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https://www.readbyqxmd.com/read/29786028/evaluation-of-a-distance-learning-academic-support-program-for-medical-graduates-during-rural-hospital-service-in-india
#1
Rashmi Vyas, Anand Zachariah, Isobel Swamidasan, Priya Doris, Ilene Harris
Background: Christian Medical College (CMC), Vellore, India, a tertiary care hospital, designed a year-long Fellowship in Secondary Hospital Medicine (FSHM) for CMC graduates, with the aim to support them during rural service and be motivated to consider practicing in these hospitals. The FSHM was a blend of 15 paper-based distance learning modules, 3 contact sessions, community project work, and networking. This paper reports on the evaluation of the FSHM program. Methods: The curriculum development process for the FSHM reflected the six-step approach including problem identification, needs assessment, formulating objectives, selecting educational strategies, implementation, and evaluation...
September 2017: Education for Health: Change in Training & Practice
https://www.readbyqxmd.com/read/29785306/overweight-and-undernutrition-in-the-cases-of-school-going-adolescents-in-wolaita-sodo-town-southern-ethiopia-cross-sectional-study
#2
Dereje Yohannes Teferi, Gudina Egata Atomssa, Tefera Chane Mekonnen
Background: This study aimed to assess the prevalence of malnutrition and associated factors among school adolescents in Wolaita Sodo town, Southern Ethiopia. Methods: A school-based cross-sectional study was conducted from May 18-June 10, 2015. A multistage sampling was used to select a random sample of 690 adolescents from selected schools. Data on sociodemographic information were collected by using an interviewer-administered questionnaire, and anthropometric measurements were made by using a digital Seca scale and height measuring board by trained data collectors...
2018: Journal of Nutrition and Metabolism
https://www.readbyqxmd.com/read/29781522/learning-to-provide-children-with-a-secure-base-and-a-safe-haven-the-circle-of-security-parenting-cos-p-group-intervention
#3
Monica Kim, Susan S Woodhouse, Chenchen Dai
Insecure attachment is linked to a host of negative child outcomes, including internalizing and externalizing behavior problems. Circle of Security-Parenting (COS-P) is a manualized, video-based, eight unit, group parenting intervention to promote children's attachment security. COS-P was designed to be easily implemented, so as to make attachment interventions more widely available to families. We present the theoretical background of COS-P, research evidence supporting the COS approach, as well as a description of the COS-P intervention protocol...
May 21, 2018: Journal of Clinical Psychology
https://www.readbyqxmd.com/read/29781521/working-with-video-feedback-intervention-to-promote-positive-parenting-and-sensitive-discipline-vipp-sd-a-case-study
#4
Femmie Juffer, Marian J Bakermans-Kranenburg
Video-feedback Intervention to promote Positive Parenting and Sensitive Discipline (VIPP-SD), based on attachment theory and social learning theory, is an intervention aimed at enhancing sensitivity and firm limit setting in parents, and reducing behavior problems in children. The VIPP-SD program has been tested in populations of vulnerable children and parents at risk in twelve randomized controlled trials, and shows significant effects on both positive parenting and child outcomes. Here, we present a case study of an adoptive mother and her two-and-a-half-year-old adopted daughter...
May 21, 2018: Journal of Clinical Psychology
https://www.readbyqxmd.com/read/29781350/on-line-ethics-education-for-occupational-therapy-clinician-educators-a-single-group-pre-post-test-study
#5
Sandra VanderKaay, Lori Letts, Bonny Jung, Sandra E Moll
PURPOSE: Ethics education is a critical component of training rehabilitation practitioners. There is a need for capacity-building among ethics educators regarding facilitating ethical decision-making among students. The purpose of this study was to evaluate the utility of an on-line ethics education module for occupational therapy clinician-educators (problem-based learning tutors/clinical placement preceptors/evidence-based practice facilitators). METHOD: The Knowledge-to-Action Process informed development and evaluation of the module...
May 20, 2018: Disability and Rehabilitation
https://www.readbyqxmd.com/read/29780578/towards-the-development-of-day-one-competences-in-veterinary-behaviour-medicine-survey-of-veterinary-professionals-experience-in-companion-animal-practice-in-ireland
#6
Olwen Golden, Alison J Hanlon
Background: Veterinary behaviour medicine should be a foundation subject of the veterinary curriculum because of its wide scope of applications to veterinary practice. Private practitioners are likely to be the primary source of information on animal behaviour for most pet owners, however studies indicate that behavioural issues are not frequently discussed during companion animal consultations and many practitioners lack confidence in dealing with behavioural problems, likely due to poor coverage of this subject in veterinary education...
2018: Irish Veterinary Journal
https://www.readbyqxmd.com/read/29779553/social-work-student-and-practitioner-roles-in-integrated-care-settings
#7
Erin P Fraher, Erica Lynn Richman, Lisa de Saxe Zerden, Brianna Lombardi
INTRODUCTION: Social workers are increasingly being deployed in integrated medical and behavioral healthcare settings but information about the roles they fill in these settings is not well understood. This study sought to identify the functions that social workers perform in integrated settings and identify where they acquired the necessary skills to perform them. METHODS: Master of social work students (n=21) and their field supervisors (n=21) who were part of a Health Resources and Services Administration-funded program to train and expand the behavioral health workforce in integrated settings were asked how often they engaged in 28 functions, where they learned to perform those functions, and the degree to which their roles overlapped with others on the healthcare team...
June 2018: American Journal of Preventive Medicine
https://www.readbyqxmd.com/read/29776758/using-preference-learning-for-detecting-inconsistencies-in-clinical-practice-guidelines-methods-and-application-to-antibiotherapy
#8
Rosy Tsopra, Jean-Baptiste Lamy, Karima Sedki
Clinical practice guidelines provide evidence-based recommendations. However, many problems are reported, such as contradictions and inconsistencies. For example, guidelines recommend sulfamethoxazole/trimethoprim in child sinusitis, but they also state that there is a high bacteria resistance in this context. In this paper, we propose a method for the semi-automatic detection of inconsistencies in guidelines using preference learning, and we apply this method to antibiotherapy in primary care. The preference model was learned from the recommendations and from a knowledge base describing the domain...
May 15, 2018: Artificial Intelligence in Medicine
https://www.readbyqxmd.com/read/29775951/retinal-blood-vessel-segmentation-using-fully-convolutional-network-with-transfer-learning
#9
Zhexin Jiang, Hao Zhang, Yi Wang, Seok-Bum Ko
Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or computer-aided diagnosis systems. In this paper, a supervised method is presented based on a pre-trained fully convolutional network through transfer learning. This proposed method has simplified the typical retinal vessel segmentation problem from full-size image segmentation to regional vessel element recognition and result merging...
April 26, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
https://www.readbyqxmd.com/read/29775912/an-accurate-sleep-stages-classification-system-using-a-new-class-of-optimally-time-frequency-localized-three-band-wavelet-filter-bank
#10
Manish Sharma, Deepanshu Goyal, P V Achuth, U Rajendra Acharya
Sleep related disorder causes diminished quality of lives in human beings. Sleep scoring or sleep staging is the process of classifying various sleep stages which helps to detect the quality of sleep. The identification of sleep-stages using electroencephalogram (EEG) signals is an arduous task. Just by looking at an EEG signal, one cannot determine the sleep stages precisely. Sleep specialists may make errors in identifying sleep stages by visual inspection. To mitigate the erroneous identification and to reduce the burden on doctors, a computer-aided EEG based system can be deployed in the hospitals, which can help identify the sleep stages, correctly...
May 10, 2018: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/29775850/electrical-resistivity-imaging-inversion-an-isfla-trained-kernel-principal-component-wavelet-neural-network-approach
#11
Feibo Jiang, Li Dong, Qianwei Dai
The traditional artificial neural network (ANN) inversion of electrical resistivity imaging (ERI) based on gradient descent algorithm is known to be inept for its low computation efficiency and does not ensure global convergence. In order to solve above problems, a kernel principal component wavelet neural network (KPCWNN) trained by an improved shuffled frog leaping algorithm (ISFLA) method is proposed in this study. An additional kernel principal component (KPC) layer is applied to reduce the dimensionality of apparent resistivity data and increase the computational efficiency of wavelet neural network (WNN)...
April 24, 2018: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/29772818/integrated-method-for-personal-thermal-comfort-assessment-and-optimization-through-users-feedback-iot-and-machine-learning-a-case-study-%C3%A2
#12
Francesco Salamone, Lorenzo Belussi, Cristian Currò, Ludovico Danza, Matteo Ghellere, Giulia Guazzi, Bruno Lenzi, Valentino Megale, Italo Meroni
Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV and PPD) and users as active subjects whose thermal perception is influenced by outdoor climatic conditions (adaptive approach). The latter method is the starting point to investigate thermal comfort from an overall perspective by considering endogenous variables besides the traditional physical and environmental ones...
May 17, 2018: Sensors
https://www.readbyqxmd.com/read/29772794/amid-accurate-magnetic-indoor-localization-using-deep-learning
#13
Namkyoung Lee, Sumin Ahn, Dongsoo Han
Geomagnetic-based indoor positioning has drawn a great attention from academia and industry due to its advantage of being operable without infrastructure support and its reliable signal characteristics. However, it must overcome the problems of ambiguity that originate with the nature of geomagnetic data. Most studies manage this problem by incorporating particle filters along with inertial sensors. However, they cannot yield reliable positioning results because the inertial sensors in smartphones cannot precisely predict the movement of users...
May 17, 2018: Sensors
https://www.readbyqxmd.com/read/29771918/a-hybrid-q-learning-sine-cosine-based-strategy-for-addressing-the-combinatorial-test-suite-minimization-problem
#14
Kamal Z Zamli, Fakhrud Din, Bestoun S Ahmed, Miroslav Bures
The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from -1 to 1)...
2018: PloS One
https://www.readbyqxmd.com/read/29771677/learning-based-adaptive-optimal-tracking-control-of-strict-feedback-nonlinear-systems
#15
Weinan Gao, Zhong-Ping Jiang
This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771670/optimal-fault-tolerant-control-for-discrete-time-nonlinear-strict-feedback-systems-based-on-adaptive-critic-design
#16
Zhanshan Wang, Lei Liu, Yanming Wu, Huaguang Zhang
This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highlight is the adaptive auxiliary signal of the actuator fault, which is designed to offset the effect of the fault. The considered systems are in strict-feedback forms and involve unknown nonlinear functions, which will result in the causal problem. To solve this problem, the original nonlinear systems are transformed into a novel system by employing the diffeomorphism theory...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771668/approximate-dynamic-programming-combining-regional-and-local-state-following-approximations
#17
Patryk Deptula, Joel A Rosenfeld, Rushikesh Kamalapurkar, Warren E Dixon
An infinite-horizon optimal regulation problem for a control-affine deterministic system is solved online using a local state following (StaF) kernel and a regional model-based reinforcement learning (R-MBRL) method to approximate the value function. Unlike traditional methods such as R-MBRL that aim to approximate the value function over a large compact set, the StaF kernel approach aims to approximate the value function in a local neighborhood of the state that travels within a compact set. In this paper, the value function is approximated using a state-dependent convex combination of the StaF-based and the R-MBRL-based approximations...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771664/guided-policy-exploration-for-markov-decision-processes-using-an-uncertainty-based-value-of-information-criterion
#18
Isaac J Sledge, Matthew S Emigh, Jose C Principe
Reinforcement learning in environments with many action-state pairs is challenging. The issue is the number of episodes needed to thoroughly search the policy space. Most conventional heuristics address this search problem in a stochastic manner. This can leave large portions of the policy space unvisited during the early training stages. In this paper, we propose an uncertainty-based, information-theoretic approach for performing guided stochastic searches that more effectively cover the policy space. Our approach is based on the value of information, a criterion that provides the optimal tradeoff between expected costs and the granularity of the search process...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29771662/optimal-and-autonomous-control-using-reinforcement-learning-a-survey
#19
Bahare Kiumarsi, Kyriakos G Vamvoudakis, Hamidreza Modares, Frank L Lewis
This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29770257/toeplitz-inverse-covariance-based-clustering-of-multivariate-time-series-data
#20
David Hallac, Sagar Vare, Stephen Boyd, Jure Leskovec
Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters . For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions ( i.e. , walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series...
August 2017: KDD: Proceedings
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