang, Jian; Cao, Zhiguo; Xiao, Yang; Qi, Xinyuan

2018-03-01

The present models of image caption generation have the problems of image visual semantic information attenuation and errors in guidance information. In order to solve these problems, we propose a supervised guiding Long Short Term Memory model based on object classes, named S-gLSTM for short. It uses the object detection results from R-FCN as supervisory information with high confidence, and updates the guidance word set by judging whether the last output matches the supervisory information. S-gLSTM learns how to extract the current interested information from the image visual se-mantic information based on guidance word set. The interested information is fed into the S-gLSTM at each iteration as guidance information, to guide the caption generation. To acquire the text-related visual semantic information, the S-gLSTM fine-tunes the weights of the network through the back-propagation of the guiding loss. Complementing guidance information at each iteration solves the problem of visual semantic information attenuation in the traditional LSTM model. Besides, the supervised guidance information in our model can reduce the impact of the mismatched words on the caption generation. We test our model on MSCOCO2014 dataset, and obtain better performance than the state-of-the- art models.

Image analysis and mathematical modelling for the supervision of the dough fermentation process

NASA Astrophysics Data System (ADS)

Zettel, Viktoria; Paquet-Durand, Olivier; Hecker, Florian; Hitzmann, Bernd

2016-10-01

The fermentation (proof) process of dough is one of the quality-determining steps in the production of baking goods. Beside the fluffiness, whose fundaments are built during fermentation, the flavour of the final product is influenced very much during this production stage. However, until now no on-line measurement system is available, which can supervise this important process step. In this investigation the potential of an image analysis system is evaluated, that enables the determination of the volume of fermented dough pieces. The camera is moving around the fermenting pieces and collects images from the objects by means of different angles (360° range). Using image analysis algorithms the volume increase of individual dough pieces is determined. Based on a detailed mathematical description of the volume increase, which based on the Bernoulli equation, carbon dioxide production rate of yeast cells and the diffusion processes of carbon dioxide, the fermentation process is supervised. Important process parameters, like the carbon dioxide production rate of the yeast cells and the dough viscosity can be estimated just after 300 s of proofing. The mean percentage error for forecasting the further evolution of the relative volume of the dough pieces is just 2.3 %. Therefore, a forecast of the further evolution can be performed and used for fault detection.

Technology for Range Security

DTIC Science & Technology

2005-06-01

friction- generated charge transfer between the inner and outer portions of a cable attached to the fence ( triboelectric ), by means of a charge transfer...helpful technical reviews of Paul Loechl, ERDC- CERL, and Joyce Nagle, ERDC-CRREL. This report was prepared under the general supervision of Dr...detection systems (IDSs) are designed to generate alarms when they sense human activity. IDSs attached to a fence (fence-mounted) respond to fence

Zero shot Event Detection using Multi modal Fusion of Weakly Supervised Concepts (Open Access)

DTIC Science & Technology

2014-09-25

I. Laptev. On space-time interest points. IJCV, 64(2-3):107– 123, 2005. [21] L.-J. Li, H. Su, E . Xing, and L. Fei-Fei. Object bank: A high-level image...invariant keypoints. IJCV, 60:91–110, 2004. [23] P. Natarajan, S. Wu, S. N. P. Vitaladevuni, X. Zhuang, S. Tsakalidis , U. Park, R. Prasad, and P

From new vistas to life lines: psychologists' satisfaction with supervision and confidence in supervising.

PubMed

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.

Monitoring Urban Land Cover/land Use Change in Algiers City Using Landsat Images (1987-2016)

NASA Astrophysics Data System (ADS)

Bouchachi, B.; Zhong, Y.

2017-09-01

Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

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)

Heading off boundary problems: clinical supervision as risk management.

PubMed

Walker, R; Clark, J J

1999-11-01

The effective management of risk in clinical practice includes steps to limit harm to clients resulting from ethical violations or professional misconduct. Boundary problems constitute some of the most damaging ethical violations. The authors propose an active use of clinical supervision to anticipate and head off possible ethical violations by intervening when signs of boundary problems appear. The authors encourage a facilitative, Socratic method, rather than directive approaches, to help supervisees maximize their learning about ethical complexities. Building on the idea of a slippery slope, in which seemingly insignificant acts can lead to unethical patterns of behavior, the authors discuss ten cues to potential boundary problems, including strong feelings about a client; extended sessions with clients; gift giving between clinician and client; loans, barter, and sale of goods; clinician self-disclosures; and touching and sex. The authors outline supervisory interventions to be made when the cues are detected.

Implementing the supportive supervision intervention for registered nurses in a long-term care home: a feasibility study.

PubMed

McGilton, Katherine S; Profetto-McGrath, Joanne; Robinson, Angela

2013-11-01

This pilot study was conducted in response to the call in 2009 by the International Association of Gerontology and Geriatrics to focus on effective leadership structures in nursing homes and to develop leadership capacity. Few researchers have evaluated interventions aimed at enhancing the leadership ability of registered nurses in long-term care. The aim of the pilot study was to test the feasibility of a three-part supportive supervisory intervention to improve supervisory skills of registered nurses in long-term care. A repeated measures group design was used. Quantitative data were collected from healthcare aides, licensed practical nurses (i.e., supervised staff), and registered nurses (i.e., supervisors). Focus groups with care managers and supervisors examined perceptions of the intervention. There were nonsignificant changes in both the registered nurse supervisors' job satisfaction and the supervised staff's perception of their supervisors' support. Supervised staff scores indicated an increase in the use of research utilization but did not reflect an increase in job satisfaction. Focus group discussions revealed that the supervisors and care managers perceived the workshop to be valuable; however, the weekly self-reflection, coaching, and mentoring components of the intervention were rare and inconsistent. While the primary outcomes were not influenced by the Supportive Supervision Intervention, further effort is required to understand how best to enhance the supportive supervisory skills of RNs. Examples of how to improve the possibility of a successful intervention are advanced. Effective supervisory skills among registered nurses are crucial for improving the quality of care in long-term care homes. Registered nurses are receptive to interventions that will enhance their roles as supervisors. © 2013 Sigma Theta Tau International.

What influences palliative care nurses in their choice to engage in or decline clinical supervision?

PubMed

Puffett, Nick; Perkins, Paul

2017-11-02

Clinical supervision (CS) has been around since the early 1990s in the UK and has been endorsed by government and professional bodies. Levels of engagement range from 18% to 85%. To investigate what influences palliative care nurses in their choice to engage in or decline clinical supervision. A qualitative study was undertaken in an inpatient hospice in England and employed two focus groups to compare the views of participants and non-participants in CS. Data were audio recorded and transcribed verbatim by the researchers and analysed using systematic text condensation. Palliative care nurses all used informal team support for 'in the moment' support. Some engaged in formal CS to reflect 'on action' and to challenge practice. Nurses reported a lack of clarity regarding CS but, once this was overcome and engagement with CS was established, it led to changes in practice, identification of training needs and team building. The option of choice between group and individual supervision was found to be important. Group supervision led to enhanced understanding of group members which also led to team building, individual sessions were useful for individual issues. Protected time was essential for staff to be able to engage in CS. Staff who worked in larger teams reported higher levels of engagement, whereas a small team reported less need due to more informal team support. These findings are positive as they illuminate the importance of choice for support. Nurses need to be aware of their options for support and ultimately how this support affects the care they provide. The Palliative Care Nurse's Model of Support was developed, which shows the effects of each choice and how this may lead to team-building.

[Occupational hazards survey of specially supervised enterprises during 2011-2012 in one district of Shenzhen, China].

PubMed

Zhang, Hongsheng; Zhang, Xianxing; Zhang, Chu; Liu, Song; He, Jian-Feng

2014-04-01

To analyze the results of an occupational hazards survey of specially supervised enterprises (156 enterprise-times) during 2011-2012 in one district of Shenzhen, China and find out the changes in occupational hazards in these enterprises, and to put forward countermeasures for the prevention and control of occupational hazards. Occupational hazards monitoring results for specially supervised enterprises (156 enterprise-times) during 2011-2012 were included. Comparison and analysis were performed between different years, different industries, different occupational hazards, and different sizes of enterprises. A total of 1274 monitoring sites from these specially supervised enterprises were included, of which qualification rate was 73.55% (937/1274), and the noise monitoring sites showed the lowest qualification rate. The overall qualification rate in 2012 (70.37%) was significantly lower than that in 2011 (80.94%) (χ(2) = 15.38, P < 0.01). In electronics industry, the qualification rate in 2012 was significantly lower than that in 2011 (χ2 = 11.27, P = 0.001). Comparison of various hazards in different industries indicated that electronic enterprises and furniture enterprises had the lowest qualification rate in noise monitoring, printing enterprises had the lowest qualification rate in organic solvent monitoring, and furniture enterprises had the lowest qualification rate in dust monitoring. Comparison between different sizes of enterprises indicated that the qualification rate of large and medium enterprises in 2012 was significantly lower than that in 2011, while the qualification rate of small enterprises in 2012 was significantly higher than that in 2011 (P < 0.01 or P < 0.05). In the prevention and control of occupational hazards in specially supervised enterprises, special attention should be paid to the control of organic solvents in printing enterprises and noise and dust in furniture enterprises.

Impact of a supervised worksite exercise program on back and core muscular endurance in firefighters.

PubMed

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.

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...

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…

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…

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…

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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…

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...

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…

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...

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...

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...

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.

Administrative clinical supervision as evaluated by the first-line managers in one health care organization district.

PubMed

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.

Clinical Supervision of Interns: Understanding the View of Interns and the Potential of ICT to Deliver Supervision for Safer Patient Care.

PubMed

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.

Geographic Information Technologies as an outreach activity in geo-scientific education

NASA Astrophysics Data System (ADS)

Maman, Shimrit; Isaacson, Sivan; Blumberg, Dan G.

2016-04-01

In recent years, a decline in the rates of examinees in the academic track that were entitled to an enhanced matriculation certificate in scientific-technological education was reported in Israel. To confront this problem the Earth and Planetary Image Facility (EPIF) at Ben-Gurion University of the Negev fosters interdisciplinary exploration through educational programs that make use of the facility and its equipment and enable the empowerment of the community by understanding and appreciating science and technology. This is achieved by using Geographic Information Technologies (GIT) such as remote sensing and Geographical Information Systems (GIS) for geo-physical sciences in activities that combine theoretical background with hands-on activities. Monitoring Earth from space by satellites, digital atlases and virtual-based positioning applications are examples for fusion of spatial information (geographic) and technology that the activity is based on. GIT opens a new chapter and a recent history of Cartography starting from the collection of spatial data to its presentation and analysis. GIS have replaced the use of classical atlas books and offer a variety of Web-based applications that provide maps and display up-to-date imagery. The purpose of this workshop is to expose teachers and students to GITs which are applicable in every classroom. The activity imparts free geographic information systems that exist in cyberspace and accessible to single users as the Israeli national GIS and Google earth, which are based on a spatial data and long term local and global satellite imagery coverage. In this paper, our "Think global-Map Local" activity is presented. The activity uses GIS and change detection technologies as means to encourage students to explore environmental issues both around the globe and close to their surroundings. The students detect changes by comparing multi temporal images of a chosen site and learn how to map the alterations and produce change detection maps with simple and user friendly tools. The activity is offered both for students and supervised projects for teachers and youth.

Machine Learning Methods for Attack Detection in the Smart Grid.

PubMed

Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent

2016-08-01

Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.

25 CFR 115.407 - How is an address of record for a minor's supervised account changed?

Code of Federal Regulations, 2010 CFR

2010-04-01

... custodial parent(s) or legal guardian, if applicable; (3) A custody order from a court of competent... date of birth; (3) The minor's or emancipated minor's tribal enrollment number; and (4) The minor's or...

Inner-City Schools Get More Custodial Teachers.

ERIC Educational Resources Information Center

Campbell, Lloyd P.; Williamson, John A.

1978-01-01

In comparison to a group in White, middle class schools, the Pupil Control Ideology Inventory (PCI) indicated that student teachers in ghetto-type schools were more custodial even before their student teaching. The supervising teacher was not a major factor in attitude change. (SJL)

The changing face of transit : a worldwide survey of transportation agency practices

DOT National Transportation Integrated Search

2001-02-01

This report provides information on the survey of metros from around the world, about fare sales and collection, automatic train supervision, and station personnel practices that NYC Transit conducted in the fall of 2000. The three topics addressed w...

Clinical supervision: the state of the art.

PubMed

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.

Mangrove forest distributions and dynamics in Madagascar (1975-2005)

USGS Publications Warehouse

Giri, C.; Muhlhausen, J.

2008-01-01

Mangrove forests of Madagascar are declining, albeit at a much slower rate than the global average. The forests are declining due to conversion to other land uses and forest degradation. However, accurate and reliable information on their present distribution and their rates, causes, and consequences of change have not been available. Earlier studies used remotely sensed data to map and, in some cases, to monitor mangrove forests at a local scale. Nonetheless, a comprehensive national assessment and synthesis was lacking. We interpreted time-series satellite data of 1975, 1990, 2000, and 2005 using a hybrid supervised and unsupervised classification approach. Landsat data were geometrically corrected to an accuracy of ?? one-half pixel, an accuracy necessary for change analysis. We used a postclassification change detection approach. Our results showed that Madagascar lost 7% of mangrove forests from 1975 to 2005, to a present extent of ???2,797 km2. Deforestation rates and causes varied both spatially and temporally. The forests increased by 5.6% (212 km2) from 1975 to 1990, decreased by 14.3% (455 km 2) from 1990 to 2000, and decreased by 2.6% (73 km2) from 2000 to 2005. Similarly, major changes occurred in Bombekota Bay, Mahajamba Bay, the coast of Ambanja, the Tsiribihina River, and Cap St Vincent. The main factors responsible for mangrove deforestation include conversion to agriculture (35%), logging (16%), conversion to aquaculture (3%), and urban development (1%). ?? 2008 by MDPI.

SemiBoost: boosting for semi-supervised learning.

PubMed

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.

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…

The Team-Based Internal Supervision System Development for the Primary Schools under the Office of the Basic Education Commission

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…

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…

Extending Ladders: Findings from the Annie E. Casey Foundation's Jobs Initiative.

ERIC Educational Resources Information Center

Fleischer, Wendy

In 1995, the Anne E. Casey Foundation launched the Jobs Initiative (JI) in six cities to change labor market prospects for low-income young people in order to help them get jobs that could move their families out of poverty. The JI attempts to change the way employers recruit and supervise workers and how work is structured; to prepare workers and…

Neural network with dynamically adaptable neurons

NASA Technical Reports Server (NTRS)

Tawel, Raoul (Inventor)

1994-01-01

This invention is an adaptive neuron for use in neural network processors. The adaptive neuron participates in the supervised learning phase of operation on a co-equal basis with the synapse matrix elements by adaptively changing its gain in a similar manner to the change of weights in the synapse IO elements. In this manner, training time is decreased by as much as three orders of magnitude.

Tempering pediatric hospitalist supervision of residents improves admission process efficiency without decreasing quality of care.

PubMed

Biondi, Eric A; Leonard, Michael S; Nocera, Elizabeth; Chen, Rui; Arora, Jyoti; Alverson, Brian

2014-02-01

Many academic pediatric hospital medicine (PHM) divisions have recently increased in-house supervision of residents, often providing 24/7 in-house attending coverage. Contrary to this trend, we removed mandated PHM attending input during the admission process. We present an evaluation of this process change. This cohort study compared outcomes between patients admitted to the PHM service before (July 1, 2011-September 30, 2011) and after (July 1, 2012-September 30, 2012) the process change. We evaluated time from admission request to inpatient orders, length of stay (LOS), frequency of change in antibiotic choice, and rapid response team (RRT) calls within 24 hours of admission. Data were obtained via chart abstraction and from administrative databases. Wilcoxon rank sum and Fisher exact tests were used for analysis. We identified 182 and 210 admissions in the before and after cohorts, respectively. Median time between emergency department admission request and inpatient orders was significantly shorter after the change (123 vs 62 minutes, P < 0.001). We found no significant difference in LOS, the number of changes to initial resident antibiotic choice, standard of care, or RRTs called within the first 24 hours of admission. Removing mandated attending input in decision making for PHM admissions significantly decreased time to inpatient resident admission orders without a change in measurable clinical outcomes. © 2013 Society of Hospital Medicine.

On being supervised: getting value from a clinical supervisor and making the relationship work when it is not.

PubMed

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.

Enablers of and barriers to high quality clinical supervision among occupational therapists across Queensland in Australia: findings from a qualitative study.

PubMed

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.

The Use of E-supervision to Support Speech-Language Pathology Graduate Students during Student Teaching Practica

PubMed Central

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

Development of remote sensing based site specific weed management for Midwest mint production

NASA Astrophysics Data System (ADS)

Gumz, Mary Saumur Paulson

Peppermint and spearmint are high value essential oil crops in Indiana, Michigan, and Wisconsin. Although the mints are profitable alternatives to corn and soybeans, mint production efficiency must improve in order to allow industry survival against foreign produced oils and synthetic flavorings. Weed control is the major input cost in mint production and tools to increase efficiency are necessary. Remote sensing-based site-specific weed management offers potential for decreasing weed control costs through simplified weed detection and control from accurate site specific weed and herbicide application maps. This research showed the practicability of remote sensing for weed detection in the mints. Research was designed to compare spectral response curves of field grown mint and weeds, and to use these data to develop spectral vegetation indices for automated weed detection. Viability of remote sensing in mint production was established using unsupervised classification, supervised classification, handheld spectroradiometer readings and spectral vegetation indices (SVIs). Unsupervised classification of multispectral images of peppermint production fields generated crop health maps with 92 and 67% accuracy in meadow and row peppermint, respectively. Supervised classification of multispectral images identified weed infestations with 97% and 85% accuracy for meadow and row peppermint, respectively. Supervised classification showed that peppermint was spectrally distinct from weeds, but the accuracy of these measures was dependent on extensive ground referencing which is impractical and too costly for on-farm use. Handheld spectroradiometer measurements of peppermint, spearmint, and several weeds and crop and weed mixtures were taken over three years from greenhouse grown plants, replicated field plots, and production peppermint and spearmint fields. Results showed that mints have greater near infrared (NIR) and lower green reflectance and a steeper red edge slope than all weed species. These distinguishing characteristics were combined to develop narrow band and broadband spectral vegetation indices (SVIs, ratios of NIR/green reflectance), that were effective in differentiating mint from key weed species. Hyperspectral images of production peppermint and spearmint fields were then classified using SVI-based classification. Narrowband and broadband SVIs classified early season peppermint and spearmint with 64 to 100% accuracy compared to 79 to 100% accuracy for supervised classification of multispectral images of the same fields. Broadband SVIs have potential for use as an automated spectral indicator for weeds in the mints since they require minimal ground referencing and can be calculated from multispectral imagery which is cheaper and more readily available than hyperspectral imagery. This research will allow growers to implement remote sensing based site specific weed management in mint resulting in reduced grower input costs and reduced herbicide entry into the environment and will have applications in other specialty and meadow crops.

Methods of feminist family therapy supervision.

PubMed

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.

Clinical supervision in a community setting.

PubMed

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.

Health trainer-led motivational intervention plus usual care for people under community supervision compared with usual care alone: a study protocol for a parallel-group pilot randomised controlled trial (STRENGTHEN)

PubMed Central

Thompson, Tom P; Callaghan, Lynne; Hazeldine, Emma; Quinn, Cath; Walker, Samantha; Byng, Richard; Wallace, Gary; Creanor, Siobhan; Green, Colin; Hawton, Annie; Annison, Jill; Sinclair, Julia; Senior, Jane; Taylor, Adrian H

2018-01-01

Introduction People with experience of the criminal justice system typically have worse physical and mental health, lower levels of mental well-being and have less healthy lifestyles than the general population. Health trainers have worked with offenders in the community to provide support for lifestyle change, enhance mental well-being and signpost to appropriate services. There has been no rigorous evaluation of the effectiveness and cost-effectiveness of providing such community support. This study aims to determine the feasibility and acceptability of conducting a randomised trial and delivering a health trainer intervention to people receiving community supervision in the UK. Methods and analysis A multicentre, parallel, two-group randomised controlled trial recruiting 120 participants with 1:1 individual allocation to receive support from a health trainer and usual care or usual care alone, with mixed methods process evaluation. Participants receive community supervision from an offender manager in either a Community Rehabilitation Company or the National Probation Service. If they have served a custodial sentence, then they have to have been released for at least 2 months. The supervision period must have at least 7 months left at recruitment. Participants are interested in receiving support to change diet, physical activity, alcohol use and smoking and/or improve mental well-being. The primary outcome is mental well-being with secondary outcomes related to smoking, physical activity, alcohol consumption and diet. The primary outcome will inform sample size calculations for a definitive trial. Ethics and dissemination The study has been approved by the Health and Care Research Wales Ethics Committee (REC reference 16/WA/0171). Dissemination will include publication of the intervention development process and findings for the stated outcomes, parallel process evaluation and economic evaluation in peer-reviewed journals. Results will also be disseminated to stakeholders and trial participants. Trial registration numbers ISRCTN80475744; Pre-results. PMID:29866736

The effects of Internet-based exercise compared with supervised group exercise in people with type 2 diabetes: a randomized controlled study.

PubMed

Akinci, Buket; Yeldan, Ipek; Satman, Ilhan; Dirican, Ahmet; Ozdincler, Arzu Razak

2018-06-01

To compare the effects of Internet-based exercise on glycaemic control, blood lipids, body composition, physical activity level, functional capacity, and quality of life with supervised group exercise in patients with type 2 diabetes. Single-blind, randomized controlled study. A Faculty of Health Sciences. A total of 65 patients with type 2 diabetes (47 women, 18 men). Group A ( n = 22), control group - physical activity counselling once with a brochure. Group B ( n = 22), supervised group-based exercise, three days per week for eight weeks. Group C ( n = 21), Internet-based exercise following the same programme via a website. Primary outcomes - glycosylated haemoglobin, fasting blood glucose, high-density and low-density lipoprotein, triglyceride, and cholesterol. Secondary outcomes - waist and hip circumferences, body mass index, number of steps, six-minute walking test, and Euro-Quality of Life-5 Dimension. After treatment, glycaemic control (mean change for Group B; Group C; -0.80%, -0.91%, P = 0.003), waist circumference (-4.23 cm, 5.64 cm, P = 0.006), and quality of life (0.26, 0.15, P = 0.013) significantly improved in both training groups compared with the control group. Fasting blood glucose (-46.86 mg/dL, P = 0.009) and hip circumference (-2.7 cm, P = 0.011) were significantly decreased in Group B and total cholesterol (-16.4 mg/dL, P = 0.028), six-minute walking distance (30.5 m, P = 0.01), and number of steps (1258.05, P = 0.023) significantly improved in Group C compared with control group. Group B and Group C changed with equal magnitude. In type 2 diabetes, supervised group-based and Internet-based exercise can improve equally glycaemic control, waist circumference, and quality of life, and both are better than simply counselling.

The Impact of the School Counselor Supervision Model on the Self-Efficacy of School Counselor Site Supervisors

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…

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...

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...

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...

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...

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...