Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

PubMed

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.

A semi-supervised learning framework for biomedical event extraction based on hidden topics.

PubMed

Zhou, Deyu; Zhong, Dayou

2015-05-01

Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, due to the lack of explicit structure, literature in life science, one of the most important sources of this information, prevents computer-based systems from accessing. Therefore, biomedical event extraction, automatically acquiring knowledge of molecular events in research articles, has attracted community-wide efforts recently. Most approaches are based on statistical models, requiring large-scale annotated corpora to precisely estimate models' parameters. However, it is usually difficult to obtain in practice. Therefore, employing un-annotated data based on semi-supervised learning for biomedical event extraction is a feasible solution and attracts more interests. In this paper, a semi-supervised learning framework based on hidden topics for biomedical event extraction is presented. In this framework, sentences in the un-annotated corpus are elaborately and automatically assigned with event annotations based on their distances to these sentences in the annotated corpus. More specifically, not only the structures of the sentences, but also the hidden topics embedded in the sentences are used for describing the distance. The sentences and newly assigned event annotations, together with the annotated corpus, are employed for training. Experiments were conducted on the multi-level event extraction corpus, a golden standard corpus. Experimental results show that more than 2.2% improvement on F-score on biomedical event extraction is achieved by the proposed framework when compared to the state-of-the-art approach. The results suggest that by incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely described by hidden topics and structures of the sentences. Copyright © 2015 Elsevier B.V. All rights reserved.

A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data.

PubMed

Zheng, Yin; Zhang, Yu-Jin; Larochelle, Hugo

2016-06-01

Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to deal with multimodal data, such as in image annotation tasks. Another popular approach to model the multimodal data is through deep neural networks, such as the deep Boltzmann machine (DBM). Recently, a new type of topic model called the Document Neural Autoregressive Distribution Estimator (DocNADE) was proposed and demonstrated state-of-the-art performance for text document modeling. In this work, we show how to successfully apply and extend this model to multimodal data, such as simultaneous image classification and annotation. First, we propose SupDocNADE, a supervised extension of DocNADE, that increases the discriminative power of the learned hidden topic features and show how to employ it to learn a joint representation from image visual words, annotation words and class label information. We test our model on the LabelMe and UIUC-Sports data sets and show that it compares favorably to other topic models. Second, we propose a deep extension of our model and provide an efficient way of training the deep model. Experimental results show that our deep model outperforms its shallow version and reaches state-of-the-art performance on the Multimedia Information Retrieval (MIR) Flickr data set.

Empirical Analysis of Exploiting Review Helpfulness for Extractive Summarization of Online Reviews

ERIC Educational Resources Information Center

Xiong, Wenting; Litman, Diane

2014-01-01

We propose a novel unsupervised extractive approach for summarizing online reviews by exploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for sentence-level content scoring. The proposed method is metadata-driven, requiring no…

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

PubMed Central

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

2016-01-01

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images’ spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines. PMID:27367703

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

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

Wilson, Andrew T.; Robinson, David Gerald

Most topic modeling algorithms that address the evolution of documents over time use the same number of topics at all times. This obscures the common occurrence in the data where new subjects arise and old ones diminish or disappear entirely. We propose an algorithm to model the birth and death of topics within an LDA-like framework. The user selects an initial number of topics, after which new topics are created and retired without further supervision. Our approach also accommodates many of the acceleration and parallelization schemes developed in recent years for standard LDA. In recent years, topic modeling algorithms suchmore » as latent semantic analysis (LSA)[17], latent Dirichlet allocation (LDA)[10] and their descendants have offered a powerful way to explore and interrogate corpora far too large for any human to grasp without assistance. Using such algorithms we are able to search for similar documents, model and track the volume of topics over time, search for correlated topics or model them with a hierarchy. Most of these algorithms are intended for use with static corpora where the number of documents and the size of the vocabulary are known in advance. Moreover, almost all current topic modeling algorithms fix the number of topics as one of the input parameters and keep it fixed across the entire corpus. While this is appropriate for static corpora, it becomes a serious handicap when analyzing time-varying data sets where topics come and go as a matter of course. This is doubly true for online algorithms that may not have the option of revising earlier results in light of new data. To be sure, these algorithms will account for changing data one way or another, but without the ability to adapt to structural changes such as entirely new topics they may do so in counterintuitive ways.« less

Supervising and the Law. Supervising: Industrial Relations. The Choice Series #88. A Self Learning Opportunity.

ERIC Educational Resources Information Center

McCall, Matthew S.

This student guide is intended to assist persons employed as supervisors in understanding the legal aspects of supervision. Discussed in the first four sections are the following topics: the nature of the law (criminal and civil law, why people obey the law, and the law and supervisors); health and safety at work (safety in the workplace, ways of…

Supervision and Administration: Programs, Positions, Perspectives.

ERIC Educational Resources Information Center

Mills, E. Andrew, Ed.

This anthology is a collection of 17 articles by arts supervisors and administrators. The authors discuss both specific and general aspects of art education program supervision. Topics include staff development, evaluation of art learning, integrating community cultural resources, establishing elementary art specialists, coordinating multiple arts…

Remote supervision of medical training via videoconference in northern Australia: a qualitative study of the perspectives of supervisors and trainees

PubMed Central

Ray, Robin; Sabesan, Sabe

2015-01-01

Objectives Telemedicine has revolutionised the ability to provide care to patients, relieve professional isolation and provide guidance and supervision to junior medical officers in rural areas. This study evaluated the Townsville teleoncology supervision model for the training of junior medical officers in rural areas of North Queensland, Australia. Specifically, the perspectives of junior and senior medical officers were explored to identify recommendations for future implementation. Design A qualitative approach incorporating observation and semistructured interviews was used to collect data. Interviews were uploaded into NVivo 10 data management software. Template analysis enabled themes to be tested and developed through consensus between researchers. Setting One tertiary level and four secondary level healthcare centres in rural and regional Queensland, Australia. Participants 10 junior medical officers (Interns, Registrars) and 10 senior medical officers (Senior Medical Officers, Consultants) who participated in the Townsville teleoncology model of remote supervision via videoconference (TTMRS) were included in the study. Primary and Secondary outcome measures Perspectives on the telemedicine experience, technology, engagement, professional support, satisfaction and limitations were examined. Perspectives on topics raised by participants were also examined as the interviews progressed. Results Four major themes with several subthemes emerged from the data: learning environment, beginning the learning relationship, stimulus for learning and practicalities of remote supervision via videoconference. While some themes were consistent with the current literature, new themes like increased professional edge, recognising non-verbal cues and physical examination challenges were identified. Conclusions Remote supervision via videoconference provides readily available guidance to trainees supporting their delivery of appropriate care to patients. However, resources required for upskilling, training in the use of supervision via videoconference, administration issues and nursing support, as well as physical barriers to examinations, must be addressed to enable more efficient implementation. PMID:25795687

Interdisciplinary Doctoral Research Supervision: A Scoping Review

ERIC Educational Resources Information Center

Vanstone, Meredith; Hibbert, Kathy; Kinsella, Elizabeth Anne; McKenzie, Pam; Pitman, Allan; Lingard, Lorelei

2013-01-01

This scoping literature review examines the topic of interdisciplinary doctoral research supervision. Interdisciplinary doctoral research programs are expanding in response to encouragement from funding agencies and enthusiasm from faculty and students. In an acknowledgement that the search for creative and innovative solutions to complex problems…

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks.

PubMed

Ghosh, Saurav; Chakraborty, Prithwish; Nsoesie, Elaine O; Cohn, Emily; Mekaru, Sumiko R; Brownstein, John S; Ramakrishnan, Naren

2017-01-19

In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations.

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks

NASA Astrophysics Data System (ADS)

Ghosh, Saurav; Chakraborty, Prithwish; Nsoesie, Elaine O.; Cohn, Emily; Mekaru, Sumiko R.; Brownstein, John S.; Ramakrishnan, Naren

2017-01-01

In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations.

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks

PubMed Central

Ghosh, Saurav; Chakraborty, Prithwish; Nsoesie, Elaine O.; Cohn, Emily; Mekaru, Sumiko R.; Brownstein, John S.; Ramakrishnan, Naren

2017-01-01

In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations. PMID:28102319

Instructional Aides: Employment, Payroll Procedures, Supervision, Performance Appraisal, Legal Aspects.

ERIC Educational Resources Information Center

Nielsen, Earl T.

Designed to assist school administrators in their efforts to secure, train, and retain the most qualified instructional aides available, the monograph discusses procedures for employment, payroll processing, aide supervision, performance appraisal, and legal aspects involved in the hiring of instructional aides. Specific topics include…

The Development of a Prototype Infant, Preschool and Child Day Care Center in Metropolitan Toronto. Year I Progress Report: Program Development.

ERIC Educational Resources Information Center

Fowler, William; And Others

The project reported on is designed to develop a model program of infant and child day care in a municipal setting. The development of the program is discussed under the following topics: (1) physical caregiving routines; (2) guided learning through play; (3) supervising children in free play; (4) staff guidance and communication: inservice…

A probabilistic topic model for clinical risk stratification from electronic health records.

PubMed

Huang, Zhengxing; Dong, Wei; Duan, Huilong

2015-12-01

Risk stratification aims to provide physicians with the accurate assessment of a patient's clinical risk such that an individualized prevention or management strategy can be developed and delivered. Existing risk stratification techniques mainly focus on predicting the overall risk of an individual patient in a supervised manner, and, at the cohort level, often offer little insight beyond a flat score-based segmentation from the labeled clinical dataset. To this end, in this paper, we propose a new approach for risk stratification by exploring a large volume of electronic health records (EHRs) in an unsupervised fashion. Along this line, this paper proposes a novel probabilistic topic modeling framework called probabilistic risk stratification model (PRSM) based on Latent Dirichlet Allocation (LDA). The proposed PRSM recognizes a patient clinical state as a probabilistic combination of latent sub-profiles, and generates sub-profile-specific risk tiers of patients from their EHRs in a fully unsupervised fashion. The achieved stratification results can be easily recognized as high-, medium- and low-risk, respectively. In addition, we present an extension of PRSM, called weakly supervised PRSM (WS-PRSM) by incorporating minimum prior information into the model, in order to improve the risk stratification accuracy, and to make our models highly portable to risk stratification tasks of various diseases. We verify the effectiveness of the proposed approach on a clinical dataset containing 3463 coronary heart disease (CHD) patient instances. Both PRSM and WS-PRSM were compared with two established supervised risk stratification algorithms, i.e., logistic regression and support vector machine, and showed the effectiveness of our models in risk stratification of CHD in terms of the Area Under the receiver operating characteristic Curve (AUC) analysis. As well, in comparison with PRSM, WS-PRSM has over 2% performance gain, on the experimental dataset, demonstrating that incorporating risk scoring knowledge as prior information can improve the performance in risk stratification. Experimental results reveal that our models achieve competitive performance in risk stratification in comparison with existing supervised approaches. In addition, the unsupervised nature of our models makes them highly portable to the risk stratification tasks of various diseases. Moreover, patient sub-profiles and sub-profile-specific risk tiers generated by our models are coherent and informative, and provide significant potential to be explored for the further tasks, such as patient cohort analysis. We hypothesize that the proposed framework can readily meet the demand for risk stratification from a large volume of EHRs in an open-ended fashion. Copyright © 2015 Elsevier Inc. All rights reserved.

What Makes You Tick? An Empirical Study of Space Science Related Social Media Communications Using Machine Learning

NASA Astrophysics Data System (ADS)

Hwong, Y. L.; Oliver, C.; Van Kranendonk, M. J.

2016-12-01

The rise of social media has transformed the way the public engages with scientists and science organisations. `Retweet', `Like', `Share' and `Comment' are a few ways users engage with messages on Twitter and Facebook, two of the most popular social media platforms. Despite the availability of big data from these digital footprints, research into social media science communication is scant. This paper presents the results of an empirical study into the processes and outcomes of space science related social media communications using machine learning. The study is divided into two main parts. The first part is dedicated to the use of supervised learning methods to investigate the features of highly engaging messages., e.g. highly retweeted tweets and shared Facebook posts. It is hypothesised that these messages contain certain psycholinguistic features that are unique to the field of space science. We built a predictive model to forecast the engagement levels of social media posts. By using four feature sets (n-grams, psycholinguistics, grammar and social media), we were able to achieve prediction accuracies in the vicinity of 90% using three supervised learning algorithms (Naive Bayes, linear classifier and decision tree). We conducted the same experiments on social media messages from three other fields (politics, business and non-profit) and discovered several features that are exclusive to space science communications: anger, authenticity, hashtags, visual descriptions and a tentative tone. The second part of the study focuses on the extraction of topics from a corpus of texts using topic modelling. This part of the study is exploratory in nature and uses an unsupervised method called Latent Dirichlet Allocation (LDA) to uncover previously unknown topics within a large body of documents. Preliminary results indicate a strong potential of topic model algorithms to automatically uncover themes hidden within social media chatters on space related issues, with keywords such as `exoplanet', `water' and `life' being clustered together forming a topic (i.e. 'Astrobiology'). Results also demonstrate the freewheeling nature of social media conversations, while providing evidence for the role of these platforms in facilitating meaningful exchanges among science audience.

An Undergraduate Research Experience on Studying Variable Stars

NASA Astrophysics Data System (ADS)

Amaral, A.; Percy, J. R.

2016-06-01

We describe and evaluate a summer undergraduate research project and experience by one of us (AA), under the supervision of the other (JP). The aim of the project was to sample current approaches to analyzing variable star data, and topics related to the study of Mira variable stars and their astrophysical importance. This project was done through the Summer Undergraduate Research Program (SURP) in astronomy at the University of Toronto. SURP allowed undergraduate students to explore and learn about many topics within astronomy and astrophysics, from instrumentation to cosmology. SURP introduced students to key skills which are essential for students hoping to pursue graduate studies in any scientific field. Variable stars proved to be an excellent topic for a research project. For beginners to independent research, it introduces key concepts in research such as critical thinking and problem solving, while illuminating previously learned topics in stellar physics. The focus of this summer project was to compare observations with structural and evolutionary models, including modelling the random walk behavior exhibited in the (O-C) diagrams of most Mira stars. We found that the random walk could be modelled by using random fluctuations of the period. This explanation agreed well with observations.

Accurate Traffic Flow Prediction in Heterogeneous Vehicular Networks in an Intelligent Transport System Using a Supervised Non-Parametric Classifier.

PubMed

El-Sayed, Hesham; Sankar, Sharmi; Daraghmi, Yousef-Awwad; Tiwari, Prayag; Rattagan, Ekarat; Mohanty, Manoranjan; Puthal, Deepak; Prasad, Mukesh

2018-05-24

Heterogeneous vehicular networks (HETVNETs) evolve from vehicular ad hoc networks (VANETs), which allow vehicles to always be connected so as to obtain safety services within intelligent transportation systems (ITSs). The services and data provided by HETVNETs should be neither interrupted nor delayed. Therefore, Quality of Service (QoS) improvement of HETVNETs is one of the topics attracting the attention of researchers and the manufacturing community. Several methodologies and frameworks have been devised by researchers to address QoS-prediction service issues. In this paper, to improve QoS, we evaluate various traffic characteristics of HETVNETs and propose a new supervised learning model to capture knowledge on all possible traffic patterns. This model is a refinement of support vector machine (SVM) kernels with a radial basis function (RBF). The proposed model produces better results than SVMs, and outperforms other prediction methods used in a traffic context, as it has lower computational complexity and higher prediction accuracy.

Exploring Marriage and Family Therapy Supervisees' Perspectives about Postgraduate Supervision and the Acquisition of Core Competencies

ERIC Educational Resources Information Center

Steele, Stephanie J.

2013-01-01

The topic of core competencies has been a central focus in the marriage and family therapy field since 2003. There are currently no published studies from the supervisees' perspective about the role of supervision in the acquisition of core competencies. This qualitative study used transcendental phenomenology to explore supervisees' perspectives…

Topic detection using paragraph vectors to support active learning in systematic reviews.

PubMed

Hashimoto, Kazuma; Kontonatsios, Georgios; Miwa, Makoto; Ananiadou, Sophia

2016-08-01

Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to significantly reduce the manual annotation workload by semi-automating the citation screening process of systematic reviews. In this paper, we present a new topic detection method that induces an informative representation of studies, to improve the performance of the underlying active learner. Our proposed topic detection method uses a neural network-based vector space model to capture semantic similarities between documents. We firstly represent documents within the vector space, and cluster the documents into a predefined number of clusters. The centroids of the clusters are treated as latent topics. We then represent each document as a mixture of latent topics. For evaluation purposes, we employ the active learning strategy using both our novel topic detection method and a baseline topic model (i.e., Latent Dirichlet Allocation). Results obtained demonstrate that our method is able to achieve a high sensitivity of eligible studies and a significantly reduced manual annotation cost when compared to the baseline method. This observation is consistent across two clinical and three public health reviews. The tool introduced in this work is available from https://nactem.ac.uk/pvtopic/. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Instructor's Guide to Supervised Occupational Experience Programs for Vocational Agriculture Placement. Missouri Agricultural Education Series. Volume 11, Number 6, June 1978.

ERIC Educational Resources Information Center

Stewart, Bob R.; And Others

Four units of instruction are provided in this curriculum guide designed for vocational agriculture teachers in planning and conducting classes for students with supervised occupational experience (SOE) placement programs. Unit 1 contains three lessons on starting an SOE program. Lesson topics are placement programs to consider, getting started in…

Characteristics of good supervision: a multi-perspective qualitative exploration of the Masters in Public Health dissertation.

PubMed

Katikireddi, Srinivasa Vittal; Reilly, Jacqueline

2017-09-01

A dissertation is often a core component of the Masters in Public Health (MPH) qualification. This study aims to explore its purpose, from the perspective of both students and supervisors, and identify practices viewed as constituting good supervision. A multi-perspective qualitative study drawing on in-depth one-to-one interviews with MPH supervisors (n = 8) and students (n = 10), with data thematically analysed. The MPH dissertation was viewed as providing generic as well as discipline-specific knowledge and skills. It provided an opportunity for in-depth study on a chosen topic but different perspectives were evident as to whether the project should be grounded in public health practice rather than academia. Good supervision practice was thought to require topic knowledge, generic supervision skills (including clear communication of expectations and timely feedback) and adaptation of supervision to meet student needs. Two ideal types of the MPH dissertation process were identified. Supervisor-led projects focus on achieving a clearly defined output based on a supervisor-identified research question and aspire to harmonize research and teaching practice, but often have a narrower focus. Student-led projects may facilitate greater learning opportunities and better develop skills for public health practice but could be at greater risk of course failure. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health.

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.

Intelligent topical sentiment analysis for the classification of e-learners and their topics of interest.

PubMed

Ravichandran, M; Kulanthaivel, G; Chellatamilan, T

2015-01-01

Every day, huge numbers of instant tweets (messages) are published on Twitter as it is one of the massive social media for e-learners interactions. The options regarding various interesting topics to be studied are discussed among the learners and teachers through the capture of ideal sources in Twitter. The common sentiment behavior towards these topics is received through the massive number of instant messages about them. In this paper, rather than using the opinion polarity of each message relevant to the topic, authors focus on sentence level opinion classification upon using the unsupervised algorithm named bigram item response theory (BIRT). It differs from the traditional classification and document level classification algorithm. The investigation illustrated in this paper is of threefold which are listed as follows: (1) lexicon based sentiment polarity of tweet messages; (2) the bigram cooccurrence relationship using naïve Bayesian; (3) the bigram item response theory (BIRT) on various topics. It has been proposed that a model using item response theory is constructed for topical classification inference. The performance has been improved remarkably using this bigram item response theory when compared with other supervised algorithms. The experiment has been conducted on a real life dataset containing different set of tweets and topics.

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.

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.

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

A review of supervised machine learning applied to ageing research.

PubMed

Fabris, Fabio; Magalhães, João Pedro de; Freitas, Alex A

2017-04-01

Broadly speaking, supervised machine learning is the computational task of learning correlations between variables in annotated data (the training set), and using this information to create a predictive model capable of inferring annotations for new data, whose annotations are not known. Ageing is a complex process that affects nearly all animal species. This process can be studied at several levels of abstraction, in different organisms and with different objectives in mind. Not surprisingly, the diversity of the supervised machine learning algorithms applied to answer biological questions reflects the complexities of the underlying ageing processes being studied. Many works using supervised machine learning to study the ageing process have been recently published, so it is timely to review these works, to discuss their main findings and weaknesses. In summary, the main findings of the reviewed papers are: the link between specific types of DNA repair and ageing; ageing-related proteins tend to be highly connected and seem to play a central role in molecular pathways; ageing/longevity is linked with autophagy and apoptosis, nutrient receptor genes, and copper and iron ion transport. Additionally, several biomarkers of ageing were found by machine learning. Despite some interesting machine learning results, we also identified a weakness of current works on this topic: only one of the reviewed papers has corroborated the computational results of machine learning algorithms through wet-lab experiments. In conclusion, supervised machine learning has contributed to advance our knowledge and has provided novel insights on ageing, yet future work should have a greater emphasis in validating the predictions.

Mental health nurses' experiences of managing work-related emotions through supervision.

PubMed

MacLaren, Jessica; Stenhouse, Rosie; Ritchie, Deborah

2016-10-01

The aim of this study was to explore emotion cultures constructed in supervision and consider how supervision functions as an emotionally safe space promoting critical reflection. Research published between 1995-2015 suggests supervision has a positive impact on nurses' emotional well-being, but there is little understanding of the processes involved in this and how styles of emotion interaction are established in supervision. A narrative approach was used to investigate mental health nurses' understandings and experiences of supervision. Eight semi-structured interviews were conducted with community mental health nurses in the UK during 2011. Analysis of audio data used features of speech to identify narrative discourse and illuminate meanings. A topic-centred analysis of interview narratives explored discourses shared between the participants. This supported the identification of feeling rules in participants' narratives and the exploration of the emotion context of supervision. Effective supervision was associated with three feeling rules: safety and reflexivity; staying professional; managing feelings. These feeling rules allowed the expression and exploration of emotions, promoting critical reflection. A contrast was identified between the emotion culture of supervision and the nurses' experience of their workplace cultures as requiring the suppression of difficult emotions. Despite this, contrast supervision functioned as an emotion micro-culture with its own distinctive feeling rules. The analytical construct of feeling rules allows us to connect individual emotional experiences to shared normative discourses, highlighting how these shape emotional processes taking place in supervision. This understanding supports an explanation of how supervision may positively influence nurses' emotion management and perhaps reduce burnout. © 2016 John Wiley & Sons Ltd.

Analytical aspects of plant metabolite profiling platforms: current standings and future aims.

PubMed

Seger, Christoph; Sturm, Sonja

2007-02-01

Over the past years, metabolic profiling has been established as a comprehensive systems biology tool. Mass spectrometry or NMR spectroscopy-based technology platforms combined with unsupervised or supervised multivariate statistical methodologies allow a deep insight into the complex metabolite patterns of plant-derived samples. Within this review, we provide a thorough introduction to the analytical hard- and software requirements of metabolic profiling platforms. Methodological limitations are addressed, and the metabolic profiling workflow is exemplified by summarizing recent applications ranging from model systems to more applied topics.

Best practices in nursing homes. Clinical supervision, management, and human resource practices.

PubMed

Dellefield, Mary Ellen

2008-07-01

Human resource practices including supervision and management are associated with organizational performance. Evidence supportive of such an association in nursing homes is found in the results of numerous research studies conducted during the past 17 years. In this article, best practices related to this topic have been culled from descriptive, explanatory, and intervention studies in a range of interdisciplinary research journals published between 1990 and 2007. Identified best practices include implementation of training programs on supervision and management for licensed nurses, certified nursing assistant job enrichment programs, implementation of consistent nursing assignments, and the use of electronic documentation. Organizational barriers and facilitators of these best practices are described. Copyright 2009, SLACK Incorporated.

A bibliometric analysis on tobacco regulation investigators.

PubMed

Li, Dingcheng; Okamoto, Janet; Liu, Hongfang; Leischow, Scott

2015-01-01

To facilitate the implementation of the Family Smoking Prevention and Tobacco Control Act of 2009, the Federal Drug Agency (FDA) Center for Tobacco Products (CTP) has identified research priorities under the umbrella of tobacco regulatory science (TRS). As a newly integrated field, the current boundaries and landscape of TRS research are in need of definition. In this work, we conducted a bibliometric study of TRS research by applying author topic modeling (ATM) on MEDLINE citations published by currently-funded TRS principle investigators (PIs). We compared topics generated with ATM on dataset collected with TRS PIs and topics generated with ATM on dataset collected with a TRS keyword list. It is found that all those topics show a good alignment with FDA's funding protocols. More interestingly, we can see clear interactive relationships among PIs and between PIs and topics. Based on those interactions, we can discover how diverse each PI is, how productive they are, which topics are more popular and what main components each topic involves. Temporal trend analysis of key words shows the significant evaluation in four prime TRS areas. The results show that ATM can efficiently group articles into discriminative categories without any supervision. This indicates that we may incorporate ATM into author identification systems to infer the identity of an author of articles using topics generated by the model. It can also be useful to grantees and funding administrators in suggesting potential collaborators or identifying those that share common research interests for data harmonization or other purposes. The incorporation of temporal analysis can be employed to assess the change over time in TRS as new projects are funded and the extent to which new research reflects the funding priorities of the FDA.

An Electronics "Unit Laboratory"

ERIC Educational Resources Information Center

Davies, E. R.; Penton, S. J.

1976-01-01

Describes a laboratory teaching technique in which a single topic (in this case, bipolar junction transistors) is studied over a period of weeks under the supervision of one staff member, who also designs the laboratory work. (MLH)

Filtering big data from social media--Building an early warning system for adverse drug reactions.

PubMed

Yang, Ming; Kiang, Melody; Shang, Wei

2015-04-01

Adverse drug reactions (ADRs) are believed to be a leading cause of death in the world. Pharmacovigilance systems are aimed at early detection of ADRs. With the popularity of social media, Web forums and discussion boards become important sources of data for consumers to share their drug use experience, as a result may provide useful information on drugs and their adverse reactions. In this study, we propose an automated ADR related posts filtering mechanism using text classification methods. In real-life settings, ADR related messages are highly distributed in social media, while non-ADR related messages are unspecific and topically diverse. It is expensive to manually label a large amount of ADR related messages (positive examples) and non-ADR related messages (negative examples) to train classification systems. To mitigate this challenge, we examine the use of a partially supervised learning classification method to automate the process. We propose a novel pharmacovigilance system leveraging a Latent Dirichlet Allocation modeling module and a partially supervised classification approach. We select drugs with more than 500 threads of discussion, and collect all the original posts and comments of these drugs using an automatic Web spidering program as the text corpus. Various classifiers were trained by varying the number of positive examples and the number of topics. The trained classifiers were applied to 3000 posts published over 60 days. Top-ranked posts from each classifier were pooled and the resulting set of 300 posts was reviewed by a domain expert to evaluate the classifiers. Compare to the alternative approaches using supervised learning methods and three general purpose partially supervised learning methods, our approach performs significantly better in terms of precision, recall, and the F measure (the harmonic mean of precision and recall), based on a computational experiment using online discussion threads from Medhelp. Our design provides satisfactory performance in identifying ADR related posts for post-marketing drug surveillance. The overall design of our system also points out a potentially fruitful direction for building other early warning systems that need to filter big data from social media networks. Copyright © 2015 Elsevier Inc. All rights reserved.

"See one, do one, teach one": inadequacies of current methods to train surgeons in hernia repair.

PubMed

Zahiri, H Reza; Park, Adrian E; Pugh, Carla M; Vassiliou, Melina; Voeller, Guy

2015-10-01

Residency/fellowship training in hernia repair is still too widely characterized by the "see one, do one, teach one" model. The goal of this study was to perform a needs assessment focused on surgical training to guide the creation of a curriculum by SAGES intended to improve the care of hernia patients. Using mixed methods (interviews and online survey), the SAGES hernia task force (HTF) conducted a study asking subjects about their perceived deficits in resident training to care for hernia patients, preferred training topics about hernias, ideal learning modalities, and education development. Participants included 18 of 24 HTF members, 27 chief residents and fellows, and 31 surgical residents. HTF members agreed that residency exposes trainees to a wide spectrum of hernia repairs by a variety of surgeons. They cited outdated materials, techniques, and paucity of feedback. Additionally, they identified the "see one, do one, teach one" method of training as prevalent and clearly inadequate. The topics least addressed were system-based approach to hernia care (46 %) and patient outcomes (62 %). Training topics residents considered well covered during residency were: preoperative and intraoperative decision-making (90 %), complications (94 %), and technical approach for repairs (98 %). Instructional methods used in residency include assisted/supervised surgery (96 %), Web-based learning (24 %), and simulation (30 %). Residents' preferred learning methods included simulation (82 %), Web-based training (61 %), hands-on laboratory (54 %), and videos (47 %), in addition to supervised surgery. Trainees reported their most desired training topics as basic techniques for inguinal and ventral hernia repairs (41 %) versus advanced technical training (68 %), which mirrored those reported by attending surgeons, 36 % and 71 %, respectively. There was a consensus among HTF members and surgical trainees that a comprehensive, dynamic, and flexible educational program employing various media to address contemporary key deficits in the care of hernia patients would be welcomed by surgeons.

The Common Factors Discrimination Model: An Integrated Approach to Counselor Supervision

ERIC Educational Resources Information Center

Crunk, A. Elizabeth; Barden, Sejal M.

2017-01-01

Numerous models of clinical supervision have been developed; however, there is little empirical support indicating that any one model is superior. Therefore, common factors approaches to supervision integrate essential components that are shared among counseling and supervision models. The purpose of this paper is to present an innovative model of…

Clinical supervision for allied health staff: necessary but not sufficient.

PubMed

Leggat, Sandra G; Phillips, Bev; Pearce, Philippa; Dawson, Margaret; Schulz, Debbie; Smith, Jenni

2016-09-01

Objectives The aim of the present study was to explore the perspectives of allied health professionals on appropriate content for effective clinical supervision of staff. Methods A set of statements regarding clinical supervision was identified from the literature and confirmed through a Q-sort process. The final set was administered as an online survey to 437 allied health professionals working in two Australian health services. Results Of the 120 respondents, 82 had experienced six or more clinical supervision sessions and were included in the analysis. Respondents suggested that clinical supervision was beneficial to both staff and patients, and was distinct from line management performance monitoring and development. Curiously, some of the respondents did not agree that observation of the supervisee's clinical practice was an aspect of clinical supervision. Conclusions Although clinical supervision is included as a pillar of clinical governance, current practice may not be effective in addressing clinical risk. Australian health services need clear organisational policies that outline the relationship between supervisor and supervisee, the role and responsibilities of managers, the involvement of patients and the types of situations to be communicated to the line managers. What is known about the topic? Clinical supervision for allied health professionals is an essential component of clinical governance and is aimed at ensuring safe and high-quality care. However, there is varied understanding of the relationship between clinical supervision and performance management. What does this paper add? This paper provides the perspectives of allied health professionals who are experienced as supervisors or who have experienced supervision. The findings suggest a clear role for clinical supervision that needs to be better recognised within organisational policy and procedure. What are the implications for practitioners? Supervisors and supervisees must remember their duty of care and ensure compliance with organisational policies in their clinical supervisory practices.

Risk to researchers in qualitative research on sensitive topics: issues and strategies.

PubMed

Dickson-Swift, Virginia; James, Erica L; Kippen, Sandra; Liamputtong, Pranee

2008-01-01

Traditionally, risk assessments in research have been limited to examining the risks to the research participants. Although doing so is appropriate and important, there is growing recognition that undertaking research can pose risks to researchers as well. A grounded theory study involving a range of researchers who had undertaken qualitative health research on a sensitive topic was completed. Analysis of the in-depth, face-to-face unstructured individual interviews with 30 Australian public health researchers provided evidence that researchers do confront a number of physical and emotional risks when undertaking research. Training, preparation, and supervision must be taken into account so that the risk to researchers can be minimized. Researchers need to consider occupational health and safety issues in designing research projects that deal with physical and emotional risks. Recommendations for professional supervision, policy development, and minimum training standards for researchers are provided.

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.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Providing effective supervision in clinical neuropsychology.

PubMed

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

2010-01-01

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

How do we know what makes for "best practice" in clinical supervision for psychological therapists? A content analysis of supervisory models and approaches.

PubMed

Simpson-Southward, Chloe; Waller, Glenn; Hardy, Gillian E

2017-11-01

Clinical supervision for psychotherapies is widely used in clinical and research contexts. Supervision is often assumed to ensure therapy adherence and positive client outcomes, but there is little empirical research to support this contention. Regardless, there are numerous supervision models, but it is not known how consistent their recommendations are. This review aimed to identify which aspects of supervision are consistent across models, and which are not. A content analysis of 52 models revealed 71 supervisory elements. Models focus more on supervisee learning and/or development (88.46%), but less on emotional aspects of work (61.54%) or managerial or ethical responsibilities (57.69%). Most models focused on the supervisee (94.23%) and supervisor (80.77%), rather than the client (48.08%) or monitoring client outcomes (13.46%). Finally, none of the models were clearly or adequately empirically based. Although we might expect clinical supervision to contribute to positive client outcomes, the existing models have limited client focus and are inconsistent. Therefore, it is not currently recommended that one should assume that the use of such models will ensure consistent clinician practice or positive therapeutic outcomes. There is little evidence for the effectiveness of supervision. There is a lack of consistency in supervision models. Services need to assess whether supervision is effective for practitioners and patients. Copyright © 2017 John Wiley & Sons, Ltd.

Topical treatment of psoriasis.

PubMed

Laws, Philip M; Young, Helen S

2010-08-01

The majority of patients with psoriasis can be safely and effectively treated with topical therapy alone, either under the supervision of a family physician or dermatologist. For those requiring systemic agents, topical therapies can provide additional benefit. Optimal use of topical therapy requires an awareness of the range and efficacy of all products. The review covers the efficacy and role of topical therapies including emollients, corticosteroids, vitamin D analogs, calcineurin inhibitors, dithranol, coal tar, retinoids, keratolyics and combination therapy. The report was prepared following a PubMed and Embase literature search up to April 2010. The paper provides a broad review of the relevant topical therapeutic options available in routine clinical practice for the management of psoriasis and a recommendation for selection of treatment. Topical therapies used appropriately provide a safe and effective option for the management of psoriasis. An awareness of the available products and their efficacy is key to treatment selection and patient satisfaction.

Agricultural Production.

ERIC Educational Resources Information Center

Lehigh County Area Vocational-Technical School, Schnecksville, PA.

This brochure describes the philosophy and scope of a secondary-level course in agricultural production. Addressed in the individual units of the course are the following topics: careers in agriculture and agribusiness, animal science and livestock production, agronomy, agricultural mechanics, supervised occupational experience programs, and the…

Form Follows Function: A Model for Clinical Supervision of Genetic Counseling Students.

PubMed

Wherley, Colleen; Veach, Patricia McCarthy; Martyr, Meredith A; LeRoy, Bonnie S

2015-10-01

Supervision plays a vital role in genetic counselor training, yet models describing genetic counseling supervision processes and outcomes are lacking. This paper describes a proposed supervision model intended to provide a framework to promote comprehensive and consistent clinical supervision training for genetic counseling students. Based on the principle "form follows function," the model reflects and reinforces McCarthy Veach et al.'s empirically derived model of genetic counseling practice - the "Reciprocal Engagement Model" (REM). The REM consists of mutually interactive educational, relational, and psychosocial components. The Reciprocal Engagement Model of Supervision (REM-S) has similar components and corresponding tenets, goals, and outcomes. The 5 REM-S tenets are: Learning and applying genetic information are key; Relationship is integral to genetic counseling supervision; Student autonomy must be supported; Students are capable; and Student emotions matter. The REM-S outcomes are: Student understands and applies information to independently provide effective services, develop professionally, and engage in self-reflective practice. The 16 REM-S goals are informed by the REM of genetic counseling practice and supported by prior literature. A review of models in medicine and psychology confirms the REM-S contains supervision elements common in healthcare fields, while remaining unique to genetic counseling. The REM-S shows promise for enhancing genetic counselor supervision training and practice and for promoting research on clinical supervision. The REM-S is presented in detail along with specific examples and training and research suggestions.

Race in Supervision: Let's Talk About It.

PubMed

Schen, Cathy R; Greenlee, Alecia

2018-01-01

Addressing race and racial trauma within psychotherapy supervision is increasingly important in psychiatry training. A therapist's ability to discuss race and racial trauma in psychotherapy supervision increases the likelihood that these topics will be explored as they arise in the therapeutic setting. The authors discuss the contextual and sociocultural dynamics that contributed to their own avoidance of race and racial trauma within the supervisory relationship. The authors examine the features that eventually led to a robust discussion of race and culture within the supervisory setting and identify salient themes that occurred during three phases of the conversation about race: pre-dialogue, the conversation, and after the conversation. These themes include building an alliance, supercompetence, avoidance, shared vulnerability, "if I speak on this, I own it," closeness versus distance, and speaking up. This article reviews the key literature in the field of psychiatry and psychology that has shaped how we understand race and racial trauma and concludes with guidelines for supervisors on how to facilitate talking about race in supervision.

Intellectual Production Supervision Perform based on RFID Smart Electricity Meter

NASA Astrophysics Data System (ADS)

Chen, Xiangqun; Huang, Rui; Shen, Liman; chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng

2018-03-01

This topic develops the RFID intelligent electricity meter production supervision project management system. The system is designed for energy meter production supervision in the management of the project schedule, quality and cost information management requirements in RFID intelligent power, and provide quantitative information more comprehensive, timely and accurate for supervision engineer and project manager management decisions, and to provide technical information for the product manufacturing stage file. From the angle of scheme analysis, design, implementation and test, the system development of production supervision project management system for RFID smart meter project is discussed. Focus on the development of the system, combined with the main business application and management mode at this stage, focuses on the energy meter to monitor progress information, quality information and cost based information on RFID intelligent power management function. The paper introduces the design scheme of the system, the overall client / server architecture, client oriented graphical user interface universal, complete the supervision of project management and interactive transaction information display, the server system of realizing the main program. The system is programmed with C# language and.NET operating environment, and the client and server platforms use Windows operating system, and the database server software uses Oracle. The overall platform supports mainstream information and standards and has good scalability.

The Doctoral Thesis and Supervision: The Student Perspective

ERIC Educational Resources Information Center

Kiguwa, Peace; Langa, Malose

2009-01-01

The doctoral thesis constitutes both a negotiation of the supervision relationship as well as mastery and skill in participating in a specific community of practice. Two models of supervision are discussed: the technical rationality model with its emphasis on technical aspects of supervision, and the negotiated order model with an emphasis on…

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…

Reflective practice and guided discovery: clinical supervision.

PubMed

Todd, G; Freshwater, D

This article explores the parallels between reflective practice as a model for clinical supervision, and guided discovery as a skill in cognitive psychotherapy. A description outlining the historical development of clinical supervision in relationship to positional papers and policies is followed by an exposé of the difficulties in developing a clear, consistent model of clinical supervision with a coherent focus; reflective practice is proposed as a model of choice for clinical supervision in nursing. The article examines the parallels and processes of a model of reflection in an individual clinical supervision session, and the use of guided discovery through Socratic dialogue with a depressed patient in cognitive psychotherapy. Extracts from both sessions are used to illuminate the subsequent discussion.

Development of the Artistic Supervision Model Scale (ASMS)

ERIC Educational Resources Information Center

Kapusuzoglu, Saduman; Dilekci, Umit

2017-01-01

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

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...

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.

Clinical Supervision and Psychological Functions: A New Direction for Theory and Practice.

ERIC Educational Resources Information Center

Pajak, Edward

2002-01-01

Relates Carl Jung's concept of psychological functions to four families of clinical supervision: the original clinical models, the humanistic/artistic models, the technical/didactic models, and the developmental/reflective models. Differences among clinical supervision models within these families are clarified as representing "communication…

Dual-Focus Supervision a Nonapprenticeship Approach.

ERIC Educational Resources Information Center

McBride, Martha C.; Martin, G. Eric

1986-01-01

Provides a professional model for practicum supervision using supervisors with equal responsibility and status. The model stresses the use of professional knowledge in both the content and process of practicum supervision. Dual-focus supervision is seen as the integration and application of theory congruency and interpersonal dynamics. (Author/BL)

Linking Portfolio Development to Clinical Supervision: A Case Study.

ERIC Educational Resources Information Center

Zepeda, Sally J.

2002-01-01

Describes a model for portfolio supervision based on the results of a 2-year study of one elementary school's experience in implementing portfolio supervision. Includes four propositions that guided the development of the model. Describes the skills inherent in portfolio supervision. Provides general guidelines for implementation of the portfolio…

Collective Academic Supervision: A Model for Participation and Learning in Higher Education

ERIC Educational Resources Information Center

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

2013-01-01

Supervision of graduate students is a core activity in higher education. Previous research on graduate supervision focuses on individual and relational aspects of the supervisory relationship rather than collective, pedagogical and methodological aspects of the supervision process. In presenting a collective model we have developed for academic…

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.

Supervision in School Psychology: The Developmental/Ecological/Problem-Solving Model

ERIC Educational Resources Information Center

Simon, Dennis J.; Cruise, Tracy K.; Huber, Brenda J.; Swerdlik, Mark E.; Newman, Daniel S.

2014-01-01

Effective supervision models guide the supervisory relationship and supervisory tasks leading to reflective and purposeful practice. The Developmental/Ecological/Problem-Solving (DEP) Model provides a contemporary framework for supervision specific to school psychology. Designed for the school psychology internship, the DEP Model is also…

Intern Performance in Three Supervisory Models

ERIC Educational Resources Information Center

Womack, Sid T.; Hanna, Shellie L.; Callaway, Rebecca; Woodall, Peggy

2011-01-01

Differences in intern performance, as measured by a Praxis III-similar instrument were found between interns supervised in three supervisory models: Traditional triad model, cohort model, and distance supervision. Candidates in this study's particular form of distance supervision were not as effective as teachers as candidates in traditional-triad…

The collaborative model of fieldwork education: a blueprint for group supervision of students.

PubMed

Hanson, Debra J; DeIuliis, Elizabeth D

2015-04-01

Historically, occupational therapists have used a traditional one-to-one approach to supervision on fieldwork. Due to the impact of managed care on health-care delivery systems, a dramatic increase in the number of students needing fieldwork placement, and the advantages of group learning, the collaborative supervision model has evolved as a strong alternative to an apprenticeship supervision approach. This article builds on the available research to address barriers to model use, applying theoretical foundations of collaborative supervision to practical considerations for academic fieldwork coordinators and fieldwork educators as they prepare for participation in group supervision of occupational therapy and occupational therapy assistant students on level II fieldwork.

Engineer Equipment Chief.

ERIC Educational Resources Information Center

Marine Corps Inst., Washington, DC.

This student guide, one of a series of correspondence training courses designed to improve the job performance of members of the Marine Corps, deals with the skills needed by engineer equipment chiefs. Addressed in the five individual units of the course are the following topics: construction management (planning, scheduling, and supervision);…

ADVANCED ADULT EDUCATION IN ISRAEL.

ERIC Educational Resources Information Center

Ministry of Education and Culture, Jerusalem (Israel).

ADULT EDUCATION IN ISRAEL IS UNDER THE SUPERVISION OF THE CULTURAL DEPARTMENT, WHICH RECOMMENDS TEACHERS AND LECTURERS AND IS RESPONSIBLE FOR INSPECTION AND FINANCIAL SUPPORT. STUDENT FEES ARE COLLECTED LOCALLY. PREVIOUSLY DEVOTED TO JEWISH TOPICS AND HEBREW LANGUAGE, THE PROGRAM HAS BEEN EXPANDED TO INCLUDE FORMAL SECONDARY EDUCATION, HUMANITIES,…

Theme: Is Problem-Solving Teaching and SAE Needed in Agricultural Education in the 21st Century?

ERIC Educational Resources Information Center

Wardlow, George, Ed.

1999-01-01

Nine articles in this theme issue address problem-solving teaching and supervised agricultural experience. Topics covered include systems approaches to SAE, SAE for Y2K, SAE for science, applied SAE, types of SAE, and examples of activities. (JOW)

Core IV Materials for Metropolitan Agriculture/Horticulture Programs.

ERIC Educational Resources Information Center

Hemp, Paul; And Others

This core curriculum guide consists of materials for use in presenting a 13-unit vocational agriculture course geared toward high school students living in metropolitan areas. Addressed in the individual units of the course are the following topics: employment in agricultural occupations, supervised occupational experience, leadership in…

Adaptations of the Multifaceted Genogram in Counseling, Training, and Supervision.

ERIC Educational Resources Information Center

Magnuson, Sandy; Shaw, Holly E.

2003-01-01

Provides a review of representative literature offering modifications of traditional genogram formats, procedures, and emphases. Topics include counseling techniques and interventions for couples' issues related to sexuality, intimacy, and gender roles. Families and stepfamilies are addressed in areas such as grief and loss, alcoholism, and…

Guide for Occupational Experience Programs in Vocational Education.

ERIC Educational Resources Information Center

Gibson, Roscoe R.

Intended for use by secondary and postsecondary vocational instructors in organizing and conducting supervised occupational experiences for students, this handbook is divided into two parts. Part 1 covers planning and managing occupational experience programs and discusses the following topics: (1) basic definitions and objectives of an…

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…

Clinical Supervision in Undergraduate Nursing Students: A Review of the Literature

ERIC Educational Resources Information Center

Franklin, Natasha

2013-01-01

The concept of clinical supervision to facilitate the clinical education environment in undergraduate nursing students is well discussed within the literature. Despite the many models of clinical supervision described within the literature there is a lack of clear guidance and direction which clinical supervision model best suits the clinical…

Pedagogy of Research Supervision Pedagogy: A Constructivist Model

ERIC Educational Resources Information Center

Qureshi, Rashida; Vazir, Neelofar

2016-01-01

Graduate research is an integral part of higher education in Pakistan but formal training in supervision is not included in any standard teacher training curriculum. Hence, supervisors usually depend on their own experiences of how they were supervised as graduate students and so every supervisor builds his/her own model of supervision. In this…

Attitudes and Satisfaction with a Hybrid Model of Counseling Supervision

ERIC Educational Resources Information Center

Conn, Steven R.; Roberts, Richard L.; Powell, Barbara M.

2009-01-01

The authors investigated the relationship between type of group supervision (hybrid model vs. face-to-face) and attitudes toward technology, toward use of technology in professional practice, and toward quality of supervision among a sample of school counseling interns. Participants (N = 76) experienced one of two types of internship supervision:…

Wellness Model of Supervision: A Comparative Analysis

ERIC Educational Resources Information Center

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

2012-01-01

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

Using patient experiences on Dutch social media to supervise health care services: exploratory study.

PubMed

van de Belt, Tom H; Engelen, Lucien J L P G; Verhoef, Lise M; van der Weide, Marian J A; Schoonhoven, Lisette; Kool, Rudolf B

2015-01-15

Social media has become mainstream and a growing number of people use it to share health care-related experiences, for example on health care rating sites. These users' experiences and ratings on social media seem to be associated with quality of care. Therefore, information shared by citizens on social media could be of additional value for supervising the quality and safety of health care services by regulatory bodies, thereby stimulating participation by consumers. The objective of the study was to identify the added value of social media for two types of supervision by the Dutch Healthcare Inspectorate (DHI), which is the regulatory body charged with supervising the quality and safety of health care services in the Netherlands. These were (1) supervision in response to incidents reported by individuals, and (2) risk-based supervision. We performed an exploratory study in cooperation with the DHI and searched different social media sources such as Twitter, Facebook, and healthcare rating sites to find additional information for these incidents and topics, from five different sectors. Supervision experts determined the added value for each individual result found, making use of pre-developed scales. Searches in social media resulted in relevant information for six of 40 incidents studied and provided relevant additional information in 72 of 116 cases in risk-based supervision of long-term elderly care. The results showed that social media could be used to include the patient's perspective in supervision. However, it appeared that the rating site ZorgkaartNederland was the only source that provided information that was of additional value for the DHI, while other sources such as forums and social networks like Twitter and Facebook did not result in additional information. This information could be of importance for health care inspectorates, particularly for its enforcement by risk-based supervision in care of the elderly. Further research is needed to determine the added value for other health care sectors.

Using Patient Experiences on Dutch Social Media to Supervise Health Care Services: Exploratory Study

PubMed Central

Engelen, Lucien JLPG; Verhoef, Lise M; van der Weide, Marian JA; Schoonhoven, Lisette; Kool, Rudolf B

2015-01-01

Background Social media has become mainstream and a growing number of people use it to share health care-related experiences, for example on health care rating sites. These users’ experiences and ratings on social media seem to be associated with quality of care. Therefore, information shared by citizens on social media could be of additional value for supervising the quality and safety of health care services by regulatory bodies, thereby stimulating participation by consumers. Objective The objective of the study was to identify the added value of social media for two types of supervision by the Dutch Healthcare Inspectorate (DHI), which is the regulatory body charged with supervising the quality and safety of health care services in the Netherlands. These were (1) supervision in response to incidents reported by individuals, and (2) risk-based supervision. Methods We performed an exploratory study in cooperation with the DHI and searched different social media sources such as Twitter, Facebook, and healthcare rating sites to find additional information for these incidents and topics, from five different sectors. Supervision experts determined the added value for each individual result found, making use of pre-developed scales. Results Searches in social media resulted in relevant information for six of 40 incidents studied and provided relevant additional information in 72 of 116 cases in risk-based supervision of long-term elderly care. Conclusions The results showed that social media could be used to include the patient’s perspective in supervision. However, it appeared that the rating site ZorgkaartNederland was the only source that provided information that was of additional value for the DHI, while other sources such as forums and social networks like Twitter and Facebook did not result in additional information. This information could be of importance for health care inspectorates, particularly for its enforcement by risk-based supervision in care of the elderly. Further research is needed to determine the added value for other health care sectors. PMID:25592481

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…

Parental Monitoring Behaviors: A Model of Rules, Supervision, and Conflict

ERIC Educational Resources Information Center

Hayes, Louise; Hudson, Alan; Matthews, Jan

2004-01-01

A model of parental monitoring behaviors, comprising rule setting and supervision, was proposed. The hypothesized relationship between rules, supervision, conflict, and adolescent problem behavior was tested using structured equation modeling on self-report data from 1,285 adolescents aged 14 to 15 years. The model was an adequate fit of the data,…

The Early Patient-Oriented Care Program as an Educational Tool and Service.

ERIC Educational Resources Information Center

Grabe, Darren W.; Bailie, George R.; Manley, Harold J.; Yeaw, Barbara F.

1998-01-01

The Early Patient-Oriented Care Program provides early clinical education for pharmacy students and clinical services for patients. Six students were assigned to visit 12-15 hemodialysis patients monthly under preceptor supervision. Topics covered include approach to patient, medical information retrieval, pharmaceutical care philosophy,…

Communication Systems. Supervising: Communication. The Choice Series #63. A Self Learning Opportunity.

ERIC Educational Resources Information Center

Carr, Linda

This student guide is intended to assist persons employed as supervisors in understanding and using communication equipment. Discussed in the first three sections are the following topics: producing and storing information (communicating, storing, and retrieving information and using word processors and talking machines); communicating information…

Two Year Core Curriculum for Agricultural Education in Montana. Revised.

ERIC Educational Resources Information Center

Montana State Univ., Bozeman. Dept. of Agricultural and Industrial Education.

This core curriculum consists of materials for use in conducting a two-year secondary level agricultural education course. Addressed in the individual units of the guide are the following topics: leadership; agricultural career planning; supervised occupational experience programs (SOEPs); agricultural mechanics (shop management and safety,…

Pediatric Traumatic Brain Injury. Special Topic Report #3.

ERIC Educational Resources Information Center

Waaland, Pamela K.; Cockrell, Janice L.

This brief report summarizes what is known about pediatric traumatic brain injury, including the following: risk factors (e.g., males especially those ages 5 to 25, youth with preexisting problems including previous head injury victims, and children receiving inadequate supervision); life after injury; physical and neurological consequences (e.g.,…

Nursing clinical supervision project in a Neonatal Intensive Care and a Special Care Baby Unit: a best practice implementation project.

PubMed

Johansson, Diana

2015-04-17

Clinical supervision is a process of guided reflective practice and is used in the areas of mental health and palliative care. However, within the Neonatal Intensive Care Unit setting, stressful situations may also arise, with no policies for nurses in regards to participation in clinical supervision. With critical incidents, complex family issues and loss of nursing expertise, clinical supervision could be a potential solution to this dilemma. The aims of the project were to investigate if any hospital policies supported clinical supervision. Specifically, the aims were: (i) to conduct an audit of nurses' knowledge on the topic of clinical supervision, (ii) to investigate if nurses were aware of, or had been involved in, any clinical supervision activities conducted in a Neonatal Intensive Care Unit or a Special Care Baby Unit, and (iii) to investigate if records are maintained of any clinical supervision activities held. A three-phase approach was initiated for this project: a baseline audit, implementation of education sessions, and a follow-up audit using the Joanna Briggs Institute Practical Application of Clinical Evidence System and Getting Research into Practice programs. The Neonatal Intensive Care Unit and Special Care Baby Unit have approximately 180 registered nurses working in the units where the project was conducted. The baseline audit included 37 nurses by convenience sampling and the follow-up audit included nine of these nurses. No policy on clinical supervision has been developed to support nurses in the Neonatal Intensive Care Unit and Special Care Baby Unit. The baseline audit found that nurses described clinical supervision as educational and task orientated, and did not equate clinical supervision with a process that could be also described as "guided reflective practice". Following the education sessions, there was a better understanding of what clinical supervision entailed and the benefits that could lead to improved professional practice, but there were no activities in which nurses could engage in this process. Implementation of a pilot project to test the evidence of clinical supervision in the Neonatal Intensive Care and Special Care Baby speciality units should be undertaken with strategies to assess the effectiveness of clinical supervision and the positive aspects that have been reported in the literature. The Joanna Briggs Institute.

Wellness Model of Supervision: A Preliminary Analysis

ERIC Educational Resources Information Center

Lenz, Alan Stephen, Jr.

2011-01-01

This study compared the effectiveness of the Wellness Model of Supervision (WELMS; Lenz & Smith, 2010) against other models of supervision for developing the wellness constructs, total personal wellness, and helping skills among CITs. Participants in were 44 masters level Caucasian counseling students (9 men) completing their practicum and…

The Need for Developmental Models in Supervising School Counselors

ERIC Educational Resources Information Center

Gallo, Laura L.

2013-01-01

Developmental models, like Stoltenberg, McNeil, and Delworth's integrated developmental model (IDM) for supervision (1998), provide supervisors with an important resource in understanding and managing the counseling student's development and experience. The current status of school counseling supervision is discussed as well as the…

Human semi-supervised learning.

PubMed

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

2013-01-01

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

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…

An Exploratory Study Examining Current Assessment Supervisory Practices in Professional Psychology.

PubMed

Iwanicki, Sierra; Peterson, Catherine

2017-01-01

The extant literature reveals a considerable amount of research examining course work or technical training in psychological assessment, but a dearth of empirical research on assessment supervision. This study examined perspectives on current assessment supervisory practices in professional psychology through an online survey. Descriptive and qualitative data were collected from 125 survey respondents who were members of assessment-focused professional organizations and who had at least 1 year of supervision experience. Responses indicated a general recognition of the need for formal training in assessment supervision, ongoing training opportunities, and adherence to supervision competencies. Responses indicated more common use of developmental and skill-based models, although most did not regard any one model of assessment supervision as superior. Despite the recommended use of a supervision contract, only 65.6% (n = 80) of respondents use one. Discussion, directed readings, modeling, role-play, and case presentations were the most common supervisory interventions. Although conclusions are constrained by low survey response rate, results yielded rich data that might guide future examination of multiple perspectives on assessment supervision and ultimately contribute to curriculum advances and the development of supervision "best practices."

Development of a Web-Based Officer's Field Guide to Mental Illness

ERIC Educational Resources Information Center

Staley, Georgiana M.

2012-01-01

Probation and parole officers supervise a disproportionate amount of offenders with mental illness. Many causes contribute to this over-representation ranging from deinstitutionalization, to co-occurring disorders, to homelessness. It appears there may be a lack of training specifically for probation and parole officers on the topic of mental…

Discipline and the Law. Supervising: Industrial Relations. The Choice Series #82. A Self Learning Opportunity.

ERIC Educational Resources Information Center

Stirling, John

This student guide is intended to assist persons employed as supervisors in understanding the law relating to discipline and implementing disciplinary procedures. Discussed in the first five sections are the following topics: knowing the rules pertaining to employee discipline (getting information and making judgments); handling discipline…

Ten Effective Ways to Infuse Child Welfare Topics into Educational Leadership Preparation Programs

ERIC Educational Resources Information Center

Giesler, Mark A.; Palladino, John M.

2009-01-01

Administering and supervising special education programs and personnel may be daunting tasks for school leaders. Students and families who warrant the access to special education services present unique and complex needs that make administrative decisions anything but universal and simplistic, especially in regards to foster care populations. The…

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

Strategies for Effective On-Call Supervision for Internal Medicine Residents: The Superb/Safety Model

PubMed Central

Farnan, Jeanne M.; Johnson, Julie K.; Meltzer, David O.; Harris, Ilene; Humphrey, Holly J.; Schwartz, Alan; Arora, Vineet M.

2010-01-01

Background Supervision is central to resident education and patient safety, yet there is little published evidence to describe a framework for clinical supervision. The aim of this study was to describe supervision strategies for on-call internal medicine residents. Methods Between January and November 2006, internal medicine residents and attending physicians at a single hospital were interviewed within 1 week of their final call on the general medicine rotation. Appreciative inquiry and critical incident technique were used to elicit perspectives on ideal and suboptimal supervision practices. A representative portion of transcripts were analyzed using an inductive approach to develop a coding scheme that was then applied to the entire set of transcripts. All discrepancies were resolved via discussion until consensus was achieved. Results Forty-four of 50 (88%) attending physicians and 46 of 50 (92%) eligible residents completed an interview. Qualitative analysis revealed a bidirectional model of suggested supervisory strategies, the “SUPERB/SAFETY” model; an interrater reliability of 0.70 was achieved. Suggestions for attending physicians providing supervision included setting expectations, recognizing uncertainty, planning communication, having easy availability, reassuring residents, balancing supervision, and having autonomy. Suggested resident strategies for seeking supervision from attending physicians included seeking input early, contacting for active clinical decisions or feeling uncertain, end of life issues, transitions in care, or help with systems issues. Common themes suggested by trainees and attending physicians included easy availability and preservation of resident decision-making autonomy. Discussion Residents and attending physicians have explicit expectations for optimal supervision. The SUPERB/SAFETY model of supervision may be an effective resource to enhance the clinical supervision of residents. PMID:21975883

Essential processes for cognitive behavioral clinical supervision: Agenda setting, problem-solving, and formative feedback.

PubMed

Cummings, Jorden A; Ballantyne, Elena C; Scallion, Laura M

2015-06-01

Clinical supervision should be a proactive and considered endeavor, not a reactive one. To that end, supervisors should choose supervision processes that are driven by theory, best available research, and clinical experience. These processes should be aimed at helping trainees develop as clinicians. We highlight 3 supervision processes we believe should be used at each supervision meeting: agenda setting, encouraging trainee problem-solving, and formative feedback. Although these are primarily cognitive-behavioral skills, they can be helpful in combination with other supervision models. We provide example dialogue from supervision exchanges, and discuss theoretical and research support for these processes. Using these processes not only encourages trainee development but also models for them how to use the same processes and approaches with clients. (c) 2015 APA, all rights reserved).

Joint influences of individual and work unit abusive supervision on ethical intentions and behaviors: a moderated mediation model.

PubMed

Hannah, Sean T; Schaubroeck, John M; Peng, Ann C; Lord, Robert G; Trevino, Linda K; Kozlowski, Steve W J; Avolio, Bruce J; Dimotakis, Nikolaos; Doty, Joseph

2013-07-01

We develop and test a model based on social cognitive theory (Bandura, 1991) that links abusive supervision to followers' ethical intentions and behaviors. Results from a sample of 2,572 military members show that abusive supervision was negatively related to followers' moral courage and their identification with the organization's core values. In addition, work unit contexts with varying degrees of abusive supervision, reflected by the average level of abusive supervision reported by unit members, moderated relationships between the level of abusive supervision personally experienced by individuals and both their moral courage and their identification with organizational values. Moral courage and identification with organizational values accounted for the relationship between abusive supervision and followers' ethical intentions and unethical behaviors. These findings suggest that abusive supervision may undermine moral agency and that being personally abused is not required for abusive supervision to negatively influence ethical outcomes. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Psychotherapy-based supervision models in an emerging competency-based era: a commentary.

PubMed

Falender, Carol A; Shafranske, Edward P

2010-03-01

As psychology engages in a cultural shift to competency-based education and training supervision practice is being transformed to the use of competency frames and the application of benchmark competencies. In this issue, psychotherapy-based models of supervision are conceptualized in a competency framework. This paper reflects on the translation of key components of each psychotherapy-based supervision approach in terms of foundational and functional competencies articulated in the Competencies Benchmarks (Fouad et al., 2009). The commentary concludes with a discussion of implications for supervision practice and identifies directions for future articulation and development, including evidence-based psychotherapy supervision. PsycINFO Database Record (c) 2010 APA, all rights reserved

Individual Supervision to Enhance Reflexivity and the Practice of Patient-Centered Care: Experience at the Undergraduate Level.

PubMed

Berney, Alexandre; Bourquin, Céline

2017-12-22

This article reports on what is at work during individual supervision of medical students in the context of teaching breaking bad news (BBN). Surprisingly, there is a relative lack of research and report on the topic of supervision, even though it is regularly used in medical training. Building on our research and teaching experience on BBN at the undergraduate level, as well as interviews of supervisors, the following key elements have been identified: learning objectives (e.g., raising student awareness of structural elements of the interview, emotion (patients and students) handling), pedagogical approach (being centered on student's needs and supportive to promote already existing competences), essentials (e.g., discussing skills and examples from the clinical practice), and enhancing reflexivity while discussing specific issues (e.g., confusion between the needs of the patient and those of the student). Individual supervision has been identified as crucial and most satisfactory by students to provide guidance and to foster a reflexive stance enabling them to critically apprehend their communication style. Ultimately, the challenge is to teach medical students to not only connect with the patient but also with themselves.

Holder and Topic Based Analysis of Emotions on Blog Texts: A Case Study for Bengali

NASA Astrophysics Data System (ADS)

Das, Dipankar; Bandyopadhyay, Sivaji

The paper presents an extended approach of analyzing emotions of the blog users on different topics. The rule based techniques to identify emotion holders and topics with respect to their corresponding emotional expressions helps to develop the baseline system. On the other hand, the Support Vector Machine (SVM) based supervised framework identifies the holders, topics and emotional expressions from the blog sentences by outperforming the baseline system. The existence of many to many relations between the holders and the topics with respect to Ekman's six different emotion classes has been examined using two way evaluation techniques, one is with respect to holder and other is from the perspective of topic. The results of the system were found satisfactory in comparison with the agreement of the subjective annotation. The error analysis shows that the topic of a blog at document level is not always conveyed at the sentence level. Moreover, the difficulty in identifying topic from a blog document is due to the problem of identifying some features like bigrams, Named Entities and sentiment. Thus, we employed a semantic clustering approach along with these features to identify the similarity between document level topic and sentential topic as well as to improve the results of identifying the document level topic.

Psychodrama: A Creative Approach for Addressing Parallel Process in Group Supervision

ERIC Educational Resources Information Center

Hinkle, Michelle Gimenez

2008-01-01

This article provides a model for using psychodrama to address issues of parallel process during group supervision. Information on how to utilize the specific concepts and techniques of psychodrama in relation to group supervision is discussed. A case vignette of the model is provided.

Parenting and the parallel processes in parents' counseling supervision for eating-related problems.

PubMed

Golan, Moria

2014-04-01

This paper presents an integrative model for supervising counselors of parents who face eating-related problems in their families. The model is grounded in the theory of parallel processes which occur during the supervision of health-care professionals as well as the counseling of parents and patients. The aim of this model is to conceptualize components and processes in the supervision space, in order to: (a) create a nurturing environment for health-care facilitators, parents and children, (b) better understand the complex and difficult nature of parenting, the challenge counselors face, and the skills and practices used in parenting and in counseling, and (c) better own practices and oppose the judgment that often dominates in counseling and supervision. This paper reflects upon the tradition of supervision and offers a comprehensive view of this process, including its challenges, skills and practices.

ICT Strategies and Tools for the Improvement of Instructional Supervision. The Virtual Supervision

ERIC Educational Resources Information Center

Cano, Esteban Vazquez; Garcia, Ma. Luisa Sevillano

2013-01-01

This study aims to evaluate and analyze strategies, proposals, and ICT tools to promote a paradigm shift in educational supervision that enhances the schools of this century involved not only in teaching-face learning, but e-learning and blended learning. Traditional models of educational supervision do not guarantee adequate supervision of the…

Implementing a sustainable clinical supervision model for Isles nurses in Orkney.

PubMed

Hall, Ian

2018-03-02

The Isles Network of Care (INOC) community nurses work at the extreme of the remote and rural continuum, working mostly as lone practitioners. Following the development of sustainable clinical supervision model for Isles nurses in Orkney, clinical supervision was found to improve both peer support and governance for this group of isolated staff. A literature overview identified the transition of clinical supervision in general nursing over 24 years from 'carrot' to 'stick'. The study included a questionnaire survey that was sent to the 2017 Queen's Nursing Institute Scotland cohort to elicit information about the nurses' experience of clinical supervision. The survey found that 55% provide supervision and 40% receive it. Health board encouragement of its use was found to be disappointingly low at 40%. The INOC nurses were surveyed about the new peer-support (restorative) model, which relies on video-conference contact to allow face to face interaction between isolated isles nurses. Feedback prompted a review of clinical supervision pairings, and the frequency and methods of meeting. The need for supervisor training led to agreement with the Remote and Rural Health Education Alliance to provide relevant support. The perceived benefits of supervision included increased support and reflection, and improved relationships with isolated colleagues.

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…

The Research Self-Efficacy of Counselor Education and Supervision Doctoral Students

ERIC Educational Resources Information Center

Jones, Amy L.

2012-01-01

Research self-efficacy refers to a person's confidence in their ability to perform research activities (Bailey, 1999; Bard et al., 2000; Deemer, 2010; Holden et al., 1999; Kahn, 2001; Mulliken et al., 2007; Phillips et al., 2004; Unrau & Beck, 2004, Unrau & Grinnel, 2005). Little has been written on this topic in relation to Counselor…

Legal Issues Relating to School Paraprofessionals. A Legal Memorandum: Quarterly Law Topics for School Leaders, Spring 2004

ERIC Educational Resources Information Center

Ashbaker, Betty Y.; Morgan, Jill

2004-01-01

Complaints, hearings, legal opinions, and lawsuits on issues surrounding the training and supervision of paraprofessionals are increasing. Concern over the lack of preparation of paraprofessionals and the sporadic nature of the training that is available to them (Morgan, Hofmeister, & Ashbaker, 1995; Pickett, 1996) have led to the development…

Industrial Relations in Action. Supervising: Industrial Relations. The Choice Series #85. A Self Learning Opportunity.

ERIC Educational Resources Information Center

Stirling, John

This student guide is intended to assist persons employed as supervisors in learning the principles of industrial relations. Discussed in the first eight sections are the following topics: the nature and scope of industrial relations, management organizations and employers' associations, unions, the rights and roles of union representatives, the…

Accounting for Money. Supervising: Economic and Financial Aspects. The Choice Series #70. A Self Learning Opportunity.

ERIC Educational Resources Information Center

Bainbridge, Dennis

This student guide is intended to assist persons employed as supervisors in accounting for money. Discussed in the first four sections are the following topics: the need for accounts; financial accounting (basics of financial accounting, creditors and debtors, assets and liabilities, and balance sheets); cost and management accounting (company,…

Health and Safety. Supervising: Industrial Relations. The Choice Series #84. A Self Learning Opportunity.

ERIC Educational Resources Information Center

McCall, Matthew S.

This student guide is intended to assist persons employed as supervisors in understanding and practicing principles of occupational health and safety. Discussed in the first three sections are the following topics: health and safety at work (causes of accidents, ways of dealing with and reporting accidents, procedures for preventing accidents and…

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.

Topic Identification and Categorization of Public Information in Community-Based Social Media

NASA Astrophysics Data System (ADS)

Kusumawardani, RP; Basri, MH

2017-01-01

This paper presents a work on a semi-supervised method for topic identification and classification of short texts in the social media, and its application on tweets containing dialogues in a large community of dwellers in a city, written mostly in Indonesian. These dialogues comprise a wealth of information about the city, shared in real-time. We found that despite the high irregularity of the language used, and the scarcity of suitable linguistic resources, a meaningful identification of topics could be performed by clustering the tweets using the K-Means algorithm. The resulting clusters are found to be robust enough to be the basis of a classification. On three grouping schemes derived from the clusters, we get accuracy of 95.52%, 95.51%, and 96.7 using linear SVMs, reflecting the applicability of applying this method for generating topic identification and classification on such data.

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

Effect of Clinical Supervision on Job Satisfaction and Burnout among School Psychologists

ERIC Educational Resources Information Center

Kucer, Priscilla Naomi

2018-01-01

This study examined the effect of clinical supervision on job satisfaction and burnout among school psychologists in large urban school districts in Florida. The theory of work adjustment, Maslach and Jackson's three-dimensional model of burnout, and Atkinson and Woods's triadic model of supervision were the theoretical foundations and/or…

Clinical Supervision in Alcohol and Drug Abuse Counseling: Principles, Models, Methods.

ERIC Educational Resources Information Center

Powell, David J.

A case is made for professionalism in clinical training as substance abuse counseling becomes a unique field. Part 1, "Principles," includes: (1) "A Historical Review of Supervision"; (2) "A Working Definition of Supervision"; (3) "Leadership Principles for Supervisors" and; (4) "Traits of an Effective Clinical Supervisor." Part 2, "Models,"…

The Elements: A Model of Mindful Supervision

ERIC Educational Resources Information Center

Sturm, Deborah C.; Presbury, Jack; Echterling, Lennis G.

2012-01-01

Mindfulness, based on an ancient spiritual practice, is a core quality and way of being that can deepen and enrich the supervision of counselors. This model of mindful supervision incorporates Buddhist and Hindu conceptualizations of the roles of the five elements--space, earth, water, fire, air--as they relate to adhikara or studentship, the…

Model for investigating the benefits of clinical supervision in psychiatric nursing: a survey study.

PubMed

Gonge, Henrik; Buus, Niels

2011-04-01

The objective of this study was to test a model for analysing the possible benefits of clinical supervision. The model suggested a pathway from participation to effectiveness to benefits of clinical supervision, and included possible influences of individual and workplace factors. The study sample was 136 nursing staff members in permanent employment on nine general psychiatric wards and at four community mental health centres at a Danish psychiatric university hospital. Data were collected by means of a set of questionnaires. Participation in clinical supervision was associated with the effectiveness of clinical supervision, as measured by the Manchester Clinical Supervision Scale (MCSS). Furthermore, MCSS scores were associated with benefits, such as increased job satisfaction, vitality, rational coping and less stress, emotional exhaustion, and depersonalization. Multivariate analyses indicated that certain individual and workplace factors were related to subscales of the MCSS, as well as some of the benefits. The study supported the suggested model, but methodological limitations apply. © 2011 The Authors. International Journal of Mental Health Nursing © 2011 Australian College of Mental Health Nurses Inc.

The Dimensionality of Supervisor Roles: Counselor Trainees' Perceptions of Supervision.

ERIC Educational Resources Information Center

Ellis, Michael V.; And Others

A study was conducted which continued the investigation of the underlying structure of supervision by empirically testing Bernard's (1979) model of supervision using a confirmatory multidimensional scaling paradigm. To accomplish this, counselor trainees' perceptions of the underlying structure (dimensionality or cognitive map) of supervision were…

Effects of Supervision in the Training of Nonprofessional Crisis-Intervention Counselors

ERIC Educational Resources Information Center

Doyle, William W., Jr.; And Others

1977-01-01

This study evaluated three major models currently used by crisis-intervention centers to train and supervise nonprofessional counselors. Training groups included preservice training only (PSO), preservice training and delayed supervision (PSD), and preservice training and immediate supervision (PSI). Findings indicate most learning by…

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

USDA-ARS?s Scientific Manuscript database

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

Self-supervised ARTMAP.

PubMed

Amis, Gregory P; Carpenter, Gail A

2010-03-01

Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowledge from formal training, via self-directed learning that incorporates features not previously experienced. This article defines a new self-supervised learning paradigm to address these richer learning contexts, introducing a neural network called self-supervised ARTMAP. Self-supervised learning integrates knowledge from a teacher (labeled patterns with some features), knowledge from the environment (unlabeled patterns with more features), and knowledge from internal model activation (self-labeled patterns). Self-supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns. A category selection function bases system predictions on known features, and distributed network activation scales unlabeled learning to prediction confidence. Slow distributed learning on unlabeled patterns focuses on novel features and confident predictions, defining classification boundaries that were ambiguous in the labeled patterns. Self-supervised ARTMAP improves test accuracy on illustrative low-dimensional problems and on high-dimensional benchmarks. Model code and benchmark data are available from: http://techlab.eu.edu/SSART/. Copyright 2009 Elsevier Ltd. All rights reserved.

Broadening the "Ports of Entry" for Speech-Language Pathologists: A Relational and Reflective Model for Clinical Supervision

ERIC Educational Resources Information Center

Geller, Elaine; Foley, Gilbert M.

2009-01-01

Purpose: To offer a framework for clinical supervision in speech-language pathology that embeds a mental health perspective within the study of communication sciences and disorders. Method: Key mental health constructs are examined as to how they are applied in traditional versus relational and reflective supervision models. Comparisons between…

Teaching Graduate Students The Art of Science

NASA Astrophysics Data System (ADS)

Snieder, Roel; Larner, Ken; Boyd, Tom

2012-08-01

Graduate students traditionally learn the trade of research by working under the supervision of an advisor, much as in the medieval practice of apprenticeship. In practice, however, this model generally falls short in teaching students the broad professional skills needed to be a well-rounded researcher. While a large majority of graduate students considers professional training to be of great relevance, most graduate programs focus exclusively on disciplinary training as opposed to skills such as written and oral communication, conflict resolution, leadership, performing literature searches, teamwork, ethics, and client-interaction. Over the past decade, we have developed and taught the graduate course "The Art of Science", which addresses such topics; we summarize the topics covered in the course here. In order to coordinate development of professional training, the Center for Professional Education has been founded at the Colorado School of Mines. After giving an overview of the Center's program, we sketch the challenges and opportunities in offering professional education to graduate students. Offering professional education helps create better-prepared graduates. We owe it to our students to provide them with such preparation.

The National Economy. Supervising: Economic and Financial Aspects. The Choice Series #74. A Self Learning Opportunity.

ERIC Educational Resources Information Center

Rosser, John

This student guide is intended to assist persons employed as supervisors in understanding the main sectors in the national economy. Discussed in the first four sections are the following topics: the economic system (economic decisions and types of economies), the public sector (extent and control of the public sector, finance of the public sector,…

Supervision and Early Career Work Experiences of Estonian Humanities Researchers under the Conditions of Project-Based Funding

ERIC Educational Resources Information Center

Eigi, Jaana; Põiklik, Pille; Lõhkivi, Endla; Velbaum, Katrin

2014-01-01

We analyze a series of interviews with Estonian humanities researchers to explore topics related to the beginning of academic careers and the relationships with supervisors and mentors. We show how researchers strive to have meaningful relationships and produce what they consider quality research in the conditions of a system that is very strongly…

Online Supervision of School Counselors: Effects on Case Conceptualization Skills and Self-Efficacy

ERIC Educational Resources Information Center

Lin, Yi-Chun

2012-01-01

This study examined the supervision effectiveness of three online peer supervision models as measured by the two outcome variables of case conceptualization skills and self-efficacy. Also, it explored the impact of developmental levels of school counselors on the outcomes of supervision. Practicing school counselors from a national sample were…

A community-based peer support service for persons with severe mental illness in China.

PubMed

Fan, Yunge; Ma, Ning; Ma, Liang; Xu, Wei; Steven Lamberti, J; Caine, Eric D

2018-06-04

Peer support services for patients with severe mental illness (SMI) originated from Western countries and have become increasingly popular during the past twenty years. The aim of this paper is to describe a peer service model and its implementation in China, including the model's feasibility and sustainability. A peer support service was developed in four Chinese communities. Implementation, feasibility and sustainability were assessed across five domains: Service process, service contents, peer training and supervision, service satisfaction, and service perceived benefit. Service process: 214 peer support activities were held between July 2013 and June 2016. No adverse events occurred during three years. Each activity ranged from 40 to 120 min; most were conducted in a community rehabilitation center or community health care center. Service content: Activities focused on eight primary topics-daily life skills, social skills, knowledge of mental disorders, entertainment, fine motor skill practice, personal perceptions, healthy life style support, emotional support. Peer training and supervision: Intensive training was provided for all peers before they started to provide services. Regular supervision and continued training were provided thereafter; online supervision supplemented face to face meetings. Service satisfaction: Nineteen consumers (79.2%) (χ 2 (1) = 12.76, p < 0.001) were satisfied with the peers and 17 consumers (70.8%) (χ 2 (1) = 8.05, p = 0.005) expressed a strong desire to continue to participate in the service. Fourteen caregivers (93.3%) (χ 2 (1) = 11.27, p = 0.001) wanted the patients to continue to organize or participate in the service. Service perceived benefit: Six peers (85.7%) (χ 2 (1) = 3.57, p = 0.059) reported an improvement of working skills. Ten consumers (41.7%) (χ 2 (1) = 0.05, p = 0.827) reported better social communication skills. Six caregivers (40%) (χ 2 (1) = 1.67, p = 0.197) observed patients' increase in social communication skills, five (33.3%) (χ 2 (1) = 1.67, p = 0.197) found their own mood had been improved. Peer support services for patients with SMI can be sustainably implemented within Chinese communities without adverse events that jeopardize safety and patient stability. Suggestions for future service development include having professionals give increased levels of support to peers at the beginning of a new program. A culturally consistent peer service manual, including peer role definition, peer training curriculum, and supervision methods, should be developed to help implement the service smoothly.

A break-even analysis of optimum faculty assignment for ambulatory primary care training.

PubMed

Xakellis, G C; Gjerde, C L; Xakellis, M G; Klitgaard, D

1996-12-01

The increased demand that faculty teach residents in ambulatory clinics necessitates the development of ambulatory care teaching models that are both educationally effective and financially viable. This study was designed to identify the resident-to-faculty ratios needed to provide financially viable faculty supervision of residents while maintaining acceptable resident waiting times for teaching. A computer simulation was developed to estimate the number of residents one or two faculty teachers could supervise in a university-based primary care teaching clinic. The number of residents was calculated for three waiting-time constraints and three scenarios of faculty tasks. A financial analysis of each model was performed. With no non-teaching tasks, two teachers were able to supervise 11 residents and keep waiting times under two minutes, while one teacher was able to supervise only three residents with this waiting-time constraint. The financial break-even point was achieved by all of the two-teacher models, but by none of the one-teacher models. In all three scenarios, using two teachers resulted in more than double the number of residents supervised and in higher utilization of faculty time (higher productivity) than did using one teacher. The two-teacher models of ambulatory supervision allowed for sufficient numbers of residents to be supervised so that teaching costs could be covered from patient care revenues; the one-teacher models did not break even financially. These simulations offer a viable option for academic institutions that are struggling to maintain teaching quality in the face of financial constraints.

A global picture of pharmacy technician and other pharmacy support workforce cadres.

PubMed

Koehler, Tamara; Brown, Andrew

Understanding how pharmacy technicians and other pharmacy support workforce cadres assist pharmacists in the healthcare system will facilitate developing health systems with the ability to achieve universal health coverage as it is defined in different country contexts. The aim of this paper is to provide an overview of the present global variety in the technician and other pharmacy support workforce cadres considering; their scope, roles, supervision, education and legal framework. A structured online survey instrument was administered globally using the Survey Monkey platform, designed to address the following topic areas: roles, responsibilities, supervision, education and legislation. The survey was circulated to International Pharmaceutical Federation (FIP) member organisations and a variety of global list serves where pharmaceutical services are discussed. 193 entries from 67 countries and territories were included in the final analysis revealing a vast global variety with respect to the pharmacy support workforce. From no pharmacy technicians or other pharmacy support workforce cadres in Japan, through a variety of cadre interactions with pharmacists, to the autonomous practice of pharmacy support workforce cadres in Malawi. From strictly supervised practice with a focus on supply, through autonomous practice for a variety of responsibilities, to independent practice. From complete supervision for all tasks, through geographical varied supervision, to independent practice. From on the job training, through certificate level vocational courses, to 3-4 year diploma programs. From well-regulated and registered, through part regulation with weak implementation, to completely non-regulated contexts. This paper documents wide differences in supervision requirements, education systems and supportive legislation for pharmacy support workforce cadres globally. A more detailed understanding of specific country practice settings is required if the use of pharmacy support workforce cadres is to be optimized. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Building Mental Models by Dissecting Physical Models

ERIC Educational Resources Information Center

Srivastava, Anveshna

2016-01-01

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to…

General Practitioner (GP) trainees' experience of a '1-h protected supervision model' given during psychiatry placements in the United Kingdom.

PubMed

Thomas, Gareth; McNeill, Helen

2018-01-05

Background A '1-hour protected supervision model' is well established for Psychiatry trainees. This model is also extended to GP trainees who are on placement in psychiatry. To explore the experiences of the '1-hour protected supervision model' for GP trainees in psychiatry placements in the UK. Methods Using a mixed methods approach, an anonymous online questionnaire was sent to GP trainees in the North West of England who had completed a placement in Psychiatry between February and August 2015. Results Discussing clinical cases whilst using the e-portfolio was the most useful learning event in this model. Patient care can potentially improve if a positive relationship develops between trainee/supervisor, which is impacted by the knowledge of this model at the start of the placement. Trainees found that clinical pressures were impacting on the occurrence of supervision. Conclusion The model works best when both GP trainees and their supervisors understand the model. The most frequently used and educationally beneficial aspect for GP trainees in psychiatry is the exploration of clinical cases using the learning portfolio as an educational tool. For effective delivery of this model of supervision, organisations must reflect on the balance between service delivery and allowing the supervisor and trainee adequate time for it to occur.

Speaking of Supervision: A Dialogic Approach to Building Higher Degree Research Supervision Capacity in the Creative Arts

ERIC Educational Resources Information Center

Hamilton, Jillian; Carson, Sue

2015-01-01

In the emergent field of creative practice higher degrees by research, first generation supervisors have developed new models of supervision for an unprecedented form of research, which combines creative practice and a written thesis. In a national research project, entitled "Effective supervision of creative practice higher research…

Strength-based Supervision: Frameworks, Current Practice, and Future Directions A Wu-wei Method.

ERIC Educational Resources Information Center

Edwards, Jeffrey K.; Chen, Mei-Whei

1999-01-01

Discusses a method of counseling supervision similar to the wu-wei practice in Zen and Taoism. Suggests that this strength-based method and an understanding of isomorphy in supervisory relationships are the preferred practice for the supervision of family counselors. States that this model of supervision potentiates the person-of-the-counselor.…

A semi-supervised Support Vector Machine model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging.

PubMed

Tan, Lirong; Holland, Scott K; Deshpande, Aniruddha K; Chen, Ye; Choo, Daniel I; Lu, Long J

2015-12-01

We developed a machine learning model to predict whether or not a cochlear implant (CI) candidate will develop effective language skills within 2 years after the CI surgery by using the pre-implant brain fMRI data from the candidate. The language performance was measured 2 years after the CI surgery by the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2). Based on the CELF-P2 scores, the CI recipients were designated as either effective or ineffective CI users. For feature extraction from the fMRI data, we constructed contrast maps using the general linear model, and then utilized the Bag-of-Words (BoW) approach that we previously published to convert the contrast maps into feature vectors. We trained both supervised models and semi-supervised models to classify CI users as effective or ineffective. Compared with the conventional feature extraction approach, which used each single voxel as a feature, our BoW approach gave rise to much better performance for the classification of effective versus ineffective CI users. The semi-supervised model with the feature set extracted by the BoW approach from the contrast of speech versus silence achieved a leave-one-out cross-validation AUC as high as 0.97. Recursive feature elimination unexpectedly revealed that two features were sufficient to provide highly accurate classification of effective versus ineffective CI users based on our current dataset. We have validated the hypothesis that pre-implant cortical activation patterns revealed by fMRI during infancy correlate with language performance 2 years after cochlear implantation. The two brain regions highlighted by our classifier are potential biomarkers for the prediction of CI outcomes. Our study also demonstrated the superiority of the semi-supervised model over the supervised model. It is always worthwhile to try a semi-supervised model when unlabeled data are available.

The Comprehensive Evaluation Method of Supervision Risk in Electricity Transaction Based on Unascertained Rational Number

NASA Astrophysics Data System (ADS)

Haining, Wang; Lei, Wang; Qian, Zhang; Zongqiang, Zheng; Hongyu, Zhou; Chuncheng, Gao

2018-03-01

For the uncertain problems in the comprehensive evaluation of supervision risk in electricity transaction, this paper uses the unidentified rational numbers to evaluation the supervision risk, to obtain the possible result and corresponding credibility of evaluation and realize the quantification of risk indexes. The model can draw the risk degree of various indexes, which makes it easier for the electricity transaction supervisors to identify the transaction risk and determine the risk level, assisting the decision-making and realizing the effective supervision of the risk. The results of the case analysis verify the effectiveness of the model.

Quasi-supervised scoring of human sleep in polysomnograms using augmented input variables.

PubMed

Yaghouby, Farid; Sunderam, Sridhar

2015-04-01

The limitations of manual sleep scoring make computerized methods highly desirable. Scoring errors can arise from human rater uncertainty or inter-rater variability. Sleep scoring algorithms either come as supervised classifiers that need scored samples of each state to be trained, or as unsupervised classifiers that use heuristics or structural clues in unscored data to define states. We propose a quasi-supervised classifier that models observations in an unsupervised manner but mimics a human rater wherever training scores are available. EEG, EMG, and EOG features were extracted in 30s epochs from human-scored polysomnograms recorded from 42 healthy human subjects (18-79 years) and archived in an anonymized, publicly accessible database. Hypnograms were modified so that: 1. Some states are scored but not others; 2. Samples of all states are scored but not for transitional epochs; and 3. Two raters with 67% agreement are simulated. A framework for quasi-supervised classification was devised in which unsupervised statistical models-specifically Gaussian mixtures and hidden Markov models--are estimated from unlabeled training data, but the training samples are augmented with variables whose values depend on available scores. Classifiers were fitted to signal features incorporating partial scores, and used to predict scores for complete recordings. Performance was assessed using Cohen's Κ statistic. The quasi-supervised classifier performed significantly better than an unsupervised model and sometimes as well as a completely supervised model despite receiving only partial scores. The quasi-supervised algorithm addresses the need for classifiers that mimic scoring patterns of human raters while compensating for their limitations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Introduction to Computing: Lab Manual. Faculty Guide [and] Student Guide.

ERIC Educational Resources Information Center

Frasca, Joseph W.

This lab manual is designed to accompany a college course introducing students to computing. The exercises are designed to be completed by the average student in a supervised 2-hour block of time at a computer lab over 15 weeks. The intent of each lab session is to introduce a topic and have the student feel comfortable with the use of the machine…

Wage Payment Systems. Supervising: Economic and Financial Aspects. The Choice Series #73. A Self Learning Opportunity.

ERIC Educational Resources Information Center

Carlisle, Ysanne

This student guide is intended to assist persons employed as supervisors in understanding various wage payment systems. Discussed in the first four sections are the following topics: the aims and determination of payment (aims of a payment system, the economy and wage levels, the government and wage levels, and method of pay and wage levels); main…

To take responsibility or to be an onlooker. Nursing students' experiences of two models of supervision.

PubMed

Hellström-Hyson, Eva; Mårtensson, Gunilla; Kristofferzon, Marja-Leena

2012-01-01

The present study aimed at describing how nursing students engaged in their clinical practice experienced two models of supervision: supervision on student wards and traditional supervision. Supervision for nursing students in clinical practice can be organized in different ways. In the present study, parts of nursing students' clinical practice were carried out on student wards in existing hospital departments. The purpose was to give students the opportunity to assume greater responsibility for their clinical education and to apply the nursing process more independently through peer learning. A descriptive design with a qualitative approach was used. Interviews were carried out with eight nursing students in their final semester of a 3-year degree program in nursing. The data were analyzed using content analysis. Two themes were revealed in the data analysis: When supervised on the student wards, nursing students experienced assuming responsibility and finding one's professional role, while during traditional supervision, they experienced being an onlooker and having difficulties assuming responsibility. Supervision on a student ward was found to give nursing students a feeling of acknowledgment and more opportunities to develop independence, continuity, cooperation and confidence. Copyright © 2011 Elsevier Ltd. All rights reserved.

Maintaining capacity for in-practice teaching and supervision of students and general practice trainees: a cross-sectional study of early career general practitioners.

PubMed

Catzikiris, Nigel; Tapley, Amanda; Morgan, Simon; Holliday, Elizabeth G; Ball, Jean; Henderson, Kim; Elliott, Taryn; Spike, Neil; Regan, Cathy; Magin, Parker

2017-08-10

Objectives Expanding learner cohorts of medical students and general practitioner (GP) vocational trainees and the impending retirement of the 'baby boomer' GP cohort threaten the teaching and supervisory capacity of the Australian GP workforce. Engaging newly qualified GPs is essential to sustaining this workforce training capacity. The aim of the present study was to establish the prevalence and associations of in-practice clinical teaching and supervision in early career GPs. Methods The present study was a cross-sectional questionnaire-based study of recent (within 5 years) alumni of three of Australia's 17 regional general practice training programs. The outcome factor was whether the alumnus taught or supervised medical students, GP registrars or other learners in their current practice. Logistic regression analysis was used to establish associations of teaching and supervision with independent variables comprising alumnus demographics, current practice characteristics and vocational training experiences. Results In all, 230 alumni returned questionnaires (response rate 37.4%). Of currently practising alumni, 52.4% (95% confidence interval (CI) 45.6-59.0%) reported current teaching or supervisory activities. Factors significantly (P<0.05) associated with alumni currently undertaking in-practice clinical teaching and supervision were: Australian medical graduation (odds ratio (OR) for international graduates 0.36; 95% CI 0.14-0.92), working in a regional or remote area (OR 2.75; 95% CI 1.24-6.11) and currently undertaking nursing home visits, home visits or after-hours work (OR 2.01; CI 1.02-3.94). Conclusions Rural-urban and country-of-graduation differences in the engagement of early career GPs in practice-based apprenticeship-like teaching or training should inform strategies to maintain workforce training capacity. What is known about the topic? Projected changes in the demand for and supply of clinical teaching and supervision within Australian general practice will require greater uptake of teaching and supervision by recently qualified GPs to ensure sustainability of this teaching model. Although interest in and undertaking of teaching roles have been documented for GP or family medicine trainees, studies investigating the engagement in these clinical roles by GPs during their early post-training period are lacking. What does this paper add? This paper is the first to document the prevalence of teaching and supervision undertaken by early career GPs as part of their regular clinical practice. We also demonstrate associations of practice rurality, country of medical graduation and undertaking non-practice-based clinical roles with GPs' engagement in teaching and supervisory roles. What are the implications for practitioners? Establishing current teaching patterns of GPs enables appropriate targeting of new strategies to sustain an effective teaching and supervisory capacity within general practice. The findings of the present study suggest that exploring focused strategies to facilitate and support international medical graduates to engage in teaching during their vocational training, aided by focused supervisor support, may be of particular value.

Suffering in silence: Investigating the role of fear in the relationship between abusive supervision and defensive silence.

PubMed

Kiewitz, Christian; Restubog, Simon Lloyd D; Shoss, Mindy K; Garcia, Patrick Raymund James M; Tang, Robert L

2016-05-01

Drawing from an approach-avoidance perspective, we examine the relationships between subordinates' perceptions of abusive supervision, fear, defensive silence, and ultimately abusive supervision at a later time point. We also account for the effects of subordinates' assertiveness and individual perceptions of a climate of fear on these predicted mediated relationships. We test this moderated mediation model with data from three studies involving different sources collected across various measurement periods. Results corroborated our predictions by showing (a) a significant association between abusive supervision and subordinates' fear, (b) second-stage moderation effects of subordinates' assertiveness and their individual perceptions of a climate of fear in the abusive supervision-fear-defensive silence relationship (with lower assertiveness and higher levels of climate-of-fear perceptions exacerbating the detrimental effects of fear resulting from abusive supervision), and (c) first-stage moderation effects of subordinates' assertiveness and climate-of-fear perceptions in a model linking fear to defensive silence and abusive supervision at a later time. Theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning

PubMed Central

Cole-Lewis, Heather; Varghese, Arun; Sanders, Amy; Schwarz, Mary; Pugatch, Jillian

2015-01-01

Background Electronic cigarettes (e-cigarettes) continue to be a growing topic among social media users, especially on Twitter. The ability to analyze conversations about e-cigarettes in real-time can provide important insight into trends in the public’s knowledge, attitudes, and beliefs surrounding e-cigarettes, and subsequently guide public health interventions. Objective Our aim was to establish a supervised machine learning algorithm to build predictive classification models that assess Twitter data for a range of factors related to e-cigarettes. Methods Manual content analysis was conducted for 17,098 tweets. These tweets were coded for five categories: e-cigarette relevance, sentiment, user description, genre, and theme. Machine learning classification models were then built for each of these five categories, and word groupings (n-grams) were used to define the feature space for each classifier. Results Predictive performance scores for classification models indicated that the models correctly labeled the tweets with the appropriate variables between 68.40% and 99.34% of the time, and the percentage of maximum possible improvement over a random baseline that was achieved by the classification models ranged from 41.59% to 80.62%. Classifiers with the highest performance scores that also achieved the highest percentage of the maximum possible improvement over a random baseline were Policy/Government (performance: 0.94; % improvement: 80.62%), Relevance (performance: 0.94; % improvement: 75.26%), Ad or Promotion (performance: 0.89; % improvement: 72.69%), and Marketing (performance: 0.91; % improvement: 72.56%). The most appropriate word-grouping unit (n-gram) was 1 for the majority of classifiers. Performance continued to marginally increase with the size of the training dataset of manually annotated data, but eventually leveled off. Even at low dataset sizes of 4000 observations, performance characteristics were fairly sound. Conclusions Social media outlets like Twitter can uncover real-time snapshots of personal sentiment, knowledge, attitudes, and behavior that are not as accessible, at this scale, through any other offline platform. Using the vast data available through social media presents an opportunity for social science and public health methodologies to utilize computational methodologies to enhance and extend research and practice. This study was successful in automating a complex five-category manual content analysis of e-cigarette-related content on Twitter using machine learning techniques. The study details machine learning model specifications that provided the best accuracy for data related to e-cigarettes, as well as a replicable methodology to allow extension of these methods to additional topics. PMID:26307512

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning.

PubMed

Cole-Lewis, Heather; Varghese, Arun; Sanders, Amy; Schwarz, Mary; Pugatch, Jillian; Augustson, Erik

2015-08-25

Electronic cigarettes (e-cigarettes) continue to be a growing topic among social media users, especially on Twitter. The ability to analyze conversations about e-cigarettes in real-time can provide important insight into trends in the public's knowledge, attitudes, and beliefs surrounding e-cigarettes, and subsequently guide public health interventions. Our aim was to establish a supervised machine learning algorithm to build predictive classification models that assess Twitter data for a range of factors related to e-cigarettes. Manual content analysis was conducted for 17,098 tweets. These tweets were coded for five categories: e-cigarette relevance, sentiment, user description, genre, and theme. Machine learning classification models were then built for each of these five categories, and word groupings (n-grams) were used to define the feature space for each classifier. Predictive performance scores for classification models indicated that the models correctly labeled the tweets with the appropriate variables between 68.40% and 99.34% of the time, and the percentage of maximum possible improvement over a random baseline that was achieved by the classification models ranged from 41.59% to 80.62%. Classifiers with the highest performance scores that also achieved the highest percentage of the maximum possible improvement over a random baseline were Policy/Government (performance: 0.94; % improvement: 80.62%), Relevance (performance: 0.94; % improvement: 75.26%), Ad or Promotion (performance: 0.89; % improvement: 72.69%), and Marketing (performance: 0.91; % improvement: 72.56%). The most appropriate word-grouping unit (n-gram) was 1 for the majority of classifiers. Performance continued to marginally increase with the size of the training dataset of manually annotated data, but eventually leveled off. Even at low dataset sizes of 4000 observations, performance characteristics were fairly sound. Social media outlets like Twitter can uncover real-time snapshots of personal sentiment, knowledge, attitudes, and behavior that are not as accessible, at this scale, through any other offline platform. Using the vast data available through social media presents an opportunity for social science and public health methodologies to utilize computational methodologies to enhance and extend research and practice. This study was successful in automating a complex five-category manual content analysis of e-cigarette-related content on Twitter using machine learning techniques. The study details machine learning model specifications that provided the best accuracy for data related to e-cigarettes, as well as a replicable methodology to allow extension of these methods to additional topics.

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.

Supervision in primary health care--can it be carried out effectively in developing countries?

PubMed

Clements, C John; Streefland, Pieter H; Malau, Clement

2007-01-01

There is nothing new about supervision in primary health care service delivery. Supervision was even conducted by the Egyptian pyramid builders. Those supervising have often favoured ridicule and discipline to push individuals and communities to perform their duties. A traditional form of supervision, based on a top-down colonial model, was originally attempted as a tool to improve health service staff performance. This has recently been replaced by a more liberal "supportive supervision". While it is undoubtedly an improvement on the traditional model, we believe that even this version will not succeed to any great extent until there is a better understanding of the human interactions involved in supervision. Tremendous cultural differences exist over the globe regarding the acceptability of this form of management. While it is clear that health services in many countries have benefited from supervision of one sort or another, it is equally clear that in some countries, supervision is not carried out, or when carried out, is done inadequately. In some countries it may be culturally inappropriate, and may even be impossible to carry out supervision at all. We examine this issue with particular reference to immunization and other primary health care services in developing countries. Supported by field observations in Papua New Guinea, we conclude that supervision and its failure should be understood in a social and cultural context, being a far more complex activity than has so far been acknowledged. Social science-based research is needed to enable a third generation of culture-sensitive ideas to be developed that will improve staff performance in the field.

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.

Profile of 1 year of fieldwork experiences for undergraduate occupational therapy students from a large regional Australian university.

PubMed

Mackenzie, Lynette; O'Toole, Gjyn

2017-10-01

Objective Fieldwork experience is a significant component of many health professional education programs and affects future practice for graduates. The present study used self-reported student data to produce a profile of undergraduate student placement experiences. Methods Cross-sectional surveys exploring placement location, setting and client types, models of supervision, interventions and financial costs were completed by students following each placement. Data were analysed using descriptive analysis. Results Placements were predominantly conducted outside capital cities (69.8%; n=184), with 25.8% (n=68) in rural settings. Students experienced predominantly public health in-patient settings and community settings, with only 15% experiencing private settings. Conclusions The placement profile of undergraduate occupational therapy students appeared to be consistent with workforce reports on occupational therapy professional practice. What is known about the topic? Fieldwork experienced by health professional students is critical to preparing new graduates for practice. Although the World Federation of Occupational Therapy provides guidance on what is required for occupational therapy fieldwork experience, little is known about what students actually experience during their fieldwork placements. What does this paper add? The present study is the first to document the range of fieldwork experienced by occupational therapy students in one program over 1 year, and provides the basis for comparison with other occupational therapy programs, as well as other disciplines nationally and internationally. What are the implications for practitioners? Occupational therapy students experienced few opportunities in private practice or speciality services, and had mostly one-on-one supervision. To provide a future workforce that is able to address the changing health system, it is vital that students are exposed to a range of fieldwork experiences and supervision styles that replicate the demands of future practice.

When approved is not enough: development of a supervision consultation model.

PubMed

Green, S; Shilts, L; Bacigalupe, G

2001-10-01

The dramatic increase in the literature that addresses family therapy training and supervision over the last decade has been predominantly in the area of theory, rather than practice. This article describes the development of a meta-supervisory learning context for approved supervisors and provides examples of interactions between supervisors that subsequently influenced both therapy and supervision. We delineate the assumptions that inform our work and offer specific guidelines for supervisors who wish to implement a similar model in their own contexts. We provide suggestions for a proactive refiguring of supervision that may have profound effects and benefits for supervisors and supervisees alike.

Reflect and learn together - when two supervisors interact in the learning support process of nurse education.

PubMed

Berglund, Mia; Sjögren, Reet; Ekebergh, Margaretha

2012-03-01

To describe the importance of supervisors working together in supporting the learning process of nurse students through reflective caring science supervision. A supervision model has been developed in order to meet the need for interweaving theory and practice. The model is characterized by learning reflection in caring science. A unique aspect of the present project was that the student groups were led by a teacher and a nurse. Data were collected through interviews with the supervisors. The analysis was performed with a phenomenological approach. The results showed that theory and practice can be made more tangible and interwoven by using two supervisors in a dual supervision. The essential structure is built on the constituents 'Reflection as Learning Support', 'Interweaving Caring Science with the Patient's Narrative', 'The Student as a Learning Subject' and 'The Learning Environment of Supervision'. The study concludes that supervision in pairs provides unique possibilities for interweaving and developing theory and practice. The supervision model offers unique opportunities for cooperation, for the development of theory and practice and for the development of the professional roll of nurses and teachers. © 2012 Blackwell Publishing Ltd.

An Eight-Eyed Version of Hawkins and Shohet's Clinical Supervision Model: The Addition of the Cognitive Analytic Therapy Concept of the "Observing Eye/I" as the "Observing Us"

ERIC Educational Resources Information Center

Darongkamas, Jurai; John, Christopher; Walker, Mark James

2014-01-01

This paper proposes incorporating the concept of the "observing eye/I", from cognitive analytic therapy (CAT), to Hawkins and Shohet's seven modes of supervision, comprising their transtheoretical model of supervision. Each mode is described alongside explicit examples relating to CAT. This modification using a key idea from CAT (in…

Supervision in Physical Education Teacher Education Programs: Making the Case for Paired Placements

ERIC Educational Resources Information Center

Heidorn, Brent; Jenkins, Deborah Bainer

2015-01-01

Many student teaching experiences in physical education teacher education programs face challenges related to supervision and realistic preparation for the workplace. This article suggests paired placements as a model for effective supervision and increased collaboration during the student teaching internship.

An Integrative Spiritual Development Model of Supervision for Substance Abuse Counselors-in-Training

ERIC Educational Resources Information Center

Weiss Ogden, Karen R.; Sias, Shari M.

2011-01-01

Substance abuse counselors who address clients' spiritual development may provide more comprehensive counseling. This article presents an integrative supervision model designed to promote the spiritual development of substance abuse counselors-in-training, reviews the model, and discusses the implications for counselor education.

Global Optimization Ensemble Model for Classification Methods

PubMed Central

Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab

2014-01-01

Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382

Investigating the LGBTQ Responsive Model for Supervision of Group Work

ERIC Educational Resources Information Center

Luke, Melissa; Goodrich, Kristopher M.

2013-01-01

This article reports an investigation of the LGBTQ Responsive Model for Supervision of Group Work, a trans-theoretical supervisory framework to address the needs of lesbian, gay, bisexual, transgender, and questioning (LGBTQ) persons (Goodrich & Luke, 2011). Findings partially supported applicability of the LGBTQ Responsive Model for Supervision…

Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

PubMed

Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

2016-03-01

One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi-supervised learning model is one more appropriate tool for survival analysis in clinical cancer research.

Abusive supervision, psychosomatic symptoms, and deviance: Can job autonomy make a difference?

PubMed

Velez, Maria João; Neves, Pedro

2016-07-01

Recently, interest in abusive supervision has grown (Tepper, 2000). However, little is still known about organizational factors that can reduce its adverse effects on employee behavior. Based on the Job Demands-Resources Model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001), we predict that job autonomy acts as a buffer of the positive relationship between abusive supervision, psychosomatic symptoms and deviance. Therefore, when job autonomy is low, a higher level of abusive supervision should be accompanied by increased psychosomatic symptoms and thus lead to higher production deviance. When job autonomy is high, abusive supervision should fail to produce increased psychosomatic symptoms and thus should not lead to higher production deviance. Our model was explored among a sample of 170 supervisor-subordinate dyads from 4 organizations. The results of the moderated mediation analysis supported our hypotheses. That is, abusive supervision was significantly related to production deviance via psychosomatic symptoms when job autonomy was low, but not when job autonomy was high. These findings suggest that job autonomy buffers the impact of abusive supervision perceptions on psychosomatic symptoms, with consequences for production deviance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Clinical supervision, emotional exhaustion, and turnover intention: a study of substance abuse treatment counselors in the Clinical Trials Network of the National Institute on Drug Abuse.

PubMed

Knudsen, Hannah K; Ducharme, Lori J; Roman, Paul M

2008-12-01

An intriguing hypothesis is that clinical supervision may protect against counselor turnover. This idea has been mentioned in recent discussions of the substance abuse treatment workforce. To test this hypothesis, we extend our previous research on emotional exhaustion and turnover intention among counselors by estimating the associations between clinical supervision and these variables in a large sample (N = 823). An exploratory analysis reveals that clinical supervision was negatively associated with emotional exhaustion and turnover intention. Given our previous findings that emotional exhaustion and turnover intention were associated with job autonomy, procedural justice, and distributive justice, we estimate a structural equation model to examine whether these variables mediated clinical supervision's associations with emotional exhaustion and turnover intention. These data support the fully mediated model. We found that the perceived quality of clinical supervision is strongly associated with counselors' perceptions of job autonomy, procedural justice, and distributive justice, which are, in turn, associated with emotional exhaustion and turnover intention. These data offer support for the protective role of clinical supervision in substance abuse treatment counselors' turnover and occupational well-being.

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.

Clinical supervision of psychotherapy: essential ethics issues for supervisors and supervisees.

PubMed

Barnett, Jeffrey E; Molzon, Corey H

2014-11-01

Clinical supervision is an essential aspect of every mental health professional's training. The importance of ensuring that supervision is provided competently, ethically, and legally is explained. The elements of the ethical practice of supervision are described and explained. Specific issues addressed include informed consent and the supervision contract, supervisor and supervisee competence, attention to issues of diversity and multicultural competence, boundaries and multiple relationships in the supervision relationship, documentation and record keeping by both supervisor and supervisee, evaluation and feedback, self-care and the ongoing promotion of wellness, emergency coverage, and the ending of the supervision relationship. Additionally, the role of clinical supervisor as mentor, professional role model, and gatekeeper for the profession are discussed. Specific recommendations are provided for ethically and effectively conducting the supervision relationship and for addressing commonly arising dilemmas that supervisors and supervisees may confront. © 2014 Wiley Periodicals, Inc.

Systemic-Developmental Supervision: Clinical Supervisory Approach for Family Counseling Student Interns

ERIC Educational Resources Information Center

Carlson, Ryan G.; Lambie, Glenn W.

2012-01-01

Supervision models for marriage and family counseling student interns primarily focus on the use of traditional systemic techniques. In addition, a supervisee's level of development may not be considered when utilizing systemic tools. Furthermore, the supervisory relationship has been identified as a significant indicator of quality supervision,…

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…

The Collaborative Peer Supervision Group Project: A Continuing Education Model to Promote Professional Competence

ERIC Educational Resources Information Center

Thomasgard, Michael; Warfield, Janeece

2005-01-01

Thomasgard, a physician, and Warfield, a psychologist, describe the multidisciplinary Collaborative Peer Supervision Group Project, originally developed and implemented in Columbus, Ohio. Collaborative Peer Supervision Groups (CPSGs) foster the development of case-based, interdisciplinary, continuing education. CPSGs are designed to improve the…

Comparing the Effect of Two Internship Structures on Supervision Experience and Learning

ERIC Educational Resources Information Center

Winslow, Robin D.; Eliason, Meghan; Thiede, Keith W.

2016-01-01

The purpose of this study was to examine two different models of internship and competitively evaluate their effectiveness in influencing interns' experience, beliefs, and knowledge of supervision. The research questions for this study were developed from the literature on supervision of instruction and internships in educational leadership…

Combining Unsupervised and Supervised Classification to Build User Models for Exploratory Learning Environments

ERIC Educational Resources Information Center

Amershi, Saleema; Conati, Cristina

2009-01-01

In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data).…

A learning model for nursing students during clinical studies.

PubMed

Ekebergh, Margaretha

2011-11-01

This paper presents a research project where the aim was to develop a new model for learning support in nursing education that makes it possible for the student to encounter both the theoretical caring science structure and the patient's lived experiences in his/her learning process. A reflective group supervision model was developed and tested. The supervision was lead by a teacher and a nurse and started in patient narratives that the students brought to the supervision sessions. The narratives were analyzed by using caring science concepts with the purpose of creating a unity of theory and lived experiences. Data has been collected and analyzed phenomenologically in order to develop knowledge of the students' reflection and learning when using the supervision model. The result shows that the students have had good use of the theoretical concepts in creating a deeper understanding for the patient. They have learned to reflect more systematically and the learning situation has become more realistic to them as it is now carried out in a patient near context. In order to reach these results, however, demands the necessity of recognizing the students' lifeworld in the supervision process. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Creative Therapies Model for the Group Supervision of Counsellors.

ERIC Educational Resources Information Center

Wilkins, Paul

1995-01-01

Sets forth a model of group supervision, drawing on a creative therapies approach which provides an effective way of delivering process issues, conceptualization issues, and personalization issues. The model makes particular use of techniques drawn from art therapy and from psychodrama, and should be applicable to therapists of many orientations.…

The Superskills Model: A Supervisory Microskill Competency Training Model

ERIC Educational Resources Information Center

Destler, Dusty

2017-01-01

Streamlined supervision frameworks are needed to enhance and progress the practice and training of supervisors. This author proposes the SuperSkills Model (SSM), grounded in the practice of microskills and supervision common factors, with a focus on the development and foundational learning of supervisors-in-training. The SSM worksheet prompts for…

Development and validation of the ExPRESS instrument for primary health care providers' evaluation of external supervision.

PubMed

Schriver, Michael; Cubaka, Vincent Kalumire; Vedsted, Peter; Besigye, Innocent; Kallestrup, Per

2018-01-01

External supervision of primary health care facilities to monitor and improve services is common in low-income countries. Currently there are no tools to measure the quality of support in external supervision in these countries. To develop a provider-reported instrument to assess the support delivered through external supervision in Rwanda and other countries. "External supervision: Provider Evaluation of Supervisor Support" (ExPRESS) was developed in 18 steps, primarily in Rwanda. Content validity was optimised using systematic search for related instruments, interviews, translations, and relevance assessments by international supervision experts as well as local experts in Nigeria, Kenya, Uganda and Rwanda. Construct validity and reliability were examined in two separate field tests, the first using exploratory factor analysis and a test-retest design, the second for confirmatory factor analysis. We included 16 items in section A ('The most recent experience with an external supervisor'), and 13 items in section B ('The overall experience with external supervisors'). Item-content validity index was acceptable. In field test I, test-retest had acceptable kappa values and exploratory factor analysis suggested relevant factors in sections A and B used for model hypotheses. In field test II, models were tested by confirmatory factor analysis fitting a 4-factor model for section A, and a 3-factor model for section B. ExPRESS is a promising tool for evaluation of the quality of support of primary health care providers in external supervision of primary health care facilities in resource-constrained settings. ExPRESS may be used as specific feedback to external supervisors to help identify and address gaps in the supervision they provide. Further studies should determine optimal interpretation of scores and the number of respondents needed per supervisor to obtain precise results, as well as test the functionality of section B.

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.

Using topical benzocaine before lingual frenotomy did not reduce crying and should be discouraged.

PubMed

Ovental, A; Marom, R; Botzer, E; Batscha, N; Dollberg, S

2014-07-01

The US Food and Drug Administration has said that oral preparations containing benzocaine should only be used in infants under strict medical supervision, due to the rare, but potentially fatal, risk of methemoglobinemia. This study aimed to determine the analgesic effect of topical application of benzocaine prior to lingual frenotomy in infants with symptomatic tongue-tie. We hypothesised that the duration of crying immediately following frenotomy with topical benzocaine would be shorter than with no benzocaine. This randomised controlled study compared the length of crying after lingual frenotomy in term infants who did, or did not, receive topical application of benzocaine to the lingual frenulum prior to the procedure. We recruited 21 infants to this study. Crying time was less than one minute in all of the subjects. The average length of crying in the benzocaine group (21.6 ± 13.6 sec) was longer than the length of crying in the control group (13.1 ± 4.0 sec), p = 0.103. Contrary to our hypothesis, infants who were treated with topical benzocaine did not benefit from topical analgesia in terms of crying time. The use of benzocaine for analgesia prior to lingual frenotomy in term infants should therefore be discouraged. ©2014 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Off-Site Supervision in Social Work Education: What Makes It Work?

ERIC Educational Resources Information Center

Maynard, Sarah P.; Mertz, Linda K. P.; Fortune, Anne E.

2015-01-01

The field practicum is the signature pedagogy of the social work profession, yet field directors struggle to find adequate field placements--both in quantity and quality. To accommodate more students with a dwindling pool of practicum sites, creative models of field supervision have emerged. This article considers off-site supervision and its…

"They're the Bosses": Feedback in Team Supervision

ERIC Educational Resources Information Center

Guerin, Cally; Green, Ian

2015-01-01

Team supervision of PhDs is increasingly the norm in Australian and UK universities; while this model brings many improvements on the traditional one-on-one research supervision, it also introduces new complexities. In particular, many students find the diversity of opinions expressed in teams to be confusing. Such diversity in supervisor feedback…

Family Nurse Partnership: why supervision matters.

PubMed

Andrews, Lindsayws

First-time teenage mothers and their babies are likely to have increased levels of need. This article explores how supervision supports Family Nurse Partnership (FNP) nurses to undertake complex work with teenage, first-time mothers and their babies. Careful application of a supervision model can provide the structure for a safe, containing, reflective space.

The Profound of Students' Supervision Practice in Higher Education to Enhance Student Development

ERIC Educational Resources Information Center

Ismail, Affero; Abiddin, Norhasni Zainal; Hassan, Razali; Ro'is, Ihsan

2014-01-01

Supervision has become a highlight in higher education in recent years. While striving for the quality of education, the stress in research supervision has become dominant. Excellent research can contribute to the prominent of institutions' image. This paper accumulates the models from expert scholars in students' development regarding supervision…

Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments

PubMed Central

Pereira, Francisco; Botvinick, Matthew; Detre, Greg

2012-01-01

In this paper we show that a corpus of a few thousand Wikipedia articles about concrete or visualizable concepts can be used to produce a low-dimensional semantic feature representation of those concepts. The purpose of such a representation is to serve as a model of the mental context of a subject during functional magnetic resonance imaging (fMRI) experiments. A recent study [19] showed that it was possible to predict fMRI data acquired while subjects thought about a concrete concept, given a representation of those concepts in terms of semantic features obtained with human supervision. We use topic models on our corpus to learn semantic features from text in an unsupervised manner, and show that those features can outperform those in [19] in demanding 12-way and 60-way classification tasks. We also show that these features can be used to uncover similarity relations in brain activation for different concepts which parallel those relations in behavioral data from human subjects. PMID:23243317

Clinical supervision, emotional exhaustion, and turnover intention: A study of substance abuse treatment counselors in NIDA’s Clinical Trials Network

PubMed Central

Knudsen, Hannah K.; Ducharme, Lori J.; Roman, Paul M

2008-01-01

An intriguing hypothesis is that clinical supervision may protect against counselor turnover. This idea has been mentioned in recent discussions of the substance abuse treatment workforce. To test this hypothesis, we extend our previous research on emotional exhaustion and turnover intention among counselors by estimating the associations between clinical supervision and these variables in a large sample (n = 823). An exploratory analysis reveals that clinical supervision was negatively associated with emotional exhaustion and turnover intention. Given our previous findings that emotional exhaustion and turnover intention were associated with job autonomy, procedural justice, and distributive justice, we estimate a structural equation model to examine whether these variables mediated clinical supervision’s associations with emotional exhaustion and turnover intention. These data support the fully mediated model. We found the perceived quality of clinical supervision is strongly associated with counselors’ perceptions of job autonomy, procedural justice, and distributive justice, which are, in turn, associated with emotional exhaustion and turnover intention. These data offer support for the protective role of clinical supervision in substance abuse treatment counselors’ turnover and occupational wellbeing. PMID:18424048

Initial experiences and innovations in supervising community health workers for maternal, newborn, and child health in Morogoro region, Tanzania.

PubMed

Roberton, Timothy; Applegate, Jennifer; Lefevre, Amnesty E; Mosha, Idda; Cooper, Chelsea M; Silverman, Marissa; Feldhaus, Isabelle; Chebet, Joy J; Mpembeni, Rose; Semu, Helen; Killewo, Japhet; Winch, Peter; Baqui, Abdullah H; George, Asha S

2015-04-09

Supervision is meant to improve the performance and motivation of community health workers (CHWs). However, most evidence on supervision relates to facility health workers. The Integrated Maternal, Newborn, and Child Health (MNCH) Program in Morogoro region, Tanzania, implemented a CHW pilot with a cascade supervision model where facility health workers were trained in supportive supervision for volunteer CHWs, supported by regional and district staff, and with village leaders to further support CHWs. We examine the initial experiences of CHWs, their supervisors, and village leaders to understand the strengths and challenges of such a supervision model for CHWs. Quantitative and qualitative data were collected concurrently from CHWs, supervisors, and village leaders. A survey was administered to 228 (96%) of the CHWs in the Integrated MNCH Program and semi-structured interviews were conducted with 15 CHWs, 8 supervisors, and 15 village leaders purposefully sampled to represent different actor perspectives from health centre catchment villages in Morogoro region. Descriptive statistics analysed the frequency and content of CHW supervision, while thematic content analysis explored CHW, supervisor, and village leader experiences with CHW supervision. CHWs meet with their facility-based supervisors an average of 1.2 times per month. CHWs value supervision and appreciate the sense of legitimacy that arises when supervisors visit them in their village. Village leaders and district staff are engaged and committed to supporting CHWs. Despite these successes, facility-based supervisors visit CHWs in their village an average of only once every 2.8 months, CHWs and supervisors still see supervision primarily as an opportunity to check reports, and meetings with district staff are infrequent and not well scheduled. Supervision of CHWs could be strengthened by streamlining supervision protocols to focus less on report checking and more on problem solving and skills development. Facility health workers, while important for technical oversight, may not be the best mentors for certain tasks such as community relationship-building. We suggest further exploring CHW supervision innovations, such as an enhanced role for community actors, who may be more suitable to support CHWs engaged primarily in health promotion than scarce and over-worked facility health workers.

The Influence of Supervisor Multicultural Competence on the Supervisory Working Alliance, Supervisee Counseling Self-efficacy, and Supervisee Satisfaction with Supervision: A Mediation Model

ERIC Educational Resources Information Center

Crockett, Stephanie; Hays, Danica G.

2015-01-01

We developed and tested a mediation model depicting relationships among supervisor multicultural competence, the supervisory working alliance, supervisee counseling self-efficacy, and supervisee satisfaction with supervision. Results of structural equation modeling showed that supervisor multicultural competence was related to the supervisory…

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.

Supervisory Behaviors of Cooperating Agricultural Education Teachers

ERIC Educational Resources Information Center

Thobega, Moreetsi; Miller, Greg

2007-01-01

The purpose of this study was to determine the extent to which cooperating agricultural education teachers used selected supervision models. The relationships between maturity characteristics of the cooperating teachers and their choices of a supervision model were also examined. Results showed that cooperating teachers commonly used clinical,…

Effectiveness of School Counselor Supervision with Trainees Utilizing the ASCA Model

ERIC Educational Resources Information Center

Blakely, Colette; Underwood, Lee A.; Rehfuss, Mark

2009-01-01

This study sought to determine if differences existed in the supervision of school counselors in traditional school counseling programs versus Recognized ASCA Model Programs (RAMP). The findings indicated that there are significant differences between traditional counseling supervisors and RAMP counseling supervisors across all supervisory…

Supervision Anxiety as a Predictor for Organizational Cynicism in Teachers

ERIC Educational Resources Information Center

Gündüz, Hasan Basri; Ömür, Yunus Emre

2016-01-01

The purpose of this is study is to reveal how the anxiety that the teachers who work in the Beyoglu district of Istanbul experience, due to the supervision process, predict their organizational cynicism levels. With this respect, the study was conducted on 274 teachers with the relational screening model. The "Supervision Anxiety Scale"…

Parametric embedding for class visualization.

PubMed

Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B

2007-09-01

We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.

The importance, impact and influence of group clinical supervision for graduate entry nursing students.

PubMed

Sheppard, Fiona; Stacey, Gemma; Aubeeluck, Aimee

2018-01-01

This paper will report on an evaluation of group clinical supervision (CS) facilitated for graduate entry nursing (GEN) students whilst on clinical placement. The literature suggests educational forums which enable GEN students to engage in critical dialogue, promote reflective practice and ongoing support are an essential element of GEN curricula. The model of supervision employed was informed by Proctor's three function interactive CS model and Inskipp and Proctor's Supervision Alliance. Both emphasise the normative, formative and restorative functions of CS as task areas within an overarching humanistic supervisory approach. The three-function model informed the design of a questionnaire which intended to measure their importance, impact and influence through both structured and open-ended questions. Findings suggest the restorative function of supervision is most valued and is facilitated in an environment where humanistic principles of non-judgement, empathy and trust are clearly present. Also the opportunity to learn from others, consider alternative perspectives and question personal assumptions regarding capability and confidence are a priority for this student group. It is suggested that the restorative function of CS should be prioritised within future developments and models which view this function as a key purpose of CS should be explored. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quasi-Supervised Scoring of Human Sleep in Polysomnograms Using Augmented Input Variables

PubMed Central

Yaghouby, Farid; Sunderam, Sridhar

2015-01-01

The limitations of manual sleep scoring make computerized methods highly desirable. Scoring errors can arise from human rater uncertainty or inter-rater variability. Sleep scoring algorithms either come as supervised classifiers that need scored samples of each state to be trained, or as unsupervised classifiers that use heuristics or structural clues in unscored data to define states. We propose a quasi-supervised classifier that models observations in an unsupervised manner but mimics a human rater wherever training scores are available. EEG, EMG, and EOG features were extracted in 30s epochs from human-scored polysomnograms recorded from 42 healthy human subjects (18 to 79 years) and archived in an anonymized, publicly accessible database. Hypnograms were modified so that: 1. Some states are scored but not others; 2. Samples of all states are scored but not for transitional epochs; and 3. Two raters with 67% agreement are simulated. A framework for quasi-supervised classification was devised in which unsupervised statistical models—specifically Gaussian mixtures and hidden Markov models—are estimated from unlabeled training data, but the training samples are augmented with variables whose values depend on available scores. Classifiers were fitted to signal features incorporating partial scores, and used to predict scores for complete recordings. Performance was assessed using Cohen's K statistic. The quasi-supervised classifier performed significantly better than an unsupervised model and sometimes as well as a completely supervised model despite receiving only partial scores. The quasi-supervised algorithm addresses the need for classifiers that mimic scoring patterns of human raters while compensating for their limitations. PMID:25679475

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.

A cross-cultural comparison of clinical supervision in South Korea and the United States.

PubMed

Son, Eunjung; Ellis, Michael V

2013-06-01

We investigated similarities and differences in clinical supervision in two cultures: South Korea and the United States The study had two parts: (1) a test of the cross-cultural equivalence of four supervision measures; and (2) a test of two competing models of cultural differences in the relations among supervisory style, role difficulties, supervisory working alliance, and satisfaction with supervision. Participants were 191 South Korean and 187 U.S. supervisees currently engaged in clinical supervision. The U.S. measures demonstrated sufficient measurement equivalence for use in South Korea. Cultural differences moderated the relations among supervisory styles, role difficulties, supervisory working alliance, and supervision satisfaction. Specifically, the relations among these variables were significantly stronger for U.S. than for South Korean supervisees. Implications for theory, research, and practice were discussed.

Post-Disaster Social Justice Group Work and Group Supervision

ERIC Educational Resources Information Center

Bemak, Fred; Chung, Rita Chi-Ying

2011-01-01

This article discusses post-disaster group counseling and group supervision using a social justice orientation for working with post-disaster survivors from underserved populations. The Disaster Cross-Cultural Counseling model is a culturally responsive group counseling model that infuses social justice into post-disaster group counseling and…

Supervised Learning Based Hypothesis Generation from Biomedical Literature.

PubMed

Sang, Shengtian; Yang, Zhihao; Li, Zongyao; Lin, Hongfei

2015-01-01

Nowadays, the amount of biomedical literatures is growing at an explosive speed, and there is much useful knowledge undiscovered in this literature. Researchers can form biomedical hypotheses through mining these works. In this paper, we propose a supervised learning based approach to generate hypotheses from biomedical literature. This approach splits the traditional processing of hypothesis generation with classic ABC model into AB model and BC model which are constructed with supervised learning method. Compared with the concept cooccurrence and grammar engineering-based approaches like SemRep, machine learning based models usually can achieve better performance in information extraction (IE) from texts. Then through combining the two models, the approach reconstructs the ABC model and generates biomedical hypotheses from literature. The experimental results on the three classic Swanson hypotheses show that our approach outperforms SemRep system.

Does power distance exacerbate or mitigate the effects of abusive supervision? It depends on the outcome.

PubMed

Lian, Huiwen; Ferris, D Lance; Brown, Douglas J

2012-01-01

We predicted that the effects of abusive supervision are likely to be moderated by subordinate power distance orientation and that the nature of the moderating effect will depend on the outcome. Drawing upon work suggesting that high power distance orientation subordinates are more tolerant of supervisory mistreatment, we posited that high power distance orientation subordinates would be less likely to view abusive supervision as interpersonally unfair. Drawing upon social learning theory suggestions that high power distance orientation subordinates are more likely to view supervisors as role models, we posited that high power distance orientation subordinates would be more likely to pattern their own interpersonally deviant behavior after that of abusive supervisors. Across 3 samples we found support for our predicted interactions, culminating in a mediated moderation model demonstrating that social learning mediates the interaction of abusive supervision and power distance on subordinate interpersonal deviance, while ruling out alternate self-regulation impairment or displaced aggression explanations. Implications for the abusive supervision literature are discussed.

The Developmental Model of Supervision as Reflected in the Experiences of Field Supervisors and Graduate Students

ERIC Educational Resources Information Center

Everett, Joyce E.; Miehls, Dennis; DuBois, Carolyn; Garran, Ann Marie

2011-01-01

Schools of social work invest an enormous amount of time and money training new field instructors to ensure their ability to help students integrate the knowledge, skill, and values of the profession. Some schools, like the one described here, frame their training in the context of a developmental model of supervision. Such models presume that…

Clinical group supervision for integrating ethical reasoning: Views from students and supervisors.

PubMed

Blomberg, Karin; Bisholt, Birgitta

2016-11-01

Clinical group supervision has existed for over 20 years in nursing. However, there is a lack of studies about the role of supervision in nursing students' education and especially the focus on ethical reasoning. The aim of this study was to explore and describe nursing students' ethical reasoning and their supervisors' experiences related to participation in clinical group supervision. The study is a qualitative interview study with interpretative description as an analysis approach. A total of 17 interviews were conducted with nursing students (n = 12) who had participated in clinical group supervision in their first year of nursing education, and with their supervisors (n = 5). The study was based on the ethical principles outlined in the Declaration of Helsinki, and permission was obtained from the Regional Ethical Review Board in Sweden. The analysis revealed that both the form and content of clinical group supervision stimulated reflection and discussion of handling of situations with ethical aspects. Unethical situations were identified, and the process uncovered underlying caring actions. Clinical group supervision is a model that can be used in nursing education to train ethical reflection and to develop an ethical competence among nursing students. Outcomes from the model could also improve nursing education itself, as well as healthcare organizations, in terms of reducing moral blindness and unethical nursing practice. © The Author(s) 2015.

Thoughts on health supervision: learning-focused primary care.

PubMed

Needlman, Robert

2006-06-01

Primary care clinicians confront a long list of topics that are supposed to be covered during well-child visits, but evidence for the effectiveness of preventive counseling for most issues is limited, and it is doubtful that covering more topics confers correspondingly enhanced clinical benefits. Amid growing professional interest in rethinking primary care, 3 ideas that would facilitate constructive change are proposed. First, face-to-face time between doctors and parents should be allocated as a scarce resource, with priority given to topics that are both important and uniquely responsive to in-office intervention. Second, to maximize the educational value of anticipatory guidance, visits could focus on experiential, as opposed to merely didactic, learning. Finally, recommendations for primary care should be based on evidence, rather than expert opinion. Competing protocols for preventive care ought to be subjected to large-scale, coordinated research. The unit of analysis should be the visit or series of visits, rather than a single intervention. A crucial first step would be the definition of universal outcome measures.

Exploring paraprofessional and classroom factors affecting teacher supervision.

PubMed

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

2018-02-01

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

Primary process and peer consultation: an experiential model to work through countertransference.

PubMed

Markus, Howard E; Cross, Wendi F; Halewski, Paula G; Quallo, Hope; Smith, Sherrie; Sullivan, Marilyn; Sullivan, Peter; Tantillo, Mary

2003-01-01

Various models exist for peer supervision and consultation of group therapy. This article documents the authors' experience using an experiential group consultation of group therapy model that relies on primary process to overcome countertransference dilemmas. A review of group therapy supervision and consultation models is followed by vignettes from the authors' experience. Discussion of the vignettes highlight critical issues in group consultation and expound upon the strengths and challenges of using an experiential model.

An Integrative Social-Cognitive Developmental Model of Supervision for Substance Abuse Counselors-in-Training

ERIC Educational Resources Information Center

Sias, Shari M.; Lambie, Glenn W.

2008-01-01

Substance abuse counselors (SACs) at higher levels of social-cognitive maturity manage complex situations and perform counselor-related tasks more effectively than individuals at lower levels of development. This article presents an integrative clinical supervision model designed to promote the social-cognitive maturity (ego development;…

Clinical Supervision Model in Teaching Practice: Does It Make a Difference in Supervisors' Performance?

ERIC Educational Resources Information Center

Gürsoy, Esim; Kesner, John Edward; Salihoglu, Umut Muharrem

2016-01-01

In search for better practices there has been a plethora of research in preservice teacher training. To contribute to the literature, the current study aims at investigating teacher trainees' and cooperating teachers' views about the performance and contribution of supervisors during teaching practice after using Clinical Supervision Model.…

School Counselor Supervisors' Perceptions of the Discrimination Model of Supervision

ERIC Educational Resources Information Center

Luke, Melissa; Ellis, Michael V.; Bernard, Janine M.

2011-01-01

The authors examined 38 school counselor supervisors' perceptions of the Discrimination Model (DM; Bernard, 1979, 1997) of supervision, replicating and extending Ellis and Dell's (1986) investigation of the DM with mental health counselor supervisors. Participants judged the dissimilarity of each unique combination of roles and foci of the DM. The…

Expert views on clinical supervision: a study based on interviews.

PubMed

Severinsson, E I; Borgenhammar, E V

1997-05-01

Clinical supervision is a didactic process of the purpose of human development and maturity. The aim of this study is to analyse views on clinical supervision held by a number of experts, and to reflect on the effects and value of clinical supervision in relation to public health. Data were collected by interviews and analysed in accordance with the grounded theory construction model. The results showed that clinical supervision is an integration process guiding a person from 'novice to expert' by establishing a relationship of trust between supervisor and supervisee. This study indicates that implementation of systematic clinical supervision may positively affect quality of care, and patients' recovery, create improved feeling of confidence in one's work, and prevent burnout among staff. The negative aspects, as reported, were the possibility of high 'opportunity costs', e.g. the time loss for patient care by those participating in organized systematic supervision. On the other hand, clinical supervision contributes towards more efficient use of resources and hence avoids unnecessary costs. However, neither of these aspects were further elaborated on by the experts but clearly indicate an important field for further research.

A Deep Similarity Metric Learning Model for Matching Text Chunks to Spatial Entities

NASA Astrophysics Data System (ADS)

Ma, K.; Wu, L.; Tao, L.; Li, W.; Xie, Z.

2017-12-01

The matching of spatial entities with related text is a long-standing research topic that has received considerable attention over the years. This task aims at enrich the contents of spatial entity, and attach the spatial location information to the text chunk. In the data fusion field, matching spatial entities with the corresponding describing text chunks has a big range of significance. However, the most traditional matching methods often rely fully on manually designed, task-specific linguistic features. This work proposes a Deep Similarity Metric Learning Model (DSMLM) based on Siamese Neural Network to learn similarity metric directly from the textural attributes of spatial entity and text chunk. The low-dimensional feature representation of the space entity and the text chunk can be learned separately. By employing the Cosine distance to measure the matching degree between the vectors, the model can make the matching pair vectors as close as possible. Mearnwhile, it makes the mismatching as far apart as possible through supervised learning. In addition, extensive experiments and analysis on geological survey data sets show that our DSMLM model can effectively capture the matching characteristics between the text chunk and the spatial entity, and achieve state-of-the-art performance.

Adaptive supervision: a theoretical model for social workers.

PubMed

Latting, J E

1986-01-01

Two models of leadership styles are prominent in the management field: Blake and Mouton's managerial Grid and Hersey and Blanchard's Situational Leadership Model. Much of the research on supervisory styles in social work has been based on the former. A recent public debate between the two sets of theorists suggests that both have strengths and limitations. Accordingly, an adaptive model of social work supervision that combines elements of both theories is proposed.

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns

PubMed Central

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning. PMID:29209191

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

PubMed

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

Interprofessional supervision in an intercultural context: a qualitative study.

PubMed

Chipchase, Lucy; Allen, Shelley; Eley, Diann; McAllister, Lindy; Strong, Jenny

2012-11-01

Our understanding of the qualities and value of clinical supervision is based on uniprofessional clinical education models. There is little research regarding the role and qualities needed in the supervisor role for supporting interprofessional placements. This paper reports the views and perceptions of medical and allied heath students and supervisors on the characteristics of clinical supervision in an interprofessional, international context. A qualitative case study was used involving semi-structured interviews of eight health professional students and four clinical supervisors before and after an interprofessional, international clinical placement. Our findings suggest that supervision from educators whose profession differs from that of the students can be a beneficial and rewarding experience leading to the use of alternative learning strategies. Although all participants valued interprofessional supervision, there was agreement that profession-specific supervision was required throughout the placement. Further research is required to understand this view as interprofessional education aims to prepare graduates for collaborative practice where they may work in teams supervised by staff whose profession may differ from their own.

Pediatric Oncology Branch - training- resident electives | Center for Cancer Research

Cancer.gov

Resident Electives Select pediatric residents may be approved for a 4-week elective rotation at the Pediatric Oncology Branch. This rotation emphasizes the important connection between research and patient care in pediatric oncology. The resident is supervised directly by the Branch’s attending physician and clinical fellows. Residents attend daily in-patient and out-patient rounds, multiple weekly Branch conferences, and are expected to research relevant topics and present a 30-minute talk toward the end of their rotation.

Problematizing Assumptions, Examining Dilemmas, and Exploring Promising Possibilities in Culturally Relevant Pedagogy. A Response to "'I Didn't See It as a Cultural Thing': Supervisors of Student Teachers Define and Describe Culturally Responsive Supervision"

ERIC Educational Resources Information Center

Dantas-Whitney, Maria; Ulveland, R. Dana

2016-01-01

In response to the study and recommendations presented in the article "I Didn't See it as a Cultural Thing," written by Linda Griffin, Dyan Watson and Tonda Liggett, we explore three interrelated topics. First, we seek to problematize some of the assumptions in the study. We review some of the authors' approaches and assertions that seem…

Pediatric Oncology Branch - training- medical student rotations | Center for Cancer Research

Cancer.gov

Medical Student Rotations Select 4th-year medical students may be approved for a 4-week elective rotation at the Pediatric Oncology Branch. This rotation emphasizes the important connection between research and patient care in pediatric oncology. The student is supervised directly by the Branch’s attending physician and clinical fellows. Students attend daily in-patient and out-patient rounds and multiple weekly Branch conferences, and are expected to research relevant topics and present a 30-minute talk near the end of their rotation.

Improving Face Verification in Photo Albums by Combining Facial Recognition and Metadata With Cross-Matching

DTIC Science & Technology

2017-12-01

satisfactory performance. We do not use statistical models, and we do not create patterns that require supervised learning. Our methodology is intended...statistical models, and we do not create patterns that require supervised learning. Our methodology is intended for use in personal digital image...THESIS MOTIVATION .........................................................................19 III. METHODOLOGY

42 CFR § 512.600 - Waiver of direct supervision requirement for certain post-discharge home visits.

Code of Federal Regulations, 2010 CFR

2017-10-01

... & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) HEALTH CARE INFRASTRUCTURE AND MODEL PROGRAMS EPISODE PAYMENT MODEL Waivers § 512.600 Waiver of direct supervision requirement for certain post...-discharge home visits. (c) Payment. Up to the maximum post-discharge home visits for a specific EPM episode...

Reflective Process in Play Therapy: A Practical Model for Supervising Counseling Students

ERIC Educational Resources Information Center

Allen, Virginia B.; Folger, Wendy A.; Pehrsson, Dale-Elizabeth

2007-01-01

Counselor educators and other supervisors, who work with graduate student counseling interns utilizing Play Therapy, should be educated, grounded, and trained in theory, supervision, and techniques specific to Play Therapy. Unfortunately, this is often not the case. Therefore, a three step model was created to assist those who do not have specific…

The Implementation and Evaluation of a Clinical Supervision Model in Teacher Education in Turkey: Is It an Effective Method?

ERIC Educational Resources Information Center

Bulunz, Nermin; Gursoy, Esim; Kesner, John; Baltaci Goktalay, Sehnaz; Salihoglu, Umut M.

2014-01-01

Implementation of the standards established by the Higher Education Council (HEC) has shown great variation between universities, between departments and even between supervisors. A TUBITAK (111K162)-EVRENA project designed to develop a "teaching practice program" using a Clinical Supervision Model (CSM) was conducted. The present study…

A Model for Art Therapy-Based Supervision for End-of-Life Care Workers in Hong Kong.

PubMed

Potash, Jordan S; Chan, Faye; Ho, Andy H Y; Wang, Xiao Lu; Cheng, Carol

2015-01-01

End-of-life care workers and volunteers are particularly prone to burnout given the intense emotional and existential nature of their work. Supervision is one important way to provide adequate support that focuses on both professional and personal competencies. The inclusion of art therapy principles and practices within supervision further creates a dynamic platform for sustained self-reflection. A 6-week art therapy-based supervision group provided opportunities for developing emotional awareness, recognizing professional strengths, securing collegial relationships, and reflecting on death-related memories. The structure, rationale, and feedback are discussed.

Abusive supervision and subordinates' organization deviance.

PubMed

Tepper, Bennett J; Henle, Christine A; Lambert, Lisa Schurer; Giacalone, Robert A; Duffy, Michelle K

2008-07-01

The authors developed an integrated model of the relationships among abusive supervision, affective organizational commitment, norms toward organization deviance, and organization deviance and tested the framework in 2 studies: a 2-wave investigation of 243 supervised employees and a cross-sectional study of 247 employees organized into 68 work groups. Path analytic tests of mediated moderation provide support for the prediction that the mediated effect of abusive supervision on organization deviance (through affective commitment) is stronger when employees perceive that their coworkers are more approving of organization deviance (Study 1) and when coworkers perform more acts of organization deviance (Study 2).

The Marine Fire Support Team as a Model for Distributed Operations Analysis: Review of Prior Analyses, Summary of Ongoing Research, and Recommendations for Future Work

DTIC Science & Technology

2008-07-17

without excessive procrastination ; to work independently and accomplish tasks without constant supervision; to take personal responsibility for completing...difficult tasks without excessive procrastination ; to work independently and accomplish tasks without constant supervision; to take personal...tasks without excessive procrastination ; to work independently and accomplish tasks without constant supervision; to take personal responsibility for

Rethinking Resident Supervision to Improve Safety: From Hierarchical to Interprofessional Models

PubMed Central

Tamuz, Michal; Giardina, Traber Davis; Thomas, Eric J.; Menon, Shailaja; Singh, Hardeep

2011-01-01

Background Inadequate supervision is a significant contributing factor to medical errors involving trainees but supervision in high-risk settings such as the Intensive Care Unit (ICU) is not well studied. Objective We explored how residents in the ICU experienced supervision related to medication safety not only from supervising physicians but also from other professionals. Design, Setting, Measurements Using qualitative methods, we examined in-depth interviews with 17 residents working in ICUs of three tertiary-care hospitals. We analyzed residents' perspectives on receiving and initiating supervision from physicians within the traditional medical hierarchy and from other professionals, including nurses, staff pharmacists and clinical pharmacists (“interprofessional supervision”). Results While initiating their own supervision within the traditional hierarchy, residents believed in seeking assistance from fellows and attendings and articulated rules of thumb for doing so; however, they also experienced difficulties. Some residents were concerned that their questions would reflect poorly on them; others were embarrassed by their mistaken decisions. Conversely, residents described receiving interprofessional supervision from nurses and pharmacists, who proactively monitored, intervened in, and guided residents' decisions. Residents relied on nurses and pharmacists for non-judgmental answers to their queries, especially after-hours. To enhance both types of supervision, residents emphasized the importance of improving interpersonal communication skills. Conclusions Residents depended on interprofessional supervision when making decisions regarding medications in the ICU. Improving interprofessional supervision, which thus far has been under-recognized and underemphasized in graduate medical education, can potentially improve medication safety in high-risk settings. PMID:21990173

[Use of dental hygienists in caries prevention].

PubMed

Morch; Barman, O

1976-09-01

Two caries preventive programs were carried out in the Bergen School Dental Service in order to test various modes of topical application of fluorides and the efficacy of using dental hygienists in the delivery of preventive dental care to school children. In the first program, starting in 1951, A 2% netutral sodium fluoride solution was applied topically four times during one month to one quadrant of the maxillary teeth, the other quadrant serving as control. This series of application was repeated one year later, while the caries registration was followed up until 1956. The results are given in Table 1, comprising 128 children who were 11-12 years old at the start of the study and were still present at the same schools in 1956. A reduction in caries incidence of about 25 per cent was obtained during the five years period. In the second program, beginning in 1963, acid stannous hexafluoride as well as neutral sodium fluoride solutions were used separately in groups of children (7-11 years of age). The total number of children was about 2000. Two groups received four topical applications annually within one month, while in two oher groups the applications were given twice a year. This topical application program was continued for four years. For several reasons pure control groups of children of corresponding age could not be established. Instead the treated groups were compared with children who under supervision brushed their teeth (already from 1964) with 0.5% neutral sodium fluoride solutions five times per year during the school hours. All children received appropriate information and motivation for improved oral hygiene and food habits by the dental hygienists individually in the treated groups and in groups in the comparison group. The results are given in Table 2. The caries reduction obtained per year reached maximally about 40 per cent. This investigation shows that dental hygienists are able to carry out valuable caries preventive work at dental clinics, and it is justified to assign this type of health personnel to separate caries preventive tasks which require little supervision time from the responsible dentists.

Semi-supervised Learning for Phenotyping Tasks.

PubMed

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

2015-01-01

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

A Model Plan for the Supervision and Evaluation of Therapy Services in Educational Settings. TIES: Therapy in Educational Settings.

ERIC Educational Resources Information Center

Reed, Penny; And Others

The manual serves as a model for school districts developing procedures for supervising and evaluating their therapy services. The narrative is addressed to therapists rather than supervisors so that school districts can photocopy or adapt sections of the manual and assemble customized manuals for therapists in their programs. The first chapter,…

Deep Visual Attention Prediction

NASA Astrophysics Data System (ADS)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

A Multimodal Approach to Counselor Supervision.

ERIC Educational Resources Information Center

Ponterotto, Joseph G.; Zander, Toni A.

1984-01-01

Represents an initial effort to apply Lazarus's multimodal approach to a model of counselor supervision. Includes continuously monitoring the trainee's behavior, affect, sensations, images, cognitions, interpersonal functioning, and when appropriate, biological functioning (diet and drugs) in the supervisory process. (LLL)

Cost and resource implications of clinical supervision in nursing: an Australian perspective.

PubMed

White, Edward; Winstanley, Julie

2006-11-01

The aim of this article was to explore the resource and management issues in introducing and maintaining a clinical supervision programme for nurses. A number of federal, state and non-governmental agency reports have recently indicted the quality of present-day mental health service provision in Australia. Clinical supervision in nursing has been widely embraced in many parts of the developed world, as a positive contribution to the clinical governance agenda, but remains largely underdeveloped in Australia. Using data derived from several empirical clinical supervision research studies conducted in mental health nursing settings, preliminary financial modelling has provided new information for Nurse Managers, about the material implications of implementing clinical supervision. It is suggested that, on average, the cost of giving peer group one-to-one supervision to any nurse represented about 1% of an annual salary. When interpreted as a vanishingly small cap on clinical nursing practice necessary to reap demonstrable benefits, it behoves Nurse Managers to comprehend clinical supervision as bona fide nursing work, not an activity which is separate from nursing work.

Supervised Learning Using Spike-Timing-Dependent Plasticity of Memristive Synapses.

PubMed

Nishitani, Yu; Kaneko, Yukihiro; Ueda, Michihito

2015-12-01

We propose a supervised learning model that enables error backpropagation for spiking neural network hardware. The method is modeled by modifying an existing model to suit the hardware implementation. An example of a network circuit for the model is also presented. In this circuit, a three-terminal ferroelectric memristor (3T-FeMEM), which is a field-effect transistor with a gate insulator composed of ferroelectric materials, is used as an electric synapse device to store the analog synaptic weight. Our model can be implemented by reflecting the network error to the write voltage of the 3T-FeMEMs and introducing a spike-timing-dependent learning function to the device. An XOR problem was successfully demonstrated as a benchmark learning by numerical simulations using the circuit properties to estimate the learning performance. In principle, the learning time per step of this supervised learning model and the circuit is independent of the number of neurons in each layer, promising a high-speed and low-power calculation in large-scale neural networks.

Muscular dystrophy summer camp: a case study of a non-traditional level I fieldwork using a collaborative supervision model.

PubMed

Provident, Ingrid M; Colmer, Maria A

2013-01-01

A shortage of traditional medical fieldwork placements has been reported in the United States. Alternative settings are being sought to meet the Accreditation Standards for Level I fieldwork. This study was designed to examine and report the outcomes of an alternative pediatric camp setting, using a group model of supervision to fulfill the requirements for Level I fieldwork. Thirty-seven students from two Pennsylvania OT schools. Two cohorts of students were studied over a two year period using multiple methods of retrospective review and data collection. Students supervised in a group model experienced positive outcomes, including opportunities to deliver client centered care, and understanding the role of caregiving for children with disabilities. The use of a collaborative model of fieldwork education at a camp setting has resulted in a viable approach for the successful attainment of Level I fieldwork objectives for multiple students under a single supervisor.

Extracting PICO Sentences from Clinical Trial Reports using Supervised Distant Supervision

PubMed Central

Wallace, Byron C.; Kuiper, Joël; Sharma, Aakash; Zhu, Mingxi (Brian); Marshall, Iain J.

2016-01-01

Systematic reviews underpin Evidence Based Medicine (EBM) by addressing precise clinical questions via comprehensive synthesis of all relevant published evidence. Authors of systematic reviews typically define a Population/Problem, Intervention, Comparator, and Outcome (a PICO criteria) of interest, and then retrieve, appraise and synthesize results from all reports of clinical trials that meet these criteria. Identifying PICO elements in the full-texts of trial reports is thus a critical yet time-consuming step in the systematic review process. We seek to expedite evidence synthesis by developing machine learning models to automatically extract sentences from articles relevant to PICO elements. Collecting a large corpus of training data for this task would be prohibitively expensive. Therefore, we derive distant supervision (DS) with which to train models using previously conducted reviews. DS entails heuristically deriving ‘soft’ labels from an available structured resource. However, we have access only to unstructured, free-text summaries of PICO elements for corresponding articles; we must derive from these the desired sentence-level annotations. To this end, we propose a novel method – supervised distant supervision (SDS) – that uses a small amount of direct supervision to better exploit a large corpus of distantly labeled instances by learning to pseudo-annotate articles using the available DS. We show that this approach tends to outperform existing methods with respect to automated PICO extraction. PMID:27746703

Oceans apart, yet connected: Findings from a qualitative study on professional supervision in rural and remote allied health services

PubMed Central

Martin, Priya; Kumar, Saravana; Burge, Vanessa; Abernathy, LuJuana

2015-01-01

Abstract Objective Improving the quality and safety of health care in Australia is imperative to ensure the right treatment is delivered to the right person at the right time. Achieving this requires appropriate clinical governance and support for health professionals, including professional supervision. This study investigates the usefulness and effectiveness of and barriers to supervision in rural and remote Queensland. Design As part of the evaluation of the Allied Health Rural and Remote Training and Support program, a qualitative descriptive study was conducted involving semi‐structured interviews with 42 rural or remote allied health professionals, nine operational managers and four supervisors. The interviews explored perspectives on their supervision arrangements, including the perceived usefulness, effect on practice and barriers. Results Themes of reduced isolation; enhanced professional enthusiasm, growth and commitment to the organisation; enhanced clinical skills, knowledge and confidence; and enhanced patient safety were identified as perceived outcomes of professional supervision. Time, technology and organisational factors were identified as potential facilitators as well as potential barriers to effective supervision. Conclusions This research provides current evidence on the impact of professional supervision in rural and remote Queensland. A multidimensional model of organisational factors associated with effective supervision in rural and remote settings is proposed identifying positive supervision culture and a good supervisor–supervisee fit as key factors associated with effective arrangements. PMID:26052949

When Distress Hits Home: The Role of Contextual Factors and Psychological Distress in Predicting Employees' Responses to Abusive Supervision

ERIC Educational Resources Information Center

Restubog, Simon Lloyd D.; Scott, Kristin L.; Zagenczyk, Thomas J.

2011-01-01

We developed a model of the relationships among aggressive norms, abusive supervision, psychological distress, family undermining, and supervisor-directed deviance. We tested the model in 2 studies using multisource data: a 3-wave investigation of 184 full-time employees (Study 1) and a 2-wave investigation of 188 restaurant workers (Study 2).…

Psychological mechanism linking abusive supervision and compulsory citizenship behavior: a moderated mediation study.

PubMed

Zhao, Hongdan; Peng, Zhenglong; Han, Yong; Sheard, Geoff; Hudson, Alan

2013-01-01

This study seeks to examine the effect of abusive supervision on the "dark side" of organizational citizenship behavior (OCB) and, specifically, compulsory citizenship behavior (CCB). The study focuses on the mediating role of psychological safety underpinning the relationship between abusive supervision and CCB, and the moderating role of Chinese traditionality in influencing the mediation. The authors tested the model with data of 434 dyads (employee-coworker pairs) in a large Chinese service company. Results indicated that psychological safety fully mediated the relationship between abusive supervision and CCB. The authors also found that Chinese traditionality moderated the strength of the mediated relationship between abusive supervision and CCB via psychological safety, such that the mediated relationship is weaker under high Chinese traditionality than under low Chinese traditionality. The article also discusses the implications, limitations, and future research directions.

Participant supervision: supervisor and supervisee experiences of cotherapy.

PubMed

Falke, Stephanie I; Lawson, Lindsey; Pandit, Mayuri L; Patrick, Elizabeth A

2015-04-01

Participant supervision is a unique application of live supervision in which a supervisor and supervisee see clients conjointly. Although minimally discussed in the family therapy literature, it has notable advantages, chief among them being a shared clinical experience that increases attunement to supervisee skill and development, the modeling of skillful intervention, and a higher degree of collegiality. However, it is not without its challenges, including supervisee vulnerability and anxiety, diffusion of responsibility, and limited time for case discussion. This article highlights the experience of one supervisor and three doctoral-level supervisees engaging in participant supervision over the course of a 2-year period. Using illustrative examples, we discuss our experience of the advantages and challenges of participant supervision, and provide recommendations for establishing a collaborative relational context within which supervisory benefits can be maximized. © 2013 American Association for Marriage and Family Therapy.

Public health nurses' supervision of clients in Norway.

PubMed

Tveiten, S; Severinsson, E

2005-09-01

The aim of this study was to explore and describe what public health nurses (PHNs) understand by client supervision and how they perform it. The main principles of the health promotion discourse initiated by the World Health Organization (WHO) over the last 20-30 years are client participation and the view of the client as expert. Supervision is one relevant intervention strategy in the empowerment process, in which these principles play a central role. There is a lack of research pertaining to the intervention models employed by PHNs. Twenty-three transcribed audiotaped dialogues between PHNs and their clients were analysed by means of qualitative content analysis. What the PHNs understand by supervision and how they perform it can be described by three themes: continuity in relationships and reflexivity in the supervision approach, communicating with the client about his/her needs, problems and worries; and the organization of client supervision. The PHNs in this study understand client supervision as communication and relationships with clients on the subject of a healthy lifestyle, child development and coping with everyday life. The PHNs' approach to client supervision seemed to include aspects of empowerment by means of client participation and the view of the client as expert. However, the PHNs themselves had an expert role.

Factors associated with adverse clinical outcomes among obstetric trainees

PubMed Central

Aiken PhD, Catherine E.; Aiken, Abigail; Park, Hannah; Brockelsby, Jeremy C.; Prentice, Andrew

2016-01-01

Objective To determine whether UK obstetric trainees transitioning from directly to indirectly-supervised practice have a higher likelihood of adverse patient outcomes from operative deliveries compared to other indirectly supervised trainees and to examine whether performing more procedures under direct supervision is associated with fewer adverse outcomes in initial indirect practice. Methods We examined all deliveries (13,861) conducted by obstetricians at a single centre over 5 years (2008-2013). Mixed-effects logistic regression models were used to compare estimated blood loss, maternal trauma, umbilical arterial pH, delayed neonatal respiration, failed instrumental delivery, and critical incidents for trainees in their first indirectly-supervised year with trainees in all other years of indirect practice. Outcomes for trainees in their first indirectly-supervised 3 months were compared to their outcomes for the remainder of the year. Linear regression was used to examine the relationship between number of procedures performed under direct supervision and initial outcomes under indirect supervision. Results Trainees in their first indirectly-supervised year had a higher likelihood of >2 litres estimated blood loss at any delivery (OR 1.32;CI(1.01-1.64) p<0.05) and of failed instrumental delivery (OR 2.33;CI(1.37-3.29) p<0.05) compared with other indirectly-supervised trainees. Other measured outcomes showed no significant differences. Within the first three months of indirect supervision, the likelihood of operative vaginal deliveries with >1litre estimated blood loss (OR 2.54;CI(1.88-3.20) p<0.05) was higher compared to the remainder of the first year. Performing more deliveries under direct supervision prior to beginning indirectly-supervised training was associated with decreased risk of >1litre estimated blood loss (p<0.05). Conclusions Obstetric trainees in their first year of indirectly-supervised practice have a higher likelihood of immediate adverse delivery outcomes, which are primarily maternal rather than neonatal. Undertaking more directly supervised procedures prior to transitioning to indirectly-supervised practice may reduce adverse outcomes, suggesting that experience is a key consideration in obstetric training programme design. PMID:26077215

Reflective Supervision: A Clinical Supervision Model for Fostering Professional Growth

ERIC Educational Resources Information Center

Costello, Lisa H.; Belcaid, Erin; Arthur-Stanley, Amanda

2018-01-01

School psychologists experience a broad range of stressors in their role as school support professionals including feelings of isolation, insufficient resources, administrative pressures, and excessive caseloads (Boccio, Wiesz, & Lefkowitz, 2016). Ongoing support is necessary to help school psychologists successfully navigate these…

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

PubMed

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

2015-08-13

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

Essentials of Pediatric Emergency Medicine Fellowship: Part 6: Program Administration.

PubMed

Kim, In K; Zuckerbraun, Noel; Kou, Maybelle; Vu, Tien; Levasseur, Kelly; Yen, Kenneth; Chapman, Jennifer; Doughty, Cara; McAneney, Constance; Zaveri, Pavan; Hsu, Deborah

2016-10-01

This article is the sixth in a 7-part series that aims to comprehensively describe the current state and future directions of pediatric emergency medicine (PEM) fellowship training from the essential requirements to considerations for successfully administering and managing a program to the careers that may be anticipated upon program completion. This article provides a broad overview of administering and supervising a PEM fellowship program. It explores 3 topics: the principles of program administration, committee management, and recommendations for minimum time allocated for PEM fellowship program directors to administer their programs.

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.

Improving performance through concept formation and conceptual clustering

NASA Technical Reports Server (NTRS)

Fisher, Douglas H.

1992-01-01

Research from June 1989 through October 1992 focussed on concept formation, clustering, and supervised learning for purposes of improving the efficiency of problem-solving, planning, and diagnosis. These projects resulted in two dissertations on clustering, explanation-based learning, and means-ends planning, and publications in conferences and workshops, several book chapters, and journals; a complete Bibliography of NASA Ames supported publications is included. The following topics are studied: clustering of explanations and problem-solving experiences; clustering and means-end planning; and diagnosis of space shuttle and space station operating modes.

Surviving an abusive supervisor: the joint roles of conscientiousness and coping strategies.

PubMed

Nandkeolyar, Amit K; Shaffer, Jonathan A; Li, Andrew; Ekkirala, Srinivas; Bagger, Jessica

2014-01-01

The present study examines a mediated moderation model of the effects of conscientiousness and coping strategies on the relationship between abusive supervision and employees' job performance. Across 2 studies conducted in India, we found evidence that the relationship between abusive supervision and job performance was weaker when employees were high in conscientiousness. In addition, we found that the use of an avoidance coping strategy facilitated a negative relationship between abusive supervision and performance. Finally, we found that the moderating effects of conscientiousness were mediated by the use of avoidance coping strategies. Our findings contribute to theories of abusive supervision, personality, coping strategies, and job performance. PsycINFO Database Record (c) 2014 APA, all rights reserved

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.

Clinical education and training of student nurses in four moderately new European Union countries: Assessment of students' satisfaction with the learning environment.

PubMed

Antohe, Ileana; Riklikiene, Olga; Tichelaar, Erna; Saarikoski, Mikko

2016-03-01

Nurses underwent different models of education during various historical periods. The recent decade in Europe has been marked with educational transitions for the nursing profession related to Bologna Declaration and enlargement of the European Union. This paper aims to explore the situation of clinical placements for student nurses and assess students' satisfaction with the learning environment in four relatively new member states of European Union: the Czech Republic, Hungary, Lithuania and Romania. The data for cross-sectional quantitative study were collected during the exploratory phase of EmpNURS Project via a web based questionnaire which utilized a part of Clinical Learning Environment scale (CLES + T). The students evaluated their clinical learning environment mainly positively. The students' utter satisfaction with their clinical placements reached a high level and strongly correlated with the supervisory model. Although the commonest model for supervision was traditional group supervision, the most satisfied students had the experience of individualised supervision. The study gives a picture of the satisfaction of students with the learning environment and, moreover, with clinical placement education of student nurses in four EU countries. The results highlight the individualized supervision model as a crucial factor of students' total satisfaction during their clinical training periods. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Quality of clinical supervision and counselor emotional exhaustion: the potential mediating roles of organizational and occupational commitment.

PubMed

Knudsen, Hannah K; Roman, Paul M; Abraham, Amanda J

2013-01-01

Counselor emotional exhaustion has negative implications for treatment organizations as well as the health of counselors. Quality clinical supervision is protective against emotional exhaustion, but research on the mediating mechanisms between supervision and exhaustion is limited. Drawing upon data from 934 counselors affiliated with treatment programs in the National Institute on Drug Abuse's Clinical Trials Network (CTN), this study examined commitment to the treatment organization and commitment to the counseling occupation as potential mediators of the relationship between quality clinical supervision and emotional exhaustion. The final ordinary least squares (OLS) regression model, which accounted for the nesting of counselors within treatment organizations, indicated that these two types of commitment were plausible mediators of the association between clinical supervision and exhaustion. Higher quality clinical supervision was strongly correlated with commitment to the treatment organization as well as commitment to the occupation of SUD counseling. These findings suggest that quality clinical supervision has the potential to yield important benefits for counselor well-being by strengthening ties to both their employing organization as well the larger treatment field, but longitudinal research is needed to establish these causal relationships. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed Central

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. PMID:26605337

Parental supervision and alcohol use in adolescence: developmentally specific interactions.

PubMed

Clark, Duncan B; Kirisci, Levent; Mezzich, Ada; Chung, Tammy

2008-08-01

While parental supervision has been demonstrated to predict adolescent alcohol involvement, there has been little focus on the influence of adolescent characteristics, such as personality and alcohol use, on the effectiveness of parental supervisory practices. This study examined the interaction of parental supervision and adolescent alcohol use from late childhood through middle adolescence. Families were recruited through fathers with substance use disorders or fathers representing reference groups identified as having a biological child age 10 to 12 years. These children (N = 773) were assessed and follow-up visits conducted in early adolescence (ages 12-14) and middle adolescence (age 16). Parental supervision and alcohol use were determined at each visit. In the context of demographic variables and childhood psychological dysregulation, the statistical model examined global and developmental stage-specific relationships between supervision and alcohol use. Consistent with interactional hypotheses, childhood psychological dysregulation and early adolescent alcohol use predicted less effective parental supervision. While the study design limited the extent to which predictive associations could be interpreted as indicating causal relationships, adolescents with psychological dysregulation and higher levels of alcohol use may resist parental supervision. The challenges to parents presented by difficult adolescents need to be taken into consideration in developing preventive and treatment interventions.

Quality of clinical supervision and counselor emotional exhaustion: The potential mediating roles of organizational and occupational commitment

PubMed Central

Knudsen, Hannah K.; Roman, Paul M.; Abraham, Amanda J.

2013-01-01

Counselor emotional exhaustion has negative implications for treatment organizations as well as the health of counselors. Quality clinical supervision is protective against emotional exhaustion, but research on the mediating mechanisms between supervision and exhaustion is limited. Drawing upon data from 934 counselors affiliated with treatment programs in the National Institute on Drug Abuse’s Clinical Trials Network (CTN), this study examined commitment to the treatment organization and commitment to the counseling occupation as potential mediators of the relationship between quality clinical supervision and emotional exhaustion. The final ordinary least squares (OLS) regression model, which accounted for the nesting of counselors within treatment organizations, indicated that these two types of commitment were plausible mediators of the association between clinical supervision and exhaustion. Higher quality clinical supervision was strongly correlated with commitment to the treatment organization as well as commitment to the occupation of SUD counseling. These findings suggest that quality clinical supervision has the potential to yield important benefits for counselor well-being by strengthening ties to both their employing organization as well the larger treatment field, but longitudinal research is needed to establish these causal relationships. PMID:23312873

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.

Particle Theory & Cosmology

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

Shafi, Qaisar; Barr, Steven; Gaisser, Thomas

1. Executive Summary (April 1, 2012 - March 31, 2015) Title: Particle Theory, Particle Astrophysics and Cosmology Qaisar Shafi University of Delaware (Principal Investigator) Stephen M. Barr, University of Delaware (Co-Principal Investigator) Thomas K. Gaisser, University of Delaware (Co-Principal Investigator) Todor Stanev, University of Delaware (Co-Principal Investigator) The proposed research was carried out at the Bartol Research included Professors Qaisar Shafi Stephen Barr, Thomas K. Gaisser, and Todor Stanev, two postdoctoral fellows (Ilia Gogoladze and Liucheng Wang), and several graduate students. Five students of Qaisar Shafi completed their PhD during the period August 2011 - August 2014. Measures of themore » group’s high caliber performance during the 2012-2015 funding cycle included pub- lications in excellent refereed journals, contributions to working groups as well as white papers, and conference activities, which together provide an exceptional record of both individual performance as well as overall strength. Another important indicator of success is the outstanding quality of the past and current cohort of graduate students. The PhD students under our supervision regularly win the top departmental and university awards, and their publications records show excellence both in terms of quality and quantity. The topics covered under this grant cover the frontline research areas in today’s High Energy Theory & Phenomenology. For Professors Shafi and Barr they include LHC related topics including supersymmetry, collider physics, fl vor physics, dark matter physics, Higgs boson and seesaw physics, grand unifi and neutrino physics. The LHC two years ago discovered the Standard Model Higgs boson, thereby at least partially unlocking the secrets behind electroweak symmetry breaking. We remain optimistic that new and exciting physics will be found at LHC 14, which explain our focus on physics beyond the Standard Model. Professors Shafi continued his investigations in cosmology, specifically on supergravity and GUT infl models, primordial gravity waves, dark matter models. The origin of baryon and dark matter in the universe has been explored by Professors Barr and Shafi The research program of Professors Gaisser and Stanev address current research topics in Particle Astrophysics, in particular atmospheric and cosmogenic neutrinos and ultra-high energy cosmic rays. Work also included use of LHC data to improve tools for interpreting cascades generated in the atmosphere by high-energy particles from the cosmos. Cosmogenic neutrinos produced by interactions of ultra-high energy cosmic rays as they propagate through the cosmic microwave background radiation provides insight into the origin of the highest energy particles in nature. Overall, the research covered topics in the energy, cosmic and intensity frontiers.« less

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

A Customized Attention-Based Long Short-Term Memory Network for Distant Supervised Relation Extraction.

PubMed

He, Dengchao; Zhang, Hongjun; Hao, Wenning; Zhang, Rui; Cheng, Kai

2017-07-01

Distant supervision, a widely applied approach in the field of relation extraction can automatically generate large amounts of labeled training corpus with minimal manual effort. However, the labeled training corpus may have many false-positive data, which would hurt the performance of relation extraction. Moreover, in traditional feature-based distant supervised approaches, extraction models adopt human design features with natural language processing. It may also cause poor performance. To address these two shortcomings, we propose a customized attention-based long short-term memory network. Our approach adopts word-level attention to achieve better data representation for relation extraction without manually designed features to perform distant supervision instead of fully supervised relation extraction, and it utilizes instance-level attention to tackle the problem of false-positive data. Experimental results demonstrate that our proposed approach is effective and achieves better performance than traditional methods.

Maintaining professional resilience through group restorative supervision.

PubMed

Wallbank, Sonya

2013-08-01

Restorative clinical supervision has been delivered to over 2,500 professionals and has shown to be highly effective in reducing burnout, stress and increasing compassion satisfaction. Demand for the programme has shown that a sustainable model of implementation is needed for organisations who may not be able to invest in continued individual sessions. Following the initial six sessions, group restorative supervision has been developed and this paper reports on the programme's success in maintaining and continuing to improve compassion satisfaction, stress and burnout through the process of restorative group supervision. This means that organisations can continue to maintain the programme once the initial training has been completed and have confidence within the restorative group supervision to support professionals in managing the emotional demands of their role. The restorative groups have also had inadvertent positive benefits in workplace functioning. The paper outlines how professionals have been able to use this learning to support them in being more effective.

Oceans apart, yet connected: Findings from a qualitative study on professional supervision in rural and remote allied health services.

PubMed

Ducat, Wendy; Martin, Priya; Kumar, Saravana; Burge, Vanessa; Abernathy, LuJuana

2016-02-01

Improving the quality and safety of health care in Australia is imperative to ensure the right treatment is delivered to the right person at the right time. Achieving this requires appropriate clinical governance and support for health professionals, including professional supervision. This study investigates the usefulness and effectiveness of and barriers to supervision in rural and remote Queensland. As part of the evaluation of the Allied Health Rural and Remote Training and Support program, a qualitative descriptive study was conducted involving semi-structured interviews with 42 rural or remote allied health professionals, nine operational managers and four supervisors. The interviews explored perspectives on their supervision arrangements, including the perceived usefulness, effect on practice and barriers. Themes of reduced isolation; enhanced professional enthusiasm, growth and commitment to the organisation; enhanced clinical skills, knowledge and confidence; and enhanced patient safety were identified as perceived outcomes of professional supervision. Time, technology and organisational factors were identified as potential facilitators as well as potential barriers to effective supervision. This research provides current evidence on the impact of professional supervision in rural and remote Queensland. A multidimensional model of organisational factors associated with effective supervision in rural and remote settings is proposed identifying positive supervision culture and a good supervisor-supervisee fit as key factors associated with effective arrangements. © 2015 Commonwealth of Australia. Australian Journal of Rural Health published by Wiley Publishing Asia Pty Ltd. on behalf of National Rural Health Alliance Inc.

Relieving the Bottleneck: An Investigation of Barriers to Expansion of Supervision Networks at Genetic Counseling Training Programs.

PubMed

Berg, Jordan; Hoskovec, Jennifer; Hashmi, S Shahrukh; McCarthy Veach, Patricia; Ownby, Allison; Singletary, Claire N

2018-02-01

Rapid growth in the demand for genetic counselors has led to a workforce shortage. There is a prevailing assumption that the number of training slots for genetic counseling students is linked to the availability of clinical supervisors. This study aimed to determine and compare barriers to expansion of supervision networks at genetic counseling training programs as perceived by supervisors, non-supervisors, and Program Directors. Genetic counselors were recruited via National Society of Genetic Counselors e-blast; Program Directors received personal emails. Online surveys were completed by 216 supervisors, 98 non-supervisors, and 23 Program Directors. Respondents rated impact of 35 barriers; comparisons were made using Kruskal-Wallis and Wilcoxon ranked sum tests. Half of supervisors (51%) indicated willingness to increase supervision. All non-supervisors were willing to supervise. However, all agreed that being too busy impacted ability to supervise, highlighted by supervisors' most impactful barriers: lack of time, other responsibilities, intensive nature of supervision, desire for breaks, and unfilled positions. Non-supervisors noted unique barriers: distance, institutional barriers, and non-clinical roles. Program Directors' perceptions were congruent with those of genetic counselors with three exceptions they rated as impactful: lack of money, prefer not to supervise, and never been asked. In order to expand supervision networks and provide comprehensive student experiences, the profession must examine service delivery models to increase workplace efficiency, reconsider the supervision paradigm, and redefine what constitutes a countable case or place value on non-direct patient care experiences.

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

Surgical resident supervision in the operating room and outcomes of care in Veterans Affairs hospitals.

PubMed

Itani, Kamal M F; DePalma, Ralph G; Schifftner, Tracy; Sanders, Karen M; Chang, Barbara K; Henderson, William G; Khuri, Shukri F

2005-11-01

There has been concern that a reduced level of surgical resident supervision in the operating room (OR) is correlated with worse patient outcomes. Until September 2004, Veterans' Affairs (VA) hospitals entered in the surgical record level 3 supervision on every surgical case when the attending physician was available but not physically present in the OR or the OR suite. In this study, we assessed the impact of level 3 on risk-adjusted morbidity and mortality in the VA system. Surgical cases entered into the National Surgical Quality Improvement Program database between 1998 and 2004, from 99 VA teaching facilities, were included in a logistic regression analysis for each year. Level 3 versus all other levels of supervision were forced into the model, and patient characteristics then were selected stepwise to arrive at a final model. Confidence limits for the odds ratios were calculated by profile likelihood. A total of 610,660 cases were available for analysis. Thirty-day mortality and morbidity rates were reported in 14,441 (2.36%) and 63,079 (10.33%) cases, respectively. Level 3 supervision decreased from 8.72% in 1998 to 2.69% in 2004. In the logistic regression analysis, the odds ratios for mortality for level 3 ranged from .72 to 1.03. Only in the year 2000 were the odds ratio for mortality statistically significant at the .05 level (odds ratio, .72; 95% confidence interval, .594-.858). For morbidity, the odds ratios for level 3 supervision ranged from .66 to 1.01, and all odds ratios except for the year 2004 were statistically significant. Between 1998 and 2004, the level of resident supervision in the OR did not affect clinical outcomes adversely for surgical patients in the VA teaching hospitals.

Supervision--growing and building a sustainable general practice supervisor system.

PubMed

Thomson, Jennifer S; Anderson, Katrina J; Mara, Paul R; Stevenson, Alexander D

2011-06-06

This article explores various models and ideas for future sustainable general practice vocational training supervision in Australia. The general practitioner supervisor in the clinical practice setting is currently central to training the future general practice workforce. Finding ways to recruit, retain and motivate both new and experienced GP teachers is discussed, as is the creation of career paths for such teachers. Some of the newer methods of practice-based teaching are considered for further development, including vertically integrated teaching, e-learning, wave consulting and teaching on the run, teaching teams and remote teaching. Approaches to supporting and resourcing teaching and the required infrastructure are also considered. Further research into sustaining the practice-based general practice supervision model will be required.

Intervention Strategies in Counselor Supervision.

ERIC Educational Resources Information Center

West, John; Sonstegard, Manford

This paper contains a model for practicum supervision developed by Dr. Manford Sonstegard. The procedure allows the supervisor, student-counselor, client, and practicum class to participate in the session. Whereas one-way mirrors, audio tapes and audio-visual tapes allow for only delayed feedback from the supervisor, Dr. Sonstegard's approach…

New graduate transition to practice: how can the literature inform support strategies?

PubMed

Moores, Alis; Fitzgerald, Cate

2017-07-01

Objective The transition to practice for new graduate health professionals has been identified as challenging, with health services typically adopting a range of support and management strategies to assist safe professional practice. Queensland's state-wide Occupational Therapy Clinical Education Program supporting new graduates within public sector health facilities conducted a narrative literature review to identify evidence-based recommended actions that would assist new graduate occupational therapists' to transition from student to practitioner. Method Searches of Medline, CINAHL and PubMed databases were used to locate articles describing or evaluating occupational therapy new graduate support actions. Results The themes of supervision, support and education emerged from the literature. Additionally, four interactions were identified as factors potentially influencing and being influenced by the processes and outcomes of supervision, support and education actions. The interactions identified were professional reasoning, professional identity, an active approach to learning and reflective practice. Conclusions The interactions emerging from the literature will serve to inform the delivery and focus of supervision, support and education for new graduate occupational therapists as they transition to practice. The results may have application for other health professions. What is known about the topic? The transition to practice for new graduate occupational therapists has been reported as challenging with health services implementing various actions to support and assist this transition. A previous literature review of recommended support strategies could not be found providing an impetus for this enquiry. What does this paper add? This narrative literature review identified three themes of actions supporting the transition of new graduates from student to practitioner. In addition to these themes of supervision, support and education, also emerging from the literature were factors identified as important to facilitating the transition of new graduates to the workplace. These factors, or interactions, are identified in this paper as professional reasoning, professional identity, an active approach to learning, and reflective practice. It is proposed that these interactions have an effect on and can be effected by supervision, support and education actions. The articulation between the interactions and the themes was a notable outcome emerging from this literature review. What are the implications for practitioners? This literature review will assist those planning actions to guide new graduates' transition into practice. It is proposed that the methods of implementing supervision, support and education actions are optimised by the identified interactions.

Training for Leadership Roles in Academic Medicine: Opportunities for Psychologists in the AAMC LEAD Program.

PubMed

LaPaglia, Donna; Thompson, Britta; Hafler, Janet; Chauvin, Sheila

2017-06-01

Psychologists' roles within academic medicine have expanded well beyond research and scholarship. They are active as providers of patient care, medical education, and clinical supervision. Although the number of psychologists in academic health centers continues to grow, they represent a small portion of total medical school faculties. However, with the movement toward collaborative care models, emphasis on interprofessional teams, and increased emphasis on psychological science topics in medical curricula, psychologists are well-positioned to make further contributions. Another path through which psychologists can further increase their contributions and value within academic health centers is to aspire to leadership roles. This article describes the first author's reflections on her experiences in a two-year, cohort-based, educational leadership development certificate program in academic medicine. The cohort was comprised largely of physicians and basic scientists, and a small number of non-physician participants of which the first author was the only clinical psychologist. The insights gained from this experience provide recommendations for psychologists interested in leadership opportunities in academic medicine.

Introducing clinical supervision across Western Australian public mental health services.

PubMed

Taylor, Monica; Harrison, Carole A

2010-08-01

Retention and recruitment of the mental health nursing workforce is a critical issue in Australia and more specifically in Western Australia (WA), partly due to the isolation of the state. It has been suggested that these workforce issues might be minimized through the introduction of clinical supervision within WA mental health services, where, historically, it has been misunderstood and viewed with caution by mental health nurses. This may have been partly due to a lack of understanding of clinical supervision, its models, and its many benefits, due to a paucity of information delivered into initial nurse education programs. The aim of this pilot project is to explore and evaluate the introduction of clinical supervision in WA public mental health services. A quantitative approach informed the study and included the use of an information gathering survey initially, which was followed with evaluation questionnaires. The findings show that education can increase the uptake of clinical supervision. Further, the findings illustrate the importance of linking clinicians from all professional groups via a clinical supervision web-based database.

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.

Beyond the individual victim: multilevel consequences of abusive supervision in teams.

PubMed

Farh, Crystal I C; Chen, Zhijun

2014-11-01

We conceptualize a multilevel framework that examines the manifestation of abusive supervision in team settings and its implications for the team and individual members. Drawing on Hackman's (1992) typology of ambient and discretionary team stimuli, our model features team-level abusive supervision (the average level of abuse reported by team members) and individual-level abusive supervision as simultaneous and interacting forces. We further draw on team-relevant theories of social influence to delineate two proximal outcomes of abuse-members' organization-based self-esteem (OBSE) at the individual level and relationship conflict at the team level-that channel the independent and interactive effects of individual- and team-level abuse onto team members' voice, team-role performance, and turnover intentions. Results from a field study and a scenario study provided support for these multilevel pathways. We conclude that abusive supervision in team settings holds toxic consequences for the team and individual, and offer practical implications as well as suggestions for future research on abusive supervision as a multilevel phenomenon. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

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

PubMed Central

Gönen, Mehmet

2014-01-01

Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian method that combines linear dimensionality reduction with linear binary classification for supervised multilabel learning and present a deterministic variational approximation algorithm to learn the proposed probabilistic model. We then extend the proposed method to find intrinsic dimensionality of the projected subspace using automatic relevance determination and to handle semi-supervised learning using a low-density assumption. We perform supervised learning experiments on four benchmark multilabel learning data sets by comparing our method with baseline linear dimensionality reduction algorithms. These experiments show that the proposed approach achieves good performance values in terms of hamming loss, average AUC, macro F1, and micro F1 on held-out test data. The low-dimensional embeddings obtained by our method are also very useful for exploratory data analysis. We also show the effectiveness of our approach in finding intrinsic subspace dimensionality and semi-supervised learning tasks. PMID:24532862

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

PubMed

Gönen, Mehmet

2014-03-01

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

Building mental models by dissecting physical models.

PubMed

Srivastava, Anveshna

2016-01-01

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose "model-dissection" as an alternative to "model-building," whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to "dissect" out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model-based interventions for two cohorts of students, we find that both the "builders" and the "dissectors" improve in the post-test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic time-efficiency of "model dissection," suggest that it could be a valuable pedagogical tool. © 2015 The International Union of Biochemistry and Molecular Biology.

Wages and Labor Management in African Manufacturing

ERIC Educational Resources Information Center

Fafchamps, Marcel; Soderbom, Mans

2006-01-01

Using matched employer-employee data from ten African countries, we examine the relationship between wages, worker supervision, and labor productivity in manufacturing. Wages increase with firm size for both production workers and supervisors. We develop a two-tier model of supervision that can account for this stylized fact and we fit the…

Postgraduate Research Supervision: Transforming (R)Elations. Eruptions: New Feminism across the Disciplines, Volume 11.

ERIC Educational Resources Information Center

Bartlett, Alison, Ed.; Mercer, Gina, Ed.

This anthology explores the relationships between postgraduate research candidates and their supervisors. Through stories from candidates and supervisors, the collection proposes alternatives to the prevailing models of postgraduate research supervision. The chapters are: (1) "Introduction" (Alison Bartlett and Gina Mercer); (2) "Dirty Work: 'A…

Four Models of Clinical Supervision in Virginia.

ERIC Educational Resources Information Center

Buckley, Pamela K.; And Others

The Virginia State Department of Education funded four, 3-year pilot clinical faculty programs to provide training and compensation to cooperating teachers for the purpose of improving the supervision of student teachers. Two of the programs which received grants were collaborative projects: partners Virginia Tech University and Hollins College…

Automatic Classification Using Supervised Learning in a Medical Document Filtering Application.

ERIC Educational Resources Information Center

Mostafa, J.; Lam, W.

2000-01-01

Presents a multilevel model of the information filtering process that permits document classification. Evaluates a document classification approach based on a supervised learning algorithm, measures the accuracy of the algorithm in a neural network that was trained to classify medical documents on cell biology, and discusses filtering…

Cultivating Self-Awareness in Counselors-in-Training through Group Supervision

ERIC Educational Resources Information Center

Del Moro, Ronald R.

2012-01-01

This study investigated processes, strategies, and frameworks that took place during group supervision classes, which best cultivate the self-awareness of Mental Health and Marriage and Family Counselors-in-Training (CITs). It was designed to explore factors across multiple theoretical models, which contributed to the cultivation of self-awareness…

Self-Supervised Chinese Ontology Learning from Online Encyclopedias

PubMed Central

Shao, Zhiqing; Ruan, Tong

2014-01-01

Constructing ontology manually is a time-consuming, error-prone, and tedious task. We present SSCO, a self-supervised learning based chinese ontology, which contains about 255 thousand concepts, 5 million entities, and 40 million facts. We explore the three largest online Chinese encyclopedias for ontology learning and describe how to transfer the structured knowledge in encyclopedias, including article titles, category labels, redirection pages, taxonomy systems, and InfoBox modules, into ontological form. In order to avoid the errors in encyclopedias and enrich the learnt ontology, we also apply some machine learning based methods. First, we proof that the self-supervised machine learning method is practicable in Chinese relation extraction (at least for synonymy and hyponymy) statistically and experimentally and train some self-supervised models (SVMs and CRFs) for synonymy extraction, concept-subconcept relation extraction, and concept-instance relation extraction; the advantages of our methods are that all training examples are automatically generated from the structural information of encyclopedias and a few general heuristic rules. Finally, we evaluate SSCO in two aspects, scale and precision; manual evaluation results show that the ontology has excellent precision, and high coverage is concluded by comparing SSCO with other famous ontologies and knowledge bases; the experiment results also indicate that the self-supervised models obviously enrich SSCO. PMID:24715819

Self-supervised Chinese ontology learning from online encyclopedias.

PubMed

Hu, Fanghuai; Shao, Zhiqing; Ruan, Tong

2014-01-01

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

The Moderating Effect of Interaction Avoidance Between Abusive Supervision and Subordinates' Job Promotions.

PubMed

Peltokorpi, Vesa

2017-10-03

While abusive supervision is shown to have negative stress-related effects on targets, less is known about the factors capable of mitigating these negative effects and their career-related outcomes. In this paper, we drew on the transactional model of stress and coping (Lazarus & Folkman, 1986) and the upward mobility theory (Turner, 1960) to explore the moderating effect of subordinates' interaction avoidance between abusive supervision and job promotions. To test this moderating effect, we collected data from 604 full-time employees at three points in time over a 12-month time period in Japan. The findings suggest that interaction avoidance moderates the relationship between abusive supervision and promotions, such that this relationship will be less negative as interaction avoidance increases.

Professional Supervision as Storied Experience: Narrative Analysis Findings for Australian-Based Registered Music Therapists.

PubMed

Kennelly, Jeanette D; Baker, Felicity A; Daveson, Barbara A

2017-03-01

Limited research exists to inform a music therapist's supervision story from their pre-professional training to their practice as a professional. Evidence is needed to understand the complex nature of supervision experiences and their impact on professional practice. This qualitative study explored the supervisory experiences of Australian-based Registered Music Therapists, according to the: 1) themes that characterize their experiences, 2) influences of the supervisor's professional background, 3) outcomes of supervision, and 4) roles of the employer, the professional music therapy association, and the university in supervision standards and practice. Seven professionals were interviewed for this study. Five stages of narrative analysis were used to create their supervision stories: a life course graph, narrative psychological analysis, component story framework and narrative analysis, analysis of narratives, and final integration of the seven narrative summaries. Findings revealed that supervision practice is influenced by a supervisee's personal and professional needs. A range of supervision models or approaches is recommended, including the access of supervisors from different professional backgrounds to support each stage of learning and development. A quality supervisory experience facilitates shifts in awareness and insight, which results in improved or increased skills, confidence, and accountability of practice. Participants' concern about stakeholders included a limited understanding of the role of the supervisor, a lack of clarity about accountability of supervisory practice, and minimal guidelines, which monitor professional competencies. The benefits of supervision in music therapy depend on the quality of the supervision provided, and clarity about the roles of those involved. Research and guidelines are recommended to target these areas. © the American Music Therapy Association 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Objective coding of content and techniques in workplace-based supervision of an EBT in public mental health.

PubMed

Dorsey, Shannon; Kerns, Suzanne E U; Lucid, Leah; Pullmann, Michael D; Harrison, Julie P; Berliner, Lucy; Thompson, Kelly; Deblinger, Esther

2018-01-24

Workplace-based clinical supervision as an implementation strategy to support evidence-based treatment (EBT) in public mental health has received limited research attention. A commonly provided infrastructure support, it may offer a relatively cost-neutral implementation strategy for organizations. However, research has not objectively examined workplace-based supervision of EBT and specifically how it might differ from EBT supervision provided in efficacy and effectiveness trials. Data come from a descriptive study of supervision in the context of a state-funded EBT implementation effort. Verbal interactions from audio recordings of 438 supervision sessions between 28 supervisors and 70 clinicians from 17 public mental health organizations (in 23 offices) were objectively coded for presence and intensity coverage of 29 supervision strategies (16 content and 13 technique items), duration, and temporal focus. Random effects mixed models estimated proportion of variance in content and techniques attributable to the supervisor and clinician levels. Interrater reliability among coders was excellent. EBT cases averaged 12.4 min of supervision per session. Intensity of coverage for EBT content varied, with some discussed frequently at medium or high intensity (exposure) and others infrequently discussed or discussed only at low intensity (behavior management; assigning/reviewing client homework). Other than fidelity assessment, supervision techniques common in treatment trials (e.g., reviewing actual practice, behavioral rehearsal) were used rarely or primarily at low intensity. In general, EBT content clustered more at the clinician level; different techniques clustered at either the clinician or supervisor level. Workplace-based clinical supervision may be a feasible implementation strategy for supporting EBT implementation, yet it differs from supervision in treatment trials. Time allotted per case is limited, compressing time for EBT coverage. Techniques that involve observation of clinician skills are rarely used. Workplace-based supervision content appears to be tailored to individual clinicians and driven to some degree by the individual supervisor. Our findings point to areas for intervention to enhance the potential of workplace-based supervision for implementation effectiveness. NCT01800266 , Clinical Trials, Retrospectively Registered (for this descriptive study; registration prior to any intervention [part of phase II RCT, this manuscript is only phase I descriptive results]).

Weakly supervised visual dictionary learning by harnessing image attributes.

PubMed

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

2014-12-01

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

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

"Unscrambling what's in your head": A mixed method evaluation of clinical supervision for midwives.

PubMed

Love, Bev; Sidebotham, Mary; Fenwick, Jennifer; Harvey, Susan; Fairbrother, Greg

2017-08-01

As a strategy to promote workforce sustainability a number of midwives working in one health district in New South Wales, Australia were trained to offer a reflective model of clinical supervision. The expectation was that these midwives would then be equipped to facilitate clinical supervision for their colleagues with the organisational aim of supporting professional development and promoting emotional well-being. To identify understanding, uptake, perceptions of impact, and the experiences of midwives accessing clinical supervision. Mixed Methods. In phase one 225 midwives were invited to complete a self-administered survey. Descriptive and inferential statistics were used to analyse the data. In phase two 12 midwives were interviewed. Thematic analysis was used to deepen understanding of midwives' experiences of receiving clinical supervision. Sixty percent of midwives responding in phase one had some experience of clinical supervision. Findings from both phases were complementary with midwives reporting a positive impact on their work, interpersonal skills, situational responses and career goals. Midwives described clinical supervision as a formal, structured and confidential space for 'safe reflection' that was valued as an opportunity for self-care. Barriers included misconceptions, perceived work related pressures and a sense that taking time out was unjustifiable. Education, awareness raising and further research into reflective clinical supervision, to support emotional well-being and professional midwifery practice is needed. In addition, health organisations need to design, implement and evaluate strategies that support the embedding of clinical supervision within midwives' clinical practice. Copyright © 2016 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

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.

Roof Type Selection Based on Patch-Based Classification Using Deep Learning for High Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Partovi, T.; Fraundorfer, F.; Azimi, S.; Marmanis, D.; Reinartz, P.

2017-05-01

3D building reconstruction from remote sensing image data from satellites is still an active research topic and very valuable for 3D city modelling. The roof model is the most important component to reconstruct the Level of Details 2 (LoD2) for a building in 3D modelling. While the general solution for roof modelling relies on the detailed cues (such as lines, corners and planes) extracted from a Digital Surface Model (DSM), the correct detection of the roof type and its modelling can fail due to low quality of the DSM generated by dense stereo matching. To reduce dependencies of roof modelling on DSMs, the pansharpened satellite images as a rich resource of information are used in addition. In this paper, two strategies are employed for roof type classification. In the first one, building roof types are classified in a state-of-the-art supervised pre-trained convolutional neural network (CNN) framework. In the second strategy, deep features from deep layers of different pre-trained CNN model are extracted and then an RBF kernel using SVM is employed to classify the building roof type. Based on roof complexity of the scene, a roof library including seven types of roofs is defined. A new semi-automatic method is proposed to generate training and test patches of each roof type in the library. Using the pre-trained CNN model does not only decrease the computation time for training significantly but also increases the classification accuracy.

[An overview of clinical practice education models for nursing students: a literature review].

PubMed

Canzan, Federica; Marognolli, Oliva; Bevilacqua, Anita; Defanti, Francesca; Ambrosi, Elisa; Cavada, Luisa; Saiani, Luisa

2017-01-01

. An overview of education models for nursing students clinical practice: a literature review. In the past decade the nursing education research developed and tested a number of clinical educational models. To describe the most used clinical educational models and to analyze their strengths and weaknesses in fostering the learning processes of nursing students. A literature review of studies on clinical education models for undergraduate nursing student, published in English, was performed. Electronic database Pubmed and Cinhal were searched until November 2016. Nineteen studies were included in the review and five clinical education model identified: 1) the university tutor supervises a group of students and selects learning opportunities; 2) a clinical expert/tutor nurse works side by side with one student; 3) the student is responsible of his/her learning process with the supervision of the ward staff; 4) a clinical tutor of the ward is dedicated to the students' supervision; 5) the student is not assigned to a ward but clinical learning opportunities matched with his/her needs are selected by the university. All the clinical education models shared the focus on students' learning needs. Their specific characteristics better suit them for different stages of students' education and to different clinical settings.

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

PubMed

Yamazaki, Keisuke

2015-09-01

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

An Overview of the Elements that Influence Efficiency in Postgraduate Supervisory Practice Arrangements

ERIC Educational Resources Information Center

Buttery, Ernest Alan; Richter, Ewa Maria; Filho, Walter Leal

2005-01-01

Purpose: To outline the role of the group supervision model in postgraduate training, especially its advantages in respect of research involving industry sponsors. Design/methodology/approach: The paper considers the various categories of supervision and the pivotal role played by the supervisor. It analyses indicators of supervisor effectiveness…

An Examination of University Supervision in a Physical Education Teacher Education Program

ERIC Educational Resources Information Center

Wright, Steven; Grenier, Michelle A.; Channell, Kathy

2015-01-01

The purpose of this descriptive study was to analyze university supervision from the perspective of student teachers (STs), and to examine postlesson conference discourse between STs and university supervisors (USs) to determine if STs perspectives on supervisory models aligned with what actually occurred. Determining STs expectations and desires…

Case Studies of Five Teacher Supervision/Evaluation Systems.

ERIC Educational Resources Information Center

Patrick, Edward M.; Dawson, Judith A.

In the 1984-85 school year, the Pennsylvania Department of Education (PDE) began to actively encourage Pennsylvania school districts to reform their teacher supervision/evaluation (TS/E) procedures. To obtain data necessary for developing TS/E models, the PDE commissioned Research for Better Schools (RBS) to conduct a study of five school…

"The Fly on the Wall" Reflecting Team Supervision.

ERIC Educational Resources Information Center

Prest, Layne E.; And Others

1990-01-01

Adapts reflecting team concept, a practical application of constructivist ideas, for use in group supervision. Evolving model includes a focus on the unique "fly on the wall" perspective of the reflecting team. Trainees are introduced to a multiverse of new ideas and perspectives in a context which integrates some of the most challenging…

Trainee Therapists' Views on the Alliance in Psychotherapy and Supervision: A Longitudinal Study

ERIC Educational Resources Information Center

Ybrandt, H.; Sundin, E. C.; Capone, G.

2016-01-01

The shape of alliance in psychotherapy and supervision using growth curve modeling was examined for clinically inexperienced trainee therapists, who were engaged in long-term cognitive behavioral--or psychodynamic individual psychotherapy at a Psychology Clinic in Sweden. Trainee therapists rated their view of the alliance with their clients and…

Supervisee Countertransference: A Holistic Supervision Approach

ERIC Educational Resources Information Center

Ponton, Richard F.; Sauerheber, Jill Duba

2014-01-01

Countertransference (CT) has been recognized as a significant variable in the process and outcome of therapy and counseling for over 100 years. A review of the literature suggests that little attention has been devoted to strategies that supervisors can use to address CT in supervision with novice counselors. Informed by models of CT proposed by…

The Media Center & the Internet: Selection, Supervision and Staff Development.

ERIC Educational Resources Information Center

Anderson, Mary Alice

1999-01-01

The Internet's unique scope, characteristics and potential make it a vehicle for media specialists to model good use of information technology and provide far-reaching instructional leadership in schools. This article focuses on approaches to Web site selection, supervision, and staff development for effective use of the Internet in schools. (AEF)

Using a Blended Approach to Facilitate Postgraduate Supervision

ERIC Educational Resources Information Center

de Beer, Marie; Mason, Roger B.

2009-01-01

This paper explores the feasibility of using a blended approach to postgraduate research-degree supervision. Such a model could reduce research supervisors' workloads and improve the quality and success of Masters and Doctoral students' research output. The paper presents a case study that is based on a framework that was originally designed for…

Emotions, Social Work Practice and Supervision: An Uneasy Alliance?

PubMed Central

Ingram, Richard

2012-01-01

This paper examines the place of emotions within social work practice. The perceived tensions between emotions and rational decision making are explored and it is argued that their relationship is compatible and necessary. A model for the co-creation of emotionally intelligent supervision is developed to support this vision of practice. PMID:24764612

When Approved Is not Enough: Development of a Supervision Consultation Model.

ERIC Educational Resources Information Center

Green, Shelley; Shilts, Lee; Bacigalupe, Gonzalo

2001-01-01

The dramatic increase in literature that addresses family therapy training and supervision over the last decade has been predominantly in the area of theory, rather than practice. This article describes the development of a meta-supervisory learning context for approved supervisors and provides examples of interactions between supervisors that…

Team Modes and Power: Supervision of Doctoral Students

ERIC Educational Resources Information Center

Robertson, Margaret J.

2017-01-01

Currently, team supervision in doctoral studies is widely practised across Australian universities. The interpretation of 'team' is broad and there is evidence of experimentation with supervisory models. This paper elaborates upon a taxonomy of team modes and power forms based on a recent qualitative study across universities in a number of states…

Epiphany? A Case Study of Learner-Centredness in Educational Supervision

ERIC Educational Resources Information Center

Talbot, Martin

2009-01-01

Graduate medical trainees in the UK appreciate mentors who demonstrate learner-centredness as modelled by Rogers. This case study was undertaken to examine how, in one instance, learner-centred may be supervision within the tight confines of a formal, competency-based programme of training. Four formal interviews (in 18 months), were analysed to…

Emotions, Social Work Practice and Supervision: An Uneasy Alliance?

PubMed

Ingram, Richard

2013-03-01

This paper examines the place of emotions within social work practice. The perceived tensions between emotions and rational decision making are explored and it is argued that their relationship is compatible and necessary. A model for the co-creation of emotionally intelligent supervision is developed to support this vision of practice.

Task-driven dictionary learning.

PubMed

Mairal, Julien; Bach, Francis; Ponce, Jean

2012-04-01

Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal processing. For signals such as natural images that admit such sparse representations, it is now well established that these models are well suited to restoration tasks. In this context, learning the dictionary amounts to solving a large-scale matrix factorization problem, which can be done efficiently with classical optimization tools. The same approach has also been used for learning features from data for other purposes, e.g., image classification, but tuning the dictionary in a supervised way for these tasks has proven to be more difficult. In this paper, we present a general formulation for supervised dictionary learning adapted to a wide variety of tasks, and present an efficient algorithm for solving the corresponding optimization problem. Experiments on handwritten digit classification, digital art identification, nonlinear inverse image problems, and compressed sensing demonstrate that our approach is effective in large-scale settings, and is well suited to supervised and semi-supervised classification, as well as regression tasks for data that admit sparse representations.

Student nurses' experiences of the clinical learning environment in relation to the organization of supervision: a questionnaire survey.

PubMed

Sundler, Annelie J; Björk, Maria; Bisholt, Birgitta; Ohlsson, Ulla; Engström, Agneta Kullén; Gustafsson, Margareta

2014-04-01

The aim was to investigate student nurses' experiences of the clinical learning environment in relation to how the supervision was organized. The clinical environment plays an essential part in student nurses' learning. Even though different models for supervision have been previously set forth, it has been stressed that there is a need both of further empirical studies on the role of preceptorship in undergraduate nursing education and of studies comparing different models. A cross-sectional study with comparative design was carried out with a mixed method approach. Data were collected from student nurses in the final term of the nursing programme at three universities in Sweden by means of a questionnaire. In general the students had positive experiences of the clinical learning environment with respect to pedagogical atmosphere, leadership style of the ward manager, premises of nursing, supervisory relationship, and role of the nurse preceptor and nurse teacher. However, there were significant differences in their ratings of the supervisory relationship (p<0.001) and the pedagogical atmosphere (p 0.025) depending on how the supervision was organized. Students who had the same preceptor all the time were more satisfied with the supervisory relationship than were those who had different preceptors each day. Students' comments on the supervision confirmed the significance of the preceptor and the supervisory relationship. The organization of the supervision was of significance with regard to the pedagogical atmosphere and the students' relation to preceptors. Students with the same preceptor throughout were more positive concerning the supervisory relationship and the pedagogical atmosphere. © 2013.

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.

Introduction to the Special Section on Teaching, Training, and Supervision in Personality and Psychological Assessment.

PubMed

Smith, Justin D

2017-01-01

This special section contains empirical and conceptual articles pertaining to the broad topic of teaching, training, and supervision of assessment. Despite some evidence of a decline in recent decades, assessment remains a defining practice of professional psychologists in many subfields, including clinical, counseling, school, and neuropsychology, that consumes a consequential proportion of their time. To restore assessment to its rightful place of prominence, a clear agenda needs to be developed for advancing teaching and training methods, increasing instruction to state-of-the-art methods, and defining aims that could be elucidated through empirical inquiry. The 7 articles in this special section provide a developmental perspective of these issues that collectively provide practical tools for instructors and begin to set the stage for a research agenda in this somewhat neglected area of study that is vital to the identity of professional psychology. Additionally, 2 comments are provided by distinguished figures in the field concerning the implications of the articles in the special section to health services psychology and the competencies-based movement in applied psychology.

Weakly supervised classification in high energy physics

DOE PAGES

Dery, Lucio Mwinmaarong; Nachman, Benjamin; Rubbo, Francesco; ...

2017-05-01

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

Weakly supervised classification in high energy physics

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

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

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

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Chemistry 300. Administration Manual for Supervising Teachers, Provincial Examination, Answer Key--Multiple-Choice and Written-Answer Questions, and Provincial Summary Report = Chimie 300. Guide d'administration a l'intention des surveillants d'examen, Examen provincial, Cle de correction--Questions choix multiple et Questions responses ouvertes, et Rapport sommaire provincial.

ERIC Educational Resources Information Center

Manitoba Dept. of Education and Training, Winnipeg.

This collection of manuals contains the Manitoba Provincial Chemistry Examination for students seeking credit in Senior 4 Chemistry (Chemistry 300) and instructions for its use and grading. The examination is based on the Core Topics of the Senior 4 Chemistry course and accounts for 30% of the student's final grade in the course. The examination…

Conceptualisations and perceptions of the nurse preceptor's role: A scoping review.

PubMed

Trede, Franziska; Sutton, Katelin; Bernoth, Maree

2016-01-01

The practice of nursing is a substantially different undertaking to supervising nursing students. A clear conceptualisation of the preceptor role reveals its scope, expectations and responsibilities. The aim of this scoping review is to investigate what is known in the pertinent literature about preceptors' experiences of their supervision practices and their perceptions of what makes a good workplace environment that enables good preceptorship and is conducive to student learning. The literature scoping review design by Arksey and O'Malley was adopted for this literature review study because it enables researchers to chart, gather and summarise known literature on a given topic. Databases searched included Scopus, Ebsco, Informit and VOCEDplus. To answer our research question what is known about how undergraduate nursing student preceptors' supervision practices are conceptualised and perceived we posed four analysis questions to our literature set: (1) How do the articles conceptualise preceptorship? (2) What pedagogical frameworks are used to understand preceptorship? (3) What are the messages for preceptorship practices? (4) What are the recommendations for future research? A total of 25 articles were identified as eligible for this study. The results are ordered into four sections: theoretical conceptualisations of the preceptorship role, pedagogical framework, messages about preceptoring and recommendations for further research. The discourse of preceptorship is not underpinned by a strong theoretical and pedagogical base. The role of preceptors has not been expanded to include theoretical perspectives from socio-cultural practice and social learning paradigms. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

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.

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

Clinical Oversight: Conceptualizing the Relationship Between Supervision and Safety

PubMed Central

Lingard, Lorelei; Baker, G. Ross; Kitchen, Lisa; Regehr, Glenn

2007-01-01

Background Concern about the link between clinical supervision and safe, quality health care has led to widespread increases in the supervision of medical trainees. The effects of increased supervision on patient care and trainee education are not known, primarily because the current multifacted and poorly operationalized concept of clinical supervision limits the potential for evaluation. Objective To develop a conceptual model of clinical supervision to inform and guide policy and research. Design, Setting, and Participants Observational fieldwork and interviews were conducted in the Emergency Department and General Internal Medicine in-patient teaching wards of two academic health sciences centers associated with an urban Canadian medical school. Members of 12 Internal Medicine and Emergency Medicine teaching teams (n = 88) were observed during regular clinical activities (216 hours). Sixty-five participants (12 physicians, 28 residents, 17 medical students, 8 nurses) also completed interviews about supervision. Field notes and interview transcripts were analyzed for emergent themes using grounded theory methodology. Results The term “clinical oversight” was developed to describe patient care activities performed by supervisors to ensure quality of care. “Routine oversight” (preplanned monitoring of trainees’ clinical work) can expose supervisors to concerns that trigger “responsive oversight” (a double-check or elaboration of trainees’ clinical work). Supervisors sometimes engage in “backstage oversight” (oversight of which the trainee is not directly aware). When supervisors encounter a situation that exceeds a trainee’s competence, they move beyond clinical oversight to “direct patient care”. Conclusions This study elaborates a typology of clinical oversight activities including routine, responsive, and backstage oversight. This new typology provides a framework for clinical supervision policy and for research to evaluate the relationship between supervision and safety. PMID:17557190

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.

Training with O (Observing) and T (Treatment) Teams in Live Supervision: Reflections in the Looking Glass.

ERIC Educational Resources Information Center

Roberts, Janine; And Others

1989-01-01

Describes process that six counselor trainees and two supervisors used with treatment and observation teams to examine their own coevolution as a therapeutic system using the Milan model of family therapy and Ericksonian hypnotherapy. Concludes with a discussion of advantages and pitfalls of this type of dual supervision. (Author/ABL)

Beyond Technology...Learning with the Wired Curriculum. 1998 Yearbook of the Massachusetts Association for Supervision and Curriculum Development.

ERIC Educational Resources Information Center

Zimmerman, Isa Kaftal, Ed.; Hayes, Mary Forte, Ed.

This yearbook for the Massachusetts Association for Supervision and Curriculum Development (MASCD) provides educators with models of successful practices and raises questions and potential solutions to issues of accountability, policy, long-term planning, funding, and student motivation for learning. This 1998 yearbook assists educators at all…

Abusive Supervision by Academic Supervisors and Postgraduate Research Students' Creativity: The Mediating Role of Leader-Member Exchange and Intrinsic Motivation

ERIC Educational Resources Information Center

Meng, Yi; Tan, Jing; Li, Jing

2017-01-01

Drawing upon the componential theory of creativity, cognitive evaluation theory and social exchange theory, the study reported in this paper tested a mediating model based on the hypothesis that abusive supervision negatively influences creativity sequentially through leader-member exchange (LMX) and intrinsic motivation. The study employed…

High Quality Family Day Care: Financial Considerations.

ERIC Educational Resources Information Center

Corsini, David A.; Caruso, Grace-Ann

The expenses and sources of income for two supervised family day care (SFDC) systems in Denmark, where SFDC is the national family day care model, are compared with two supervised systems in Connecticut, where SFDC is rare, as in the United States generally. SFDC differs from family day care in general by the systematic involvement of trained…

A systematic review of supportive supervision as a strategy to improve primary healthcare services in Sub-Saharan Africa.

PubMed

Bailey, Claire; Blake, Carolyn; Schriver, Michael; Cubaka, Vincent Kalumire; Thomas, Tisa; Martin Hilber, Adriane

2016-01-01

It may be assumed that supportive supervision effectively builds capacity, improves the quality of care provided by frontline health workers, and positively impacts clinical outcomes. Evidence on the role of supervision in Sub-Saharan Africa has been inconclusive, despite the critical need to maximize the workforce in low-resource settings. To review the published literature from Sub-Saharan Africa on the effects of supportive supervision on quality of care, and health worker motivation and performance. A systematic review of seven databases of both qualitative and quantitative studies published in peer-reviewed journals. Selected studies were based in primary healthcare settings in Sub-Saharan Africa and present primary data concerning supportive supervision. Thematic synthesis where data from the identified studies were grouped and interpreted according to prominent themes. Supportive supervision can increase job satisfaction and health worker motivation. Evidence is mixed on whether this translates to increased clinical competence and there is little evidence of the effect on clinical outcomes. Results highlight the lack of sound evidence on the effects of supportive supervision owing to limitations in research design and the complexity of evaluating such interventions. The approaches required a high level of external inputs, which challenge the sustainability of such models. Copyright © 2015 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

An overview of topic modeling and its current applications in bioinformatics.

PubMed

Liu, Lin; Tang, Lin; Dong, Wen; Yao, Shaowen; Zhou, Wei

2016-01-01

With the rapid accumulation of biological datasets, machine learning methods designed to automate data analysis are urgently needed. In recent years, so-called topic models that originated from the field of natural language processing have been receiving much attention in bioinformatics because of their interpretability. Our aim was to review the application and development of topic models for bioinformatics. This paper starts with the description of a topic model, with a focus on the understanding of topic modeling. A general outline is provided on how to build an application in a topic model and how to develop a topic model. Meanwhile, the literature on application of topic models to biological data was searched and analyzed in depth. According to the types of models and the analogy between the concept of document-topic-word and a biological object (as well as the tasks of a topic model), we categorized the related studies and provided an outlook on the use of topic models for the development of bioinformatics applications. Topic modeling is a useful method (in contrast to the traditional means of data reduction in bioinformatics) and enhances researchers' ability to interpret biological information. Nevertheless, due to the lack of topic models optimized for specific biological data, the studies on topic modeling in biological data still have a long and challenging road ahead. We believe that topic models are a promising method for various applications in bioinformatics research.

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

PubMed

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

2017-10-12

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

Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling

PubMed Central

Zhou, Fuqun; Zhang, Aining

2016-01-01

Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2–3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests’ features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data. PMID:27792152

Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling.

PubMed

Zhou, Fuqun; Zhang, Aining

2016-10-25

Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2-3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests' features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data.

K-Means Subject Matter Expert Refined Topic Model Methodology

DTIC Science & Technology

2017-01-01

Refined Topic Model Methodology Topic Model Estimation via K-Means U.S. Army TRADOC Analysis Center-Monterey 700 Dyer Road...January 2017 K-means Subject Matter Expert Refined Topic Model Methodology Topic Model Estimation via K-Means Theodore T. Allen, Ph.D. Zhenhuan...Matter Expert Refined Topic Model Methodology Topic Model Estimation via K-means 5a. CONTRACT NUMBER W9124N-15-P-0022 5b. GRANT NUMBER 5c

Classification

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.

2011-01-01

A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. In supervised learning, a set of training examples---examples with known output values---is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate's measurements. This chapter discusses methods to perform machine learning, with examples involving astronomy.

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

PubMed

Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

2015-08-01

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

Characterization and reconstruction of 3D stochastic microstructures via supervised learning.

PubMed

Bostanabad, R; Chen, W; Apley, D W

2016-12-01

The need for computational characterization and reconstruction of volumetric maps of stochastic microstructures for understanding the role of material structure in the processing-structure-property chain has been highlighted in the literature. Recently, a promising characterization and reconstruction approach has been developed where the essential idea is to convert the digitized microstructure image into an appropriate training dataset to learn the stochastic nature of the morphology by fitting a supervised learning model to the dataset. This compact model can subsequently be used to efficiently reconstruct as many statistically equivalent microstructure samples as desired. The goal of this paper is to build upon the developed approach in three major directions by: (1) extending the approach to characterize 3D stochastic microstructures and efficiently reconstruct 3D samples, (2) improving the performance of the approach by incorporating user-defined predictors into the supervised learning model, and (3) addressing potential computational issues by introducing a reduced model which can perform as effectively as the full model. We test the extended approach on three examples and show that the spatial dependencies, as evaluated via various measures, are well preserved in the reconstructed samples. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

The Learning Process of Supervisees Who Engage in the Reflecting Team Model within Group Supervision: A Grounded Theory Inquiry

ERIC Educational Resources Information Center

Pender, Rebecca Lynn

2012-01-01

In recent years, counselor educators have begun to incorporate the use of the reflecting team process with the training of counselors. Specifically, the reflecting team has been used in didactic courses (Cox, 2003; Landis & Young, 1994; Harrawood, Wilde & Parmanand, 2011) and in supervision (Cox, 1997; Prest, Darden, & Keller, 1990;…

Supervision on Social Media: Use and Perception of Facebook as a Research Education Tool in Disadvantaged Areas

ERIC Educational Resources Information Center

Pimmer, Christoph; Chipps, Jennifer; Brysiewicz, Petra; Walters, Fiona; Linxen, Sebastian; Gröhbiel, Urs

2016-01-01

This exploratory study investigates how a typically disadvantaged user group of older, female learners from rural, low-tech settings used and perceived a Facebook group as a research supervision and distance learning tool over time. The within-stage mixed-model research was carried out in a module of a part-time, advanced midwifery education…

17 CFR 240.17i-2 - Notice of intention to be supervised by the Commission as a supervised investment bank holding...

Code of Federal Regulations, 2010 CFR

2010-04-01

... or controls a broker or dealer that maintains a substantial presence in the securities business as...) Supplemental information including: (i) A description of the business and organization of the investment bank... description of mathematical models that the investment bank holding company proposes to use to price positions...

The Missing Ingredients in Reflective Supervision: Helping Staff Members Learn about and Fully Participate in the Supervisory Process

ERIC Educational Resources Information Center

Heffron, Mary Claire; Murch, Trudi

2018-01-01

Successful implementation of a reflective supervision (RS) model in an agency or system requires careful attention to the learning needs of supervisees. Although supervisors and managers typically receive orientation and training to help them understand and implement RS, their staff rarely do. In this article, the authors explore supervisees'…

Should First-Year Doctoral Students Be Supervised Collectively or Individually? Effects on Thesis Completion and Time to Completion

ERIC Educational Resources Information Center

Agné, Hans; Mörkenstam, Ulf

2018-01-01

Whether supervision of doctoral students is best pursued individually or collectively is a recurring but unresolved question in debates on higher education. The rarity of longitudinal data and the common usage of qualitative methods to analyse a limited number of cases have left the effectiveness of either model largely untested. To assist with…

The Issue of Education Supervision in Turkey in the Views of Teachers, Administrators, Supervisors and Lecturers

ERIC Educational Resources Information Center

Memduhoglu, Hasan Basri

2012-01-01

The aim of this study is to determine the views of teachers, administrators, supervisors and lecturers that are experts in their fields as people having roles in education regarding the aim, structure, process, strong sides and main problems of the education supervision in Turkey. In this research, the scanning model research was employed through…

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.

Precision assessment of some supervised and unsupervised algorithms for genotype discrimination in the genus Pisum using SSR molecular data.

PubMed

Nasiri, Jaber; Naghavi, Mohammad Reza; Kayvanjoo, Amir Hossein; Nasiri, Mojtaba; Ebrahimi, Mansour

2015-03-07

For the first time, prediction accuracies of some supervised and unsupervised algorithms were evaluated in an SSR-based DNA fingerprinting study of a pea collection containing 20 cultivars and 57 wild samples. In general, according to the 10 attribute weighting models, the SSR alleles of PEAPHTAP-2 and PSBLOX13.2-1 were the two most important attributes to generate discrimination among eight different species and subspecies of genus Pisum. In addition, K-Medoids unsupervised clustering run on Chi squared dataset exhibited the best prediction accuracy (83.12%), while the lowest accuracy (25.97%) gained as K-Means model ran on FCdb database. Irrespective of some fluctuations, the overall accuracies of tree induction models were significantly high for many algorithms, and the attributes PSBLOX13.2-3 and PEAPHTAP could successfully detach Pisum fulvum accessions and cultivars from the others when two selected decision trees were taken into account. Meanwhile, the other used supervised algorithms exhibited overall reliable accuracies, even though in some rare cases, they gave us low amounts of accuracies. Our results, altogether, demonstrate promising applications of both supervised and unsupervised algorithms to provide suitable data mining tools regarding accurate fingerprinting of different species and subspecies of genus Pisum, as a fundamental priority task in breeding programs of the crop. Copyright © 2015 Elsevier Ltd. All rights reserved.

A COMMUNITY MENTAL HEALTH PROFESSIONAL DEVELOPMENT MODEL FOR THE EXPANSION OF REFLECTIVE PRACTICE AND SUPERVISION: EVALUATION OF A PILOT TRAINING SERIES FOR INFANT MENTAL HEALTH PROFESSIONALS.

PubMed

Shea, Sarah E; Goldberg, Sheryl; Weatherston, Deborah J

2016-11-01

The Michigan Association for Infant Mental Health identified a need for reflective supervision training for infant mental health (IMH) specialists providing home-based services to highly vulnerable infants and their families. Findings indicate that this pilot of an IMH community mental health professional development model was successful, as measured by the participants' increased capacity to apply reflective practice and supervisory knowledge and skills. Furthermore, IMH clinicians demonstrated an increase in the frequency of their use of reflective practice skills, and their supervisors demonstrated an increase in their sense of self-efficacy regarding reflective supervisory tasks. Finally, the evaluation included a successful pilot of new measures designed to measure reflective practice, contributing to the growing body of research in the area of reflective supervision. © 2016 Michigan Association for Infant Mental Health.

Supervised space robots are needed in space exploration

NASA Technical Reports Server (NTRS)

Erickson, Jon D.

1994-01-01

High level systems engineering models were developed to simulate and analyze the types, numbers, and roles of intelligent systems, including supervised autonomous robots, which will be required to support human space exploration. Conventional and intelligent systems were compared for two missions: (1) a 20-year option 5A space exploration; and (2) the First Lunar Outpost (FLO). These studies indicate that use of supervised intelligent systems on planet surfaces will 'enable' human space exploration. The author points out that space robotics can be considered a form of the emerging technology of field robotics and solutions to many space applications will apply to problems relative to operating in Earth-based hazardous environments.

Molecular activity prediction by means of supervised subspace projection based ensembles of classifiers.

PubMed

Cerruela García, G; García-Pedrajas, N; Luque Ruiz, I; Gómez-Nieto, M Á

2018-03-01

This paper proposes a method for molecular activity prediction in QSAR studies using ensembles of classifiers constructed by means of two supervised subspace projection methods, namely nonparametric discriminant analysis (NDA) and hybrid discriminant analysis (HDA). We studied the performance of the proposed ensembles compared to classical ensemble methods using four molecular datasets and eight different models for the representation of the molecular structure. Using several measures and statistical tests for classifier comparison, we observe that our proposal improves the classification results with respect to classical ensemble methods. Therefore, we show that ensembles constructed using supervised subspace projections offer an effective way of creating classifiers in cheminformatics.

Supervised chaos genetic algorithm based state of charge determination for LiFePO4 batteries in electric vehicles

NASA Astrophysics Data System (ADS)

Shen, Yanqing

2018-04-01

LiFePO4 battery is developed rapidly in electric vehicle, whose safety and functional capabilities are influenced greatly by the evaluation of available cell capacity. Added with adaptive switch mechanism, this paper advances a supervised chaos genetic algorithm based state of charge determination method, where a combined state space model is employed to simulate battery dynamics. The method is validated by the experiment data collected from battery test system. Results indicate that the supervised chaos genetic algorithm based state of charge determination method shows great performance with less computation complexity and is little influenced by the unknown initial cell state.

"They put you on your toes": Physical Therapists' Perceived Benefits from and Barriers to Supervising Students in the Clinical Setting.

PubMed

Davies, Robyn; Hanna, Elizabeth; Cott, Cheryl

2011-01-01

To identify the perceived benefits of and barriers to clinical supervision of physical therapy (PT) students. In this qualitative descriptive study, three focus groups and six key-informant interviews were conducted with clinical physical therapists or administrators working in acute care, orthopaedic rehabilitation, or complex continuing care. Data were coded and analyzed for common ideas using a constant comparison approach. Perceived barriers to supervising students tended to be extrinsic: time and space constraints, challenging or difficult students, and decreased autonomy or flexibility for the clinical physical therapists. Benefits tended to be intrinsic: teaching provided personal gratification by promoting reflective practice and exposing clinical educators to current knowledge. The culture of different health care institutions was an important factor in therapists' perceptions of student supervision. Despite different disciplines and models of supervision, there is considerable synchronicity in the issues reported by physical therapists and other disciplines. Embedding the value of clinical teaching in the institution, along with strong communication links among academic partners, institutions, and potential clinical faculty, may mitigate barriers and increase the commitment and satisfaction of teaching staff.

The role of peer respect in linking abusive supervision to follower outcomes: Dual moderation of group potency.

PubMed

Schaubroeck, John M; Peng, Ann C; Hannah, Sean T

2016-02-01

We develop a model in which abusive supervision undermines individuals' perceptions of the level of respect they are accorded by their group peers, which in turn reduces their performance and disconnects them psychologically from the organization. High group potency strengthens each of these connections. We studied the theorized relationships across 3 periods during a 10-week residential organizational entry program. Group potency, representing shared group perceptions, moderated relationships at the individual level. These included the negative relationship between abusive supervision (Time 1) and perceived peer respect (Time 2) and the relationship between perceived peer respect and organizational commitment, organizational identification, and turnover intention (Time 3). We found stronger relationships between abusive supervision and perceived peer respect--and between peer respect and the attitudinal outcomes and turnover intention--among groups with higher potency. Perceived peer respect was also positively related to followers' task performance. We discuss implications of the conceptual framework and findings for future research and theory development concerning how groups and individuals respond to abusive supervision and to treatment by their peers. (c) 2016 APA, all rights reserved).

A cost-benefit/cost-effectiveness analysis of proposed supervised injection facilities in Montreal, Canada.

PubMed

Jozaghi, Ehsan; Reid, Andrew A; Andresen, Martin A

2013-07-09

This paper will determine whether expanding Insite (North America's first and only supervised injection facility) to more locations in Canada such as Montreal, cost less than the health care consequences of not having such expanded programs for injection drug users. By analyzing secondary data gathered in 2012, this paper relies on mathematical models to estimate the number of new HIV and Hepatitis C (HCV) infections prevented as a result of additional SIF locations in Montreal. With very conservative estimates, it is predicted that the addition of each supervised injection facility (up-to a maximum of three) in Montreal will on average prevent 11 cases of HIV and 65 cases of HCV each year. As a result, there is a net cost saving of CDN$0.686 million (HIV) and CDN$0.8 million (HCV) for each additional supervised injection site each year. This translates into a net average benefit-cost ratio of 1.21: 1 for both HIV and HCV. Funding supervised injection facilities in Montreal appears to be an efficient and effective use of financial resources in the public health domain.

Minimal supervision out-patient clinical teaching.

PubMed

Figueiró-Filho, Ernesto Antonio; Amaral, Eliana; McKinley, Danette; Bezuidenhout, Juanita; Tekian, Ara

2014-08-01

Minimal faculty member supervision of students refers to a method of instruction in which the patient-student encounter is not directly supervised by a faculty member, and presents a feasible solution in clinical teaching. It is unclear, however, how such practices are perceived by patients and how they affect student learning. We aimed to assess patient and medical student perceptions of clinical teaching with minimal faculty member supervision. Questionnaires focusing on the perception of students' performance were administered to patients pre- and post-consultation. Students' self-perceptions on their performance were obtained using a questionnaire at the end of the consultation. Before encounters with students, 22 per cent of the 95 patients were not sure if they would feel comfortable or trust the students; after the consultation, almost all felt comfortable (97%) and relied on the students (99%). The 81 students surveyed agreed that instruction with minimal faculty member supervision encouraged their participation and engagement (86%). They expressed interest in knowing patients' opinions about their performance (94%), and they felt comfortable about being assessed by the patients (86%). The minimal faculty member supervision model was well accepted by patients. Responses from the final-year students support the use of assessments that incorporate feedback from patients in their overall clinical evaluations. © 2014 John Wiley & Sons Ltd.

A diagnostic study of Department of Health training courses for family planning providers.

PubMed

Rood, S; Raquepo, M; Ladia, M A

1993-01-01

A study in the Philippines sought to observe and describe the family planning (FP) training program in two regions. This program trains physicians, nurses, and midwives as a team and includes a Basic/Comprehensive (B/C) course in FP with didactic and practicum elements, training in interpersonal communication skills (ICS) for those who have completed with B/C course, and a Preceptors Course for those who will supervise the practicum phase of the B/C course. The study gathered specific information on 1) trainee absenteeism and drop-out rates, 2) course content and effects, 3) the trainee selection process, 4) the practicum requirement for the B/C course, and 5) service delivery values and quality of care. Data were collected through observations, questionnaires, exit interviews with clients during the practicum phase, interviews with supervisors and public officials (mayors), and focus group discussions with regional trainers. This assessment led to the following recommendations: 1) maintain the current team approach; 2) reserve basic orientation-type subjects for office-based training to allow more time for FP topics in the training programs; 3) use caution in making a switch to "competency-based" training because of the possibility that supervision is inadequate for such a training method; 4) improve scheduling; 5) enforce the prerequisites for participation in the ICS and Preceptors Courses; 6) assign only one trainee to a preceptor area during the practicum and reduce the quota of IUD insertions to reduce pressure to obtain IUD acceptors; 7) create a "model" FP clinic each time a preceptor is trained; 8) pay more attention to natural FP methods; and 9) maintain an emphasis on quality of care.

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.

Multi-Topic Tracking Model for dynamic social network

NASA Astrophysics Data System (ADS)

Li, Yuhua; Liu, Changzheng; Zhao, Ming; Li, Ruixuan; Xiao, Hailing; Wang, Kai; Zhang, Jun

2016-07-01

The topic tracking problem has attracted much attention in the last decades. However, existing approaches rarely consider network structures and textual topics together. In this paper, we propose a novel statistical model based on dynamic bayesian network, namely Multi-Topic Tracking Model for Dynamic Social Network (MTTD). It takes influence phenomenon, selection phenomenon, document generative process and the evolution of textual topics into account. Specifically, in our MTTD model, Gibbs Random Field is defined to model the influence of historical status of users in the network and the interdependency between them in order to consider the influence phenomenon. To address the selection phenomenon, a stochastic block model is used to model the link generation process based on the users' interests to topics. Probabilistic Latent Semantic Analysis (PLSA) is used to describe the document generative process according to the users' interests. Finally, the dependence on the historical topic status is also considered to ensure the continuity of the topic itself in topic evolution model. Expectation Maximization (EM) algorithm is utilized to estimate parameters in the proposed MTTD model. Empirical experiments on real datasets show that the MTTD model performs better than Popular Event Tracking (PET) and Dynamic Topic Model (DTM) in generalization performance, topic interpretability performance, topic content evolution and topic popularity evolution performance.

Self-report after randomly assigned supervision does not predict ability to practice Motivational Interviewing

PubMed Central

Kutner, Bryan A.; Smith, Jennifer L.; Carpenter, K. M.; Hu, M-C.; Amrhein, Paul C.; Nunes, E. V.

2015-01-01

The objective of this study was to investigate the relation between self-report and objective assessment of Motivational Interviewing (MI) skills following training and supervision. After an MI workshop, 96 clinicians from 26 community programs (age 21–68, 65% female, 40.8% Black, 29.6% Caucasian, 24.5% Hispanic, 2.0% Asian, 3.1% other) were randomized to supervision (tele-conferencing or tape-based), or workshop only. At four time points, trainees completed a self-report of MI skill, using items from the MI Understanding questionnaire (MIU), and were objectively assessed by raters using the Motivational Interviewing Treatment Integrity (MITI) system. Correlations were calculated between MIU and MITI scores. A generalized linear mixed model was tested on MIU scores, with MITI scores, supervision condition and time as independent variables. MIU scores increased from pre-workshop (Mean = 4.74, SD = 1.79) to post-workshop (Mean = 6.31, SD = 1.03) (t = 8.69, p < .0001). With supervision, scores continued to increase, from post-workshop to week 8 (Mean = 7.07, SD = 0.91, t = 5.60, p < .0001) and from week 8 to week 20 (Mean = 7.28, SD = 0.94, t = 2.43, p = .02). However, MIU scores did not significantly correlate with MITI scores, with or without supervision. Self- reported ability increased with supervision, but self-report was not an indicator of objectively measured skill. This suggests that training does not increase correspondence between self-report and objective assessment, so community treatment programs should not rely on clinician self- report to assess the need for ongoing training and supervision and it may be necessary to train clinicians to accurately assess their own skill. PMID:25963775

Self-Report After Randomly Assigned Supervision Does not Predict Ability to Practice Motivational Interviewing.

PubMed

Wain, R Morgan; Kutner, Bryan A; Smith, Jennifer L; Carpenter, Kenneth M; Hu, Mei-Chen; Amrhein, Paul C; Nunes, Edward V

2015-10-01

The objective of this study was to investigate the relation between self-report and objective assessment of motivational interviewing (MI) skills following training and supervision. After an MI workshop, 96 clinicians from 26 community programs (age 21-68, 65% female, 40.8% Black, 29.6% Caucasian, 24.5% Hispanic, 2.0% Asian, 3.1% other) were randomized to supervision (tele-conferencing or tape-based), or workshop only. At four time points, trainees completed a self-report of MI skill, using items from the MI understanding questionnaire (MIU), and were objectively assessed by raters using the Motivational Interviewing Treatment Integrity (MITI) system. Correlations were calculated between MIU and MITI scores. A generalized linear mixed model was tested on MIU scores, with MITI scores, supervision condition and time as independent variables. MIU scores increased from pre-workshop (mean = 4.74, SD = 1.79) to post-workshop (mean = 6.31, SD = 1.03) (t = 8.69, p < .0001). With supervision, scores continued to increase, from post-workshop to week 8 (mean = 7.07, SD = 0.91, t = 5.60, p < .0001) and from week 8 to week 20 (mean = 7.28, SD = 0.94, t = 2.43, p = .02). However, MIU scores did not significantly correlate with MITI scores, with or without supervision. Self-reported ability increased with supervision, but self-report was not an indicator of objectively measured skill. This suggests that training does not increase correspondence between self-report and objective assessment, so community treatment programs should not rely on clinician self-report to assess the need for ongoing training and supervision and it may be necessary to train clinicians to accurately assess their own skill. Copyright © 2015 Elsevier Inc. All rights reserved.

Speaking from the Inside: Challenges Faced by Communication Researchers Investigating Disease-Related Issues in a Hospital Setting.

PubMed

Bourquin, Céline; Stiefel, Friedrich; Singy, Pascal

2015-09-01

This commentary came from within the framework of integrating the humanities in medicine and from accompanying research on disease-related issues by teams involving clinicians and researchers in medical humanities. The purpose is to reflect on the challenges faced by researchers when conducting emotionally laden research and on how they impact observations and subsequent research findings. This commentary is furthermore a call to action since it promotes the institutionalization of a supportive context for medical humanities researchers who have not been trained to cope with sensitive medical topics in research. To that end, concrete recommendations regarding training and supervision were formulated.

The effectiveness of clinical teaching of mental health courses in nursing using clinical supervision and Kirkpatrick's model.

PubMed

Maddineshat, Maryam; Hashemi, Mitra; Besharati, Reza; Gholami, Sepideh; Ghavidel, Fatemeh

2018-01-01

Clinical experience associated with the fear and anxiety of nursing students in the psychiatric unit. Mental health nursing instructors find it challenging to teach nursing students to deal with patients with mental disorders in an environment where they need to provide patient teaching and clinical decision-making based on evidence and new technology. To measure the effectiveness of clinical teaching of mental health courses in nursing using clinical supervision and Kirkpatrick's model evaluation in the psychiatry unit of Imam Reza Hospital, Bojnurd, Iran. This cross-sectional study was carried out from 2011 to 2016 on 76 nursing students from a university as part of a clinical mental health course in two semesters. The students were selected by a non-probable convenient sampling method. After completing their clinical education, each student responded to checklist questions based on the four-level Kirkpatrick's model evaluation and open questions relating to clinical supervision. Finally, all data was analyzed using the SPSS version 16. The students have evaluated clinical supervision as a useful approach, and appreciated the instructor's supportive behavior during teaching and imparting clinical skills. This has made them feel relaxed at the end of the clinical teaching course. In addition, in the evaluation through Kirkpatrick's model, more than 70% of the students have been satisfied with the method of conducting the teaching and average score of nursing students' attitude toward mental health students: Their mean self-confidence score was 18.33±1.69, and the mean score of their performance in the study was evaluated to be 93.74±5.3 from 100 points. The results of clinical mental health teaching through clinical supervision and Kirkpatrick's model evaluation show that the satisfaction, self-esteem, attitude, and skill of nursing students are excellent, thereby portraying the effectiveness of clinical teaching. But this program still needs to be reformed. To establish long-term goals and obtain knowledge and clinical skills of nursing, it is recommended to develop a curriculum and evaluate it appropriately.

Do Patients Understand the Role of Resident Physicians in the Operating Room? A Survey of Gynaecology Patients.

PubMed

Cantor, Arielle; Flood, Catherine; Boutin, Savanna; Regan, Shauna; Ross, Sue

2018-01-01

Studies from disciplines outside gynaecology have found that most patients do not understand the clinical responsibilities allocated to physicians-in-training. No research on this topic has been published in gynaecology, despite litigation against gynaecological surgeons regarding the role of residents in surgery. The goal of this research was to explore what gynaecological surgery patients understand about the role of resident doctors. A questionnaire was distributed to female patients in gynaecological surgery pre-admission clinics in Edmonton, Alberta. Surveys included knowledge and opinion statements about residents' duties. Anonymous responses were entered into a secure database. Descriptive statistics were used to characterize the results. Of 108 participants, 83% understood that residents had a higher level of training than medical students, yet 40% were unsure whether residents were doctors. Almost one half (43%) of participants were uncertain whether residents required supervision, including while operating (20%). Most (92%) believed it was important to know their physician's level of training, yet only 63% reported knowing this information. Only 50% of participants would be comfortable with residents operating on them under supervision. A considerable number (56%) wanted to learn more about residents' roles. Patients do not fully understand the role of residents, and many are uncomfortable with trainees operating on them under supervision. Considering the significant role of residents in patient care, educating patients is essential to improve their comfort and the overall consent process. Copyright © 2018 Society of Obstetricians and Gynaecologists of Canada. Published by Elsevier Inc. All rights reserved.

Conditional High-Order Boltzmann Machines for Supervised Relation Learning.

PubMed

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

2017-09-01

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

Self-Observation and Self-Analysis in Teacher Training. Teacher Materials and Curriculum Together with Preliminary Findings on Their Use. Research Bulletin No. 14.

ERIC Educational Resources Information Center

Brusling, Christer; Tingsell, Jan-Gunnar

This new model for the supervision of student teachers utilizes videotaping hardware which allows the student teacher and his supervisor to evaluate teaching methods and behavior. Thus, the student teacher is better able to supervise himself. Employing Flanders Interaction Analysis, the student is able to interpret his teaching on closed-circuit…

On the unsupervised analysis of domain-specific Chinese texts

PubMed Central

Deng, Ke; Bol, Peter K.; Li, Kate J.; Liu, Jun S.

2016-01-01

With the growing availability of digitized text data both publicly and privately, there is a great need for effective computational tools to automatically extract information from texts. Because the Chinese language differs most significantly from alphabet-based languages in not specifying word boundaries, most existing Chinese text-mining methods require a prespecified vocabulary and/or a large relevant training corpus, which may not be available in some applications. We introduce an unsupervised method, top-down word discovery and segmentation (TopWORDS), for simultaneously discovering and segmenting words and phrases from large volumes of unstructured Chinese texts, and propose ways to order discovered words and conduct higher-level context analyses. TopWORDS is particularly useful for mining online and domain-specific texts where the underlying vocabulary is unknown or the texts of interest differ significantly from available training corpora. When outputs from TopWORDS are fed into context analysis tools such as topic modeling, word embedding, and association pattern finding, the results are as good as or better than that from using outputs of a supervised segmentation method. PMID:27185919

A practical guide to big data research in psychology.

PubMed

Chen, Eric Evan; Wojcik, Sean P

2016-12-01

The massive volume of data that now covers a wide variety of human behaviors offers researchers in psychology an unprecedented opportunity to conduct innovative theory- and data-driven field research. This article is a practical guide to conducting big data research, covering data management, acquisition, processing, and analytics (including key supervised and unsupervised learning data mining methods). It is accompanied by walkthrough tutorials on data acquisition, text analysis with latent Dirichlet allocation topic modeling, and classification with support vector machines. Big data practitioners in academia, industry, and the community have built a comprehensive base of tools and knowledge that makes big data research accessible to researchers in a broad range of fields. However, big data research does require knowledge of software programming and a different analytical mindset. For those willing to acquire the requisite skills, innovative analyses of unexpected or previously untapped data sources can offer fresh ways to develop, test, and extend theories. When conducted with care and respect, big data research can become an essential complement to traditional research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

An integrated network of Arabidopsis growth regulators and its use for gene prioritization.

PubMed

Sabaghian, Ehsan; Drebert, Zuzanna; Inzé, Dirk; Saeys, Yvan

2015-12-01

Elucidating the molecular mechanisms that govern plant growth has been an important topic in plant research, and current advances in large-scale data generation call for computational tools that efficiently combine these different data sources to generate novel hypotheses. In this work, we present a novel, integrated network that combines multiple large-scale data sources to characterize growth regulatory genes in Arabidopsis, one of the main plant model organisms. The contributions of this work are twofold: first, we characterized a set of carefully selected growth regulators with respect to their connectivity patterns in the integrated network, and, subsequently, we explored to which extent these connectivity patterns can be used to suggest new growth regulators. Using a large-scale comparative study, we designed new supervised machine learning methods to prioritize growth regulators. Our results show that these methods significantly improve current state-of-the-art prioritization techniques, and are able to suggest meaningful new growth regulators. In addition, the integrated network is made available to the scientific community, providing a rich data source that will be useful for many biological processes, not necessarily restricted to plant growth.

LDA-Based Unified Topic Modeling for Similar TV User Grouping and TV Program Recommendation.

PubMed

Pyo, Shinjee; Kim, Eunhui; Kim, Munchurl

2015-08-01

Social TV is a social media service via TV and social networks through which TV users exchange their experiences about TV programs that they are viewing. For social TV service, two technical aspects are envisioned: grouping of similar TV users to create social TV communities and recommending TV programs based on group and personal interests for personalizing TV. In this paper, we propose a unified topic model based on grouping of similar TV users and recommending TV programs as a social TV service. The proposed unified topic model employs two latent Dirichlet allocation (LDA) models. One is a topic model of TV users, and the other is a topic model of the description words for viewed TV programs. The two LDA models are then integrated via a topic proportion parameter for TV programs, which enforces the grouping of similar TV users and associated description words for watched TV programs at the same time in a unified topic modeling framework. The unified model identifies the semantic relation between TV user groups and TV program description word groups so that more meaningful TV program recommendations can be made. The unified topic model also overcomes an item ramp-up problem such that new TV programs can be reliably recommended to TV users. Furthermore, from the topic model of TV users, TV users with similar tastes can be grouped as topics, which can then be recommended as social TV communities. To verify our proposed method of unified topic-modeling-based TV user grouping and TV program recommendation for social TV services, in our experiments, we used real TV viewing history data and electronic program guide data from a seven-month period collected by a TV poll agency. The experimental results show that the proposed unified topic model yields an average 81.4% precision for 50 topics in TV program recommendation and its performance is an average of 6.5% higher than that of the topic model of TV users only. For TV user prediction with new TV programs, the average prediction precision was 79.6%. Also, we showed the superiority of our proposed model in terms of both topic modeling performance and recommendation performance compared to two related topic models such as polylingual topic model and bilingual topic model.

Arrangement and Applying of Movement Patterns in the Cerebellum Based on Semi-supervised Learning.

PubMed

Solouki, Saeed; Pooyan, Mohammad

2016-06-01

Biological control systems have long been studied as a possible inspiration for the construction of robotic controllers. The cerebellum is known to be involved in the production and learning of smooth, coordinated movements. Therefore, highly regular structure of the cerebellum has been in the core of attention in theoretical and computational modeling. However, most of these models reflect some special features of the cerebellum without regarding the whole motor command computational process. In this paper, we try to make a logical relation between the most significant models of the cerebellum and introduce a new learning strategy to arrange the movement patterns: cerebellar modular arrangement and applying of movement patterns based on semi-supervised learning (CMAPS). We assume here the cerebellum like a big archive of patterns that has an efficient organization to classify and recall them. The main idea is to achieve an optimal use of memory locations by more than just a supervised learning and classification algorithm. Surely, more experimental and physiological researches are needed to confirm our hypothesis.

Evaluating topic model interpretability from a primary care physician perspective.

PubMed

Arnold, Corey W; Oh, Andrea; Chen, Shawn; Speier, William

2016-02-01

Probabilistic topic models provide an unsupervised method for analyzing unstructured text. These models discover semantically coherent combinations of words (topics) that could be integrated in a clinical automatic summarization system for primary care physicians performing chart review. However, the human interpretability of topics discovered from clinical reports is unknown. Our objective is to assess the coherence of topics and their ability to represent the contents of clinical reports from a primary care physician's point of view. Three latent Dirichlet allocation models (50 topics, 100 topics, and 150 topics) were fit to a large collection of clinical reports. Topics were manually evaluated by primary care physicians and graduate students. Wilcoxon Signed-Rank Tests for Paired Samples were used to evaluate differences between different topic models, while differences in performance between students and primary care physicians (PCPs) were tested using Mann-Whitney U tests for each of the tasks. While the 150-topic model produced the best log likelihood, participants were most accurate at identifying words that did not belong in topics learned by the 100-topic model, suggesting that 100 topics provides better relative granularity of discovered semantic themes for the data set used in this study. Models were comparable in their ability to represent the contents of documents. Primary care physicians significantly outperformed students in both tasks. This work establishes a baseline of interpretability for topic models trained with clinical reports, and provides insights on the appropriateness of using topic models for informatics applications. Our results indicate that PCPs find discovered topics more coherent and representative of clinical reports relative to students, warranting further research into their use for automatic summarization. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluating Topic Model Interpretability from a Primary Care Physician Perspective

PubMed Central

Arnold, Corey W.; Oh, Andrea; Chen, Shawn; Speier, William

2015-01-01

Background and Objective Probabilistic topic models provide an unsupervised method for analyzing unstructured text. These models discover semantically coherent combinations of words (topics) that could be integrated in a clinical automatic summarization system for primary care physicians performing chart review. However, the human interpretability of topics discovered from clinical reports is unknown. Our objective is to assess the coherence of topics and their ability to represent the contents of clinical reports from a primary care physician’s point of view. Methods Three latent Dirichlet allocation models (50 topics, 100 topics, and 150 topics) were fit to a large collection of clinical reports. Topics were manually evaluated by primary care physicians and graduate students. Wilcoxon Signed-Rank Tests for Paired Samples were used to evaluate differences between different topic models, while differences in performance between students and primary care physicians (PCPs) were tested using Mann-Whitney U tests for each of the tasks. Results While the 150-topic model produced the best log likelihood, participants were most accurate at identifying words that did not belong in topics learned by the 100-topic model, suggesting that 100 topics provides better relative granularity of discovered semantic themes for the data set used in this study. Models were comparable in their ability to represent the contents of documents. Primary care physicians significantly outperformed students in both tasks. Conclusion This work establishes a baseline of interpretability for topic models trained with clinical reports, and provides insights on the appropriateness of using topic models for informatics applications. Our results indicate that PCPs find discovered topics more coherent and representative of clinical reports relative to students, warranting further research into their use for automatic summarization. PMID:26614020

Educating psychotherapy supervisors.

PubMed

Watkins, C Edward

2012-01-01

What do we know clinically and empirically about the education of psychotherapy supervisors? In this paper, I attempt to address that question by: (1) reviewing briefly current thinking about psychotherapy supervisor training; and (2) examining the available research where supervisor training and supervision have been studied. The importance of such matters as training format and methods, supervision topics for study, supervisor development, and supervisor competencies are considered, and some prototypical, competency-based supervisor training programs that hold educational promise are identified and described. Twenty supervisor training studies are critiqued, and their implications for practice and research are examined. Based on this review of training programs and research, the following conclusions are drawn: (1) the clinical validity of supervisor education appears to be strong, solid, and sound, (2) although research suggests that supervisor training can have value in stimulating the development of supervisor trainees and better preparing them for the supervisory role, any such base of empirical support or validity should be regarded as tentative at best; and (3) the most formidable challenge for psychotherapy supervisor education may well be correcting the imbalance that currently exists between clinical and empirical validity and "raising the bar" on the rigor, relevance, and replicability of future supervisor training research.

Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior

PubMed Central

Gris, Katsiaryna V.; Coutu, Jean-Philippe; Gris, Denis

2017-01-01

Quantifying behavior is a challenge for scientists studying neuroscience, ethology, psychology, pathology, etc. Until now, behavior was mostly considered as qualitative descriptions of postures or labor intensive counting of bouts of individual movements. Many prominent behavioral scientists conducted studies describing postures of mice and rats, depicting step by step eating, grooming, courting, and other behaviors. Automated video assessment technologies permit scientists to quantify daily behavioral patterns/routines, social interactions, and postural changes in an unbiased manner. Here, we extensively reviewed published research on the topic of the structural blocks of behavior and proposed a structure of behavior based on the latest publications. We discuss the importance of defining a clear structure of behavior to allow professionals to write viable algorithms. We presented a discussion of technologies that are used in automated video assessment of behavior in mice and rats. We considered advantages and limitations of supervised and unsupervised learning. We presented the latest scientific discoveries that were made using automated video assessment. In conclusion, we proposed that the automated quantitative approach to evaluating animal behavior is the future of understanding the effect of brain signaling, pathologies, genetic content, and environment on behavior. PMID:28804452

[The German academic degree "Dr. med." is better than its reputation. Results of a questionnaire of doctoral students].

PubMed

Pabst, R; Park, D-H; Paulmann, V

2012-11-01

Recently there were mostly emotional debates about the scientific background and relevance of the German academic title "Dr. med.", while objective data are scarce. When submitting their doctoral thesis at the Medical School of Hannover students were asked anonymously about the type, topic, duration, quality of supervision as well as frequency and type of publication of the results. 180 doctoral candidates (62% women) participated in the study. The supervision was graded as good by the majority of students. The duration working on the thesis was equivalent to 47 weeks of a full time employment. There was some negative influence in participating in lectures and courses. Nearly all participants (98%) would recommend younger students to work on a dissertation as they had done themselves in parallel to the curriculum. The ability of how to interprete scientific data was assumed to be positively influenced. About two thirds stated that the results had been published in original articles at the time of submitting the thesis. More data from other medical faculties are needed to document the relevance of the medical dissertation to replace the emotional by a more rational debate. © Georg Thieme Verlag KG Stuttgart · New York.

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.

Weakly Supervised Dictionary Learning

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

An Alternative Approach for Supportive Supervision and Skill Measurements of Health Workers for Integrated Management of Neonatal and Childhood Illnesses Program in 10 Districts of Haryana.

PubMed

Aggarwal, Arun K; Gupta, Rakesh; Das, Dhritiman; Dhakar, Anar S; Sharma, Gourav; Anand, Himani; Kaur, Kamalpreet; Sheoran, Kiran; Dalpath, Suresh; Khatri, Jaidev; Gupta, Madhu

2018-01-01

"Integrated Management of Neonatal and Childhood Illnesses" (IMNCI) needs regular supportive supervision (SS). The aim of this study was to find suitable SS model for implementing IMNCI. This was a prospective interventional study in 10 high-focus districts of Haryana. Two methods of SS were used: (a) visit to subcenters and home visits (model 1) and (b) organization of IMNCI clinics/camps at primary health center (PHC) and community health center (CHC) (model 2). Skill scores were measured at different time points. Routine IMNCI data from study block and randomly selected control block of each district were retrieved for 4 months before and after the training and supervision. Change in percentage mean skill score difference and percentage difference in median number of children were assessed in two areas. Mean skill scores increased significantly from 2.1 (pretest) to 7.0 (posttest 1). Supportive supervisory visits sustained and improved skill scores. While model 2 of SS could positively involve health system officials, model 1 was not well received. Outcome indicator in terms of number of children assessed showed a significant improvement in intervention areas. SS in IMNCI clinics/camps at PHC/CHC level and innovative skill scoring method is a promising approach.

Block versus longitudinal integrated clerkships: students' views of rural clinical supervision.

PubMed

Witney, Martin; Isaac, Vivian; Playford, Denese; Walker, Leesa; Garne, David; Walters, Lucie

2018-07-01

Medical students undertaking longitudinal integrated clerkships (LICs) train in multiple disciplines concurrently, compared with students in block rotations who typically address one medical discipline at a time. Current research suggests that LICs afford students increased access to patients and continuity of clinical supervision. However, these factors are less of an issue in rural placements where there are fewer learners. The aim of this study was to compare rural LIC and rural block rotation students' reported experiences of clinical supervision. De-identified data from the 2015 version of the Australian national rural clinical schools (RCSs) exit survey was used to compare students in LICs with those in block rotations in relation to how they evaluate their clinical supervisors and how they rate their own clinical competence. Multivariate general linear modelling showed no association between placement type (LIC versus Block) and reported clinical supervision. The single independent predictor of positive perception of clinical supervisors was choosing an RCS as a first preference. There was also no association between placement type (LIC versus Block) and self-rated clinical competence. Instead, the clinical supervision score and male gender predicted more positive self-ratings of clinical competence. The quality of clinical supervision in block placements and LIC programmes in rural Australian settings was reported by students as equivalent. © 2018 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Interesting examples of supervised continuous variable systems

NASA Technical Reports Server (NTRS)

Chase, Christopher; Serrano, Joe; Ramadge, Peter

1990-01-01

The authors analyze two simple deterministic flow models for multiple buffer servers which are examples of the supervision of continuous variable systems by a discrete controller. These systems exhibit what may be regarded as the two extremes of complexity of the closed loop behavior: one is eventually periodic, the other is chaotic. The first example exhibits chaotic behavior that could be characterized statistically. The dual system, the switched server system, exhibits very predictable behavior, which is modeled by a finite state automaton. This research has application to multimodal discrete time systems where the controller can choose from a set of transition maps to implement.

Polarization in the social sciences: Assortative mixing in social science collaboration networks is resilient to interventions

NASA Astrophysics Data System (ADS)

Leifeld, Philip

2018-10-01

Academic collaboration in the social sciences is characterized by a polarization between hermeneutic and nomological researchers. This polarization is expressed in different publication strategies. The present article analyzes the complete co-authorship networks in a social science discipline in two separate countries over five years using an exponential random graph model. It examines whether and how assortative mixing in publication strategies is present and leads to a polarization in scientific collaboration. In the empirical analysis, assortative mixing is found to play a role in shaping the topology of the network and significantly explains collaboration. Co-authorship edges are more prevalent within each of the groups, but this mixing pattern does not fully account for the extent of polarization. Instead, a thought experiment reveals that other components of the complex system dampen or amplify polarization in the data-generating process and that microscopic interventions targeting behavior change with regard to assortativity would be hindered by the resilience of the system. The resilience to interventions is quantified in a series of simulations on the effect of microscopic behavior on macroscopic polarization. The empirical study controls for geographic proximity, supervision, and topical similarity (using a vector space model), and the interplay of these factors is likely responsible for this resilience. The paper also predicts the co-authorship network in one country based on the model of collaborations in the other country.

The Roles and Responsibilities of Paraprofessionals Who Work with Students with Visual Impairments in Public Schools as Recommended by Experts/Practitioners to Influence and Develop In-Service Training and Supervision

ERIC Educational Resources Information Center

Casias, Nicholas

2017-01-01

Purpose: The purpose of this study was to determine, through the feedback of experts, the roles and responsibilities, training needs, and supervision needs of paraprofessionals who work with students with visual impairments in public schools (within the itinerant orientation and mobility [O&M] service delivery model). Theoretical Framework:…

Rapid classification of heavy metal-exposed freshwater bacteria by infrared spectroscopy coupled with chemometrics using supervised method

NASA Astrophysics Data System (ADS)

Gurbanov, Rafig; Gozen, Ayse Gul; Severcan, Feride

2018-01-01

Rapid, cost-effective, sensitive and accurate methodologies to classify bacteria are still in the process of development. The major drawbacks of standard microbiological, molecular and immunological techniques call for the possible usage of infrared (IR) spectroscopy based supervised chemometric techniques. Previous applications of IR based chemometric methods have demonstrated outstanding findings in the classification of bacteria. Therefore, we have exploited an IR spectroscopy based chemometrics using supervised method namely Soft Independent Modeling of Class Analogy (SIMCA) technique for the first time to classify heavy metal-exposed bacteria to be used in the selection of suitable bacteria to evaluate their potential for environmental cleanup applications. Herein, we present the powerful differentiation and classification of laboratory strains (Escherichia coli and Staphylococcus aureus) and environmental isolates (Gordonia sp. and Microbacterium oxydans) of bacteria exposed to growth inhibitory concentrations of silver (Ag), cadmium (Cd) and lead (Pb). Our results demonstrated that SIMCA was able to differentiate all heavy metal-exposed and control groups from each other with 95% confidence level. Correct identification of randomly chosen test samples in their corresponding groups and high model distances between the classes were also achieved. We report, for the first time, the success of IR spectroscopy coupled with supervised chemometric technique SIMCA in classification of different bacteria under a given treatment.

Validation of automated supervised segmentation of multibeam backscatter data from the Chatham Rise, New Zealand

NASA Astrophysics Data System (ADS)

Hillman, Jess I. T.; Lamarche, Geoffroy; Pallentin, Arne; Pecher, Ingo A.; Gorman, Andrew R.; Schneider von Deimling, Jens

2018-06-01

Using automated supervised segmentation of multibeam backscatter data to delineate seafloor substrates is a relatively novel technique. Low-frequency multibeam echosounders (MBES), such as the 12-kHz EM120, present particular difficulties since the signal can penetrate several metres into the seafloor, depending on substrate type. We present a case study illustrating how a non-targeted dataset may be used to derive information from multibeam backscatter data regarding distribution of substrate types. The results allow us to assess limitations associated with low frequency MBES where sub-bottom layering is present, and test the accuracy of automated supervised segmentation performed using SonarScope® software. This is done through comparison of predicted and observed substrate from backscatter facies-derived classes and substrate data, reinforced using quantitative statistical analysis based on a confusion matrix. We use sediment samples, video transects and sub-bottom profiles acquired on the Chatham Rise, east of New Zealand. Inferences on the substrate types are made using the Generic Seafloor Acoustic Backscatter (GSAB) model, and the extents of the backscatter classes are delineated by automated supervised segmentation. Correlating substrate data to backscatter classes revealed that backscatter amplitude may correspond to lithologies up to 4 m below the seafloor. Our results emphasise several issues related to substrate characterisation using backscatter classification, primarily because the GSAB model does not only relate to grain size and roughness properties of substrate, but also accounts for other parameters that influence backscatter. Better understanding these limitations allows us to derive first-order interpretations of sediment properties from automated supervised segmentation.

“They put you on your toes”: Physical Therapists' Perceived Benefits from and Barriers to Supervising Students in the Clinical Setting

PubMed Central

Hanna, Elizabeth; Cott, Cheryl

2011-01-01

ABSTRACT Purpose: To identify the perceived benefits of and barriers to clinical supervision of physical therapy (PT) students. Method: In this qualitative descriptive study, three focus groups and six key-informant interviews were conducted with clinical physical therapists or administrators working in acute care, orthopaedic rehabilitation, or complex continuing care. Data were coded and analyzed for common ideas using a constant comparison approach. Results: Perceived barriers to supervising students tended to be extrinsic: time and space constraints, challenging or difficult students, and decreased autonomy or flexibility for the clinical physical therapists. Benefits tended to be intrinsic: teaching provided personal gratification by promoting reflective practice and exposing clinical educators to current knowledge. The culture of different health care institutions was an important factor in therapists' perceptions of student supervision. Conclusions: Despite different disciplines and models of supervision, there is considerable synchronicity in the issues reported by physical therapists and other disciplines. Embedding the value of clinical teaching in the institution, along with strong communication links among academic partners, institutions, and potential clinical faculty, may mitigate barriers and increase the commitment and satisfaction of teaching staff. PMID:22379263

Supportive supervision for volunteers to deliver reproductive health education: a cluster randomized trial.

PubMed

Singh, Debra; Negin, Joel; Orach, Christopher Garimoi; Cumming, Robert

2016-10-03

Community Health Volunteers (CHVs) can be effective in improving pregnancy and newborn outcomes through community education. Inadequate supervision of CHVs, whether due to poor planning, irregular visits, or ineffective supervisory methods, is, however, recognized as a weakness in many programs. There has been little research on best practice supervisory or accompaniment models. From March 2014 to February 2015 a proof of concept study was conducted to compare training alone versus training and supportive supervision by paid CHWs (n = 4) on the effectiveness of CHVs (n = 82) to deliver education about pregnancy, newborn care, family planning and hygiene. The pair-matched cluster randomized trial was conducted in eight villages (four intervention and four control) in Budondo sub-county in Jinja, Uganda. Increases in desired behaviors were seen in both the intervention and control arms over the study period. Both arms showed high retention rates of CHVs (95 %). At 1 year follow-up there was a significantly higher prevalence of installed and functioning tippy taps for hand washing (p < 0.002) in the intervention villages (47 %) than control villages (35 %). All outcome and process measures related to home-visits to homes with pregnant women and newborn babies favored the intervention villages. The CHVs in both groups implemented what they learnt and were role models in the community. A team of CHVs and CHWs can facilitate families accessing reproductive health care by addressing cultural norms and scientific misconceptions. Having a team of 2 CHWs to 40 CHVs enables close to community access to information, conversation and services. Supportive supervision involves creating a non-threatening, empowering environment in which both the CHV and the supervising CHW learn together and overcome obstacles that might otherwise demotivate the CHV. While the results seem promising for added value with supportive supervision for CHVs undertaking reproductive health activities, further research on a larger scale will be needed to substantiate the effect.

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

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.

A cost-benefit/cost-effectiveness analysis of proposed supervised injection facilities in Ottawa, Canada.

PubMed

Jozaghi, Ehsan; Reid, Andrew A; Andresen, Martin A; Juneau, Alexandre

2014-08-04

Supervised injection facilities (SIFs) are venues where people who inject drugs (PWID) have access to a clean and medically supervised environment in which they can safely inject their own illicit drugs. There is currently only one legal SIF in North America: Insite in Vancouver, British Columbia, Canada. The responses and feedback generated by the evaluations of Insite in Vancouver have been overwhelmingly positive. This study assesses whether the above mentioned facility in the Downtown Eastside of Vancouver needs to be expanded to other locations, more specifically that of Canada's capital city, Ottawa. The current study is aimed at contributing to the existing literature on health policy by conducting cost-benefit and cost-effective analyses for the opening of SIFs in Ottawa, Ontario. In particular, the costs of operating numerous SIFs in Ottawa was compared to the savings incurred; this was done after accounting for the prevention of new HIV and Hepatitis C (HCV) infections. To ensure accuracy, two distinct mathematical models and a sensitivity analysis were employed. The sensitivity analyses conducted with the models reveals the potential for SIFs in Ottawa to be a fiscally responsible harm reduction strategy for the prevention of HCV cases--when considered independently. With a baseline sharing rate of 19%, the cumulative annual cost model supported the establishment of two SIFs and the marginal annual cost model supported the establishment of a single SIF. More often, the prevention of HIV or HCV alone were not sufficient to justify the establishment cost-effectiveness; rather, only when both HIV and HCV are considered does sufficient economic support became apparent. Funded supervised injection facilities in Ottawa appear to be an efficient and effective use of financial resources in the public health domain.

A cost-benefit/cost-effectiveness analysis of proposed supervised injection facilities in Ottawa, Canada

PubMed Central

2014-01-01

Background Supervised injection facilities (SIFs) are venues where people who inject drugs (PWID) have access to a clean and medically supervised environment in which they can safely inject their own illicit drugs. There is currently only one legal SIF in North America: Insite in Vancouver, British Columbia, Canada. The responses and feedback generated by the evaluations of Insite in Vancouver have been overwhelmingly positive. This study assesses whether the above mentioned facility in the Downtown Eastside of Vancouver needs to be expanded to other locations, more specifically that of Canada’s capital city, Ottawa. Methods The current study is aimed at contributing to the existing literature on health policy by conducting cost-benefit and cost-effective analyses for the opening of SIFs in Ottawa, Ontario. In particular, the costs of operating numerous SIFs in Ottawa was compared to the savings incurred; this was done after accounting for the prevention of new HIV and Hepatitis C (HCV) infections. To ensure accuracy, two distinct mathematical models and a sensitivity analysis were employed. Results The sensitivity analyses conducted with the models reveals the potential for SIFs in Ottawa to be a fiscally responsible harm reduction strategy for the prevention of HCV cases – when considered independently. With a baseline sharing rate of 19%, the cumulative annual cost model supported the establishment of two SIFs and the marginal annual cost model supported the establishment of a single SIF. More often, the prevention of HIV or HCV alone were not sufficient to justify the establishment cost-effectiveness; rather, only when both HIV and HCV are considered does sufficient economic support became apparent. Conclusions Funded supervised injection facilities in Ottawa appear to be an efficient and effective use of financial resources in the public health domain. PMID:25091704

Using Supervised Learning Techniques for Diagnosis of Dynamic Systems

DTIC Science & Technology

2002-05-04

M. Gasca 2 , Juan A. Ortega2 Abstract. This paper describes an approach based on supervised diagnose systems faults are needed to maintain the systems...labelled, data will be used for this purpose [5] [6]. treated to add additional information about the running of system. In [7] the fundaments of the based ...8] proposes classification tool to the set of labelled and treated data. This a consistency- based approach with qualitative models. way, any

A Prerecognition Model for Hot Topic Discovery Based on Microblogging Data

PubMed Central

Zhu, Tongyu

2014-01-01

The microblogging is prevailing since its easy and anonymous information sharing at Internet, which also brings the issue of dispersing negative topics, or even rumors. Many researchers have focused on how to find and trace emerging topics for analysis. When adopting topic detection and tracking techniques to find hot topics with streamed microblogging data, it will meet obstacles like streamed microblogging data clustering, topic hotness definition, and emerging hot topic discovery. This paper schemes a novel prerecognition model for hot topic discovery. In this model, the concepts of the topic life cycle, the hot velocity, and the hot acceleration are promoted to calculate the change of topic hotness, which aims to discover those emerging hot topics before they boost and break out. Our experiments show that this new model would help to discover potential hot topics efficiently and achieve considerable performance. PMID:25254235

A prerecognition model for hot topic discovery based on microblogging data.

PubMed

Zhu, Tongyu; Yu, Jianjun

2014-01-01

The microblogging is prevailing since its easy and anonymous information sharing at Internet, which also brings the issue of dispersing negative topics, or even rumors. Many researchers have focused on how to find and trace emerging topics for analysis. When adopting topic detection and tracking techniques to find hot topics with streamed microblogging data, it will meet obstacles like streamed microblogging data clustering, topic hotness definition, and emerging hot topic discovery. This paper schemes a novel prerecognition model for hot topic discovery. In this model, the concepts of the topic life cycle, the hot velocity, and the hot acceleration are promoted to calculate the change of topic hotness, which aims to discover those emerging hot topics before they boost and break out. Our experiments show that this new model would help to discover potential hot topics efficiently and achieve considerable performance.

Evaluation of a 2 to 1 peer placement supervision model by physiotherapy students and their educators.

PubMed

Alpine, Lucy M; Caldas, Francieli Tanji; Barrett, Emer M

2018-04-02

The objective of the study was to investigate student and practice educator evaluations of practice placements using a structured 2 to 1 supervision and implementation model. Cross-sectional pilot study set in clinical sites providing placements for physiotherapy students in Ireland. Students and practice educators completing a 2.1 peer placement between 2013 and 2015 participated. A self-reported questionnaire which measured indicators linked to quality assured placements was used. Three open-ended questions captured comments on the benefits and challenges associated with the 2 to 1 model. Ten students (10/20; 50% response rate) and 10 practice educators (10/10; 100% response rate) responded to the questionnaire. Student responses included four pairs of students and one student from a further two pairs. There was generally positive agreement with the questionnaire indicating that placements using the 2 to 1 model were positively evaluated by participants. There were no significant differences between students and practice educators. The main benefits of the 2 to 1 model were shared learning experiences, a peer supported environment, and the development of peer evaluation and feedback skills by students. A key component of the model was the peer scripting process which provided time for reflection, self-evaluation, and peer review. 2 to 1 placements were positively evaluated by students and educators when supported by a structured supervision model. Clear guidance to students on the provision of peer feedback and support for educators providing feedback to two different students is recommended.

Developing psychotherapists’ competence through clinical supervision: protocol for a qualitative study of supervisory dyads

PubMed Central

2013-01-01

Background Mental health professionals face unique demands and stressors in their work, resulting in high rates of burnout and distress. Clinical supervision is a widely adopted and valued mechanism of professional support, development, and accountability, despite the very limited evidence of specific impacts on therapist or client outcomes. The current study aims to address this by exploring how psychotherapists develop competence through clinical supervision and what impact this has on the supervisees’ practice and their clients’ outcomes. This paper provides a rationale for the study and describes the protocol for an in-depth qualitative study of supervisory dyads, highlighting how it addresses gaps in the literature. Methods/Design The study of 16–20 supervisor-supervisee dyads uses a qualitative mixed method design, with two phases. In phase one, supervisors who are nominated as expert by their peers are interviewed about their supervision practice. In phase two, supervisors record a supervision session with a consenting supervisee; interpersonal process recall interviews are conducted separately with supervisor and supervisee to reflect in depth on the teaching and learning processes occurring. All interviews will be transcribed, coded and analysed to identify the processes that build competence, using a modified form of Consensual Qualitative Research (CQR) strategies. Using a theory-building case study method, data from both phases of the study will be integrated to develop a model describing the processes that build competence and support wellbeing in practising psychotherapists, reflecting the accumulated wisdom of the expert supervisors. Discussion The study addresses past study limitations by examining expert supervisors and their supervisory interactions, by reflecting on actual supervision sessions, and by using dyadic analysis of the supervisory pairs. The study findings will inform the development of future supervision training and practice and identify fruitful avenues for future research. PMID:23298408

Characteristics of Infant Deaths during Sleep While Under Nonparental Supervision.

PubMed

Lagon, Elena; Moon, Rachel Y; Colvin, Jeffrey D

2018-03-28

To compare risk factors for infant sleep-related deaths under the supervision of parents and nonparents. We conducted a secondary analysis of sleep-related infant deaths from 2004 to 2014 in the National Center for Fatality Review and Prevention Child Death Review Case Reporting System. The main exposure was supervisor at time of death. Primary outcomes included sleep position, location, and objects in the environment. Risk factors for parental vs nonparental supervisor were compared using χ 2 and multivariable logistic regression models. Risk factors associated with different nonparental supervisors were analyzed using χ 2 . Of the 10 490 deaths, 1375 (13.1%) occurred under nonparental supervision. Infants who died under nonparental supervision had higher adjusted odds of dying outside the home (OR 12.87, 95% CI 11.31-14.65), being placed prone (OR 1.61, 95% CI 1.39-1.86) or on their side (OR 1.35, 95% CI 1.12-1.62), or being found prone (OR 1.74, 95% CI 1.50-2.02). Among infants who died under nonparental supervision, those supervised by relatives or friends were more often placed on an adult bed or couch for sleep and bed sharing (P < .0001), and to have objects in the sleep environment (P = .01). Infants who died of sleep-related causes under nonparental supervision were more likely to have been placed nonsupine. Among nonparental supervisors, relatives and friends were more likely to use unsafe sleep environments, such as locations other than a crib or bassinet and bed sharing. Pediatricians should educate parents that all caregivers must always follow safe sleep practices. Copyright © 2018 Elsevier Inc. All rights reserved.

Developing psychotherapists' competence through clinical supervision: protocol for a qualitative study of supervisory dyads.

PubMed

Schofield, Margot J; Grant, Jan

2013-01-08

Mental health professionals face unique demands and stressors in their work, resulting in high rates of burnout and distress. Clinical supervision is a widely adopted and valued mechanism of professional support, development, and accountability, despite the very limited evidence of specific impacts on therapist or client outcomes. The current study aims to address this by exploring how psychotherapists develop competence through clinical supervision and what impact this has on the supervisees' practice and their clients' outcomes. This paper provides a rationale for the study and describes the protocol for an in-depth qualitative study of supervisory dyads, highlighting how it addresses gaps in the literature. The study of 16-20 supervisor-supervisee dyads uses a qualitative mixed method design, with two phases. In phase one, supervisors who are nominated as expert by their peers are interviewed about their supervision practice. In phase two, supervisors record a supervision session with a consenting supervisee; interpersonal process recall interviews are conducted separately with supervisor and supervisee to reflect in depth on the teaching and learning processes occurring. All interviews will be transcribed, coded and analysed to identify the processes that build competence, using a modified form of Consensual Qualitative Research (CQR) strategies. Using a theory-building case study method, data from both phases of the study will be integrated to develop a model describing the processes that build competence and support wellbeing in practising psychotherapists, reflecting the accumulated wisdom of the expert supervisors. The study addresses past study limitations by examining expert supervisors and their supervisory interactions, by reflecting on actual supervision sessions, and by using dyadic analysis of the supervisory pairs. The study findings will inform the development of future supervision training and practice and identify fruitful avenues for future research.

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.

[Undergraduate training in physician-patient communication].

PubMed

Berney, Alexandre; Pécoud, Pascale; Bourquin, Céline; Stiefel, Friedrich

2017-02-08

In addition to providing psychiatric care to patients with somatic diseases, liaison psychiatry plays an important role in the teaching of the relational aspects of the clinical encounter between patients and clinicians. This series of three articles proposes a critical reflection on this topic, and presents examples of undergraduate and postgraduate teaching programs developed by the psychiatric liaison service at Lausanne University Hospital. This article describes the general context of undergraduate teaching, and focuses on our training with simulated patient of a breaking bad news situation, taking place during the fourth year of medical studies. Individual supervision, provided for each student, is discussed as a relatively unique opportunity within the curriculum of medical school.

HMI conventions for process control graphics.

PubMed

Pikaar, Ruud N

2012-01-01

Process operators supervise and control complex processes. To enable the operator to do an adequate job, instrumentation and process control engineers need to address several related topics, such as console design, information design, navigation, and alarm management. In process control upgrade projects, usually a 1:1 conversion of existing graphics is proposed. This paper suggests another approach, efficiently leading to a reduced number of new powerful process graphics, supported by a permanent process overview displays. In addition a road map for structuring content (process information) and conventions for the presentation of objects, symbols, and so on, has been developed. The impact of the human factors engineering approach on process control upgrade projects is illustrated by several cases.

Effective and ineffective supervision in postgraduate dental education: a qualitative study.

PubMed

Subramanian, J; Anderson, V R; Morgaine, K C; Thomson, W M

2013-02-01

Research suggests that students' perceptions should be considered in any discussion of their education, but there has been no systematic examination of New Zealand postgraduate dental students' learning experiences. This study aimed to obtain in-depth qualitative insights into student and graduate perceptions of effective and ineffective learning in postgraduate dental education. Data were collected in 2010 using semi-structured individual interviews. Participants included final-year students and graduates of the University of Otago Doctor of Clinical Dentistry programme. Using the Critical Incident Technique, participants were asked to describe atleast one effective and one ineffective learning experience in detail. Interview transcripts were analysed using a general inductive approach. Broad themes which emerged included supervisory approaches, characteristics of the learning process, and the physical learning environment. This paper considers students' and graduates' perceptions of postgraduate supervision in dentistry as it promotes or precludes effective learning. Effective learning was associated by participants with approachable and supportive supervisory practices, and technique demonstrations accompanied by explicit explanations. Ineffective learning was associated with minimal supervisor demonstrations and guidance (particularly when beginning postgraduate study), and aggressive, discriminatory and/or culturally insensitive supervisory approaches. Participants' responses provided rich, in-depth insights into their reflections and understandings of effective and ineffective approaches to supervision as it influenced their learning in the clinical and research settings. These findings provide a starting point for the development of curriculum and supervisory practices, enhancement of supervisory and mentoring approaches, and the design of continuing education programmes for supervisors at an institutional level. Additionally, these findings might also stimulate topics for reflection and discussion amongst dental educators and administrators more broadly. © 2012 John Wiley & Sons A/S.

Duty hours and perceived competence in surgery: are interns ready?

PubMed

Lindeman, Brenessa M; Sacks, Bethany C; Hirose, Kenzo; Lipsett, Pamela A

2014-07-01

A fundamental shift in the structure of many surgical training programs has occurred after the July 2011 rule changes. Our intern didactic program was intensified in 2011 with targeted lectures, laboratories, and clinical cases as well as direct supervision until competency was achieved for basic clinical problems. We sought to compare interns' perceived preparedness throughout and at the end of the academic years before and after July 2011. Intern perceptions of preparedness to manage common clinical scenarios and perform procedures in general surgery were serially surveyed in academic years ending in 2011 and 2012 based on the Residency Review Committee supervision guidelines. Interns felt less prepared across all measured domains from 2011-2012. Interns felt significantly less prepared to manage hypotension (3.00/4 points to 2.67/4 points; P=0.04), place a tube thoracostomy (2.45/4 points to 1.92/4 points; P=0.04), or perform an inguinal hernia repair (1.91/4 points to 0.92/4 points; P=0.01) without supervision. Interns were also significantly less likely to agree that they were able to gain clinical skills based on experience (4.31/5 points versus 4.15/5 points; P=0.02). Longitudinal analysis throughout internship demonstrated improved preparedness to manage common clinical problems and perform procedures between the second and the fifth months of internship. First-year residents after July 2011 felt less prepared in the topics surveyed than those before July 2011. Interns made the greatest gains in preparedness between months 2 and 5, suggesting that despite planned interventions, no substitute currently exists for actual clinical experience. Planned educational interventions to improve intern preparedness are also indicated. Copyright © 2014 Elsevier Inc. All rights reserved.

(Machine) learning to do more with less

NASA Astrophysics Data System (ADS)

Cohen, Timothy; Freytsis, Marat; Ostdiek, Bryan

2018-02-01

Determining the best method for training a machine learning algorithm is critical to maximizing its ability to classify data. In this paper, we compare the standard "fully supervised" approach (which relies on knowledge of event-by-event truth-level labels) with a recent proposal that instead utilizes class ratios as the only discriminating information provided during training. This so-called "weakly supervised" technique has access to less information than the fully supervised method and yet is still able to yield impressive discriminating power. In addition, weak supervision seems particularly well suited to particle physics since quantum mechanics is incompatible with the notion of mapping an individual event onto any single Feynman diagram. We examine the technique in detail — both analytically and numerically — with a focus on the robustness to issues of mischaracterizing the training samples. Weakly supervised networks turn out to be remarkably insensitive to a class of systematic mismodeling. Furthermore, we demonstrate that the event level outputs for weakly versus fully supervised networks are probing different kinematics, even though the numerical quality metrics are essentially identical. This implies that it should be possible to improve the overall classification ability by combining the output from the two types of networks. For concreteness, we apply this technology to a signature of beyond the Standard Model physics to demonstrate that all these impressive features continue to hold in a scenario of relevance to the LHC. Example code is provided on GitHub.

Two-echelon logistics service supply chain decision game considering quality supervision

NASA Astrophysics Data System (ADS)

Shi, Jiaying

2017-10-01

Due to the increasing importance of supply chain logistics service, we established the Stackelberg game model between single integrator and single subcontractors under decentralized and centralized circumstances, and found that logistics services integrators as a leader prefer centralized decision-making but logistics service subcontractors tend to the decentralized decision-making. Then, we further analyzed why subcontractor chose to deceive and rebuilt a principal-agent game model to monitor the logistics services quality of them. Mixed Strategy Nash equilibrium and related parameters were discussed. The results show that strengthening the supervision and coordination can improve the quality level of logistics service supply chain.

Supervised interpretation of echocardiograms with a psychological model of expert supervision

NASA Astrophysics Data System (ADS)

Revankar, Shriram V.; Sher, David B.; Shalin, Valerie L.; Ramamurthy, Maya

1993-07-01

We have developed a collaborative scheme that facilitates active human supervision of the binary segmentation of an echocardiogram. The scheme complements the reliability of a human expert with the precision of segmentation algorithms. In the developed system, an expert user compares the computer generated segmentation with the original image in a user friendly graphics environment, and interactively indicates the incorrectly classified regions either by pointing or by circling. The precise boundaries of the indicated regions are computed by studying original image properties at that region, and a human visual attention distribution map obtained from the published psychological and psychophysical research. We use the developed system to extract contours of heart chambers from a sequence of two dimensional echocardiograms. We are currently extending this method to incorporate a richer set of inputs from the human supervisor, to facilitate multi-classification of image regions depending on their functionality. We are integrating into our system the knowledge related constraints that cardiologists use, to improve the capabilities of our existing system. This extension involves developing a psychological model of expert reasoning, functional and relational models of typical views in echocardiograms, and corresponding interface modifications to map the suggested actions to image processing algorithms.

Method of Grassland Information Extraction Based on Multi-Level Segmentation and Cart Model

NASA Astrophysics Data System (ADS)

Qiao, Y.; Chen, T.; He, J.; Wen, Q.; Liu, F.; Wang, Z.

2018-04-01

It is difficult to extract grassland accurately by traditional classification methods, such as supervised method based on pixels or objects. This paper proposed a new method combing the multi-level segmentation with CART (classification and regression tree) model. The multi-level segmentation which combined the multi-resolution segmentation and the spectral difference segmentation could avoid the over and insufficient segmentation seen in the single segmentation mode. The CART model was established based on the spectral characteristics and texture feature which were excavated from training sample data. Xilinhaote City in Inner Mongolia Autonomous Region was chosen as the typical study area and the proposed method was verified by using visual interpretation results as approximate truth value. Meanwhile, the comparison with the nearest neighbor supervised classification method was obtained. The experimental results showed that the total precision of classification and the Kappa coefficient of the proposed method was 95 % and 0.9, respectively. However, the total precision of classification and the Kappa coefficient of the nearest neighbor supervised classification method was 80 % and 0.56, respectively. The result suggested that the accuracy of classification proposed in this paper was higher than the nearest neighbor supervised classification method. The experiment certificated that the proposed method was an effective extraction method of grassland information, which could enhance the boundary of grassland classification and avoid the restriction of grassland distribution scale. This method was also applicable to the extraction of grassland information in other regions with complicated spatial features, which could avoid the interference of woodland, arable land and water body effectively.

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.

Evidence-based treatment and supervision practices for co-occurring mental and substance use disorders in the criminal justice system.

PubMed

Peters, Roger H; Young, M Scott; Rojas, Elizabeth C; Gorey, Claire M

2017-07-01

Over seven million persons in the United States are supervised by the criminal justice system, including many who have co-occurring mental and substance use disorders (CODs). This population is at high risk for recidivism and presents numerous challenges to those working in the justice system. To provide a contemporary review of the existing research and examine key issues and evidence-based treatment and supervision practices related to CODs in the justice system. We reviewed COD research involving offenders that has been conducted over the past 20 years and provide an analysis of key findings. Several empirically supported frameworks are available to guide services for offenders who have CODs, including Integrated Dual Disorders Treatment (IDDT), the Risk-Need-Responsivity (RNR) model, and Cognitive-Behavioral Therapy (CBT). Evidence-based services include integrated assessment that addresses both sets of disorders and the risk for criminal recidivism. Although several evidence-based COD interventions have been implemented at different points in the justice system, there remains a significant gap in services for offenders who have CODs. Existing program models include Crisis Intervention Teams (CIT), day reporting centers, specialized community supervision teams, pre- and post-booking diversion programs, and treatment-based courts (e.g., drug courts, mental health courts, COD dockets). Jail-based COD treatment programs provide stabilization of acute symptoms, medication consultation, and triage to community services, while longer-term prison COD programs feature Modified Therapeutic Communities (MTCs). Despite the availability of multiple evidence-based interventions that have been implemented across diverse justice system settings, these services are not sufficiently used to address the scope of treatment and supervision needs among offenders with CODs.

Benchmarking protein classification algorithms via supervised cross-validation.

PubMed

Kertész-Farkas, Attila; Dhir, Somdutta; Sonego, Paolo; Pacurar, Mircea; Netoteia, Sergiu; Nijveen, Harm; Kuzniar, Arnold; Leunissen, Jack A M; Kocsor, András; Pongor, Sándor

2008-04-24

Development and testing of protein classification algorithms are hampered by the fact that the protein universe is characterized by groups vastly different in the number of members, in average protein size, similarity within group, etc. Datasets based on traditional cross-validation (k-fold, leave-one-out, etc.) may not give reliable estimates on how an algorithm will generalize to novel, distantly related subtypes of the known protein classes. Supervised cross-validation, i.e., selection of test and train sets according to the known subtypes within a database has been successfully used earlier in conjunction with the SCOP database. Our goal was to extend this principle to other databases and to design standardized benchmark datasets for protein classification. Hierarchical classification trees of protein categories provide a simple and general framework for designing supervised cross-validation strategies for protein classification. Benchmark datasets can be designed at various levels of the concept hierarchy using a simple graph-theoretic distance. A combination of supervised and random sampling was selected to construct reduced size model datasets, suitable for algorithm comparison. Over 3000 new classification tasks were added to our recently established protein classification benchmark collection that currently includes protein sequence (including protein domains and entire proteins), protein structure and reading frame DNA sequence data. We carried out an extensive evaluation based on various machine-learning algorithms such as nearest neighbor, support vector machines, artificial neural networks, random forests and logistic regression, used in conjunction with comparison algorithms, BLAST, Smith-Waterman, Needleman-Wunsch, as well as 3D comparison methods DALI and PRIDE. The resulting datasets provide lower, and in our opinion more realistic estimates of the classifier performance than do random cross-validation schemes. A combination of supervised and random sampling was used to construct model datasets, suitable for algorithm comparison.

Using Support Vector Machine Ensembles for Target Audience Classification on Twitter

PubMed Central

Lo, Siaw Ling; Chiong, Raymond; Cornforth, David

2015-01-01

The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results show that the methods presented are able to successfully identify a target audience with high accuracy. In addition, we show that using a statistical inference approach such as bootstrapping in over-sampling, instead of using random sampling, to construct training datasets can achieve a better classifier in an SVM ensemble. We conclude that such an ensemble system can take advantage of data diversity, which enables real-world applications for differentiating prospective customers from the general audience, leading to business advantage in the crowded social media space. PMID:25874768

Using support vector machine ensembles for target audience classification on Twitter.

PubMed

Lo, Siaw Ling; Chiong, Raymond; Cornforth, David

2015-01-01

The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results show that the methods presented are able to successfully identify a target audience with high accuracy. In addition, we show that using a statistical inference approach such as bootstrapping in over-sampling, instead of using random sampling, to construct training datasets can achieve a better classifier in an SVM ensemble. We conclude that such an ensemble system can take advantage of data diversity, which enables real-world applications for differentiating prospective customers from the general audience, leading to business advantage in the crowded social media space.

NASA/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program 1987

NASA Technical Reports Server (NTRS)

Tiwari, Surendra N. (Compiler)

1987-01-01

Since 1964, NASA has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 or 11 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. Objectives: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate and exchange ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of participants' institutions; (4) to contribute to the research objectives of the NASA center. Program Description: College or university faculty members were appointed as Research Fellows to spend 10 weeks in cooperative research and study at the NASA Langley Research Center. The Fellow devoted approximately 90 percent of the time to a research problem and the remaining time to a study program. The study program consisted of lectures and seminars on topics of interest or that are directly relevant to the Fellows' research topic.

Speech reconstruction using a deep partially supervised neural network.

PubMed

McLoughlin, Ian; Li, Jingjie; Song, Yan; Sharifzadeh, Hamid R

2017-08-01

Statistical speech reconstruction for larynx-related dysphonia has achieved good performance using Gaussian mixture models and, more recently, restricted Boltzmann machine arrays; however, deep neural network (DNN)-based systems have been hampered by the limited amount of training data available from individual voice-loss patients. The authors propose a novel DNN structure that allows a partially supervised training approach on spectral features from smaller data sets, yielding very good results compared with the current state-of-the-art.

Supervisor self-disclosure: balancing the uncontrollable narcissist with the indomitable altruist.

PubMed

Ladany, Nicholas; Walker, Jessica A

2003-05-01

The purpose of this article is to provide supervisors with a framework to determine the effectiveness of self-disclosure in supervision. We posit how self-disclosures can be both memorable to the trainee and facilitative of supervision process and outcome, specifically the supervisory working alliance, trainee disclosure, and trainee edification. Case examples based on the literature and our own personal experiences are offered to illustrate the models' applicability. Copyright 2003 Wiley Periodicals, Inc.

A Hybrid Semi-supervised Classification Scheme for Mining Multisource Geospatial Data

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

Vatsavai, Raju; Bhaduri, Budhendra L

2011-01-01

Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of large number of accurate training samples (10 to 30 |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, itmore » is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 25 to 35% improvement in overall classification accuracy over conventional classification schemes.« less

Acquiring and refining CBT skills and competencies: which training methods are perceived to be most effective?

PubMed

Bennett-Levy, James; McManus, Freda; Westling, Bengt E; Fennell, Melanie

2009-10-01

A theoretical and empirical base for CBT training and supervision has started to emerge. Increasingly sophisticated maps of CBT therapist competencies have recently been developed, and there is evidence that CBT training and supervision can produce enhancement of CBT skills. However, the evidence base suggesting which specific training techniques are most effective for the development of CBT competencies is lacking. This paper addresses the question: What training or supervision methods are perceived by experienced therapists to be most effective for training CBT competencies? 120 experienced CBT therapists rated which training or supervision methods in their experience had been most effective in enhancing different types of therapy-relevant knowledge or skills. In line with the main prediction, it was found that different training methods were perceived to be differentially effective. For instance, reading, lectures/talks and modelling were perceived to be most useful for the acquisition of declarative knowledge, while enactive learning strategies (role-play, self-experiential work), together with modelling and reflective practice, were perceived to be most effective in enhancing procedural skills. Self-experiential work and reflective practice were seen as particularly helpful in improving reflective capability and interpersonal skills. The study provides a framework for thinking about the acquisition and refinement of therapist skills that may help trainers, supervisors and clinicians target their learning objectives with the most effective training strategies.

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.

The clinical learning environment and supervision by staff nurses: developing the instrument.

PubMed

Saarikoski, Mikko; Leino-Kilpi, Helena

2002-03-01

The aims of this study were (1) to describe students' perceptions of the clinical learning environment and clinical supervision and (2) to develop an evaluation scale by using the empirical results of this study. The data were collected using the Clinical Learning Environment and Supervision instrument (CLES). The instrument was based on the literature review of earlier studies. The derived instrument was tested empirically in a study involving nurse students (N=416) from four nursing colleges in Finland. The results demonstrated that the method of supervision, the number of separate supervision sessions and the psychological content of supervisory contact within a positive ward atmosphere are the most important variables in the students' clinical learning. The results also suggest that ward managers can create the conditions of a positive ward culture and a positive attitude towards students and their learning needs. The construct validity of the instrument was analysed by using exploratory factor analysis. The analysis indicated that the most important factor in the students' clinical learning is the supervisory relationship. The two most important factors constituting a 'good' clinical learning environment are the management style of the ward manager and the premises of nursing on the ward. The results of the factor analysis support the theoretical construction of the clinical learning environment modelled by earlier empirical studies.

Front-line managers as boundary spanners: effects of span and time on nurse supervision satisfaction.

PubMed

Meyer, Raquel M; O'Brien-Pallas, Linda; Doran, Diane; Streiner, David; Ferguson-Paré, Mary; Duffield, Christine

2011-07-01

To examine the influence of nurse manager span (number of direct report staff), time in staff contact, transformational leadership practices and operational hours on nurse supervision satisfaction. Increasing role complexity has intensified the boundary spanning functions of managers. Because work demands and scope vary by management position, time in staff contact rather than span may better explain managers' capacity to support staff. A descriptive, correlational design was used to collect cross-sectional survey and prospective work log and administrative data from a convenience sample of 558 nurses in 51 clinical areas and 31 front-line nurse managers from four acute care hospitals in 2007-2008. Data were analysed using hierarchical linear modelling. Span, but not time in staff contact, interacted with leadership and operational hours to explain supervision satisfaction. With compressed operational hours, supervision satisfaction was lower with highly transformational leadership in combination with wider spans. With extended operational hours, supervision satisfaction was higher with highly transformational leadership, and this effect was more pronounced under wider spans. Operational hours, which influence the manager's daily span (average number of direct report staff working per weekday), should be factored into the design of front-line management positions. © 2011 The Authors. Journal compilation © 2011 Blackwell Publishing Ltd.

Maximum margin semi-supervised learning with irrelevant data.

PubMed

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

2015-10-01

Semi-supervised learning (SSL) is a typical learning paradigms training a model from both labeled and unlabeled data. The traditional SSL models usually assume unlabeled data are relevant to the labeled data, i.e., following the same distributions of the targeted labeled data. In this paper, we address a different, yet formidable scenario in semi-supervised classification, where the unlabeled data may contain irrelevant data to the labeled data. To tackle this problem, we develop a maximum margin model, named tri-class support vector machine (3C-SVM), to utilize the available training data, while seeking a hyperplane for separating the targeted data well. Our 3C-SVM exhibits several characteristics and advantages. First, it does not need any prior knowledge and explicit assumption on the data relatedness. On the contrary, it can relieve the effect of irrelevant unlabeled data based on the logistic principle and maximum entropy principle. That is, 3C-SVM approaches an ideal classifier. This classifier relies heavily on labeled data and is confident on the relevant data lying far away from the decision hyperplane, while maximally ignoring the irrelevant data, which are hardly distinguished. Second, theoretical analysis is provided to prove that in what condition, the irrelevant data can help to seek the hyperplane. Third, 3C-SVM is a generalized model that unifies several popular maximum margin models, including standard SVMs, Semi-supervised SVMs (S(3)VMs), and SVMs learned from the universum (U-SVMs) as its special cases. More importantly, we deploy a concave-convex produce to solve the proposed 3C-SVM, transforming the original mixed integer programming, to a semi-definite programming relaxation, and finally to a sequence of quadratic programming subproblems, which yields the same worst case time complexity as that of S(3)VMs. Finally, we demonstrate the effectiveness and efficiency of our proposed 3C-SVM through systematical experimental comparisons. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Rat Model in Microsurgery Education: Classical Exercises and New Horizons

PubMed Central

Shurey, Sandra; Akelina, Yelena; Legagneux, Josette; Malzone, Gerardo; Jiga, Lucian

2014-01-01

Microsurgery is a precise surgical skill that requires an extensive training period and the supervision of expert instructors. The classical training schemes in microsurgery have started with multiday experimental courses on the rat model. These courses have offered a low threat supervised high fidelity laboratory setting in which students can steadily and rapidly progress. This simulated environment allows students to make and recognise mistakes in microsurgery techniques and thus shifts any related risks of the early training period from the operating room to the lab. To achieve a high level of skill acquisition before beginning clinical practice, students are trained on a comprehensive set of exercises the rat model can uniquely provide, with progressive complexity as competency improves. This paper presents the utility of the classical rat model in three of the earliest microsurgery training centres and the new prospects that this versatile and expansive training model offers. PMID:24883268

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...

Comparative Analysis of River Flow Modelling by Using Supervised Learning Technique

NASA Astrophysics Data System (ADS)

Ismail, Shuhaida; Mohamad Pandiahi, Siraj; Shabri, Ani; Mustapha, Aida

2018-04-01

The goal of this research is to investigate the efficiency of three supervised learning algorithms for forecasting monthly river flow of the Indus River in Pakistan, spread over 550 square miles or 1800 square kilometres. The algorithms include the Least Square Support Vector Machine (LSSVM), Artificial Neural Network (ANN) and Wavelet Regression (WR). The forecasting models predict the monthly river flow obtained from the three models individually for river flow data and the accuracy of the all models were then compared against each other. The monthly river flow of the said river has been forecasted using these three models. The obtained results were compared and statistically analysed. Then, the results of this analytical comparison showed that LSSVM model is more precise in the monthly river flow forecasting. It was found that LSSVM has he higher r with the value of 0.934 compared to other models. This indicate that LSSVM is more accurate and efficient as compared to the ANN and WR model.

Transport and Dynamics in Toroidal Fusion Systems

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

Sovinec, Carl

The study entitled, "Transport and Dynamics in Toroidal Fusion Systems," (TDTFS) applied analytical theory and numerical computation to investigate topics of importance to confining plasma, the fourth state of matter, with magnetic fields. A central focus of the work is how non-thermal components of the ion particle distribution affect the "sawtooth" collective oscillation in the core of the tokamak magnetic configuration. Previous experimental and analytical research had shown and described how the oscillation frequency decreases and amplitude increases, leading to "monster" or "giant" sawteeth, when the non-thermal component is increased by injecting particle beams or by exciting ions with imposedmore » electromagnetic waves. The TDTFS study applied numerical computation to self-consistently simulate the interaction between macroscopic collective plasma dynamics and the non-thermal particles. The modeling used the NIMROD code [Sovinec, Glasser, Gianakon, et al., J. Comput. Phys. 195, 355 (2004)] with the energetic component represented by simulation particles [Kim, Parker, Sovinec, and the NIMROD Team, Comput. Phys. Commun. 164, 448 (2004)]. The computations found decreasing growth rates for the instability that drives the oscillations, but they were ultimately limited from achieving experimentally relevant parameters due to computational practicalities. Nonetheless, this effort provided valuable lessons for integrated simulation of macroscopic plasma dynamics. It also motivated an investigation of the applicability of fluid-based modeling to the ion temperature gradient instability, leading to the journal publication [Schnack, Cheng, Barnes, and Parker, Phys. Plasmas 20, 062106 (2013)]. Apart from the tokamak-specific topics, the TDTFS study also addressed topics in the basic physics of magnetized plasma and in the dynamics of the reversed-field pinch (RFP) configuration. The basic physics work contributed to a study of two-fluid effects on interchange dynamics, where "two-fluid" refers to modeling independent dynamics of electron and ion species without full kinetic effects. In collaboration with scientist Ping Zhu, who received separate support, it was found that the rule-of-thumb criteria on stabilizing interchange has caveats that depend on the plasma density and temperature profiles. This work was published in [Zhu, Schnack, Ebrahimi, et al., Phys. Rev. Lett. 101, 085005 (2008)]. An investigation of general nonlinear relaxation with fluid models was partially supported by the TDTFS study and led to the publication [Khalzov, Ebrahimi, Schnack, and Mirnov, Phys. Plasmas 19, 012111 (2012)]. Work specific to the RFP included an investigation of interchange at large plasma pressure and support for applications [for example, Scheffel, Schnack, and Mirza, Nucl. Fusion 53, 113007 (2013)] of the DEBS code [Schnack, Barnes, Mikic, Harned, and Caramana, J. Comput. Phys. 70, 330 (1987)]. Finally, the principal investigator over most of the award period, Dalton Schnack, supervised a numerical study of modeling magnetic island suppression [Jenkins, Kruger, Hegna, Schnack, and Sovinec, Phys. Plasmas 17, 12502 (2010)].« less

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.

Exploration of an allied health workforce redesign model: quantifying the work of allied health assistants in a community workforce.

PubMed

Somerville, Lisa; Davis, Annette; Milne, Sarah; Terrill, Desiree; Philip, Kathleen

2017-07-25

The Victorian Assistant Workforce Model (VAWM) enables a systematic approach for the identification and quantification of work that can be delegated from allied health professionals (AHPs) to allied health assistants (AHAs). The aim of the present study was to explore the effect of implementation of VAWM in the community and ambulatory health care setting. Data captured using mixed methods from allied health professionals working across the participating health services enabled the measurement of opportunity for workforce redesign in the community and ambulatory allied health workforce. A total of 1112 AHPs and 135 AHAs from the 27 participating organisations took part in the present study. AHPs identified that 24% of their time was spent undertaking tasks that could safely be delegated to an appropriately qualified and supervised AHA. This equates to 6837h that could be redirected to advanced and expanded AHP practice roles or expanded patient-centred service models. The VAWM demonstrates potential for more efficient implementation of assistant workforce roles across allied health. Data outputs from implementation of the VAWM are vital in informing strategic planning and sustainability of workforce change. A more efficient and effective workforce promotes service delivery by the right person, in the right place, at the right time. What is known about this topic? There are currently workforce shortages that are predicted to grow across the allied health workforce. Ensuring that skill mix is optimal is one way to address these shortages. Matching the right task to right worker will also enable improved job satisfaction for both allied health assistants and allied health professionals. Workforce redesign efforts are more effective when there is strong data to support the redesign. What does this paper add? This paper builds on a previous paper by Somerville et al. with a case study applying the workforce redesign model to a community and ambulatory health care setting. It provides evidence that this workforce redesign model enables data to be collected to identify the opportunity for redesign in the allied health workforce in this clinical setting. What are the implications for practitioners? There are career pathways and opportunity for growth in the allied health assistant workforce in the community and ambulatory health care setting. These opportunities will need to be coupled with the development of supervision and delegation skills in the allied health professional workforce to ensure that an integrated workforce is built to provide optimal clinical care in the community and ambulatory setting.

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.

Support and performance improvement for primary health care workers in low- and middle-income countries: a scoping review of intervention design and methods

PubMed Central

Mabey, David C.; Chaudhri, Simran; Brown Epstein, Helen-Ann; Lawn, Stephen D.

2017-01-01

Abstract Primary health care workers (HCWs) in low- and middle-income settings (LMIC) often work in challenging conditions in remote, rural areas, in isolation from the rest of the health system and particularly specialist care. Much attention has been given to implementation of interventions to support quality and performance improvement for workers in such settings. However, little is known about the design of such initiatives and which approaches predominate, let alone those that are most effective. We aimed for a broad understanding of what distinguishes different approaches to primary HCW support and performance improvement and to clarify the existing evidence as well as gaps in evidence in order to inform decision-making and design of programs intended to support and improve the performance of health workers in these settings. We systematically searched the literature for articles addressing this topic, and undertook a comparative review to document the principal approaches to performance and quality improvement for primary HCWs in LMIC settings. We identified 40 eligible papers reporting on interventions that we categorized into five different approaches: (1) supervision and supportive supervision; (2) mentoring; (3) tools and aids; (4) quality improvement methods, and (5) coaching. The variety of study designs and quality/performance indicators precluded a formal quantitative data synthesis. The most extensive literature was on supervision, but there was little clarity on what defines the most effective approach to the supervision activities themselves, let alone the design and implementation of supervision programs. The mentoring literature was limited, and largely focused on clinical skills building and educational strategies. Further research on how best to incorporate mentorship into pre-service clinical training, while maintaining its function within the routine health system, is needed. There is insufficient evidence to draw conclusions about coaching in this setting, however a review of the corporate and the business school literature is warranted to identify transferrable approaches. A substantial literature exists on tools, but significant variation in approaches makes comparison challenging. We found examples of effective individual projects and designs in specific settings, but there was a lack of comparative research on tools across approaches or across settings, and no systematic analysis within specific approaches to provide evidence with clear generalizability. Future research should prioritize comparative intervention trials to establish clear global standards for performance and quality improvement initiatives. Such standards will be critical to creating and sustaining a well-functioning health workforce and for global initiatives such as universal health coverage. PMID:27993961

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.

Abusive supervision, leader-member exchange and moral disengagement: a moderated-mediation model of organizational deviance.

PubMed

Valle, Matthew; Kacmar, K Michele; Zivnuska, Suzanne; Harting, Troy

2018-04-20

This paper draws from social exchange theory and social cognitive theory to explore moral disengagement as a potential mediator of the relationship between abusive supervision and organizational deviance. We also explore the moderating effect of leader-member exchange (LMX) on this mediated relationship. Results indicate that employees with abusive supervisors engaged in moral disengagement strategies and subsequently in organizational deviance behaviors. Additionally, this relationship was stronger for those higher in LMX. Important implications for management research and practice are discussed.

A functional supervised learning approach to the study of blood pressure data.

PubMed

Papayiannis, Georgios I; Giakoumakis, Emmanuel A; Manios, Efstathios D; Moulopoulos, Spyros D; Stamatelopoulos, Kimon S; Toumanidis, Savvas T; Zakopoulos, Nikolaos A; Yannacopoulos, Athanasios N

2018-04-15

In this work, a functional supervised learning scheme is proposed for the classification of subjects into normotensive and hypertensive groups, using solely the 24-hour blood pressure data, relying on the concepts of Fréchet mean and Fréchet variance for appropriate deformable functional models for the blood pressure data. The schemes are trained on real clinical data, and their performance was assessed and found to be very satisfactory. Copyright © 2017 John Wiley & Sons, Ltd.

Long short-term memory for speaker generalization in supervised speech separation

PubMed Central

Chen, Jitong; Wang, DeLiang

2017-01-01

Speech separation can be formulated as learning to estimate a time-frequency mask from acoustic features extracted from noisy speech. For supervised speech separation, generalization to unseen noises and unseen speakers is a critical issue. Although deep neural networks (DNNs) have been successful in noise-independent speech separation, DNNs are limited in modeling a large number of speakers. To improve speaker generalization, a separation model based on long short-term memory (LSTM) is proposed, which naturally accounts for temporal dynamics of speech. Systematic evaluation shows that the proposed model substantially outperforms a DNN-based model on unseen speakers and unseen noises in terms of objective speech intelligibility. Analyzing LSTM internal representations reveals that LSTM captures long-term speech contexts. It is also found that the LSTM model is more advantageous for low-latency speech separation and it, without future frames, performs better than the DNN model with future frames. The proposed model represents an effective approach for speaker- and noise-independent speech separation. PMID:28679261

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.…

Social Cognition, Child Neglect, and Child Injury Risk: The Contribution of Maternal Social Information Processing to Maladaptive Injury Prevention Beliefs Within a High-Risk Sample.

PubMed

Azar, Sandra T; Miller, Elizabeth A; Stevenson, Michael T; Johnson, David R

2017-08-01

Inadequate supervision has been linked to children's injuries. Parental injury prevention beliefs may play a role in supervision, yet little theory has examined the origins of such beliefs. This study examined whether mothers who perpetrated child neglect, who as a group provide inadequate supervision, have more maladaptive beliefs. Then, it tested a social information processing (SIP) model for explaining these beliefs. SIP and injury prevention beliefs were assessed in disadvantaged mothers of preschoolers (N  =  145), half with child neglect histories. The neglect group exhibited significantly more maladaptive injury prevention beliefs than comparisons. As predicted, SIP was linked to beliefs that may increase injury risk, even after accounting for relevant sociodemographic variables. Findings support the link of beliefs to injury risk and suggest that specific cognitive problems may underlie these beliefs. Future work should further validate this model, which may inform enhancements to prevention efforts. © 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

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

PubMed

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

2017-12-01

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

A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

PubMed

Zhang, Xiaotian; Yin, Jian; Zhang, Xu

2018-03-02

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh-Bonab plain aquifer, Iran

NASA Astrophysics Data System (ADS)

Fijani, Elham; Nadiri, Ata Allah; Asghari Moghaddam, Asghar; Tsai, Frank T.-C.; Dixon, Barnali

2013-10-01

Contamination of wells with nitrate-N (NO3-N) poses various threats to human health. Contamination of groundwater is a complex process and full of uncertainty in regional scale. Development of an integrative vulnerability assessment methodology can be useful to effectively manage (including prioritization of limited resource allocation to monitor high risk areas) and protect this valuable freshwater source. This study introduces a supervised committee machine with artificial intelligence (SCMAI) model to improve the DRASTIC method for groundwater vulnerability assessment for the Maragheh-Bonab plain aquifer in Iran. Four different AI models are considered in the SCMAI model, whose input is the DRASTIC parameters. The SCMAI model improves the committee machine artificial intelligence (CMAI) model by replacing the linear combination in the CMAI with a nonlinear supervised ANN framework. To calibrate the AI models, NO3-N concentration data are divided in two datasets for the training and validation purposes. The target value of the AI models in the training step is the corrected vulnerability indices that relate to the first NO3-N concentration dataset. After model training, the AI models are verified by the second NO3-N concentration dataset. The results show that the four AI models are able to improve the DRASTIC method. Since the best AI model performance is not dominant, the SCMAI model is considered to combine the advantages of individual AI models to achieve the optimal performance. The SCMAI method re-predicts the groundwater vulnerability based on the different AI model prediction values. The results show that the SCMAI outperforms individual AI models and committee machine with artificial intelligence (CMAI) model. The SCMAI model ensures that no water well with high NO3-N levels would be classified as low risk and vice versa. The study concludes that the SCMAI model is an effective model to improve the DRASTIC model and provides a confident estimate of the pollution risk.

Nurse supervisors' actions in relation to their decision-making style and ethical approach to clinical supervision.

PubMed

Berggren, Ingela; Severinsson, Elisabeth

2003-03-01

The aim of the study was to explore the decision-making style and ethical approach of nurse supervisors by focusing on their priorities and interventions in the supervision process. Clinical supervision promotes ethical awareness and behaviour in the nursing profession. A focus group comprised of four clinical nurse supervisors with considerable experience was studied using qualitative hermeneutic content analysis. The essence of the nurse supervisors' decision-making style is deliberations and priorities. The nurse supervisors' willingness, preparedness, knowledge and awareness constitute and form their way of creating a relationship. The nurse supervisors' ethical approach focused on patient situations and ethical principles. The core components of nursing supervision interventions, as demonstrated in supervision sessions, are: guilt, reconciliation, integrity, responsibility, conscience and challenge. The nurse supervisors' interventions involved sharing knowledge and values with the supervisees and recognizing them as nurses and human beings. Nurse supervisors frequently reflected upon the ethical principle of autonomy and the concept and substance of integrity. The nurse supervisors used an ethical approach that focused on caring situations in order to enhance the provision of patient care. They acted as role models, shared nursing knowledge and ethical codes, and focused on patient related situations. This type of decision-making can strengthen the supervisees' professional identity. The clinical nurse supervisors in the study were experienced and used evaluation decisions as their form of clinical decision-making activity. The findings underline the need for further research and greater knowledge in order to improve the understanding of the ethical approach to supervision.

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.

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

The structure and content of telephonic scripts found useful in a Medicaid Chronic Disease Management Program.

PubMed

Roth, Alexis M; Ackermann, Ronald T; Downs, Stephen M; Downs, Anne M; Zillich, Alan J; Holmes, Ann M; Katz, Barry P; Murray, Michael D; Inui, Thomas S

2010-06-01

In 2003, the Indiana Office of Medicaid Policy and Planning launched the Indiana Chronic Disease Management Program (ICDMP), a programme intended to improve the health and healthcare utilization of 15,000 Aged, Blind and Disabled Medicaid members living with diabetes and/or congestive heart failure in Indiana. Within ICDMP, programme components derived from the Chronic Care Model and education based on an integrated theoretical framework were utilized to create a telephonic care management intervention that was delivered by trained, non-clinical Care Managers (CMs) working under the supervision of a Registered Nurse. CMs utilized computer-assisted health education scripts to address clinically important topics, including medication adherence, diet, exercise and prevention of disease-specific complications. Employing reflective listening techniques, barriers to optimal self-management were assessed and members were encouraged to engage in health-improving actions. ICDMP evaluation results suggest that this low-intensity telephonic intervention shifted utilization and lowered costs. We discuss this patient-centred method for motivating behaviour change, the theoretical constructs underlying the scripts and the branched-logic format that makes them suitable to use as a computer-based application. Our aim is to share these public-domain materials with other programmes.

A Model of Instructional Supervision That Meets Today's Needs.

ERIC Educational Resources Information Center

Beck, John J.; Seifert, Edward H.

1983-01-01

The proposed Instructional Technologist Model is based on a closed loop feedback system allowing for continuous monitoring of teachers by expert instructional technologists. Principals are thereby released for instructional evaluation and general educational management. (MJL)

Prototype Vector Machine for Large Scale Semi-Supervised Learning

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

Zhang, Kai; Kwok, James T.; Parvin, Bahram

2009-04-29

Practicaldataminingrarelyfalls exactlyinto the supervisedlearning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised learning (SSL). We note that the computationalintensivenessofgraph-based SSLarises largely from the manifold or graph regularization, which in turn lead to large models that are dificult to handle. To alleviate this, we proposed the prototype vector machine (PVM), a highlyscalable,graph-based algorithm for large-scale SSL. Our key innovation is the use of"prototypes vectors" for effcient approximation on both the graph-based regularizer and model representation. The choice of prototypes are grounded upon two important criteria: they not only perform effective low-rank approximation of themore » kernel matrix, but also span a model suffering the minimum information loss compared with the complete model. We demonstrate encouraging performance and appealing scaling properties of the PVM on a number of machine learning benchmark data sets.« less

12 CFR 573.2 - Model privacy form and examples.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 6 2014-01-01 2012-01-01 true Model privacy form and examples. 573.2 Section 573.2 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY PRIVACY OF CONSUMER FINANCIAL INFORMATION § 573.2 Model privacy form and examples. (a) Model privacy form. Use of the model...

12 CFR 573.2 - Model privacy form and examples.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 5 2011-01-01 2011-01-01 false Model privacy form and examples. 573.2 Section 573.2 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY PRIVACY OF CONSUMER FINANCIAL INFORMATION § 573.2 Model privacy form and examples. (a) Model privacy form. Use of the model...

12 CFR 573.2 - Model privacy form and examples.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 6 2012-01-01 2012-01-01 false Model privacy form and examples. 573.2 Section 573.2 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY PRIVACY OF CONSUMER FINANCIAL INFORMATION § 573.2 Model privacy form and examples. (a) Model privacy form. Use of the model...

12 CFR 573.2 - Model privacy form and examples.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 12 Banks and Banking 6 2013-01-01 2012-01-01 true Model privacy form and examples. 573.2 Section 573.2 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY PRIVACY OF CONSUMER FINANCIAL INFORMATION § 573.2 Model privacy form and examples. (a) Model privacy form. Use of the model...

12 CFR 573.2 - Model privacy form and examples.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Model privacy form and examples. 573.2 Section 573.2 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY PRIVACY OF CONSUMER FINANCIAL INFORMATION § 573.2 Model privacy form and examples. (a) Model privacy form. Use of the model...

Approximate Optimal Control as a Model for Motor Learning

ERIC Educational Resources Information Center

Berthier, Neil E.; Rosenstein, Michael T.; Barto, Andrew G.

2005-01-01

Current models of psychological development rely heavily on connectionist models that use supervised learning. These models adapt network weights when the network output does not match the target outputs computed by some agent. The authors present a model of motor learning in which the child uses exploration to discover appropriate ways of…

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.

Emerging governance approaches for tourism in the protected areas of china.

PubMed

Su, Dan; Wall, Geoffrey; Eagles, Paul F J

2007-06-01

This paper examines the recent evolution in the governance of protected area tourism in China. China now sees cooperation in the form of public-private partnerships occurring between authorized private tourism enterprises in various organizational forms and the public managers from specific portfolio departments of governments at different levels. Three types of governance models are visible: the Leasing Model, the Non-listed Share-holding Model, and the Public-listed Share-holding Model. Theories of corporate governance were applied to these models to analyze the internal and external mechanisms of supervision and incentives for both the government agencies and the authorized tourism enterprises for nature-based tourism operations. The Principal-Agent problem and the supervision mechanism are the focus of the analysis. The emerging governance approaches for tourism in protected areas of China are all theoretically viable, as explained by the theory of property rights and corporate governance, and practically viable as elaborated in the cases of the three types of governance models summarized in this paper.

Computational Psychotherapy Research: Scaling up the evaluation of patient-provider interactions

PubMed Central

Imel, Zac E.; Steyvers, Mark; Atkins, David C.

2014-01-01

In psychotherapy, the patient-provider interaction contains the treatment’s active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required in order to “scale up” to larger evaluation tasks and “drill down” into the raw linguistic data of patient-therapist interactions. In the current paper we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, content, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time, and we conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice. PMID:24866972

Computational psychotherapy research: scaling up the evaluation of patient-provider interactions.

PubMed

Imel, Zac E; Steyvers, Mark; Atkins, David C

2015-03-01

In psychotherapy, the patient-provider interaction contains the treatment's active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required to "scale up" to larger evaluation tasks and "drill down" into the raw linguistic data of patient-therapist interactions. In the current article, we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, relational, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment-related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive-behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model-derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time. We conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

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.

Enhancing adult learning in clinical supervision.

PubMed

Goldman, Stuart

2011-01-01

For decades, across almost every training site, clinical supervision has been considered "central to the development of skills" in psychiatry. The crucial supervisor/supervisee relationship has been described extensively in the literature, most often framed as a clinical apprenticeship of the novice to the master craftsman. This approach fails to directly incorporate adult-learning theory (ALT), despite a clear literature supporting its superiority. In this article, the author describes the basic principles of ALT, reviewing the limitations of current supervisory practice from the ALT perspective. He then describes system insights gleaned from elements of the manufacturing process and integrates them into a model that enhances ALT-informed approaches to clinical supervision that can be utilized in all settings. Although there are clear benefits of ALT and the proposed "pull" manufacturing management-informed approaches to supervision, there are several anticipated areas of likely resistance: the issues of time for the collaborative goal-setting, monitoring progress, and revising the educational plan. Much of this is already a factor in the current, labor-intensive patterns of individual supervision, and, in practice, even the formal monthly review has, in almost all cases, taken appreciably less than half of a supervisory hour. Any possible increases in time or effort would be more than compensated for by the inherent efficiency of resident-specific teaching and learning. Current supervisory practices can be revised to include principles of ALT and "pull" manufacturing systems that can enhance resident education.

[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.

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

Adaptability of Physicians Offering Primary Care to the Poor: Social Competency Revisited

PubMed Central

Loignon, Christine; Boudreault-Fournier,, Alexandrine

2013-01-01

This paper attempts to go deeper into the topic of social competency of physicians who provide primary care to populations living in poverty in Montreal. Adaptability as well as the ability to tailor practices according to patient expectations, needs and capabilities were found to be important in the development of the concept of social competency. The case of paternalism is used to demonstrate how a historically and socially contested medical approach is readapted by players in certain contexts in order to better meet patient expectations. This paper presents data collected in a qualitative study comprising 25 semi-supervised interviews with physicians recognized by their peers as having developed exemplary practices in Montreal's impoverished neighbourhoods. PMID:24289940

Anesthesia Methods in Laser Resurfacing

PubMed Central

Gaitan, Sergio; Markus, Ramsey

2012-01-01

Laser resurfacing technology offers the ability to treat skin changes that are the result of the aging process. One of the major drawbacks of laser resurfacing technologies is the pain associated with the procedure. The methods of anesthesia used in laser resurfacing to help minimize the pain include both noninvasive and invasive procedures. The noninvasive procedures can be divided into topical, cryoanesthesia, and a combination of both. The invasive methods of anesthesia include injected forms (infiltrative, nerve blocks, and tumescent anesthesia) and supervised anesthesia (monitored anesthesia care and general anesthesia). In this review, the authors summarize the types of anesthesia used in laser resurfacing to aid the provider in offering the most appropriate method for the patient to have as painless a procedure as possible. PMID:23904819

Habanapp: Havana's Architectural Heritage a Click Away

NASA Astrophysics Data System (ADS)

Morganti, C.; Bartolomei, C.

2018-05-01

The research treats the application of technologies related with augmented and virtual reality to architectural and historical context in the city of Havana, Cuba, on the basis of historical studies and Range-Imaging techniques on buildings bordering old city's five main squares. The specific aim is to transfer all of the data received thanks to the most recent mobiles apps about Augmented Reality (AR) and Virtual reality (VR), in order to give birth to an innovative App never seen before in Cuba. The "Oficina del Historiador de la ciudad de La Habana", institution supervising architectural and cultural asset in Cuba, is widely interested in the topic in order to develop a new educational, cultural and artistic tool to be used both online and offline.

Generative Topic Modeling in Image Data Mining and Bioinformatics Studies

ERIC Educational Resources Information Center

Chen, Xin

2012-01-01

Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…

Forecasting Chronic Diseases Using Data Fusion.

PubMed

Acar, Evrim; Gürdeniz, Gözde; Savorani, Francesco; Hansen, Louise; Olsen, Anja; Tjønneland, Anne; Dragsted, Lars Ove; Bro, Rasmus

2017-07-07

Data fusion, that is, extracting information through the fusion of complementary data sets, is a topic of great interest in metabolomics because analytical platforms such as liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy commonly used for chemical profiling of biofluids provide complementary information. In this study, with a goal of forecasting acute coronary syndrome (ACS), breast cancer, and colon cancer, we jointly analyzed LC-MS, NMR measurements of plasma samples, and the metadata corresponding to the lifestyle of participants. We used supervised data fusion based on multiple kernel learning and exploited the linearity of the models to identify significant metabolites/features for the separation of healthy referents and the cases developing a disease. We demonstrated that (i) fusing LC-MS, NMR, and metadata provided better separation of ACS cases and referents compared with individual data sets, (ii) NMR data performed the best in terms of forecasting breast cancer, while fusion degraded the performance, and (iii) neither the individual data sets nor their fusion performed well for colon cancer. Furthermore, we showed the strengths and limitations of the fusion models by discussing their performance in terms of capturing known biomarkers for smoking and coffee. While fusion may improve performance in terms of separating certain conditions by jointly analyzing metabolomics and metadata sets, it is not necessarily always the best approach as in the case of breast cancer.

A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data

NASA Astrophysics Data System (ADS)

Cavuoti, S.; Tortora, C.; Brescia, M.; Longo, G.; Radovich, M.; Napolitano, N. R.; Amaro, V.; Vellucci, C.; La Barbera, F.; Getman, F.; Grado, A.

2017-04-01

Photometric redshifts (photo-z) are fundamental in galaxy surveys to address different topics, from gravitational lensing and dark matter distribution to galaxy evolution. The Kilo Degree Survey (KiDS), I.e. the European Southern Observatory (ESO) public survey on the VLT Survey Telescope (VST), provides the unprecedented opportunity to exploit a large galaxy data set with an exceptional image quality and depth in the optical wavebands. Using a KiDS subset of about 25000 galaxies with measured spectroscopic redshifts, we have derived photo-z using (I) three different empirical methods based on supervised machine learning; (II) the Bayesian photometric redshift model (or BPZ); and (III) a classical spectral energy distribution (SED) template fitting procedure (LE PHARE). We confirm that, in the regions of the photometric parameter space properly sampled by the spectroscopic templates, machine learning methods provide better redshift estimates, with a lower scatter and a smaller fraction of outliers. SED fitting techniques, however, provide useful information on the galaxy spectral type, which can be effectively used to constrain systematic errors and to better characterize potential catastrophic outliers. Such classification is then used to specialize the training of regression machine learning models, by demonstrating that a hybrid approach, involving SED fitting and machine learning in a single collaborative framework, can be effectively used to improve the accuracy of photo-z estimates.

The origin of the Universe by the Big Bang theory applied in the classroom, following the proposal of the school curriculum of the State of São Paulo

NASA Astrophysics Data System (ADS)

Oliveira, J. F. dos R.

2017-07-01

The purpose of this work is show to a bibliographic study based on the analysis made to the content applied in the first year of High School, through the booklet primer of the educational curriculum of the state of São Paulo, as predicted: "Natural Sciences and their Technologies" (São Paulo, 2010), implemented since 2008 in the public education network. The analysis made compares from the content addressed by the "Student Notebook" versus "Teacher's Notebook", an indispensable tool in the teaching network on the approach of theory of the emergence of the universe. An essential theme for educational knowledge in this cycle, revealing a hypothetical model of the Big Bang, and also curved space and cosmic inflation. Possibly this model may still be a controversial subject for some groups, because it involves belief, religion, science or another perspective of universe. The field of research was carried out in a group of 40 first year students of the High School, at the State School "Professor Rômulo Pero", in the city of São Paulo, supervised by the State Board of Education - Central Region. The completion of this task presents an important tool to be used by the teacher, a Conceptual Map, in order to raise previous knowledge and probing for the established topic, in the teaching of Physics.

Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR.

PubMed

Tustison, Nicholas J; Shrinidhi, K L; Wintermark, Max; Durst, Christopher R; Kandel, Benjamin M; Gee, James C; Grossman, Murray C; Avants, Brian B

2015-04-01

Segmenting and quantifying gliomas from MRI is an important task for diagnosis, planning intervention, and for tracking tumor changes over time. However, this task is complicated by the lack of prior knowledge concerning tumor location, spatial extent, shape, possible displacement of normal tissue, and intensity signature. To accommodate such complications, we introduce a framework for supervised segmentation based on multiple modality intensity, geometry, and asymmetry feature sets. These features drive a supervised whole-brain and tumor segmentation approach based on random forest-derived probabilities. The asymmetry-related features (based on optimal symmetric multimodal templates) demonstrate excellent discriminative properties within this framework. We also gain performance by generating probability maps from random forest models and using these maps for a refining Markov random field regularized probabilistic segmentation. This strategy allows us to interface the supervised learning capabilities of the random forest model with regularized probabilistic segmentation using the recently developed ANTsR package--a comprehensive statistical and visualization interface between the popular Advanced Normalization Tools (ANTs) and the R statistical project. The reported algorithmic framework was the top-performing entry in the MICCAI 2013 Multimodal Brain Tumor Segmentation challenge. The challenge data were widely varying consisting of both high-grade and low-grade glioma tumor four-modality MRI from five different institutions. Average Dice overlap measures for the final algorithmic assessment were 0.87, 0.78, and 0.74 for "complete", "core", and "enhanced" tumor components, respectively.

Liability of physicians supervising nonphysician clinicians.

PubMed

Paterick, Barbara B; Waterhouse, Blake E; Paterick, Timothy E; Sanbar, Sandy S

2014-01-01

Physicians confront a variety of liability issues when supervising nonphysician clinicians (NPC) including: (1) direct liability resulting from a failure to meet the state-defined standards of supervision/collaboration with NPCs; (2) vicarious liability, arising from agency law, where physicians are held accountable for NPC clinical care that does not meet the national standard of care; and (3) responsibility for medical errors when the NPC and physician are co-employees of the corporate enterprise. Physician-NPC co-employee relationships are highlighted because they are new and becoming predominant in existing healthcare models. Because of their novelty, there is a paucity of judicial decisions determining liability for NPC errors in this setting. Knowledge of the existence of these risks will allow physicians to make informed decisions on what relationships they will enter with NPCs and how these relationships will be structured and monitored.

Cognitive Inference Device for Activity Supervision in the Elderly

PubMed Central

2014-01-01

Human activity, life span, and quality of life are enhanced by innovations in science and technology. Aging individual needs to take advantage of these developments to lead a self-regulated life. However, maintaining a self-regulated life at old age involves a high degree of risk, and the elderly often fail at this goal. Thus, the objective of our study is to investigate the feasibility of implementing a cognitive inference device (CI-device) for effective activity supervision in the elderly. To frame the CI-device, we propose a device design framework along with an inference algorithm and implement the designs through an artificial neural model with different configurations, mapping the CI-device's functions to minimise the device's prediction error. An analysis and discussion are then provided to validate the feasibility of CI-device implementation for activity supervision in the elderly. PMID:25405211

Social work in oncology-managing vicarious trauma-the positive impact of professional supervision.

PubMed

Joubert, Lynette; Hocking, Alison; Hampson, Ralph

2013-01-01

This exploratory study focused on the experience and management of vicarious trauma in a team of social workers (N = 16) at a specialist cancer hospital in Melbourne. Respondents completed the Traumatic Stress Institute Belief Scale (TSIBS), the Professional Quality of Life Scale (ProQOL), and participated in four focus groups. The results from the TSIBS and the ProQol scales confirm that there is a stress associated with the social work role within a cancer service, as demonstrated by the high scores related to stress. However at the same time the results indicated a high level of satisfaction which acted as a mitigating factor. The study also highlighted the importance of supervision and management support. A model for clinical social work supervision is proposed to reduce the risks associated with vicarious trauma.

Topic Modeling of NASA Space System Problem Reports: Research in Practice

NASA Technical Reports Server (NTRS)

Layman, Lucas; Nikora, Allen P.; Meek, Joshua; Menzies, Tim

2016-01-01

Problem reports at NASA are similar to bug reports: they capture defects found during test, post-launch operational anomalies, and document the investigation and corrective action of the issue. These artifacts are a rich source of lessons learned for NASA, but are expensive to analyze since problem reports are comprised primarily of natural language text. We apply topic modeling to a corpus of NASA problem reports to extract trends in testing and operational failures. We collected 16,669 problem reports from six NASA space flight missions and applied Latent Dirichlet Allocation topic modeling to the document corpus. We analyze the most popular topics within and across missions, and how popular topics changed over the lifetime of a mission. We find that hardware material and flight software issues are common during the integration and testing phase, while ground station software and equipment issues are more common during the operations phase. We identify a number of challenges in topic modeling for trend analysis: 1) that the process of selecting the topic modeling parameters lacks definitive guidance, 2) defining semantically-meaningful topic labels requires nontrivial effort and domain expertise, 3) topic models derived from the combined corpus of the six missions were biased toward the larger missions, and 4) topics must be semantically distinct as well as cohesive to be useful. Nonetheless,topic modeling can identify problem themes within missions and across mission lifetimes, providing useful feedback to engineers and project managers.

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.

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.

PubMed

El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher

2018-01-01

Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

@AACAnatomy twitter account goes live: A sustainable social media model for professional societies.

PubMed

Benjamin, Hannah K; Royer, Danielle F

2018-05-01

Social media, with its capabilities of fast, global information sharing, provides a useful medium for professional development, connecting and collaborating with peers, and outreach. The goals of this study were to describe a new, sustainable model for Twitter use by professional societies, and analyze its impact on @AACAnatomy, the Twitter account of the American Association of Clinical Anatomists. Under supervision of an Association committee member, an anatomy graduate student developed a protocol for publishing daily tweets for @AACAnatomy. Five tweet categories were used: Research, Announcements, Replies, Engagement, and Community. Analytics from the 6-month pilot phase were used to assess the impact of the new model. @AACAnatomy had a steady average growth of 33 new followers per month, with less than 10% likely representing Association members. Research tweets, based on Clinical Anatomy articles with an abstract link, were the most shared, averaging 5,451 impressions, 31 link clicks, and nine #ClinAnat hashtag clicks per month. However, tweets from non-Research categories accounted for the highest impression and engagement metrics in four out of six months. For all tweet categories, monthly averages show consistent interaction of followers with the account. Daily tweet publication resulted in a 103% follower increase. An active Twitter account successfully facilitated regular engagement with @AACAnatomy followers and the promotion of clinical anatomy topics within a broad community. This Twitter model has the potential for implementation by other societies as a sustainable medium for outreach, networking, collaboration, and member engagement. Clin. Anat. 31:566-575, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The nature and structure of supervision in health visiting with victims of child sexual abuse.

PubMed

Scott, L

1999-03-01

Part of a higher research degree to explore professional practice. To explore how health visitors work with victims of child sexual abuse and the supervision systems to support them. To seek the views and experiences of practising health visitors relating to complex care in order to consider the nature and structure of supervision. The research reported in this paper used a qualitative method of research and semi-structured interviews with practising health visitors of varying levels of experience in venues around England. Qualitative research enabled the exploration of experiences. Identification of the need for regular, structured, accountable opportunities in a 'private setting' to discuss whole caseload work and current practice issues. Supervision requires a structured, formalized process, in both regularity and content, as a means to explore and acknowledge work with increasingly complex care, to enable full discussion of whole caseloads. Supervision is demonstrated as a vehicle to enable the sharing of good practices and for weak practices to be identified and managed appropriately. Supervision seeks to fulfil the above whilst promoting a stimulating, learning experience, accommodating the notion that individuals learn at their own pace and bring a wealth of human experience to the service. The size of the study was dictated by the amount of time available within which to complete a research master's degree course primarily in the author's own time, over a 2-year period. The majority of participants volunteered their accounts in their own time. For others I obtained permission from their employers for them to participate once they approached me with an interest in being interviewed. This research provides a model of supervision based on practitioner views and experiences. The article highlights the value of research and evidence-based information to enhance practice accountability and the quality of care. Proactive risk management can safeguard the health and safety of the public, the practitioner and the organization.

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.

Task-Driven Comparison of Topic Models.

PubMed

Alexander, Eric; Gleicher, Michael

2016-01-01

Topic modeling, a method of statistically extracting thematic content from a large collection of texts, is used for a wide variety of tasks within text analysis. Though there are a growing number of tools and techniques for exploring single models, comparisons between models are generally reduced to a small set of numerical metrics. These metrics may or may not reflect a model's performance on the analyst's intended task, and can therefore be insufficient to diagnose what causes differences between models. In this paper, we explore task-centric topic model comparison, considering how we can both provide detail for a more nuanced understanding of differences and address the wealth of tasks for which topic models are used. We derive comparison tasks from single-model uses of topic models, which predominantly fall into the categories of understanding topics, understanding similarity, and understanding change. Finally, we provide several visualization techniques that facilitate these tasks, including buddy plots, which combine color and position encodings to allow analysts to readily view changes in document similarity.

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

PubMed Central

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease. PMID:27977767

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

PubMed

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease.

An Introduction to Topic Modeling as an Unsupervised Machine Learning Way to Organize Text Information

ERIC Educational Resources Information Center

Snyder, Robin M.

2015-01-01

The field of topic modeling has become increasingly important over the past few years. Topic modeling is an unsupervised machine learning way to organize text (or image or DNA, etc.) information such that related pieces of text can be identified. This paper/session will present/discuss the current state of topic modeling, why it is important, and…

Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation

PubMed Central

Khaligh-Razavi, Seyed-Mahdi; Kriegeskorte, Nikolaus

2014-01-01

Inferior temporal (IT) cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total), testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet) along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network). We compared the representational dissimilarity matrices (RDMs) of the model representations with the RDMs obtained from human IT (measured with fMRI) and monkey IT (measured with cell recording) for the same set of stimuli (not used in training the models). Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining IT requires computational features trained through supervised learning to emphasize the behaviorally important categorical divisions prominently reflected in IT. PMID:25375136

Topical video object discovery from key frames by modeling word co-occurrence prior.

PubMed

Zhao, Gangqiang; Yuan, Junsong; Hua, Gang; Yang, Jiong

2015-12-01

A topical video object refers to an object, that is, frequently highlighted in a video. It could be, e.g., the product logo and the leading actor/actress in a TV commercial. We propose a topic model that incorporates a word co-occurrence prior for efficient discovery of topical video objects from a set of key frames. Previous work using topic models, such as latent Dirichelet allocation (LDA), for video object discovery often takes a bag-of-visual-words representation, which ignored important co-occurrence information among the local features. We show that such data driven co-occurrence information from bottom-up can conveniently be incorporated in LDA with a Gaussian Markov prior, which combines top-down probabilistic topic modeling with bottom-up priors in a unified model. Our experiments on challenging videos demonstrate that the proposed approach can discover different types of topical objects despite variations in scale, view-point, color and lighting changes, or even partial occlusions. The efficacy of the co-occurrence prior is clearly demonstrated when compared with topic models without such priors.

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.

Linguistic Extensions of Topic Models

ERIC Educational Resources Information Center

Boyd-Graber, Jordan

2010-01-01

Topic models like latent Dirichlet allocation (LDA) provide a framework for analyzing large datasets where observations are collected into groups. Although topic modeling has been fruitfully applied to problems social science, biology, and computer vision, it has been most widely used to model datasets where documents are modeled as exchangeable…

“Old Dogs” and New Skills: How Clinician Characteristics Relate to Motivational Interviewing Skills Before, During, and After Training

PubMed Central

Carpenter, Kenneth M.; Cheng, Wendy Y.; Smith, Jennifer L.; Brooks, Adam C.; Amrhein, Paul C.; Wain, R. Morgan; Nunes, Edward V.

2012-01-01

Objective The relationships between the occupational, educational, and verbal-cognitive characteristics of health care professionals and their Motivational Interviewing (MI) skills before, during, and after training were investigated. Method Fifty-eight community-based addiction clinicians (M = 42.1 yrs., SD =10.0; 66% Female) were assessed prior to enrolling in a two-day MI training workshop and being randomized to one of three post-workshop supervision programs: live supervision via tele-conferencing (TCS), standard tape-based supervision (Tape), or workshop training alone. Audiotaped sessions with clients were rated for MI skillfulness with the Motivational Interviewing Treatment Integrity (MITI) coding system v 2.0 at pre-workshop and 1, 8, and 20 weeks post-workshop. Correlation coefficients and generalized linear models were used to test the relationships between clinician characteristics and MI skill at each assessment point. Results Baseline MI skill levels were the most robust predictors of pre- and post-supervision performances. Clinician characteristics were associated with MI Spirit and reflective listening skill throughout training and moderated the effect of post-workshop supervision method on MI skill. TCS, which provided immediate feedback during practice sessions, was most effective for increasing MI Spirit and reflective listening among clinicians with no graduate degree and stronger vocabulary performances. Tape supervision was more effective for increasing these skills among clinicians with a graduate degree. Further, TCS and Tape were most likely to enhance MI Spirit among clinicians with low average to average verbal and abstract reasoning performances. Conclusions Clinician attributes influence the effectiveness of methods used to promote the acquisition of evidence-based practices among community-based practitioners. PMID:22563640

Supervised exercise reduces cancer-related fatigue: a systematic review.

PubMed

Meneses-Echávez, José F; González-Jiménez, Emilio; Ramírez-Vélez, Robinson

2015-01-01

Does supervised physical activity reduce cancer-related fatigue? Systematic review with meta-analysis of randomised trials. People diagnosed with any type of cancer, without restriction to a particular stage of diagnosis or treatment. Supervised physical activity interventions (eg, aerobic, resistance and stretching exercise), defined as any planned or structured body movement causing an increase in energy expenditure, designed to maintain or enhance health-related outcomes, and performed with systematic frequency, intensity and duration. The primary outcome measure was fatigue. Secondary outcomes were physical and functional wellbeing assessed using the Functional Assessment of Cancer Therapy Fatigue Scale, European Organisation for Research and Treatment of Cancer Quality of Life QUESTIONnaire, Piper Fatigue Scale, Schwartz Cancer Fatigue Scale and the Multidimensional Fatigue Inventory. Methodological quality, including risk of bias of the studies, was evaluated using the PEDro Scale. Eleven studies involving 1530 participants were included in the review. The assessment of quality showed a mean score of 6.5 (SD 1.1), indicating a low overall risk of bias. The pooled effect on fatigue, calculated as a standardised mean difference (SMD) using a random-effects model, was -1.69 (95% CI -2.99 to -0.39). Beneficial reductions in fatigue were also found with combined aerobic and resistance training with supervision (SMD=-0.41, 95% CI -0.70 to -0.13) and with combined aerobic, resistance and stretching training with supervision (SMD=-0.67, 95% CI -1.17 to -0.17). Supervised physical activity interventions reduce cancer-related fatigue. These findings suggest that combined aerobic and resistance exercise regimens with or without stretching should be included as part of rehabilitation programs for people who have been diagnosed with cancer. PROSPERO CRD42013005803. Copyright © 2014 Australian Physiotherapy Association. Published by Elsevier B.V. All rights reserved.

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…

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.

Multisource Data Classification Using A Hybrid Semi-supervised Learning Scheme

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

Vatsavai, Raju; Bhaduri, Budhendra L; Shekhar, Shashi

2009-01-01

In many practical situations thematic classes can not be discriminated by spectral measurements alone. Often one needs additional features such as population density, road density, wetlands, elevation, soil types, etc. which are discrete attributes. On the other hand remote sensing image features are continuous attributes. Finding a suitable statistical model and estimation of parameters is a challenging task in multisource (e.g., discrete and continuous attributes) data classification. In this paper we present a semi-supervised learning method by assuming that the samples were generated by a mixture model, where each component could be either a continuous or discrete distribution. Overall classificationmore » accuracy of the proposed method is improved by 12% in our initial experiments.« less

Improved supervised classification of accelerometry data to distinguish behaviors of soaring birds.

PubMed

Sur, Maitreyi; Suffredini, Tony; Wessells, Stephen M; Bloom, Peter H; Lanzone, Michael; Blackshire, Sheldon; Sridhar, Srisarguru; Katzner, Todd

2017-01-01

Soaring birds can balance the energetic costs of movement by switching between flapping, soaring and gliding flight. Accelerometers can allow quantification of flight behavior and thus a context to interpret these energetic costs. However, models to interpret accelerometry data are still being developed, rarely trained with supervised datasets, and difficult to apply. We collected accelerometry data at 140Hz from a trained golden eagle (Aquila chrysaetos) whose flight we recorded with video that we used to characterize behavior. We applied two forms of supervised classifications, random forest (RF) models and K-nearest neighbor (KNN) models. The KNN model was substantially easier to implement than the RF approach but both were highly accurate in classifying basic behaviors such as flapping (85.5% and 83.6% accurate, respectively), soaring (92.8% and 87.6%) and sitting (84.1% and 88.9%) with overall accuracies of 86.6% and 92.3% respectively. More detailed classification schemes, with specific behaviors such as banking and straight flights were well classified only by the KNN model (91.24% accurate; RF = 61.64% accurate). The RF model maintained its accuracy of classifying basic behavior classification accuracy of basic behaviors at sampling frequencies as low as 10Hz, the KNN at sampling frequencies as low as 20Hz. Classification of accelerometer data collected from free ranging birds demonstrated a strong dependence of predicted behavior on the type of classification model used. Our analyses demonstrate the consequence of different approaches to classification of accelerometry data, the potential to optimize classification algorithms with validated flight behaviors to improve classification accuracy, ideal sampling frequencies for different classification algorithms, and a number of ways to improve commonly used analytical techniques and best practices for classification of accelerometry data.

Improved supervised classification of accelerometry data to distinguish behaviors of soaring birds

PubMed Central

Suffredini, Tony; Wessells, Stephen M.; Bloom, Peter H.; Lanzone, Michael; Blackshire, Sheldon; Sridhar, Srisarguru; Katzner, Todd

2017-01-01

Soaring birds can balance the energetic costs of movement by switching between flapping, soaring and gliding flight. Accelerometers can allow quantification of flight behavior and thus a context to interpret these energetic costs. However, models to interpret accelerometry data are still being developed, rarely trained with supervised datasets, and difficult to apply. We collected accelerometry data at 140Hz from a trained golden eagle (Aquila chrysaetos) whose flight we recorded with video that we used to characterize behavior. We applied two forms of supervised classifications, random forest (RF) models and K-nearest neighbor (KNN) models. The KNN model was substantially easier to implement than the RF approach but both were highly accurate in classifying basic behaviors such as flapping (85.5% and 83.6% accurate, respectively), soaring (92.8% and 87.6%) and sitting (84.1% and 88.9%) with overall accuracies of 86.6% and 92.3% respectively. More detailed classification schemes, with specific behaviors such as banking and straight flights were well classified only by the KNN model (91.24% accurate; RF = 61.64% accurate). The RF model maintained its accuracy of classifying basic behavior classification accuracy of basic behaviors at sampling frequencies as low as 10Hz, the KNN at sampling frequencies as low as 20Hz. Classification of accelerometer data collected from free ranging birds demonstrated a strong dependence of predicted behavior on the type of classification model used. Our analyses demonstrate the consequence of different approaches to classification of accelerometry data, the potential to optimize classification algorithms with validated flight behaviors to improve classification accuracy, ideal sampling frequencies for different classification algorithms, and a number of ways to improve commonly used analytical techniques and best practices for classification of accelerometry data. PMID:28403159

Improved supervised classification of accelerometry data to distinguish behaviors of soaring birds

USGS Publications Warehouse

Sur, Maitreyi; Suffredini, Tony; Wessells, Stephen M.; Bloom, Peter H.; Lanzone, Michael J.; Blackshire, Sheldon; Sridhar, Srisarguru; Katzner, Todd

2017-01-01

Soaring birds can balance the energetic costs of movement by switching between flapping, soaring and gliding flight. Accelerometers can allow quantification of flight behavior and thus a context to interpret these energetic costs. However, models to interpret accelerometry data are still being developed, rarely trained with supervised datasets, and difficult to apply. We collected accelerometry data at 140Hz from a trained golden eagle (Aquila chrysaetos) whose flight we recorded with video that we used to characterize behavior. We applied two forms of supervised classifications, random forest (RF) models and K-nearest neighbor (KNN) models. The KNN model was substantially easier to implement than the RF approach but both were highly accurate in classifying basic behaviors such as flapping (85.5% and 83.6% accurate, respectively), soaring (92.8% and 87.6%) and sitting (84.1% and 88.9%) with overall accuracies of 86.6% and 92.3% respectively. More detailed classification schemes, with specific behaviors such as banking and straight flights were well classified only by the KNN model (91.24% accurate; RF = 61.64% accurate). The RF model maintained its accuracy of classifying basic behavior classification accuracy of basic behaviors at sampling frequencies as low as 10Hz, the KNN at sampling frequencies as low as 20Hz. Classification of accelerometer data collected from free ranging birds demonstrated a strong dependence of predicted behavior on the type of classification model used. Our analyses demonstrate the consequence of different approaches to classification of accelerometry data, the potential to optimize classification algorithms with validated flight behaviors to improve classification accuracy, ideal sampling frequencies for different classification algorithms, and a number of ways to improve commonly used analytical techniques and best practices for classification of accelerometry data.

Mathematical Modelling Approach in Mathematics Education

ERIC Educational Resources Information Center

Arseven, Ayla

2015-01-01

The topic of models and modeling has come to be important for science and mathematics education in recent years. The topic of "Modeling" topic is especially important for examinations such as PISA which is conducted at an international level and measures a student's success in mathematics. Mathematical modeling can be defined as using…

Link-topic model for biomedical abbreviation disambiguation.

PubMed

Kim, Seonho; Yoon, Juntae

2015-02-01

The ambiguity of biomedical abbreviations is one of the challenges in biomedical text mining systems. In particular, the handling of term variants and abbreviations without nearby definitions is a critical issue. In this study, we adopt the concepts of topic of document and word link to disambiguate biomedical abbreviations. We newly suggest the link topic model inspired by the latent Dirichlet allocation model, in which each document is perceived as a random mixture of topics, where each topic is characterized by a distribution over words. Thus, the most probable expansions with respect to abbreviations of a given abstract are determined by word-topic, document-topic, and word-link distributions estimated from a document collection through the link topic model. The model allows two distinct modes of word generation to incorporate semantic dependencies among words, particularly long form words of abbreviations and their sentential co-occurring words; a word can be generated either dependently on the long form of the abbreviation or independently. The semantic dependency between two words is defined as a link and a new random parameter for the link is assigned to each word as well as a topic parameter. Because the link status indicates whether the word constitutes a link with a given specific long form, it has the effect of determining whether a word forms a unigram or a skipping/consecutive bigram with respect to the long form. Furthermore, we place a constraint on the model so that a word has the same topic as a specific long form if it is generated in reference to the long form. Consequently, documents are generated from the two hidden parameters, i.e. topic and link, and the most probable expansion of a specific abbreviation is estimated from the parameters. Our model relaxes the bag-of-words assumption of the standard topic model in which the word order is neglected, and it captures a richer structure of text than does the standard topic model by considering unigrams and semantically associated bigrams simultaneously. The addition of semantic links improves the disambiguation accuracy without removing irrelevant contextual words and reduces the parameter space of massive skipping or consecutive bigrams. The link topic model achieves 98.42% disambiguation accuracy on 73,505 MEDLINE abstracts with respect to 21 three letter abbreviations and their 139 distinct long forms. Copyright © 2014 Elsevier Inc. All rights reserved.

A Problem Solving Model for Use in Science Student Teacher Supervision.

ERIC Educational Resources Information Center

Cavallo, Ann M. L.; Tice, Craig J.

1993-01-01

Describes and suggests the use of a problem-solving model that improves communication between student teachers and supervisors through the student teaching practicum. The aim of the model is to promote experimentation with various teaching techniques and to stimulate thinking among student teachers about their teaching experiences. (PR)

A Descriptive Study of Differing School Health Delivery Models

ERIC Educational Resources Information Center

Becker, Sherri I.; Maughan, Erin

2017-01-01

The purpose of this exploratory qualitative study was to identify and describe emerging models of school health services. Participants (N = 11) provided information regarding their models in semistructured phone interviews. Results identified a variety of funding sources as well as different staffing configurations and supervision. Strengths of…