Decentralized stabilization for a class of continuous-time nonlinear interconnected systems using online learning optimal control approach.

PubMed

Liu, Derong; Wang, Ding; Li, Hongliang

2014-02-01

In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuous-time nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control strategy of the overall system can be established by adding appropriate feedback gains to the optimal control policies of the isolated subsystems. Next, an online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman equations related to the optimal control problem. Through constructing a set of critic neural networks, the cost functions can be obtained approximately, followed by the control policies. Furthermore, the dynamics of the estimation errors of the critic networks are verified to be uniformly and ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the present decentralized control scheme.

Motorized CPM/CAM physiotherapy device with sliding-mode Fuzzy Neural Network control loop.

PubMed

Ho, Hung-Jung; Chen, Tien-Chi

2009-11-01

Continuous passive motion (CPM) and controllable active motion (CAM) physiotherapy devices promote rehabilitation of damaged joints. This paper presents a computerized CPM/CAM system that obviates the need for mechanical resistance devices such as springs. The system is controlled by a computer which performs sliding-mode Fuzzy Neural Network (FNN) calculations online. CAM-type resistance force is generated by the active performance of an electric motor which is controlled so as to oppose the motion of the patient's leg. A force sensor under the patient's foot on the device pedal provides data for feedback in a sliding-mode FNN control loop built around the motor. Via an active impedance control feedback system, the controller drives the motor to behave similarly to a damped spring by generating and controlling the amplitude and direction of the pedal force in relation to the patient's leg. Experiments demonstrate the high sensitivity and speed of the device. The PC-based feedback nature of the control loop means that sophisticated auto-adaptable CPM/CAM custom-designed physiotherapy becomes possible. The computer base also allows extensive data recording, data analysis and network-connected remote patient monitoring.

Interaction in Spoken Word Recognition Models: Feedback Helps.

PubMed

Magnuson, James S; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis.

Interaction in Spoken Word Recognition Models: Feedback Helps

PubMed Central

Magnuson, James S.; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D.

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis. PMID:29666593

CRank: A Credit Assessment Model in C2C e-Commerce

NASA Astrophysics Data System (ADS)

Zhang, Zhiqiang; Xie, Xiaoqin; Pan, Haiwei; Han, Qilong

An increasing number of consumers not only purchase but also resell merchandise through C2C web sites. One of the greatest concerns for the netizens is the lacking of a fair credit assessment system. Trust and trustworthiness are crucial to the survival of online markets. Reputation systems that rely on feedback from traders help to sustain the trust. And reputation systems provide one of the ways of building trusts online. In this chapter, we investigate a credit assessment model, CRank, for the members in the context of e-market systems, such as Alibaba, eBay, to solve such problem as how to choose a credible business partner when the customer wants to purchase some products from the Internet. CRank makes use of feedback profile made up of ranks from other users as well as an overall feedback rating for the user based on the idea of PageRank. This model can be used to build a trustable relation network among business participants.

A multimodal interface device for online board games designed for sight-impaired people.

PubMed

Caporusso, Nicholas; Mkrtchyan, Lusine; Badia, Leonardo

2010-03-01

Online games between remote opponents playing over computer networks are becoming a common activity of everyday life. However, computer interfaces for board games are usually based on the visual channel. For example, they require players to check their moves on a video display and interact by using pointing devices such as a mouse. Hence, they are not suitable for visually impaired people. The present paper discusses a multipurpose system that allows especially blind and deafblind people playing chess or other board games over a network, therefore reducing their disability barrier. We describe and benchmark a prototype of a special interactive haptic device for online gaming providing a dual tactile feedback. The novel interface of this proposed device is able to guarantee not only a better game experience for everyone but also an improved quality of life for sight-impaired people.

Online Instructor's Use of Audio Feedback to Increase Social Presence and Student Satisfaction

ERIC Educational Resources Information Center

Portolese Dias, Laura; Trumpy, Robert

2014-01-01

This study investigates the impact of written group feedback, versus audio feedback, based upon four student satisfaction measures in the online classroom environment. Undergraduate students in the control group were provided both individual written feedback and group written feedback, while undergraduate students in the experimental treatment…

Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration

PubMed Central

Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B.

2017-01-01

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of speech but retain the ability to make online feedback corrections; indeed, the patients show an increased sensitivity to feedback. These results indicate that the cerebellum forms a crucial part of the feedforward control system for speech but is not essential for online, feedback control. PMID:28842410

Interface Prostheses With Classifier-Feedback-Based User Training.

PubMed

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.

OCT-based angiography in real time with hand-held probe

NASA Astrophysics Data System (ADS)

Gelikonov, Grigory V.; Moiseev, Alexander A.; Ksenofontov, Sergey Y.; Terpelov, Dmitry A.; Gelikonov, Valentine M.

2018-03-01

This work is dedicated to development of the OCT system capable to visualize blood vessel network for everyday clinical use. Following problems were solved during the development: compensation of specific natural tissue displacements, induced by contact scanning mode and physiological motion of patients (e.g. respiratory and cardiac motions) and on-line visualization of vessel net to provide the feedback for system operator.

General Practitioners' Concerns About Online Patient Feedback: Findings From a Descriptive Exploratory Qualitative Study in England.

PubMed

Patel, Salma; Cain, Rebecca; Neailey, Kevin; Hooberman, Lucy

2015-12-08

The growth in the volume of online patient feedback, including online patient ratings and comments, suggests that patients are embracing the opportunity to review online their experience of receiving health care. Very little is known about health care professionals' attitudes toward online patient feedback and whether health care professionals are comfortable with the public nature of the feedback. The aim of the overall study was to explore and describe general practitioners' attitudes toward online patient feedback. This paper reports on the findings of one of the aims of the study, which was to explore and understand the concerns that general practitioners (GPs) in England have about online patient feedback. This could then be used to improve online patient feedback platforms and help to increase usage of online patient feedback by GPs and, by extension, their patients. A descriptive qualitative approach using face-to-face semistructured interviews was used in this study. A topic guide was developed following a literature review and discussions with key stakeholders. GPs (N=20) were recruited from Cambridgeshire, London, and Northwest England through probability and snowball sampling. Interviews were transcribed verbatim and analyzed in NVivo using the framework method, a form of thematic analysis. Most participants in this study had concerns about online patient feedback. They questioned the validity of online patient feedback because of data and user biases and lack of representativeness, the usability of online patient feedback due to the feedback being anonymous, the transparency of online patient feedback because of the risk of false allegations and breaching confidentiality, and the resulting impact of all those factors on them, their professional practice, and their relationship with their patients. The majority of GPs interviewed had reservations and concerns about online patient feedback and questioned its validity and usefulness among other things. Based on the findings from the study, recommendations for online patient feedback website providers in England are given. These include suggestions to make some specific changes to the platform and the need to promote online patient feedback more among both GPs and health care users, which may help to reduce some of the concerns raised by GPs about online patient feedback in this study.

General Practitioners’ Concerns About Online Patient Feedback: Findings From a Descriptive Exploratory Qualitative Study in England

PubMed Central

Cain, Rebecca; Neailey, Kevin; Hooberman, Lucy

2015-01-01

Background The growth in the volume of online patient feedback, including online patient ratings and comments, suggests that patients are embracing the opportunity to review online their experience of receiving health care. Very little is known about health care professionals’ attitudes toward online patient feedback and whether health care professionals are comfortable with the public nature of the feedback. Objective The aim of the overall study was to explore and describe general practitioners’ attitudes toward online patient feedback. This paper reports on the findings of one of the aims of the study, which was to explore and understand the concerns that general practitioners (GPs) in England have about online patient feedback. This could then be used to improve online patient feedback platforms and help to increase usage of online patient feedback by GPs and, by extension, their patients. Methods A descriptive qualitative approach using face-to-face semistructured interviews was used in this study. A topic guide was developed following a literature review and discussions with key stakeholders. GPs (N=20) were recruited from Cambridgeshire, London, and Northwest England through probability and snowball sampling. Interviews were transcribed verbatim and analyzed in NVivo using the framework method, a form of thematic analysis. Results Most participants in this study had concerns about online patient feedback. They questioned the validity of online patient feedback because of data and user biases and lack of representativeness, the usability of online patient feedback due to the feedback being anonymous, the transparency of online patient feedback because of the risk of false allegations and breaching confidentiality, and the resulting impact of all those factors on them, their professional practice, and their relationship with their patients. Conclusions The majority of GPs interviewed had reservations and concerns about online patient feedback and questioned its validity and usefulness among other things. Based on the findings from the study, recommendations for online patient feedback website providers in England are given. These include suggestions to make some specific changes to the platform and the need to promote online patient feedback more among both GPs and health care users, which may help to reduce some of the concerns raised by GPs about online patient feedback in this study. PMID:26681299

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

PubMed

Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

2013-08-14

High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. ClinicalTrials.gov NCT01142804.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

PubMed

Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

PubMed Central

Gerstner, Wulfram

2017-01-01

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically. PMID:29173280

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

Exploring the Impact of Role-Playing on Peer Feedback in an Online Case-Based Learning Activity

ERIC Educational Resources Information Center

Ching, Yu-Hui

2014-01-01

This study explored the impact of role-playing on the quality of peer feedback and learners' perception of this strategy in a case-based learning activity with VoiceThread in an online course. The findings revealed potential positive impact of role-playing on learners' generation of constructive feedback as role-playing was associated with higher…

Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration.

PubMed

Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B

2017-09-20

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of speech but retain the ability to make online feedback corrections; indeed, the patients show an increased sensitivity to feedback. These results indicate that the cerebellum forms a crucial part of the feedforward control system for speech but is not essential for online, feedback control. Copyright © 2017 the authors 0270-6474/17/379249-10$15.00/0.

Towards benchmarking citizen observatories: Features and functioning of online amateur weather networks.

PubMed

Gharesifard, Mohammad; Wehn, Uta; van der Zaag, Pieter

2017-05-15

Crowd-sourced environmental observations are increasingly being considered as having the potential to enhance the spatial and temporal resolution of current data streams from terrestrial and areal sensors. The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public and has resulted in the formation of various online environmental citizen observatory networks. Online amateur weather networks are a particular example of such ICT-mediated observatories that are rooted in one of the oldest and most widely practiced citizen science activities, namely amateur weather observation. The objective of this paper is to introduce a conceptual framework that enables a systematic review of the features and functioning of these expanding networks. This is done by considering distinct dimensions, namely the geographic scope and types of participants, the network's establishment mechanism, revenue stream(s), existing communication paradigm, efforts required by data sharers, support offered by platform providers, and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run the networks, and their sustainability. This framework is then utilized to perform a critical review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) there are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks; (2) the revenue stream(s) of online amateur weather networks is one of the least discussed but arguably most important dimensions that is crucial for the sustainability of these networks; and (3) all of the networks included in this study have one or more explicit modes of bi-directional communication, however, this is limited to feedback mechanisms that are mainly designed to educate the data sharers. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Comparison of Electronic and Paper-Based Assignment Submission and Feedback

ERIC Educational Resources Information Center

Bridge, Pete; Appleyard, Rob

2008-01-01

This paper presents the results of a study evaluating student perceptions of online assignment submission. 47 students submitted assignments and received feedback via features within the Virtual Learning Environment Blackboard[TM]. The students then completed questionnaires comparing their experience of online submission and feedback with…

Online Assessment Feedback: Competitive, Individualistic, or? Preferred Form!

ERIC Educational Resources Information Center

Bower, Matt

2005-01-01

This study investigated the "the effects of receiving the preferred form of online assessment feedback upon middle school mathematics students." Students completed a Web-based quadratics equations learning module followed by a randomly generated online quiz that they could practise as often as they liked. The effect of receiving their preferred…

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model

PubMed Central

2013-01-01

Background High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. Methods/Design A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants’ online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Discussion Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. Trial registration ClinicalTrials.gov NCT01142804 PMID:23945138

Feedforward-Feedback Hybrid Control for Magnetic Shape Memory Alloy Actuators Based on the Krasnosel'skii-Pokrovskii Model

PubMed Central

Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

2014-01-01

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system. PMID:24828010

Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

PubMed

Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

2014-01-01

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

Online screening and feedback to increase help-seeking for mental health problems: population-based randomised controlled trial.

PubMed

Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Brewer, Jacqueline L

2016-01-01

Community-based screening for mental health problems may increase service use through feedback to individuals about their severity of symptoms and provision of contacts for appropriate services. The effect of symptom feedback on service use was assessed. Secondary outcomes included symptom change and study attrition. Using online recruitment, 2773 participants completed a comprehensive survey including screening for depression ( n =1366) or social anxiety ( n =1407). Across these two versions, approximately half ( n =1342) of the participants were then randomly allocated to receive tailored feedback. Participants were reassessed after 3 months (Australian New Zealand Clinical Trials Registry ANZCTR12614000324617). A negative effect of providing social anxiety feedback to individuals was observed, with significant reductions in professional service use. Greater attrition and lower intentions to seek help were also observed after feedback. Online mental health screening with feedback is not effective for promoting professional service use. Alternative models of online screening require further investigation. None. © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

Online screening and feedback to increase help-seeking for mental health problems: population-based randomised controlled trial

PubMed Central

Calear, Alison L.; Sunderland, Matthew; Carragher, Natacha; Brewer, Jacqueline L.

2016-01-01

Background Community-based screening for mental health problems may increase service use through feedback to individuals about their severity of symptoms and provision of contacts for appropriate services. Aims The effect of symptom feedback on service use was assessed. Secondary outcomes included symptom change and study attrition. Method Using online recruitment, 2773 participants completed a comprehensive survey including screening for depression (n=1366) or social anxiety (n=1407). Across these two versions, approximately half (n=1342) of the participants were then randomly allocated to receive tailored feedback. Participants were reassessed after 3 months (Australian New Zealand Clinical Trials Registry ANZCTR12614000324617). Results A negative effect of providing social anxiety feedback to individuals was observed, with significant reductions in professional service use. Greater attrition and lower intentions to seek help were also observed after feedback. Conclusions Online mental health screening with feedback is not effective for promoting professional service use. Alternative models of online screening require further investigation. Declaration of interest None. Copyright and usage © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence. PMID:27703756

How social network analysis can be used to monitor online collaborative learning and guide an informed intervention

PubMed Central

Fors, Uno; Tedre, Matti; Nouri, Jalal

2018-01-01

To ensure online collaborative learning meets the intended pedagogical goals (is actually collaborative and stimulates learning), mechanisms are needed for monitoring the efficiency of online collaboration. Various studies have indicated that social network analysis can be particularly effective in studying students’ interactions in online collaboration. However, research in education has only focused on the theoretical potential of using SNA, not on the actual benefits they achieved. This study investigated how social network analysis can be used to monitor online collaborative learning, find aspects in need of improvement, guide an informed intervention, and assess the efficacy of intervention using an experimental, observational repeated-measurement design in three courses over a full-term duration. Using a combination of SNA-based visual and quantitative analysis, we monitored three SNA constructs for each participant: the level of interactivity, the role, and position in information exchange, and the role played by each participant in the collaboration. On the group level, we monitored interactivity and group cohesion indicators. Our monitoring uncovered a non-collaborative teacher-centered pattern of interactions in the three studied courses as well as very few interactions among students, limited information exchange or negotiation, and very limited student networks dominated by the teacher. An intervention based on SNA-generated insights was designed. The intervention was structured into five actions: increasing awareness, promoting collaboration, improving the content, preparing teachers, and finally practicing with feedback. Evaluation of the intervention revealed that it has significantly enhanced student-student interactions and teacher-student interactions, as well as produced a collaborative pattern of interactions among most students and teachers. Since efficient and communicative activities are essential prerequisites for successful content discussion and for realizing the goals of collaboration, we suggest that our SNA-based approach will positively affect teaching and learning in many educational domains. Our study offers a proof-of-concept of what SNA can add to the current tools for monitoring and supporting teaching and learning in higher education. PMID:29566058

How social network analysis can be used to monitor online collaborative learning and guide an informed intervention.

PubMed

Saqr, Mohammed; Fors, Uno; Tedre, Matti; Nouri, Jalal

2018-01-01

To ensure online collaborative learning meets the intended pedagogical goals (is actually collaborative and stimulates learning), mechanisms are needed for monitoring the efficiency of online collaboration. Various studies have indicated that social network analysis can be particularly effective in studying students' interactions in online collaboration. However, research in education has only focused on the theoretical potential of using SNA, not on the actual benefits they achieved. This study investigated how social network analysis can be used to monitor online collaborative learning, find aspects in need of improvement, guide an informed intervention, and assess the efficacy of intervention using an experimental, observational repeated-measurement design in three courses over a full-term duration. Using a combination of SNA-based visual and quantitative analysis, we monitored three SNA constructs for each participant: the level of interactivity, the role, and position in information exchange, and the role played by each participant in the collaboration. On the group level, we monitored interactivity and group cohesion indicators. Our monitoring uncovered a non-collaborative teacher-centered pattern of interactions in the three studied courses as well as very few interactions among students, limited information exchange or negotiation, and very limited student networks dominated by the teacher. An intervention based on SNA-generated insights was designed. The intervention was structured into five actions: increasing awareness, promoting collaboration, improving the content, preparing teachers, and finally practicing with feedback. Evaluation of the intervention revealed that it has significantly enhanced student-student interactions and teacher-student interactions, as well as produced a collaborative pattern of interactions among most students and teachers. Since efficient and communicative activities are essential prerequisites for successful content discussion and for realizing the goals of collaboration, we suggest that our SNA-based approach will positively affect teaching and learning in many educational domains. Our study offers a proof-of-concept of what SNA can add to the current tools for monitoring and supporting teaching and learning in higher education.

Supporting More Inclusive Learning with Social Networking: A Case Study of Blended Socialised Design Education

ERIC Educational Resources Information Center

Rodrigo, Russell; Nguyen, Tam

2013-01-01

This paper presents a qualitative case study of socialised blended learning, using a social network platform to investigate the level of literacies and interactions of students in a blended learning environment of traditional face-to-face design studio and online participatory teaching. Using student and staff feedback, the paper examines the use…

Design and evaluation of a peer network to support adherence to a web-based intervention for adolescents

PubMed Central

Ho, Joyce; Corden, Marya E.; Caccamo, Lauren; Tomasino, Kathryn Noth; Duffecy, Jenna; Begale, Mark; Mohr, David C.

2016-01-01

Background Depression during adolescence is common but can be prevented. Behavioral intervention technologies (BITs) designed to prevent depression in adolescence, especially standalone web-based interventions, have shown mixed outcomes, likely due to poor intervention adherence. BIT research involving adults has shown that the presence of coaches or peers promotes intervention use. Developmentally, adolescence is a time when peer-based social relationships take precedence. This study examines whether peer-networked support may promote adherence to BITs in this age group. Objective Adopting the framework of the Supportive Accountability model, which defines the types of human support and interactions required to maintain engagement and persistence with BITs, this paper presents a feasibility study of a peer-networked online intervention for depression prevention among adolescents. We described the development of the peer network, the evaluation of participant use of the peer networking features, and qualitative user feedback to inform continued BIT development. Method Two groups of adolescents (N = 13) participated in 10-week programs of the peer networked based online intervention. Adolescents had access to didactic lessons, CBT based mood management tools, and peer networking features. The peer networking features are integrated into the site by making use expectations explicit, allow network members to monitor the activities of others, and to supportively hold each other accountable for meeting use expectations. The study collected qualitative feedback from participants as well as usage of site features and tools. Results Participants logged in an average of 12.8 sessions over an average of 10.4 unique days during the 10-week program. On average, 66% of all use sessions occurred within the first 3 weeks of use. The number of “exchange comments”, that is, comments posted that were part of an exchange between two or more participants, was significantly positively correlated with mean time spent on site (r = 0.62, p = 0.032), use of the Activity Tracker (r = 0.70, p = 0.012) and Didactic Lesson (r = 0.73, p = 0.007). Qualitative interviews revealed that adolescents generally liked and were motivated by the peer networking features during the first weeks of the intervention when general site use by group members was high. However, the decrease of site use by group members during the subsequent weeks negatively affected participants’ desire to log on or engage with group members. Conclusions This pilot study highlights the potential that a BIT designed to harness the connection among a peer network, thereby promoting supportive accountability, may improve adolescent adherence to BITs for depression prevention. PMID:27722095

Examining a Web-Based Peer Feedback System in an Introductory Computer Literacy Course

ERIC Educational Resources Information Center

Adiguzel, Tufan; Varank, Ilhan; Erkoç, Mehmet Fatih; Buyukimdat, Meryem Koskeroglu

2017-01-01

This study focused on formative use of peer feedback in an online system that was used in basic computer literacy for word processing assignment-related purposes. Specifically, the effect of quantity, modality and satisfaction of peer feedback provided through the online system on students' performance, self-efficacy, and technology acceptance was…

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

PubMed

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

Exploring "DIALANG'S" Diagnostic Feedback in Online L2 Dynamic Assessment

ERIC Educational Resources Information Center

Ebadi, Saman

2016-01-01

Dynamic assessment (DA) as an alternative to psychometric-based testing focuses on the collaborative dialogue between the learners and the mediator to move the learners from their current capabilities. This study represents a web-based qualitative inquiry in online DA which aims at addressing the inadequacy of the diagnostic feedback of the…

Feedback and Feed-Forward for Promoting Problem-Based Learning in Online Learning Environments

ERIC Educational Resources Information Center

Webb, Ashley; Moallem, Mahnaz

2016-01-01

Purpose: The study aimed to (1) review the literature to construct conceptual models that could guide instructional designers in developing problem/project-based learning environments while applying effective feedback strategies, (2) use the models to design, develop, and implement an online graduate course, and (3) assess the efficiency of the…

Feedback-Based Projected-Gradient Method for Real-Time Optimization of Aggregations of Energy Resources

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize operational objectives of distribution-level distributed energy resources (DERs), while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power flows, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying convex optimization problem.« less

Feedback-Based Projected-Gradient Method For Real-Time Optimization of Aggregations of Energy Resources: Preprint

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize the operational objectives of distribution-level distributed energy resources (DERs) while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying optimization problem.« less

Testing Quick Response (QR) Codes as an Innovation to Improve Feedback Among Geographically-Separated Clerkship Sites.

PubMed

Snyder, Matthew J; Nguyen, Dana R; Womack, Jasmyne J; Bunt, Christopher W; Westerfield, Katie L; Bell, Adriane E; Ledford, Christy J W

2018-03-01

Collection of feedback regarding medical student clinical experiences for formative or summative purposes remains a challenge across clinical settings. The purpose of this study was to determine whether the use of a quick response (QR) code-linked online feedback form improves the frequency and efficiency of rater feedback. In 2016, we compared paper-based feedback forms, an online feedback form, and a QR code-linked online feedback form at 15 family medicine clerkship sites across the United States. Outcome measures included usability, number of feedback submissions per student, number of unique raters providing feedback, and timeliness of feedback provided to the clerkship director. The feedback method was significantly associated with usability, with QR code scoring the highest, and paper second. Accessing feedback via QR code was associated with the shortest time to prepare feedback. Across four rotations, separate repeated measures analyses of variance showed no effect of feedback system on the number of submissions per student or the number of unique raters. The results of this study demonstrate that preceptors in the family medicine clerkship rate QR code-linked feedback as a high usability platform. Additionally, this platform resulted in faster form completion than paper or online forms. An overarching finding of this study is that feedback forms must be portable and easily accessible. Potential implementation barriers and the social norm for providing feedback in this manner need to be considered.

Prosody production networks are modulated by sensory cues and social context.

PubMed

Klasen, Martin; von Marschall, Clara; Isman, Güldehen; Zvyagintsev, Mikhail; Gur, Ruben C; Mathiak, Klaus

2018-03-05

The neurobiology of emotional prosody production is not well investigated. In particular, the effects of cues and social context are not known. The present study sought to differentiate cued from free emotion generation and the effect of social feedback from a human listener. Online speech filtering enabled fMRI during prosodic communication in 30 participants. Emotional vocalizations were a) free, b) auditorily cued, c) visually cued, or d) with interactive feedback. In addition to distributed language networks, cued emotions increased activity in auditory and - in case of visual stimuli - visual cortex. Responses were larger in pSTG at the right hemisphere and the ventral striatum when participants were listened to and received feedback from the experimenter. Sensory, language, and reward networks contributed to prosody production and were modulated by cues and social context. The right pSTG is a central hub for communication in social interactions - in particular for interpersonal evaluation of vocal emotions.

Impact of Interactive Video Communication Versus Text-Based Feedback on Teaching, Social, and Cognitive Presence in Online Learning Communities.

PubMed

Seckman, Charlotte

A key element to online learning is the ability to create a sense of presence to improve learning outcomes. This quasi-experimental study evaluated the impact of interactive video communication versus text-based feedback and found a significant difference between the 2 groups related to teaching, social, and cognitive presence. Recommendations to enhance presence should focus on providing timely feedback, interactive learning experiences, and opportunities for students to establish relationships with peers and faculty.

Stabilization of model-based networked control systems

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

Miranda, Francisco; Instituto Politécnico de Viana do Castelo, Viana do Castelo; Abreu, Carlos

2016-06-08

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtainmore » an optimal feedback control is also presented.« less

The Effectiveness of Instructor Personalized and Formative Feedback Provided by Instructor in an Online Setting: Some Unresolved Issues

ERIC Educational Resources Information Center

Planar, Dolors; Moya, Soledad

2016-01-01

Formative feedback has great potential for teaching and learning in online undergraduate programmes. There is a large number of courses where the main source of feedback is provided by the instructor. This is particularly seen in subjects where assessments are designed based on specific activities which are the same for all students, and where the…

A New KE-Free Online ICALL System Featuring Error Contingent Feedback

ERIC Educational Resources Information Center

Tokuda, Naoyuki; Chen, Liang

2004-01-01

As a first step towards implementing a human language teacher, we have developed a new template-based on-line ICALL (intelligent computer assisted language learning) system capable of automatically diagnosing learners' free-format translated inputs and returning error contingent feedback. The system architecture we have adopted allows language…

The role of automated feedback in training and retaining biological recorders for citizen science.

PubMed

van der Wal, René; Sharma, Nirwan; Mellish, Chris; Robinson, Annie; Siddharthan, Advaith

2016-06-01

The rapid rise of citizen science, with lay people forming often extensive biodiversity sensor networks, is seen as a solution to the mismatch between data demand and supply while simultaneously engaging citizens with environmental topics. However, citizen science recording schemes require careful consideration of how to motivate, train, and retain volunteers. We evaluated a novel computing science framework that allowed for the automated generation of feedback to citizen scientists using natural language generation (NLG) technology. We worked with a photo-based citizen science program in which users also volunteer species identification aided by an online key. Feedback is provided after photo (and identification) submission and is aimed to improve volunteer species identification skills and to enhance volunteer experience and retention. To assess the utility of NLG feedback, we conducted two experiments with novices to assess short-term (single session) and longer-term (5 sessions in 2 months) learning, respectively. Participants identified a specimen in a series of photos. One group received only the correct answer after each identification, and the other group received the correct answer and NLG feedback explaining reasons for misidentification and highlighting key features that facilitate correct identification. We then developed an identification training tool with NLG feedback as part of the citizen science program BeeWatch and analyzed learning by users. Finally, we implemented NLG feedback in the live program and evaluated this by randomly allocating all BeeWatch users to treatment groups that received different types of feedback upon identification submission. After 6 months separate surveys were sent out to assess whether views on the citizen science program and its feedback differed among the groups. Identification accuracy and retention of novices were higher for those who received automated feedback than for those who received only confirmation of the correct identification without explanation. The value of NLG feedback in the live program, captured through questionnaires and evaluation of the online photo-based training tool, likewise showed that the automated generation of informative feedback fostered learning and volunteer engagement and thus paves the way for productive and long-lived citizen science projects. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Information Feedback Strategies in a Signal Controlled Network with Overlapped Routes

NASA Astrophysics Data System (ADS)

Tian, Li-Jun; Huang, Hai-Jun; Liu, Tian-Liang

2009-07-01

We investigate the effects of four different information feedback strategies on the dynamics of traffic, travelers' route choice and the resultant system performance in a signal controlled network with overlapped routes. Simulation results given by the cellular automaton model show that the system purpose-based mean velocity feedback strategy and the congestion coefficient feedback strategy have more advantages in improving network utilization efficiency and reducing travelers' travel times. The travel time feedback strategy and the individual purposed-based mean velocity feedback strategy behave slightly better to ensure user equity.

The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy.

PubMed

Garcia, David; Tessone, Claudio J; Mavrodiev, Pavlin; Perony, Nicolas

2014-10-06

What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesize that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large datasets: price on online exchanges, volume of word-of-mouth communication in online social media, volume of information search and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters. We also observe that spikes in information search, presumably linked to external events, precede drastic price declines. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena that leave digital footprints, such as online social network usage. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy

PubMed Central

Garcia, David; Tessone, Claudio J.; Mavrodiev, Pavlin; Perony, Nicolas

2014-01-01

What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesize that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large datasets: price on online exchanges, volume of word-of-mouth communication in online social media, volume of information search and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters. We also observe that spikes in information search, presumably linked to external events, precede drastic price declines. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena that leave digital footprints, such as online social network usage. PMID:25100315

A neural network controller for automated composite manufacturing

NASA Technical Reports Server (NTRS)

Lichtenwalner, Peter F.

1994-01-01

At McDonnell Douglas Aerospace (MDA), an artificial neural network based control system has been developed and implemented to control laser heating for the fiber placement composite manufacturing process. This neurocontroller learns an approximate inverse model of the process on-line to provide performance that improves with experience and exceeds that of conventional feedback control techniques. When untrained, the control system behaves as a proportional plus integral (PI) controller. However after learning from experience, the neural network feedforward control module provides control signals that greatly improve temperature tracking performance. Faster convergence to new temperature set points and reduced temperature deviation due to changing feed rate have been demonstrated on the machine. A Cerebellar Model Articulation Controller (CMAC) network is used for inverse modeling because of its rapid learning performance. This control system is implemented in an IBM compatible 386 PC with an A/D board interface to the machine.

Hold on to This!: Strategies for Teacher Feedback in Online Dance Courses

ERIC Educational Resources Information Center

Risner, Doug

2014-01-01

Drawn from current research on web-based learning, this practical article presents applied research and informed applications for online dance educators engaged in undergraduate and graduate dance education course work. With a focus on written assessment feedback, the author provides a review of recent literature, an overview of written feedback…

Sexual health professionals' evaluations of a prototype computer-based contraceptive planning intervention for adolescents: implications for practice.

PubMed

Brown, K E; Abraham, C; Joshi, P; Wallace, L M

2012-09-01

This paper aims to demonstrate how an online planning intervention to enhance contraceptive and condom use among adolescents was viewed by sexual health professionals. It identifies feedback that has facilitated improvement of the intervention both in terms of potential effectiveness and sustainability in practice. The data illustrate how professionals' feedback can enhance intervention development. Ten practitioners (two male; eight female) representing a range of roles in sexual health education and healthcare were given electronic copies of the prototype intervention. Interviews were conducted to elicit feedback. Transcripts of the interviews were subjected to thematic analysis. Practitioners provided positive feedback about the intervention content, use of on-line media, the validity of planning techniques and the inclusion of males in contraceptive planning. Issues with rapport building, trust, privacy, motivation, and time and resources were raised, however, and the promotion of condom carrying was contentious. Professionals' feedback provided scope for developing the intervention to meet practitioners' concerns, thus enhancing likely feasibility and acceptability in practice. Ways in which particular feedback was generalisable to wider theory-based and online intervention development are explored. Some responses indicated that health practitioners would benefit from training to embed theory-based interventions into sexual health education and healthcare.

Building inhabitant feedback: Creating a reflective practice for environmental design using activity theory

NASA Astrophysics Data System (ADS)

Cunningham, Dara Suzanne

The way buildings are designed now, there is little feedback from use involved in the design process. Attempts to correct this problem have been made in the form of Post Occupancy Evaluations (POEs) for 50-years but have largely failed. POEs are the accepted method for environmental designers to collect feedback about buildings in use. They are infrequently conducted, after the building is built, in a one-time only evaluation, and not funded as part of the build process. Other products receive feedback about the design in use from online critiques. Online critiques could provide a platform for feedback from actors engaged with buildings in use for environmental designers to utilize in developing reflective design rationale to avoid adverse consequences in future designs or correct consequences in past and current designs. Since buildings constitute such a large part of the human environment, it's important to research the effects of buildings on their inhabitants. In order for environmental designers to act on feedback from situated use, designers need to have access to that feedback and all actors interacting with the building design need to have an easy, inexpensive, and accessible method to submit feedback. These needs can be addressed by utilizing modern networked and mobile computing to collect and access building feedback. The analysis presented in this dissertation is informed by a thorough evaluation of the theory of reflective practice, activity theory, environmental design, and cognitive science research. From this analysis, I developed the following contributions. First, I expanded Schon's reflective practice by combining his theory with a modified version of activity theory, using activity theory to enrich reflective practice and create Reflective Activity Systems Theory (RAST), which provides a new framework to develop design rationale based on feedback from use and a focus on the activity. Second, I suggest the design of an activity information system, Socio-Technical Environments for Evolutionary Design (STEED), which provides an interactive platform for actor and artifact feedback from the use situation. Third, I discuss implications for practice by discussing how the feedback from actors and artifacts in situated use can be used to create reflective design rationale.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease

NASA Astrophysics Data System (ADS)

Gorzelic, P.; Schiff, S. J.; Sinha, A.

2013-04-01

Objective. To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). Approach. A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. Main Results. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Significance. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease.

PubMed

Gorzelic, P; Schiff, S J; Sinha, A

2013-04-01

To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

State feedback controller design for the synchronization of Boolean networks with time delays

NASA Astrophysics Data System (ADS)

Li, Fangfei; Li, Jianning; Shen, Lijuan

2018-01-01

State feedback control design to make the response Boolean network synchronize with the drive Boolean network is far from being solved in the literature. Motivated by this, this paper studies the feedback control design for the complete synchronization of two coupled Boolean networks with time delays. A necessary condition for the existence of a state feedback controller is derived first. Then the feedback control design procedure for the complete synchronization of two coupled Boolean networks is provided based on the necessary condition. Finally, an example is given to illustrate the proposed design procedure.

Assessing Online Textual Feedback to Support Student Intrinsic Motivation Using a Collaborative Text-Based Dialogue System: A Qualitative Study

ERIC Educational Resources Information Center

Shroff, Ronnie H.; Deneen, Christopher

2011-01-01

This paper assesses textual feedback to support student intrinsic motivation using a collaborative text-based dialogue system. A research model is presented based on research into intrinsic motivation, and the specific construct of feedback provides a framework for the model. A qualitative research methodology is used to validate the model.…

Adaptive Inner-Loop Rover Control

NASA Technical Reports Server (NTRS)

Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

2006-01-01

Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

Space shuttle main engine fault detection using neural networks

NASA Technical Reports Server (NTRS)

Bishop, Thomas; Greenwood, Dan; Shew, Kenneth; Stevenson, Fareed

1991-01-01

A method for on-line Space Shuttle Main Engine (SSME) anomaly detection and fault typing using a feedback neural network is described. The method involves the computation of features representing time-variance of SSME sensor parameters, using historical test case data. The network is trained, using backpropagation, to recognize a set of fault cases. The network is then able to diagnose new fault cases correctly. An essential element of the training technique is the inclusion of randomly generated data along with the real data, in order to span the entire input space of potential non-nominal data.

The Effect of Online Gaming, Cognition and Feedback Type in Facilitating Delayed Achievement of Different Learning Objectives

ERIC Educational Resources Information Center

Cameron, Brian; Dwyer, Francis

2005-01-01

Online and computer-based instructional gaming is becoming a viable instructional strategy at all levels of education. The purpose of this study was to examine the effect of (a) gaming, (b) gaming plus embedded questions, and (c) gaming plus questions plus feedback on delayed retention of different types of educational objectives for students…

Facilitating Student Learning in Distance Education: A Case Study on the Development and Implementation of a Multifaceted Feedback System

ERIC Educational Resources Information Center

Uribe, Samantha N.; Vaughan, Michelle

2017-01-01

This paper reports on a case study conducted in an American university investigating the role of feedback within a distance education environment. Based on data gathered from online and hybrid undergraduate students in a teacher education program and supported by existing research, we describe how we support online learners by implementing a…

Improving Student Engagement Using Course-Based Social Networks

ERIC Educational Resources Information Center

Imlawi, Jehad Mohammad

2013-01-01

This study proposes an engagement model that supports use of course-based online social networks for engaging student, and hence, improving their educational outcomes. This research demonstrates that instructors who create course-based online social networks to communicate with students can increase the student engagement in these online social…

Compensation of significant parametric uncertainties using sliding mode online learning

NASA Astrophysics Data System (ADS)

Schnetter, Philipp; Kruger, Thomas

An augmented nonlinear inverse dynamics (NID) flight control strategy using sliding mode online learning for a small unmanned aircraft system (UAS) is presented. Because parameter identification for this class of aircraft often is not valid throughout the complete flight envelope, aerodynamic parameters used for model based control strategies may show significant deviations. For the concept of feedback linearization this leads to inversion errors that in combination with the distinctive susceptibility of small UAS towards atmospheric turbulence pose a demanding control task for these systems. In this work an adaptive flight control strategy using feedforward neural networks for counteracting such nonlinear effects is augmented with the concept of sliding mode control (SMC). SMC-learning is derived from variable structure theory. It considers a neural network and its training as a control problem. It is shown that by the dynamic calculation of the learning rates, stability can be guaranteed and thus increase the robustness against external disturbances and system failures. With the resulting higher speed of convergence a wide range of simultaneously occurring disturbances can be compensated. The SMC-based flight controller is tested and compared to the standard gradient descent (GD) backpropagation algorithm under the influence of significant model uncertainties and system failures.

What Online Networks Offer: "Online Network Compositions and Online Learning Experiences of Three Ethnic Groups"

ERIC Educational Resources Information Center

Lecluijze, Suzanne Elisabeth; de Haan, Mariëtte; Ünlüsoy, Asli

2015-01-01

This exploratory study examines ethno-cultural diversity in youth's narratives regarding their "online" learning experiences while also investigating how these narratives can be understood from the analysis of their online network structure and composition. Based on ego-network data of 79 respondents this study compared the…

Adaptive output feedback control of flexible-joint robots using neural networks: dynamic surface design approach.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2008-10-01

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.

Studies on the population dynamics of a rumor-spreading model in online social networks

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

2018-02-01

This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

Advanced Feedback Methods in Information Retrieval.

ERIC Educational Resources Information Center

Salton, G.; And Others

1985-01-01

In this study, automatic feedback techniques are applied to Boolean query statements in online information retrieval to generate improved query statements based on information contained in previously retrieved documents. Feedback operations are carried out using conventional Boolean logic and extended logic. Experimental output is included to…

Student and Instructor Perceptions of Feedback in Asynchronous Online Learning: A Mixed-Methods Study

ERIC Educational Resources Information Center

Conrad, Susan

2016-01-01

Research about online learning suggests that instructor feedback is essential for student learning, especially when the feedback is personalized, specific, and timely. Feedback enhances instructor presence in online learning and has been shown to positively affect student outcomes. However, even with the technical ability to receive feedback at…

Hybrid attacks on model-based social recommender systems

NASA Astrophysics Data System (ADS)

Yu, Junliang; Gao, Min; Rong, Wenge; Li, Wentao; Xiong, Qingyu; Wen, Junhao

2017-10-01

With the growing popularity of the online social platform, the social network based approaches to recommendation emerged. However, because of the open nature of rating systems and social networks, the social recommender systems are susceptible to malicious attacks. In this paper, we present a certain novel attack, which inherits characteristics of the rating attack and the relation attack, and term it hybrid attack. Furtherly, we explore the impact of the hybrid attack on model-based social recommender systems in multiple aspects. The experimental results show that, the hybrid attack is more destructive than the rating attack in most cases. In addition, users and items with fewer ratings will be influenced more when attacked. Last but not the least, the findings suggest that spammers do not depend on the feedback links from normal users to become more powerful, the unilateral links can make the hybrid attack effective enough. Since unilateral links are much cheaper, the hybrid attack will be a great threat to model-based social recommender systems.

Student Responses to a Flipped Introductory Physics Class with built-in Post-Video Feedback Quizzes

NASA Astrophysics Data System (ADS)

Ramos, Roberto

We present and analyze student responses to multiple Introductory physics classes in a university setting, taught in a ''flipped'' class format. The classes included algebra- and calculus-based introductory physics. Outside class, students viewed over 100 online video lectures on Classical Mechanics, Electricity and Magnetism, and Modern Physics prepared by this author and in some cases, by a third-party lecture package available over YouTube. Inside the class, students solved and discussed problems and conceptual issues in greater detail. A pre-class online quiz was deployed as an important source of feedback. I will report on the student reactions to the feedback mechanism, student responses using data based on anonymous surveys, as well as on learning gains from pre-/post- physics diagnostic tests. The results indicate a broad mixture of responses to different lecture video packages that depend on learning styles and perceptions. Students preferred the online quizzes as a mechanism to validate their understanding. The learning gains based on FCI and CSEM surveys were significant.

SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

NASA Astrophysics Data System (ADS)

Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

2017-10-01

Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

Myoelectric intuitive control and transcutaneous electrical stimulation of the forearm for vibrotactile sensation feedback applied to a 3D printed prosthetic hand.

PubMed

Germany, Enrique I; Pino, Esteban J; Aqueveque, Pablo E

2016-08-01

This paper presents the development of a myoelectric prosthetic hand based on a 3D printed model. A myoelectric control strategy based on artificial neural networks is implemented on a microcontroller for online position estimation. Position estimation performance achieves a correlation index of 0.78. Also a study involving transcutaneous electrical stimulation was performed to provide tactile feedback. A series of stimulations with controlled parameters were tested on five able-body subjects. A single channel stimulator was used, positioning the electrodes 8 cm on the wrist over the ulnar and median nerve. Controlling stimulation parameters such as intensity, frequency and pulse width, the subjects were capable of distinguishing different sensations over the palm of the hand. Three main sensations where achieved: tickling, pressure and pain. Tickling and pressure were discretized into low, moderate and high according to the magnitude of the feeling. The parameters at which each sensation was obtained are further discussed in this paper.

Alcohol perceptions and behavior in a residential peer social network.

PubMed

Kenney, Shannon R; Ott, Miles; Meisel, Matthew K; Barnett, Nancy P

2017-01-01

Personalized normative feedback is a recommended component of alcohol interventions targeting college students. However, normative data are commonly collected through campus-based surveys, not through actual participant-referent relationships. In the present investigation, we examined how misperceptions of residence hall peers, both overall using a global question and those designated as important peers using person-specific questions, were related to students' personal drinking behaviors. Participants were 108 students (88% freshman, 54% White, 51% female) residing in a single campus residence hall. Participants completed an online baseline survey in which they reported their own alcohol use and perceptions of peer alcohol use using both an individual peer network measure and a global peer perception measure of their residential peers. We employed network autocorrelation models, which account for the inherent correlation between observations, to test hypotheses. Overall, participants accurately perceived the drinking of nominated friends but overestimated the drinking of residential peers. Consistent with hypotheses, overestimating nominated friend and global residential peer drinking predicted higher personal drinking, although perception of nominated peers was a stronger predictor. Interaction analyses showed that the relationship between global misperception and participant self-reported drinking was significant for heavy drinkers, but not non-heavy drinkers. The current findings explicate how student perceptions of peer drinking within an established social network influence drinking behaviors, which may be used to enhance the effectiveness of normative feedback interventions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hybrid adaptive ascent flight control for a flexible launch vehicle

NASA Astrophysics Data System (ADS)

Lefevre, Brian D.

For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the hybrid adaptive flight controller, development of a Newton's method based online parameter update that is modified to include a step size which regulates the rate of change in the parameter estimates, comparison of the modified Newton's method and recursive least squares online parameter update algorithms, modification of the neural network's input structure to accommodate for the nature of the nonlinearities present in a launch vehicle's ascent flight, examination of both tracking error based and modeling error based neural network weight update laws, and integration of feedback filters for the purpose of preventing harmful interaction between the flight control system and flexible structural modes. To validate the hybrid adaptive controller, a high-fidelity Ares I ascent flight simulator and a classical gain-scheduled proportional-integral-derivative (PID) ascent flight controller were obtained from the NASA Marshall Space Flight Center. The classical PID flight controller is used as a benchmark when analyzing the performance of the hybrid adaptive flight controller. Simulations are conducted which model both nominal and off-nominal flight conditions with structural flexibility of the vehicle either enabled or disabled. First, rigid body ascent simulations are performed with the hybrid adaptive controller under nominal flight conditions for the purpose of selecting the update laws which drive the indirect and direct adaptive components. With the neural network disabled, the results revealed that the recursive least squares online parameter update caused high frequency oscillations to appear in the engine gimbal commands. This is highly undesirable for long and slender launch vehicles, such as the Ares I, because such oscillation of the rocket nozzle could excite unstable structural flex modes. In contrast, the modified Newton's method online parameter update produced smooth control signals and was thus selected for use in the hybrid adaptive launch vehicle flight controller. In the simulations where the online parameter identification algorithm was disabled, the tracking error based neural network weight update law forced the network's output to diverge despite repeated reductions of the adaptive learning rate. As a result, the modeling error based neural network weight update law (which generated bounded signals) is utilized by the hybrid adaptive controller in all subsequent simulations. Comparing the PID and hybrid adaptive flight controllers under nominal flight conditions in rigid body ascent simulations showed that their tracking error magnitudes are similar for a period of time during the middle of the ascent phase. Though the PID controller performs better for a short interval around the 20 second mark, the hybrid adaptive controller performs far better from roughly 70 to 120 seconds. Elevating the aerodynamic loads by increasing the force and moment coefficients produced results very similar to the nominal case. However, applying a 5% or 10% thrust reduction to the first stage rocket motor causes the tracking error magnitude observed by the PID controller to be significantly elevated and diverge rapidly as the simulation concludes. In contrast, the hybrid adaptive controller steadily maintains smaller errors (often less than 50% of the corresponding PID value). Under the same sets of flight conditions with flexibility enabled, the results exhibit similar trends with the hybrid adaptive controller performing even better in each case. Again, the reduction of the first stage rocket motor's thrust clearly illustrated the superior robustness of the hybrid adaptive flight controller.

Student Writing, Teacher Feedback, and Working Online: Launching the Drive to Write Program

ERIC Educational Resources Information Center

Balu, Rekha; Alterman, Emma; Haider, Zeest; Quinn, Kelly

2018-01-01

The Drive to Write program was organized by New Visions for Public Schools (a New York City school support network that helps schools with professional development, data infrastructure, leadership training, certification, and more), and New Visions hopes it will lead to a new standard in writing instruction and student learning. New Visions is…

The Art of Giving Online Feedback

ERIC Educational Resources Information Center

Leibold, Nancyruth; Schwarz, Laura Marie

2015-01-01

The cultivation of providing online feedback that is positive, effective, and enhances the learning experience is a valuable educator skill. Acquisition of the art of providing feedback is through education, practice, and faculty development. This article provides information about the best practices for delivering online feedback to learners. An…

Exploring the Feasibility and Potential of Virtual Panels for Soliciting Feedback on Nutrition Education Materials: A Proof-of-Concept Study.

PubMed

Norman, Cameron D; Haresign, Helen; Mehling, Christine; Bloomberg, Honey

2016-01-01

A changing and cluttered information landscape has put pressure on health organizations to produce consumer information materials that are not only factual but high quality and engaging to audiences. User-centered design methods can be useful in obtaining feedback from consumers; however, they are labor intensive and slow, which is not responsive to the fast-paced communication landscape influenced by social media. EatRight Ontario (ERO), a provincial nutrition and health support program of Dietitians of Canada, develops evidence-based resources for consumers and sought to increase user-centered design activities by exploring whether the standard approach to feedback could be replicated online. While online feedback has been used in marketing research, few examples are available in health promotion and public health to guide programming and policy. This study compared a traditional in-person approach for recruitment and feedback using paper surveys with an Internet-based approach using Facebook as a recruitment tool and collecting user feedback via the Web. The purpose of the proof-of-concept study was to explore the feasibility of the approach and compare an online versus traditional approach in terms of recruitment issues and response. An exploratory, two-group comparative trial was conducted using a convenience and purposive sampling. Participants reviewed a handout on healthy eating and then completed an 18-item survey with both forced-choice items and open-ended responses. One group viewed a hard-copy prototype and completed a paper survey and the other viewed a PDF prototype via Web links and completed a Web survey. The total days required to fulfill the sample for each group were used as the primary method of efficiency calculation. In total, 44 participants (22 per condition) completed the study, consisting of 42 women and 2 men over the age of 18. Few significant differences were detected between the groups. Statistically significant (P≤.05) differences were detected on four attitudinal variables related to the document reviewed and include perceived length of the document, perceived attractiveness, likelihood of contacting ERO for food and nutrition questions in the future, and likelihood of recommending ERO to a friend. In all cases, the responses were more favorable to the document or ERO with the online group. All other variables showed no difference between them. A content review of the qualitative feedback found relative consistency in word use and number of words used, indicating relative parity in the amount of data generated between conditions. The online condition achieved its sampling target in 9 days, while the in-person method took 79 days to achieve the target. An online process of recruitment through Facebook and solicitation of online feedback is a feasible model that yields comparable response levels to in-person methods for user feedback. The online approach appears to be a faster and less resource-intensive approach than traditional in-person methods for feedback generation.

Exploring the Feasibility and Potential of Virtual Panels for Soliciting Feedback on Nutrition Education Materials: A Proof-of-Concept Study

PubMed Central

Haresign, Helen; Mehling, Christine; Bloomberg, Honey

2016-01-01

Background A changing and cluttered information landscape has put pressure on health organizations to produce consumer information materials that are not only factual but high quality and engaging to audiences. User-centered design methods can be useful in obtaining feedback from consumers; however, they are labor intensive and slow, which is not responsive to the fast-paced communication landscape influenced by social media. EatRight Ontario (ERO), a provincial nutrition and health support program of Dietitians of Canada, develops evidence-based resources for consumers and sought to increase user-centered design activities by exploring whether the standard approach to feedback could be replicated online. While online feedback has been used in marketing research, few examples are available in health promotion and public health to guide programming and policy. Objective This study compared a traditional in-person approach for recruitment and feedback using paper surveys with an Internet-based approach using Facebook as a recruitment tool and collecting user feedback via the Web. The purpose of the proof-of-concept study was to explore the feasibility of the approach and compare an online versus traditional approach in terms of recruitment issues and response. Methods An exploratory, two-group comparative trial was conducted using a convenience and purposive sampling. Participants reviewed a handout on healthy eating and then completed an 18-item survey with both forced-choice items and open-ended responses. One group viewed a hard-copy prototype and completed a paper survey and the other viewed a PDF prototype via Web links and completed a Web survey. The total days required to fulfill the sample for each group were used as the primary method of efficiency calculation. Results In total, 44 participants (22 per condition) completed the study, consisting of 42 women and 2 men over the age of 18. Few significant differences were detected between the groups. Statistically significant (P≤.05) differences were detected on four attitudinal variables related to the document reviewed and include perceived length of the document, perceived attractiveness, likelihood of contacting ERO for food and nutrition questions in the future, and likelihood of recommending ERO to a friend. In all cases, the responses were more favorable to the document or ERO with the online group. All other variables showed no difference between them. A content review of the qualitative feedback found relative consistency in word use and number of words used, indicating relative parity in the amount of data generated between conditions. The online condition achieved its sampling target in 9 days, while the in-person method took 79 days to achieve the target. Conclusions An online process of recruitment through Facebook and solicitation of online feedback is a feasible model that yields comparable response levels to in-person methods for user feedback. The online approach appears to be a faster and less resource-intensive approach than traditional in-person methods for feedback generation. PMID:27227153

Prediction of missing links and reconstruction of complex networks

NASA Astrophysics Data System (ADS)

Zhang, Cheng-Jun; Zeng, An

2016-04-01

Predicting missing links in complex networks is of great significance from both theoretical and practical point of view, which not only helps us understand the evolution of real systems but also relates to many applications in social, biological and online systems. In this paper, we study the features of different simple link prediction methods, revealing that they may lead to the distortion of networks’ structural and dynamical properties. Moreover, we find that high prediction accuracy is not definitely corresponding to a high performance in preserving the network properties when using link prediction methods to reconstruct networks. Our work highlights the importance of considering the feedback effect of the link prediction methods on network properties when designing the algorithms.

Critical Thinking in Gifted Children's Offline and Online Peer Feedback

ERIC Educational Resources Information Center

Miller, Myriah T.; Olthouse, Jill

2013-01-01

This comparative study identified the differences between gifted children's offline and online peer feedback within a summer talented writer's workshop. Researchers analyzed ten students' writings for degrees of critical thinking evident in their feedback. Online feedback included students' writings in social writing sites Storybird.com and…

The Effects of Feedback on Online Quizzes

ERIC Educational Resources Information Center

Butler, Melanie; Pyzdrowski, Laura; Goodykoontz, Adam; Walker, Vennessa

2008-01-01

Online homework is unable to provide the detailed feedback of paper and pencil assignments. However, immediate feedback is an advantage that online assessments provide. A research study was conducted that focused on the effects of immediate feedback; students in 5 sections of a Pre-calculus course were participants. Three sections were randomly…

Brain-actuated gait trainer with visual and proprioceptive feedback

NASA Astrophysics Data System (ADS)

Liu, Dong; Chen, Weihai; Lee, Kyuhwa; Chavarriaga, Ricardo; Bouri, Mohamed; Pei, Zhongcai; Millán, José del R.

2017-10-01

Objective. Brain-machine interfaces (BMIs) have been proposed in closed-loop applications for neuromodulation and neurorehabilitation. This study describes the impact of different feedback modalities on the performance of an EEG-based BMI that decodes motor imagery (MI) of leg flexion and extension. Approach. We executed experiments in a lower-limb gait trainer (the legoPress) where nine able-bodied subjects participated in three consecutive sessions based on a crossover design. A random forest classifier was trained from the offline session and tested online with visual and proprioceptive feedback, respectively. Post-hoc classification was conducted to assess the impact of feedback modalities and learning effect (an improvement over time) on the simulated trial-based performance. Finally, we performed feature analysis to investigate the discriminant power and brain pattern modulations across the subjects. Main results. (i) For real-time classification, the average accuracy was 62.33 +/- 4.95 % and 63.89 +/- 6.41 % for the two online sessions. The results were significantly higher than chance level, demonstrating the feasibility to distinguish between MI of leg extension and flexion. (ii) For post-hoc classification, the performance with proprioceptive feedback (69.45 +/- 9.95 %) was significantly better than with visual feedback (62.89 +/- 9.20 %), while there was no significant learning effect. (iii) We reported individual discriminate features and brain patterns associated to each feedback modality, which exhibited differences between the two modalities although no general conclusion can be drawn. Significance. The study reported a closed-loop brain-controlled gait trainer, as a proof of concept for neurorehabilitation devices. We reported the feasibility of decoding lower-limb movement in an intuitive and natural way. As far as we know, this is the first online study discussing the role of feedback modalities in lower-limb MI decoding. Our results suggest that proprioceptive feedback has an advantage over visual feedback, which could be used to improve robot-assisted strategies for motor training and functional recovery.

Brain-actuated gait trainer with visual and proprioceptive feedback.

PubMed

Liu, Dong; Chen, Weihai; Lee, Kyuhwa; Chavarriaga, Ricardo; Bouri, Mohamed; Pei, Zhongcai; Del R Millán, José

2017-10-01

Brain-machine interfaces (BMIs) have been proposed in closed-loop applications for neuromodulation and neurorehabilitation. This study describes the impact of different feedback modalities on the performance of an EEG-based BMI that decodes motor imagery (MI) of leg flexion and extension. We executed experiments in a lower-limb gait trainer (the legoPress) where nine able-bodied subjects participated in three consecutive sessions based on a crossover design. A random forest classifier was trained from the offline session and tested online with visual and proprioceptive feedback, respectively. Post-hoc classification was conducted to assess the impact of feedback modalities and learning effect (an improvement over time) on the simulated trial-based performance. Finally, we performed feature analysis to investigate the discriminant power and brain pattern modulations across the subjects. (i) For real-time classification, the average accuracy was [Formula: see text]% and [Formula: see text]% for the two online sessions. The results were significantly higher than chance level, demonstrating the feasibility to distinguish between MI of leg extension and flexion. (ii) For post-hoc classification, the performance with proprioceptive feedback ([Formula: see text]%) was significantly better than with visual feedback ([Formula: see text]%), while there was no significant learning effect. (iii) We reported individual discriminate features and brain patterns associated to each feedback modality, which exhibited differences between the two modalities although no general conclusion can be drawn. The study reported a closed-loop brain-controlled gait trainer, as a proof of concept for neurorehabilitation devices. We reported the feasibility of decoding lower-limb movement in an intuitive and natural way. As far as we know, this is the first online study discussing the role of feedback modalities in lower-limb MI decoding. Our results suggest that proprioceptive feedback has an advantage over visual feedback, which could be used to improve robot-assisted strategies for motor training and functional recovery.

Leverage Between the Buffering Effect and the Bystander Effect in Social Networking.

PubMed

Chiu, Yu-Ping; Chang, Shu-Chen

2015-08-01

This study examined encouraged and inhibited social feedback behaviors based on the theories of the buffering effect and the bystander effect. A system program was used to collect personal data and social feedback from a Facebook data set to test the research model. The results revealed that the buffering effect induced a positive relationship between social network size and feedback gained from friends when people's social network size was under a certain cognitive constraint. For people with a social network size that exceeds this cognitive constraint, the bystander effect may occur, in which having more friends may inhibit social feedback. In this study, two social psychological theories were applied to explain social feedback behavior on Facebook, and it was determined that social network size and social feedback exhibited no consistent linear relationship.

Links between real and virtual networks: a comparative study of online communities in Japan and Korea.

PubMed

Ishii, Kenichi; Ogasahara, Morihiro

2007-04-01

The present study explores how online communities affect real-world personal relations based on a cross-cultural survey conducted in Japan and Korea. Findings indicate that the gratifications of online communities moderate the effects of online communities on social participation. Online communities are categorized into a real-group-based community and a virtual-network-based community. The membership of real-group-based online community is positively correlated with social bonding gratification and negatively correlated with information- seeking gratification. Japanese users prefer more virtual-network-based online communities, while their Korean counterparts prefer real-group-based online communities. Korean users are more active in online communities and seek a higher level of socializing gratifications, such as social bonding and making new friends, when compared with their Japanese counterparts. These results indicate that in Korea, personal relations via the online community are closely associated with the real-world personal relations, but this is not the case in Japan. This study suggests that the effects of the Internet are culture-specific and that the online community can serve a different function in different cultural environments.

The use of online word of mouth opinion in online learning: a questionnaire survey.

PubMed

Sandars, John; Walsh, Kieran

2009-04-01

There is increasing use of online word of mouth opinion (user feedback) systems for general services but its use in online learning has not been previously investigated. To understand why users of BMJ Learning provide and read word of mouth feedback, and whether this feedback influences uptake of modules by prospective users. Online questionnaire of users of BMJ Learning who had completed online user feedback. 109 questionnaires were completed (response rate 25%). The main motivation to contribute was to influence the authors of the module (66%), and 43% stated that they wanted to help other users to make an informed choice. 16% stated that they wanted to develop an online community of learners. The main motivation to read the user feedback was to see if they agreed with the comments (56%). Online word of mouth opinion (user feedback) appears to be useful for online learners. There are also system design considerations since the attempt to create an online community of learners that is desired by some users will not be appreciated by others. Further research with a larger number of users is recommended to confirm the findings.

A similarity learning approach to content-based image retrieval: application to digital mammography.

PubMed

El-Naqa, Issam; Yang, Yongyi; Galatsanos, Nikolas P; Nishikawa, Robert M; Wernick, Miles N

2004-10-01

In this paper, we describe an approach to content-based retrieval of medical images from a database, and provide a preliminary demonstration of our approach as applied to retrieval of digital mammograms. Content-based image retrieval (CBIR) refers to the retrieval of images from a database using information derived from the images themselves, rather than solely from accompanying text indices. In the medical-imaging context, the ultimate aim of CBIR is to provide radiologists with a diagnostic aid in the form of a display of relevant past cases, along with proven pathology and other suitable information. CBIR may also be useful as a training tool for medical students and residents. The goal of information retrieval is to recall from a database information that is relevant to the user's query. The most challenging aspect of CBIR is the definition of relevance (similarity), which is used to guide the retrieval machine. In this paper, we pursue a new approach, in which similarity is learned from training examples provided by human observers. Specifically, we explore the use of neural networks and support vector machines to predict the user's notion of similarity. Within this framework we propose using a hierarchal learning approach, which consists of a cascade of a binary classifier and a regression module to optimize retrieval effectiveness and efficiency. We also explore how to incorporate online human interaction to achieve relevance feedback in this learning framework. Our experiments are based on a database consisting of 76 mammograms, all of which contain clustered microcalcifications (MCs). Our goal is to retrieve mammogram images containing similar MC clusters to that in a query. The performance of the retrieval system is evaluated using precision-recall curves computed using a cross-validation procedure. Our experimental results demonstrate that: 1) the learning framework can accurately predict the perceptual similarity reported by human observers, thereby serving as a basis for CBIR; 2) the learning-based framework can significantly outperform a simple distance-based similarity metric; 3) the use of the hierarchical two-stage network can improve retrieval performance; and 4) relevance feedback can be effectively incorporated into this learning framework to achieve improvement in retrieval precision based on online interaction with users; and 5) the retrieved images by the network can have predicting value for the disease condition of the query.

Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome.

PubMed

Tremblay, Mark S; Aubert, Salomé; Barnes, Joel D; Saunders, Travis J; Carson, Valerie; Latimer-Cheung, Amy E; Chastin, Sebastien F M; Altenburg, Teatske M; Chinapaw, Mai J M

2017-06-10

The prominence of sedentary behavior research in health science has grown rapidly. With this growth there is increasing urgency for clear, common and accepted terminology and definitions. Such standardization is difficult to achieve, especially across multi-disciplinary researchers, practitioners, and industries. The Sedentary Behavior Research Network (SBRN) undertook a Terminology Consensus Project to address this need. First, a literature review was completed to identify key terms in sedentary behavior research. These key terms were then reviewed and modified by a Steering Committee formed by SBRN. Next, SBRN members were invited to contribute to this project and interested participants reviewed and provided feedback on the proposed list of terms and draft definitions through an online survey. Finally, a conceptual model and consensus definitions (including caveats and examples for all age groups and functional abilities) were finalized based on the feedback received from the 87 SBRN member participants who responded to the original invitation and survey. Consensus definitions for the terms physical inactivity, stationary behavior, sedentary behavior, standing, screen time, non-screen-based sedentary time, sitting, reclining, lying, sedentary behavior pattern, as well as how the terms bouts, breaks, and interruptions should be used in this context are provided. It is hoped that the definitions resulting from this comprehensive, transparent, and broad-based participatory process will result in standardized terminology that is widely supported and adopted, thereby advancing future research, interventions, policies, and practices related to sedentary behaviors.

Internet based personalized feedback interventions for gamblers in Singapore: First results.

PubMed

Zhang, Melvyn W B; Yi, Yang; Cheok, Christopher C S

2016-01-01

Problem or pathological gambling has been a worldwide concern in the recent years, especially so with the advances in the technology, facilitating easier access to various means of gambling. Along with the advances in web-based and smartphone technologies, these technologies have been recently applied as adjunctive clinical tools to help gamblers. Taking into careful consideration the existing evidence base for Internet based interventions for pathological gambling, it seemed that the current published literature has demonstrated largely the efficacy of a personalized feedback intervention for pathological gambling; and further studies are still under-going to try and demonstrate the clinical feasibility of online web-based cognitive behavioral interventions for pathological gamblers. Given this, the aims of the current study are to (a) replicate an online personalized feedback intervention and determine its receptiveness in an Asian cohort of gamblers; and (b) to identify the demographics and characteristics of Asian gamblers who would utilize an online intervention. The workgroup at the National Addiction Management Service, Singapore conceptualized the online personalized feedback intervention for gamblers. The English version was launched on the 31st of March 2014 and the Chinese version was launched on the 30th of September 2014. A cumulative total of 708 participants took part with rhe mean age of the participants being 32.70 (SD = 11.638), with 89.1% males and 10.9% females. The mean problem gambling severity score (PGSI) was 10.80 (SD = 8.13), with the vast majority participating in Casino gambling on board a cruise (36.0%). Of significance, approximately 59.2% of the participants who sought help with our online e-intervention did have a diagnosis of problem gambling. This is one of the first few studies to demonstrate and replicate the potential use of an Internet based intervention for non-problem and problem gamblers. The current study has demonstrated that individuals are generally receptive towards such an intervention.

Curation-Based Network Marketing: Strategies for Network Growth and Electronic Word-of-Mouth Diffusion

ERIC Educational Resources Information Center

Church, Earnie Mitchell, Jr.

2013-01-01

In the last couple of years, a new aspect of online social networking has emerged, in which the strength of social network connections is based not on social ties but mutually shared interests. This dissertation studies these "curation-based" online social networks (CBN) and their suitability for the diffusion of electronic word-of-mouth…

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Feedback 2.0 in Online Writing Instruction: Combining Audio-Visual and Text-Based Commentary to Enhance Student Revision and Writing Competency

ERIC Educational Resources Information Center

Grigoryan, Anna

2017-01-01

The continued increase in the number of students participating in online degree programs has led to an increase in the number of students taking online composition courses. Currently, most online writing programs replicate approaches used in face-to-face composition courses and simply transfer them to the online learning environment. However,…

Comparing Learning Gains: Audio Versus Text-based Instructor Communication in a Blended Online Learning Environment

NASA Astrophysics Data System (ADS)

Shimizu, Dominique

Though blended course audio feedback has been associated with several measures of course satisfaction at the postsecondary and graduate levels compared to text feedback, it may take longer to prepare and positive results are largely unverified in K-12 literature. The purpose of this quantitative study was to investigate the time investment and learning impact of audio communications with 228 secondary students in a blended online learning biology unit at a central Florida public high school. A short, individualized audio message regarding the student's progress was given to each student in the audio group; similar text-based messages were given to each student in the text-based group on the same schedule; a control got no feedback. A pretest and posttest were employed to measure learning gains in the three groups. To compare the learning gains in two types of feedback with each other and to no feedback, a controlled, randomized, experimental design was implemented. In addition, the creation and posting of audio and text feedback communications were timed in order to assess whether audio feedback took longer to produce than text only feedback. While audio feedback communications did take longer to create and post, there was no difference between learning gains as measured by posttest scores when student received audio, text-based, or no feedback. Future studies using a similar randomized, controlled experimental design are recommended to verify these results and test whether the trend holds in a broader range of subjects, over different time frames, and using a variety of assessment types to measure student learning.

Using social media for support and feedback by mental health service users: thematic analysis of a twitter conversation.

PubMed

Shepherd, Andrew; Sanders, Caroline; Doyle, Michael; Shaw, Jenny

2015-02-19

Internet based social media websites represent a growing space for interpersonal interaction. Research has been conducted in relation to the potential role of social media in the support of individuals with physical health conditions. However, limited research exists exploring such utilisation by individuals with experience of mental health problems. It could be proposed that access to wider support networks and knowledge could be beneficial for all users, although this positive interpretation has been challenged. The present study focusses on a specific discussion as a case study to assess the role of the website www.twitter.com as a medium for interpersonal communication by individuals with experience of mental disorder and possible source of feedback to mental health service providers. An electronic search was performed to identify material contributing to an online conversation entitled #dearmentalhealthprofessionals. Output from the search strategy was combined in such a way that repeated material was eliminated and all individual material anonymised. The remaining textual material was reviewed and combined in a thematic analysis to identify common themes of discussion. 515 unique communications were identified relating to the specified conversation. The majority of the material related to four overarching thematic headings: The impact of diagnosis on personal identity and as a facilitator for accessing care; Balance of power between professional and service user; Therapeutic relationship and developing professional communication; and Support provision through medication, crisis planning, service provision and the wider society. Remaining material was identified as being direct expression of thanks, self-referential in its content relating to the on-going conversation or providing a link to external resources and further discussion. The present study demonstrates the utility of online social media as both a discursive space in which individuals with experience of mental disorder may share information and develop understanding, and a medium of feedback to mental health service providers. Further research is required to establish potential individual benefit from the utilisation of such networks, its suitability as a means of service provision feedback and the potential role for, and user acceptability of, mental health service providers operating within the space.

The Persuasive Effect of Social Network Feedback on Mediated Communication: A Case Study in a Real Organization.

PubMed

Varotto, Alessandra; Gamberini, Luciano; Spagnolli, Anna; Martino, Francesco; Giovannardi, Isabella

2016-03-01

This study focuses on social feedback, namely on information on the outcome of users' online activity indirectly generated by other users, and investigates in a real setting whether it can affect subsequent activity and, if so, whether participants are aware of that. SkyPas, an application that calculates, transmits, and displays social feedback, was embedded in a common instant messaging service (Skype(™)) and used during a 7-week trial by 24 office workers at a large business organization. The trial followed an ABA scheme in which the B phase was the feedback provision phase. Results show that social feedback affects users' communication activity (participation, inward communication, outward communication, and reciprocity), sometimes even after the feedback provision phase. At the same time, users were poorly aware of this effect, showing a discrepancy between self-reported and observational measures. These results are then discussed in terms of design transparency and task compatibility.

Relaxation rates of gene expression kinetics reveal the feedback signs of autoregulatory gene networks

NASA Astrophysics Data System (ADS)

Jia, Chen; Qian, Hong; Chen, Min; Zhang, Michael Q.

2018-03-01

The transient response to a stimulus and subsequent recovery to a steady state are the fundamental characteristics of a living organism. Here we study the relaxation kinetics of autoregulatory gene networks based on the chemical master equation model of single-cell stochastic gene expression with nonlinear feedback regulation. We report a novel relation between the rate of relaxation, characterized by the spectral gap of the Markov model, and the feedback sign of the underlying gene circuit. When a network has no feedback, the relaxation rate is exactly the decaying rate of the protein. We further show that positive feedback always slows down the relaxation kinetics while negative feedback always speeds it up. Numerical simulations demonstrate that this relation provides a possible method to infer the feedback topology of autoregulatory gene networks by using time-series data of gene expression.

Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-09-07

In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.

The Online Teaching Guide: A Handbook of Attitudes, Strategies, and Techniques for the Virtual Classroom.

ERIC Educational Resources Information Center

White, Ken W., Ed.; Weight, Bob H., Ed.

This book presents 14 papers that offer guidance to college teachers venturing into online instruction. It is based on the experiences and ideas of faculty at the University of Phoenix (Arizona) online campus, which has been offering online courses since 1989. Chapters in the book discuss the importance of interaction and feedback, learner…

A globally networked hybrid approach to public health capacity training for maternal health professionals in low and middle income countries.

PubMed

McIntosh, Scott; Pérez-Ramos, José G; David, Tamala; Demment, Margaret M; Avendaño, Esteban; Ossip, Deborah J; De Ver Dye, Timothy

2017-01-01

MundoComm is a current NIH-funded project for sustainable public health capacity building in community engagement and technological advances aimed at improving maternal health issues. Two to four teams are selected annually, each consisting of three healthcare professionals and one technical person from specific low and middle income countries (LMICs) including Costa Rica, Dominican Republic, Honduras, and other LMICs. MundoComm is a course with three parts: in-person workshops, online modules, and mentored community engagement development. Two annual 1-week on-site "short courses" convened in Costa Rica are supplemented with six monthly online training modules using the Moodle® online platform for e-learning, and mentored project development. The year-long course comprises over 20 topics divided into the six modules - each module further segmented into 4 week-long assignments, with readings and assigned tasks covering different aspects of community-engaged interventions. The content is peer reviewed by experts in the respective fields from University of Rochester, UCIMED in Costa Rica, and faculty from Costa Rica and the Dominican Republic who maintain regular contact with the trainees to mentor learning and project progress. The purpose of this paper is to report the first year results of the MundoComm project. Both quantitative and qualitative feedback (using online data capturing forms) assess baseline and post-training knowledge and skills in public health project strategies. The course currently has one team each in Costa Rica, the Dominican Republic, and Honduras for a total of 12 trainees. The course and modules include best practices in information and communication technologies (ICTs), ethical reviews, community engagement, evidence-based community interventions, and e-Health strategies. To maximize successful and culturally appropriate training approaches, the multi-media didactic presentations, flexible distance learning strategies, and the use of tablets for offline data collection are offered to trainees, and then feedback from trainees and other lessons learned aid in the refinement of subsequent curricular improvements. Through remark and discussion, the authors report on 1) the feasibility of using a globally networked learning environment (GNLE) plus workshop approach to public health capacity training and 2) the capacity of LMIC teams to complete the MundoComm trainings and produce ICT-based interventions to address a maternal health issue in their respective regions.

NDRAM: nonlinear dynamic recurrent associative memory for learning bipolar and nonbipolar correlated patterns.

PubMed

Chartier, Sylvain; Proulx, Robert

2005-11-01

This paper presents a new unsupervised attractor neural network, which, contrary to optimal linear associative memory models, is able to develop nonbipolar attractors as well as bipolar attractors. Moreover, the model is able to develop less spurious attractors and has a better recall performance under random noise than any other Hopfield type neural network. Those performances are obtained by a simple Hebbian/anti-Hebbian online learning rule that directly incorporates feedback from a specific nonlinear transmission rule. Several computer simulations show the model's distinguishing properties.

Toward Personal and Emotional Connectivity in Mobile Higher Education through Asynchronous Formative Audio Feedback

ERIC Educational Resources Information Center

Rasi, Päivi; Vuojärvi, Hanna

2018-01-01

This study aims to develop asynchronous formative audio feedback practices for mobile learning in higher education settings. The development was conducted in keeping with the principles of design-based research. The research activities focused on an inter-university online course, within which the use of instructor audio feedback was tested,…

Beyond Barriers: Encouraging Teacher Use of Feedback Resources. A Report from the Teacher Feedback Resources Project

ERIC Educational Resources Information Center

Morgan, Nicholas; Killion, Joellen

2018-01-01

This report investigates factors that drive teachers to embrace or challenge the use of products and services designed to support improvements in practice. Key elements of the study include: (1) Technology-based resources studied include those designed for video observations, peer feedback and collaboration, online professional learning, and…

Social media for patients: benefits and drawbacks.

PubMed

De Martino, Ivan; D'Apolito, Rocco; McLawhorn, Alexander S; Fehring, Keith A; Sculco, Peter K; Gasparini, Giorgio

2017-03-01

Social media is increasingly utilized by patients to educate themselves on a disease process and to find hospital, physicians, and physician networks most capable of treating their condition. However, little is known about quality of the content of the multiple online platforms patients have to communicate with other potential patients and their potential benefits and drawbacks. Patients are not passive consumers of health information anymore but are playing an active role in the delivery of health services through an online environment. The control and the regulation of the sources of information are very difficult. The overall quality of the information was poor. Bad or misleading information can be detrimental for patients as well as influence their confidence on physicians and their mutual relationship. Orthopedic surgeons and hospital networks must be aware of these online patient portals as they provide important feedback on the patient opinion and experience that can have a major impact on future patient volume, patient opinion, and perceived quality of care.

Effective Instructor Feedback: Perceptions of Online Graduate Students

ERIC Educational Resources Information Center

Getzlaf, Beverley; Perry, Beth; Toffner, Greg; Lamarche, Kimberley; Edwards, Margaret

2009-01-01

This descriptive study explored online graduate students' perceptions of effective instructor feedback. The objectives of the study were to determine the students' perceptions of the content of effective instructor feedback ("what should be included in effective feedback?") and the process of effective instructor feedback ("how…

Evaluating Programs That Promote Climate and Energy Education-Meeting Teacher Needs for Online Resources

NASA Astrophysics Data System (ADS)

Lynds, S. E.; Buhr, S. M.

2011-12-01

The Climate Literacy and Energy Awareness Network (CLEAN) Pathway, is a National Science Digital Library (NSDL) Pathways project that was begun in 2010. The main goal of CLEAN is to generate a reviewed collection of educational resources that are aligned with the Essential Principles of Climate Science (EPCS). Another goal of the project is to support a community that will assist students, teachers, and citizens in climate literacy. A complementary program begun in 2010 is the ICEE (Inspiring Climate Education Excellence) program, which is developing online modules and courses designed around the climate literacy principles for use by teachers and other interested citizens. In these projects, we learn about teacher needs through a variety of evaluation mechanisms. The programs use evaluation to assist in the process of providing easy access to high quality climate and energy learning resources that meet classroom requirements. The internal evaluation of the CLEAN program is multidimensional. At the CLEAN resource review camps, teachers and scientists work together in small groups to assess the value of online resources for use in the classroom. The review camps are evaluated using observation and feedback surveys; the resulting evaluation reports provide information to managers to fine-tune future camps. In this way, a model for effective climate resource development meetings has been refined. Evaluation methods used in ICEE and CLEAN include teacher needs assessment surveys, teacher feedback at professional development opportunities, scientist feedback at resource review workshops, and regular analysis of online usage of resources, forums, and education modules. This paper will review the most successful strategies for evaluating the effectiveness of online climate and energy education resources and their use by educators and the general public.

Online adaptation and over-trial learning in macaque visuomotor control.

PubMed

Braun, Daniel A; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning.

Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

PubMed Central

Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

Efficacy Enhancing Communication within the Online Courseroom

ERIC Educational Resources Information Center

Kasitz, Christine M.

2013-01-01

Online learning is becoming more prevalent in high schools especially with at-risk students who may need to recover credits to meet graduation requirements. The purpose of this study was to examine the effects of an online courseroom design that delivers performance-based efficacy enhancing feedback at regular intervals, rather than relying on the…

Using a Multiperspective Design Team to Develop and Manage Multilayered Online Courses

ERIC Educational Resources Information Center

Anderson, Nella Bea; Poole, L. Lori; Quinn, Stephanie; Schlicht, Carrie L.

2014-01-01

The focus of this research-based review is how to best develop and manage online classes. After receiving faculty, student, and industry feedback, Colorado State University-Global Campus integrated multi-perspective design teams to develop and manage multilayered online courses. This article will reveal the instructional design, development…

Using Case-Based Reasoning to Improve the Quality of Feedback Provided by Automated Grading Systems

ERIC Educational Resources Information Center

Kyrilov, Angelo; Noelle, David C.

2014-01-01

Information technology is now ubiquitous in higher education institutions worldwide. More than 85% of American universities use e-learning systems to supplement traditional classroom activities while some have started offering Massive Online Open Courses (MOOCs), which are completely online. An obvious benefit of these online tools is their…

Reflecting on Online Course Evaluations: Five Must-Do's for Faculty and Students

ERIC Educational Resources Information Center

Cicco, Gina

2016-01-01

This article will review the experiences of a graduate counselor educator in teaching and evaluating her online courses. The author will summarize her most effective instructional and assessment mechanisms, based on student performance through achievement of course objectives as well as students' feedback and comments on specific online counseling…

Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

PubMed

Fei, Juntao; Lu, Cheng

2018-04-01

In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

Online Treatment and Virtual Therapists in Child and Adolescent Psychiatry

PubMed Central

Schueller, Stephen M.; Stiles-Shields, Colleen; Yarosh, Lana

2016-01-01

Summary Online and virtual therapies are a well-studied and efficacious treatment option for various mental and behavioral health conditions among children and adolescents. That said, many interventions have not concerned the unique affordances offered by technologies that might align with the capacities and interests of youth users. In this article, we discuss learnings from child-computer interaction that can inform future generations of interventions and guide developers, practitioners, and researchers how to best utilize new technologies for youth populations. We highlight issues related to usability and user experience including challenge and feedback, social interaction, and storytelling. We conclude with innovative examples illustrating future potentials of online and virtual therapies such as gaming and social networking. PMID:27837935

Application of Online Multimedia Courseware in College English Teaching Based on Constructivism Theory

ERIC Educational Resources Information Center

Li, Zhenying

2012-01-01

Based on Constructivism Theory, this paper aims to investigate the application of online multimedia courseware to college English teaching. By making experiments and students' feedback, some experience has been accumulated, and some problems are discovered and certain revelations are acquired as well in English teaching practice, which pave the…

Evaluation of a LENA-Based Online Intervention for Parents of Young Children

ERIC Educational Resources Information Center

Gilkerson, Jill; Richards, Jeffrey A.; Topping, Keith

2017-01-01

The efficacy of a pilot version of an online parent intervention that combined Language ENvironment Analysis (LENA)-based automated language environment feedback technology with Internet capabilities was investigated. Seventy-two parents of typically developing children aged 9 to 21 months were assigned to immediate- or delayed-treatment (control)…

Sensory-Motor Networks Involved in Speech Production and Motor Control: An fMRI Study

PubMed Central

Behroozmand, Roozbeh; Shebek, Rachel; Hansen, Daniel R.; Oya, Hiroyuki; Robin, Donald A.; Howard, Matthew A.; Greenlee, Jeremy D.W.

2015-01-01

Speaking is one of the most complex motor behaviors developed to facilitate human communication. The underlying neural mechanisms of speech involve sensory-motor interactions that incorporate feedback information for online monitoring and control of produced speech sounds. In the present study, we adopted an auditory feedback pitch perturbation paradigm and combined it with functional magnetic resonance imaging (fMRI) recordings in order to identify brain areas involved in speech production and motor control. Subjects underwent fMRI scanning while they produced a steady vowel sound /a/ (speaking) or listened to the playback of their own vowel production (playback). During each condition, the auditory feedback from vowel production was either normal (no perturbation) or perturbed by an upward (+600 cents) pitch shift stimulus randomly. Analysis of BOLD responses during speaking (with and without shift) vs. rest revealed activation of a complex network including bilateral superior temporal gyrus (STG), Heschl's gyrus, precentral gyrus, supplementary motor area (SMA), Rolandic operculum, postcentral gyrus and right inferior frontal gyrus (IFG). Performance correlation analysis showed that the subjects produced compensatory vocal responses that significantly correlated with BOLD response increases in bilateral STG and left precentral gyrus. However, during playback, the activation network was limited to cortical auditory areas including bilateral STG and Heschl's gyrus. Moreover, the contrast between speaking vs. playback highlighted a distinct functional network that included bilateral precentral gyrus, SMA, IFG, postcentral gyrus and insula. These findings suggest that speech motor control involves feedback error detection in sensory (e.g. auditory) cortices that subsequently activate motor-related areas for the adjustment of speech parameters during speaking. PMID:25623499

The NASA F-15 Intelligent Flight Control Systems: Generation II

NASA Technical Reports Server (NTRS)

Buschbacher, Mark; Bosworth, John

2006-01-01

The Second Generation (Gen II) control system for the F-15 Intelligent Flight Control System (IFCS) program implements direct adaptive neural networks to demonstrate robust tolerance to faults and failures. The direct adaptive tracking controller integrates learning neural networks (NNs) with a dynamic inversion control law. The term direct adaptive is used because the error between the reference model and the aircraft response is being compensated or directly adapted to minimize error without regard to knowing the cause of the error. No parameter estimation is needed for this direct adaptive control system. In the Gen II design, the feedback errors are regulated with a proportional-plus-integral (PI) compensator. This basic compensator is augmented with an online NN that changes the system gains via an error-based adaptation law to improve aircraft performance at all times, including normal flight, system failures, mispredicted behavior, or changes in behavior resulting from damage.

Live Synchronous Web Meetings in Asynchronous Online Courses: Reconceptualizing Virtual Office Hours

ERIC Educational Resources Information Center

Lowenthal, Patrick R.; Snelson, Chareen; Dunlap, Joanna C.

2017-01-01

Most online courses rely solely on asynchronous text-based online communication. This type of communication can foster anytime, anywhere reflection, critical thinking, and deep learning. However, it can also frustrate participants because of the lack of spontaneity and visual cues and the time it takes for conversations to develop and feedback to…

Quality of Learning Outcomes in an Online Video-Based Learning Community: Potential and Challenges for Student Teachers

ERIC Educational Resources Information Center

So, Winnie Wing-mui

2012-01-01

This study investigates the learning outcomes of 25 student teachers in an online video-based learning community (VBLC). Data were drawn from the student teachers' written comments and feedback recorded in the VBLC and the post-course interviews. Based on Biggs and Collis's Structure of Observed Learning Outcomes (SOLO) taxonomy, the majority of…

A Study on the Impact of Collective Feedback in the Online Technical and Professional Communication Classroom

ERIC Educational Resources Information Center

Singleton, Meredith

2016-01-01

This dissertation study seeks to determine whether feedback in the online Technical and Professional Communication classroom impacts student performance. This dissertation proposes that online Technical and Professional Communication instructors consider adopt such a feedback methodology in order to engage students with writing practices that…

Building online learning communities in a graduate dental hygiene program.

PubMed

Rogo, Ellen J; Portillo, Karen M

2014-08-01

The literature abounds with research related to building online communities in a single course; however, limited evidence is available on this phenomenon from a program perspective. The intent of this qualitative case study inquiry was to explore student experiences in a graduate dental hygiene program contributing or impeding the development and sustainability of online learning communities. Approval from the IRB was received. A purposive sampling technique was used to recruit participants from a stratification of students and graduates. A total of 17 participants completed semi-structured interviews. Data analysis was completed through 2 rounds - 1 for coding responses and 1 to construct categories of experiences. The participants' collective definition of an online learning community was a complex synergistic network of interconnected people who create positive energy. The findings indicated the development of this network began during the program orientation and was beneficial for building a foundation for the community. Students felt socially connected and supported by the network. Course design was another important category for participation in weekly discussions and group activities. Instructors were viewed as active participants in the community, offering helpful feedback and being a facilitator in discussions. Experiences impeding the development of online learning communities related to the poor performance of peers and instructors. Specific categories of experiences supported and impeded the development of online learning communities related to the program itself, course design, students and faculty. These factors are important to consider in order to maximize student learning potential in this environment. Copyright © 2014 The American Dental Hygienists’ Association.

Interference Alignment With Partial CSI Feedback in MIMO Cellular Networks

NASA Astrophysics Data System (ADS)

Rao, Xiongbin; Lau, Vincent K. N.

2014-04-01

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. However, most existing IA designs require full channel state information (CSI) at the transmitters, which would lead to significant CSI signaling overhead. There are two techniques, namely CSI quantization and CSI feedback filtering, to reduce the CSI feedback overhead. In this paper, we consider IA processing with CSI feedback filtering in MIMO cellular networks. We introduce a novel metric, namely the feedback dimension, to quantify the first order CSI feedback cost associated with the CSI feedback filtering. The CSI feedback filtering poses several important challenges in IA processing. First, there is a hidden partial CSI knowledge constraint in IA precoder design which cannot be handled using conventional IA design methodology. Furthermore, existing results on the feasibility conditions of IA cannot be applied due to the partial CSI knowledge. Finally, it is very challenging to find out how much CSI feedback is actually needed to support IA processing. We shall address the above challenges and propose a new IA feasibility condition under partial CSIT knowledge in MIMO cellular networks. Based on this, we consider the CSI feedback profile design subject to the degrees of freedom requirements, and we derive closed-form trade-off results between the CSI feedback cost and IA performance in MIMO cellular networks.

Chasing The 'Like': Adolescent Use Of Social Networking Sites In Australia.

PubMed

la Sala, Louise; Skues, Jason; Wise, Lisa; Theiler, Stephen

2015-01-01

The current study investigated how adolescents behave on Social Networking Sites (SNSs) and how they interpret the feedback they receive online from others. Thirty-four Australian adolescents (26 girls, 8 boys) aged 13 to 17 years participated in the study. Five semi-structured focus groups (3 mixed groups, 2 all-girl groups) were conducted to explore how adolescents perceive their own and others' SNS behaviours, the motivation underlying these behaviours, and the expected outcomes related to particular behaviours. Teenagers reported that they spend a good deal of time planning their SNS posts, felt that the information they posted was a true reflection of them as a person, and thus interpreted feedback ("likes") as measuring their self-worth. In contrast, some teenagers were perceived as "chasing the like" for status and popularity while not caring about how accurately their posts represented them as a person. A potential gender bias in these findings is discussed.

A Social Learning Management System Supporting Feedback for Incorrect Answers Based on Social Network Services

ERIC Educational Resources Information Center

Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

2016-01-01

In this research, we propose a Social Learning Management System (SLMS) enabling real-time and reliable feedback for incorrect answers by learners using a social network service (SNS). The proposed system increases the accuracy of learners' assessment results by using a confidence scale and a variety of social feedback that is created and shared…

Fuzzy self-learning control for magnetic servo system

NASA Technical Reports Server (NTRS)

Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

1994-01-01

It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

Effect of inhibitory feedback on correlated firing of spiking neural network.

PubMed

Xie, Jinli; Wang, Zhijie

2013-08-01

Understanding the properties and mechanisms that generate different forms of correlation is critical for determining their role in cortical processing. Researches on retina, visual cortex, sensory cortex, and computational model have suggested that fast correlation with high temporal precision appears consistent with common input, and correlation on a slow time scale likely involves feedback. Based on feedback spiking neural network model, we investigate the role of inhibitory feedback in shaping correlations on a time scale of 100 ms. Notably, the relationship between the correlation coefficient and inhibitory feedback strength is non-monotonic. Further, computational simulations show how firing rate and oscillatory activity form the basis of the mechanisms underlying this relationship. When the mean firing rate holds unvaried, the correlation coefficient increases monotonically with inhibitory feedback, but the correlation coefficient keeps decreasing when the network has no oscillatory activity. Our findings reveal that two opposing effects of the inhibitory feedback on the firing activity of the network contribute to the non-monotonic relationship between the correlation coefficient and the strength of the inhibitory feedback. The inhibitory feedback affects the correlated firing activity by modulating the intensity and regularity of the spike trains. Finally, the non-monotonic relationship is replicated with varying transmission delay and different spatial network structure, demonstrating the universality of the results.

Decorrelation of Neural-Network Activity by Inhibitory Feedback

PubMed Central

Einevoll, Gaute T.; Diesmann, Markus

2012-01-01

Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between excitatory (E) and inhibitory (I) neurons, but a consequence of a particular structure of correlations among the three possible pairings (EE, EI, II). PMID:23133368

Web-based video and feedback in the teaching of cardiopulmonary resuscitation.

PubMed

Bowden, Tracey; Rowlands, Angela; Buckwell, Margot; Abbott, Stephen

2012-05-01

Knowledge and skills relating to cardiopulmonary resuscitation tend to be lost over time. The combination of simulation sessions with online video records and online feedback allows for an enduring record of skills sessions to assist students in retaining and revising their learning. This paper reports a qualitative evaluation of such a combination used in inter-disciplinary sessions for volunteer nursing and medical students. Methods included focus groups and free text questionnaires; data were gathered from fourteen students and three teachers. Students had used the online material in a variety of personal ways, and found that the addition to their learning was significant. Their memories of the simulation sessions and of the feedback received immediately afterwards were incomplete, and repeated viewing enabled them to identify good and poor practice with more confidence, and to reflect more carefully on their own and others' practice. Teachers found it easier to give more detailed feedback when given the chance to watch the video than immediately after the session. All felt that the sessions would ideally be embedded in the curriculum. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparison of brief versus extended personalised feedback in an online intervention for cannabis users: Short-term findings of a randomised trial.

PubMed

Copeland, Jan; Rooke, Sally; Rodriquez, Dan; Norberg, Melissa M; Gibson, Lisa

2017-05-01

Previous studies have shown brief online self-help interventions to be a useful method of treating cannabis use and related problems; however, no studies have compared the effects of brief versus extended feedback for online brief intervention programs. The current study was a two arm randomised trial aimed at testing the short term effectiveness of a brief and extended feedback version of Grassessment, a brief online intervention for cannabis users that provides individualised feedback regarding use, motives, and harms. Participants (n=287) reporting at least one symptom of DSM IV cannabis abuse or dependence were recruited using online and offline advertising methods. Participants were randomised to receive either a brief or extended feedback version of the Grassessment program and were required to complete a one month follow up questionnaire. One hundred and ninety four participants completed the one month follow up. Wilcoxon analyses showed a significant decrease in past month quantity and frequency of cannabis use (ps<0.001; r=-0.41 and -0.40 respectively) and lower severity of dependence scores (p=0.002; r=-0.31) among those in the brief feedback condition. Participants in the extended feedback group also demonstrated significant decreases in patterns of use (ps<0.002; r=-0.39 and -0.33) but not severity of dependence (p=0.09; r=0.18). A Generalized Estimating Equation (GEE) analysis showed no significant interaction between length of feedback received and past month cannabis use frequency (p=0.78), quantity (p=0.73), or severity of dependence (p=0.47). This study adds support for the use of brief online self-complete interventions to reduce cannabis use and related problems in the short term. The findings suggest that in the case of the brief online screening and feedback program Grassessment, extended feedback does not lead to superior outcomes over brief feedback. Copyright © 2017 Elsevier Inc. All rights reserved.

MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data.

PubMed

Sella, Nadir; Verny, Louis; Uguzzoni, Guido; Affeldt, Séverine; Isambert, Hervé

2018-07-01

We present a web server running the MIIC algorithm, a network learning method combining constraint-based and information-theoretic frameworks to reconstruct causal, non-causal or mixed networks from non-perturbative data, without the need for an a priori choice on the class of reconstructed network. Starting from a fully connected network, the algorithm first removes dispensable edges by iteratively subtracting the most significant information contributions from indirect paths between each pair of variables. The remaining edges are then filtered based on their confidence assessment or oriented based on the signature of causality in observational data. MIIC online server can be used for a broad range of biological data, including possible unobserved (latent) variables, from single-cell gene expression data to protein sequence evolution and outperforms or matches state-of-the-art methods for either causal or non-causal network reconstruction. MIIC online can be freely accessed at https://miic.curie.fr. Supplementary data are available at Bioinformatics online.

Conformity under uncertainty: reliance on gender stereotypes in online hiring decisions.

PubMed

Uhlmann, Eric Luis; Silberzahn, Raphael

2014-02-01

We apply Bentley et al.'s theoretical framework to better understand gender discrimination in online labor markets. Although such settings are designed to encourage employer behavior in the northwest corner of Homo economicus, actual online hiring decisions tend to drift southeast into a "confirmation bias plus weak feedback loops" pattern of discrimination based on inaccurate social stereotypes.

Estimating feedforward vs. feedback control of speech production through kinematic analyses of unperturbed articulatory movements.

PubMed

Kim, Kwang S; Max, Ludo

2014-01-01

To estimate the contributions of feedforward vs. feedback control systems in speech articulation, we analyzed the correspondence between initial and final kinematics in unperturbed tongue and jaw movements for consonant-vowel (CV) and vowel-consonant (VC) syllables. If movement extents and endpoints are highly predictable from early kinematic information, then the movements were most likely completed without substantial online corrections (feedforward control); if the correspondence between early kinematics and final amplitude or position is low, online adjustments may have altered the planned trajectory (feedback control) (Messier and Kalaska, 1999). Five adult speakers produced CV and VC syllables with high, mid, or low vowels while movements of the tongue and jaw were tracked electromagnetically. The correspondence between the kinematic parameters peak acceleration or peak velocity and movement extent as well as between the articulators' spatial coordinates at those kinematic landmarks and movement endpoint was examined both for movements across different target distances (i.e., across vowel height) and within target distances (i.e., within vowel height). Taken together, results suggest that jaw and tongue movements for these CV and VC syllables are mostly under feedforward control but with feedback-based contributions. One type of feedback-driven compensatory adjustment appears to regulate movement duration based on variation in peak acceleration. Results from a statistical model based on multiple regression are presented to illustrate how the relative strength of these feedback contributions can be estimated.

A neural network based artificial vision system for licence plate recognition.

PubMed

Draghici, S

1997-02-01

This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

Feedback Design Patterns for Math Online Learning Systems

ERIC Educational Resources Information Center

Inventado, Paul Salvador; Scupelli, Peter; Heffernan, Cristina; Heffernan, Neil

2017-01-01

Increasingly, computer-based learning systems are used by educators to facilitate learning. Evaluations of several math learning systems show that they result in significant student learning improvements. Feedback provision is one of the key features in math learning systems that contribute to its success. We have recently been uncovering feedback…

Picture Me Smokefree: a qualitative study using social media and digital photography to engage young adults in tobacco reduction and cessation.

PubMed

Haines-Saah, Rebecca J; Kelly, Mary T; Oliffe, John L; Bottorff, Joan L

2015-01-26

Young adults have high rates of tobacco use compared to other subpopulations, yet there are relatively few tobacco interventions specifically targeted to this group. Picture Me Smokefree is an online tobacco reduction and cessation intervention for young adults that uses digital photography and social networking. The main goal of the project was to determine the feasibility of engaging young adults in participating in user-driven, online forums intended to provide peer support and motivate critical reflection about tobacco use and cessation among this high-use, hard-to-reach population. A related aim was to explore the influence of gender-related factors on participation, in order to determine the need for online interventions to be tailored to the specific gender preferences reflecting young men and women's participation styles. A total of 60 young adults ages 19-24 years who self-identified as current cigarette smokers or who had quit within the last year were recruited from across British Columbia, Canada, and participated in an online photo group on Facebook over a period of 12 consecutive weeks. A variety of data collection methods were used including tracking online activity, a brief online follow-up survey, and qualitative interviews with study participants. Data analysis involved descriptive statistics on recruitment, retention, and participation and qualitative (eg, narrative analysis, synthesis of feedback) feedback about participant engagement. Findings from this study suggest good potential for Facebook as an accessible, low-cost platform for engaging young adults to reflect on the reasons for their tobacco use, the benefits of quitting or reducing, and the best strategies for tobacco reduction. Young adults' frequent use of mobile phones and other mobile devices to access social networking permitted ease of access and facilitated real-time peer-to-peer support across a diverse group of participants. However, our experience of conducting the study suggests that working with young tobacco users can be accompanied by considerable recruitment, participation, and retention challenges. Our findings also pointed to differences in how young women and men engaged the photo-group intervention that should be considered, bearing in mind that in follow-up interviews participants indicated their preference for a mixed gender and "gender neutral" group format. Tobacco interventions for youth and young adults should be embedded within the existing social networking platforms they access most frequently, rather than designing a stand-alone online prevention or intervention resource. This subpopulation would likely benefit from tobacco reduction interventions that are gender-sensitive rather than gender-specific.

Picture Me Smokefree: A Qualitative Study Using Social Media and Digital Photography to Engage Young Adults in Tobacco Reduction and Cessation

PubMed Central

Kelly, Mary T; Oliffe, John L; Bottorff, Joan L

2015-01-01

Background Young adults have high rates of tobacco use compared to other subpopulations, yet there are relatively few tobacco interventions specifically targeted to this group. Picture Me Smokefree is an online tobacco reduction and cessation intervention for young adults that uses digital photography and social networking. Objective The main goal of the project was to determine the feasibility of engaging young adults in participating in user-driven, online forums intended to provide peer support and motivate critical reflection about tobacco use and cessation among this high-use, hard-to-reach population. A related aim was to explore the influence of gender-related factors on participation, in order to determine the need for online interventions to be tailored to the specific gender preferences reflecting young men and women’s participation styles. Methods A total of 60 young adults ages 19-24 years who self-identified as current cigarette smokers or who had quit within the last year were recruited from across British Columbia, Canada, and participated in an online photo group on Facebook over a period of 12 consecutive weeks. A variety of data collection methods were used including tracking online activity, a brief online follow-up survey, and qualitative interviews with study participants. Data analysis involved descriptive statistics on recruitment, retention, and participation and qualitative (eg, narrative analysis, synthesis of feedback) feedback about participant engagement. Results Findings from this study suggest good potential for Facebook as an accessible, low-cost platform for engaging young adults to reflect on the reasons for their tobacco use, the benefits of quitting or reducing, and the best strategies for tobacco reduction. Young adults’ frequent use of mobile phones and other mobile devices to access social networking permitted ease of access and facilitated real-time peer-to-peer support across a diverse group of participants. However, our experience of conducting the study suggests that working with young tobacco users can be accompanied by considerable recruitment, participation, and retention challenges. Our findings also pointed to differences in how young women and men engaged the photo-group intervention that should be considered, bearing in mind that in follow-up interviews participants indicated their preference for a mixed gender and “gender neutral” group format. Conclusions Tobacco interventions for youth and young adults should be embedded within the existing social networking platforms they access most frequently, rather than designing a stand-alone online prevention or intervention resource. This subpopulation would likely benefit from tobacco reduction interventions that are gender-sensitive rather than gender-specific. PMID:25624064

Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems.

PubMed

Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

2016-01-01

This paper presents a novel adaptive neural network (NN) control of single-input and single-output uncertain nonlinear discrete-time systems under event sampled NN inputs. In this control scheme, the feedback signals are transmitted, and the NN weights are tuned in an aperiodic manner at the event sampled instants. After reviewing the NN approximation property with event sampled inputs, an adaptive state estimator (SE), consisting of linearly parameterized NNs, is utilized to approximate the unknown system dynamics in an event sampled context. The SE is viewed as a model and its approximated dynamics and the state vector, during any two events, are utilized for the event-triggered controller design. An adaptive event-trigger condition is derived by using both the estimated NN weights and a dead-zone operator to determine the event sampling instants. This condition both facilitates the NN approximation and reduces the transmission of feedback signals. The ultimate boundedness of both the NN weight estimation error and the system state vector is demonstrated through the Lyapunov approach. As expected, during an initial online learning phase, events are observed more frequently. Over time with the convergence of the NN weights, the inter-event times increase, thereby lowering the number of triggered events. These claims are illustrated through the simulation results.

Making Space for Innovative Practice Supporting Teaching and Learning through Integrating Online Peer-to-Peer Feedback between Geographically Separated Students

ERIC Educational Resources Information Center

Kim, Cathleen K. H.

2017-01-01

This dissertation is comprised of three linked studies investigating integrating online feedback practices into traditional classrooms. It focuses on one innovative practice, that of online peer-to-peer feedback, and highlights aspects of the process of developing this practice in each article. Each article relies on separate but connected…

Online social networking services in the management of patients with diabetes mellitus: systematic review and meta-analysis of randomised controlled trials.

PubMed

Toma, Tania; Athanasiou, Thanos; Harling, Leanne; Darzi, Ara; Ashrafian, Hutan

2014-11-01

Social networking services (SNS) can facilitate real-time communication and feedback of blood glucose and other physiological data between patients and healthcare professionals. This systematic review and meta-analysis aims to summarise the current evidence surrounding the role of online social networking services in diabetes care. We performed a systematic literature review of the Medline, EMBASE and PsychINFO databases of all studies reporting HbA1c (glycated haemoglobin) as a measure of glycaemic control for social networking services in diabetes care. HbA1c, clinical outcomes and the type of technology used were extracted. Study quality and publication bias were assessed. SNS interventions beneficially reduced HbA1c when compared to controls, which was confirmed by sensitivity analysis. SNS interventions also significantly improved systolic and diastolic blood pressure, triglycerides and total cholesterol. Subgroup analysis according to diabetes type demonstrated that Type 2 diabetes patients had a significantly greater reduction in HbA1c than those with Type 1 diabetes. Online SNS provide a novel, feasible approach to improving glycaemic control, particularly in patients with Type 2 diabetes. Further mechanistic and cost-effectiveness studies are required to improve our understanding of SNS and its efficacy in diabetes care. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Which Measures of Online Control Are Least Sensitive to Offline Processes?

PubMed

de Grosbois, John; Tremblay, Luc

2018-02-28

A major challenge to the measurement of online control is the contamination by offline, planning-based processes. The current study examined the sensitivity of four measures of online control to offline changes in reaching performance induced by prism adaptation and terminal feedback. These measures included the squared Z scores (Z 2 ) of correlations of limb position at 75% movement time versus movement end, variable error, time after peak velocity, and a frequency-domain analysis (pPower). The results indicated that variable error and time after peak velocity were sensitive to the prism adaptation. Furthermore, only the Z 2 values were biased by the terminal feedback. Ultimately, the current study has demonstrated the sensitivity of limb kinematic measures to offline control processes and that pPower analyses may yield the most suitable measure of online control.

Effect of online formative assessment on summative performance in integrated musculoskeletal system module.

PubMed

Mitra, Nilesh Kumar; Barua, Ankur

2015-03-03

The impact of web-based formative assessment practices on performance of undergraduate medical students in summative assessments is not widely studied. This study was conducted among third-year undergraduate medical students of a designated university in Malaysia to compare the effect, on performance in summative assessment, of repeated computer-based formative assessment with automated feedback with that of single paper-based formative assessment with face-to face feedback. This quasi-randomized trial was conducted among two groups of undergraduate medical students who were selected by stratified random technique from a cohort undertaking the Musculoskeletal module. The control group C (n = 102) was subjected to a paper-based formative MCQ test. The experimental group E (n = 65) was provided three online formative MCQ tests with automated feedback. The summative MCQ test scores for both these groups were collected after the completion of the module. In this study, no significant difference was observed between the mean summative scores of the two groups. However, Band 1 students from group E with higher entry qualification showed higher mean score in the summative assessment. A trivial, but significant and positive correlation (r(2) = +0.328) was observed between the online formative test scores and summative assessment scores of group E. The proportionate increase of performance in group E was found to be almost double than group C. The use of computer based formative test with automated feedback improved the performance of the students with better academic background in the summative assessment. Computer-based formative test can be explored as an optional addition to the curriculum of pre-clinical integrated medical program to improve the performance of the students with higher academic ability.

Quantifying Users' Interconnectedness in Online Social Networks - An Indispensible Step for Economic Valuation

NASA Astrophysics Data System (ADS)

Gneiser, Martin; Heidemann, Julia; Klier, Mathias; Landherr, Andrea; Probst, Florian

Online social networks have been gaining increasing economic importance in light of the rising number of their users. Numerous recent acquisitions priced at enormous amounts have illustrated this development and revealed the need for adequate business valuation models. The value of an online social network is largely determined by the value of its users, the relationships between these users, and the resulting network effects. Therefore, the interconnectedness of a user within the network has to be considered explicitly to get a reasonable estimate for the economic value. Established standard business valuation models, however, do not sufficiently take these aspects into account. Thus, we propose a measure based on the PageRank-algorithm to quantify users’ interconnectedness in an online social network. This is a first but indispensible step towards an adequate economic valuation of online social networks.

Sensory-motor networks involved in speech production and motor control: an fMRI study.

PubMed

Behroozmand, Roozbeh; Shebek, Rachel; Hansen, Daniel R; Oya, Hiroyuki; Robin, Donald A; Howard, Matthew A; Greenlee, Jeremy D W

2015-04-01

Speaking is one of the most complex motor behaviors developed to facilitate human communication. The underlying neural mechanisms of speech involve sensory-motor interactions that incorporate feedback information for online monitoring and control of produced speech sounds. In the present study, we adopted an auditory feedback pitch perturbation paradigm and combined it with functional magnetic resonance imaging (fMRI) recordings in order to identify brain areas involved in speech production and motor control. Subjects underwent fMRI scanning while they produced a steady vowel sound /a/ (speaking) or listened to the playback of their own vowel production (playback). During each condition, the auditory feedback from vowel production was either normal (no perturbation) or perturbed by an upward (+600 cents) pitch-shift stimulus randomly. Analysis of BOLD responses during speaking (with and without shift) vs. rest revealed activation of a complex network including bilateral superior temporal gyrus (STG), Heschl's gyrus, precentral gyrus, supplementary motor area (SMA), Rolandic operculum, postcentral gyrus and right inferior frontal gyrus (IFG). Performance correlation analysis showed that the subjects produced compensatory vocal responses that significantly correlated with BOLD response increases in bilateral STG and left precentral gyrus. However, during playback, the activation network was limited to cortical auditory areas including bilateral STG and Heschl's gyrus. Moreover, the contrast between speaking vs. playback highlighted a distinct functional network that included bilateral precentral gyrus, SMA, IFG, postcentral gyrus and insula. These findings suggest that speech motor control involves feedback error detection in sensory (e.g. auditory) cortices that subsequently activate motor-related areas for the adjustment of speech parameters during speaking. Copyright © 2015 Elsevier Inc. All rights reserved.

Identifying online user reputation of user-object bipartite networks

NASA Astrophysics Data System (ADS)

Liu, Xiao-Lu; Liu, Jian-Guo; Yang, Kai; Guo, Qiang; Han, Jing-Ti

2017-02-01

Identifying online user reputation based on the rating information of the user-object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part of all user opinions. The experimental results show that the AUC values of the presented algorithm could reach 0.8929 and 0.8483 for the MovieLens and Netflix data sets, respectively, which is better than the results generated by the CR and IARR methods. Furthermore, the experimental results for different user groups indicate that the presented algorithm outperforms the iterative ranking methods in both ranking accuracy and computation complexity. Moreover, the results for the synthetic networks show that the computation complexity of the presented algorithm is a linear function of the network size, which suggests that the presented algorithm is very effective and efficient for the large scale dynamic online systems.

Lexicon-enhanced sentiment analysis framework using rule-based classification scheme.

PubMed

Asghar, Muhammad Zubair; Khan, Aurangzeb; Ahmad, Shakeel; Qasim, Maria; Khan, Imran Ali

2017-01-01

With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA) applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-specific words expressed in the public's feedback about the products. However, the un-supervised learning approach employed in previous studies is becoming less efficient due to data sparseness, low accuracy due to non-consideration of emoticons, modifiers, and presence of domain specific words, as they may result in inaccurate classification of users' reviews. Lexicon-enhanced sentiment analysis based on Rule-based classification scheme is an alternative approach for improving sentiment classification of users' reviews in online communities. In addition to the sentiment terms used in general purpose sentiment analysis, we integrate emoticons, modifiers and domain specific terms to analyze the reviews posted in online communities. To test the effectiveness of the proposed method, we considered users reviews in three domains. The results obtained from different experiments demonstrate that the proposed method overcomes limitations of previous methods and the performance of the sentiment analysis is improved after considering emoticons, modifiers, negations, and domain specific terms when compared to baseline methods.

Online social and professional support for smokers trying to quit: an exploration of first time posts from 2562 members.

PubMed

Selby, Peter; van Mierlo, Trevor; Voci, Sabrina C; Parent, Danielle; Cunningham, John A

2010-08-18

Both intratreatment and extratreatment social support are associated with increased rates of smoking cessation. Internet-based social support groups have the capability of connecting widely dispersed groups of people trying to quit smoking, making social support available 24 hours a day, seven days a week, at minimal cost. However, to date there has been little research to guide development of this particular feature of Web-assisted tobacco interventions (WATIs). Our objectives were to compare the characteristics of smokers who post in an online smoking cessation support group with smokers who do not post, conduct a qualitative analysis of discussion board content, and determine the time it takes for new users to receive feedback from existing members or moderators. Data were collected from StopSmokingCenter.net version 5.0, a WATI equipped with an online social support network moderated by trained program health educators that was operational from November 6, 2004, to May 15, 2007. Demographic and smoking characteristics for both users and nonusers of the online social support network were analyzed, and qualitative analyses were conducted to explore themes in message content. Posting patterns and their frequency were also analyzed. During the study period, 16,764 individuals registered; of these, 70% (11,723) reported being American. The mean age of registrants was 38.9 years and 65% (10,965) were female. The mean number of cigarettes smoked was 20.6 per day. The mean score for the 41% (6849) of users who completed the Fagerström Test for Nicotine Dependence was 5.6. Of all registered members, 15% (2562) made at least one post in the online social support network; 25% of first posts received a response from another member within 12 minutes, 50% within 29 minutes. The most frequent first posts were from recent quitters who were struggling with their quit attempts, and most responses were from members who had quit for a month or more. Differences in demographic and smoking characteristics between members who posted on the support group board at least once and those who did not post were statistically but not clinically significant. Peer responses to new users were rapid, indicating that online social support networks may be particularly beneficial to smokers requiring more immediate assistance with their cessation attempt. This function may be especially advantageous for relapse prevention. Accessing this kind of rapid in-person support from a professional would take an inordinate amount of time and money. Further research regarding the effectiveness of WATIs with online social support networks is required to better understand the contribution of this feature to cessation, for both active users (posters) and passive users ("lurkers") alike.

Gradient calculations for dynamic recurrent neural networks: a survey.

PubMed

Pearlmutter, B A

1995-01-01

Surveys learning algorithms for recurrent neural networks with hidden units and puts the various techniques into a common framework. The authors discuss fixed point learning algorithms, namely recurrent backpropagation and deterministic Boltzmann machines, and nonfixed point algorithms, namely backpropagation through time, Elman's history cutoff, and Jordan's output feedback architecture. Forward propagation, an on-line technique that uses adjoint equations, and variations thereof, are also discussed. In many cases, the unified presentation leads to generalizations of various sorts. The author discusses advantages and disadvantages of temporally continuous neural networks in contrast to clocked ones continues with some "tricks of the trade" for training, using, and simulating continuous time and recurrent neural networks. The author presents some simulations, and at the end, addresses issues of computational complexity and learning speed.

A policy iteration approach to online optimal control of continuous-time constrained-input systems.

PubMed

Modares, Hamidreza; Naghibi Sistani, Mohammad-Bagher; Lewis, Frank L

2013-09-01

This paper is an effort towards developing an online learning algorithm to find the optimal control solution for continuous-time (CT) systems subject to input constraints. The proposed method is based on the policy iteration (PI) technique which has recently evolved as a major technique for solving optimal control problems. Although a number of online PI algorithms have been developed for CT systems, none of them take into account the input constraints caused by actuator saturation. In practice, however, ignoring these constraints leads to performance degradation or even system instability. In this paper, to deal with the input constraints, a suitable nonquadratic functional is employed to encode the constraints into the optimization formulation. Then, the proposed PI algorithm is implemented on an actor-critic structure to solve the Hamilton-Jacobi-Bellman (HJB) equation associated with this nonquadratic cost functional in an online fashion. That is, two coupled neural network (NN) approximators, namely an actor and a critic are tuned online and simultaneously for approximating the associated HJB solution and computing the optimal control policy. The critic is used to evaluate the cost associated with the current policy, while the actor is used to find an improved policy based on information provided by the critic. Convergence to a close approximation of the HJB solution as well as stability of the proposed feedback control law are shown. Simulation results of the proposed method on a nonlinear CT system illustrate the effectiveness of the proposed approach. Copyright © 2013 ISA. All rights reserved.

Improving General Chemistry Course Performance through Online Homework-Based Metacognitive Training

ERIC Educational Resources Information Center

Casselman, Brock L.; Atwood, Charles H.

2017-01-01

In a first-semester general chemistry course, metacognitive training was implemented as part of an online homework system. Students completed weekly quizzes and multiple practice tests to regularly assess their abilities on the chemistry principles. Before taking these assessments, students predicted their score, receiving feedback after…

Students' Groupwork Management in Online Collaborative Learning Environments

ERIC Educational Resources Information Center

Xu, Jianzhong; Du, Jianxia; Fan, Xitao

2015-01-01

The present study investigates empirical models of groupwork management in online collaborative learning environments, based on the data from 298 students (86 groups) in United States. Data revealed that, at the group level, groupwork management was positively associated with feedback and help seeking. Data further revealed that, at the individual…

Seeing the hand while reaching speeds up on-line responses to a sudden change in target position

PubMed Central

Reichenbach, Alexandra; Thielscher, Axel; Peer, Angelika; Bülthoff, Heinrich H; Bresciani, Jean-Pierre

2009-01-01

Goal-directed movements are executed under the permanent supervision of the central nervous system, which continuously processes sensory afferents and triggers on-line corrections if movement accuracy seems to be compromised. For arm reaching movements, visual information about the hand plays an important role in this supervision, notably improving reaching accuracy. Here, we tested whether visual feedback of the hand affects the latency of on-line responses to an external perturbation when reaching for a visual target. Two types of perturbation were used: visual perturbation consisted in changing the spatial location of the target and kinesthetic perturbation in applying a force step to the reaching arm. For both types of perturbation, the hand trajectory and the electromyographic (EMG) activity of shoulder muscles were analysed to assess whether visual feedback of the hand speeds up on-line corrections. Without visual feedback of the hand, on-line responses to visual perturbation exhibited the longest latency. This latency was reduced by about 10% when visual feedback of the hand was provided. On the other hand, the latency of on-line responses to kinesthetic perturbation was independent of the availability of visual feedback of the hand. In a control experiment, we tested the effect of visual feedback of the hand on visual and kinesthetic two-choice reaction times – for which coordinate transformation is not critical. Two-choice reaction times were never facilitated by visual feedback of the hand. Taken together, our results suggest that visual feedback of the hand speeds up on-line corrections when the position of the visual target with respect to the body must be re-computed during movement execution. This facilitation probably results from the possibility to map hand- and target-related information in a common visual reference frame. PMID:19675067

Functional electrical stimulation controlled by artificial neural networks: pilot experiments with simple movements are promising for rehabilitation applications.

PubMed

Ferrante, Simona; Pedrocchi, Alessandra; Iannò, Marco; De Momi, Elena; Ferrarin, Maurizio; Ferrigno, Giancarlo

2004-01-01

This study falls within the ambit of research on functional electrical stimulation for the design of rehabilitation training for spinal cord injured patients. In this context, a crucial issue is the control of the stimulation parameters in order to optimize the patterns of muscle activation and to increase the duration of the exercises. An adaptive control system (NEURADAPT) based on artificial neural networks (ANNs) was developed to control the knee joint in accordance with desired trajectories by stimulating quadriceps muscles. This strategy includes an inverse neural model of the stimulated limb in the feedforward line and a neural network trained on-line in the feedback loop. NEURADAPT was compared with a linear closed-loop proportional integrative derivative (PID) controller and with a model-based neural controller (NEUROPID). Experiments on two subjects (one healthy and one paraplegic) show the good performance of NEURADAPT, which is able to reduce the time lag introduced by the PID controller. In addition, control systems based on ANN techniques do not require complicated calibration procedures at the beginning of each experimental session. After the initial learning phase, the ANN, thanks to its generalization capacity, is able to cope with a certain range of variability of skeletal muscle properties.

75 FR 71376 - Simplified Network Application Processing System, On-Line Registration and Account Maintenance

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-23

...-02] RIN 0694-AE98 Simplified Network Application Processing System, On-Line Registration and Account...'') electronically via BIS's Simplified Network Application Processing (SNAP-R) system. Currently, parties must... Network Applications Processing System (SNAP-R) in October 2006. The SNAP-R system provides a Web based...

Evaluation of an Interactive Case-Based Online Network (ICON) in a Problem Based Learning Environment

ERIC Educational Resources Information Center

Nathoo, Arif N.; Goldhoff, Patricia; Quattrochi, James J.

2005-01-01

Purpose: This study sought to assess the introduction of a web-based innovation in medical education that complements traditional problem-based learning curricula. Utilizing the case method as its fundamental educational approach, the Interactive Case-based Online Network (ICON) allows students to interact with each other, faculty and a virtual…

Improving Patient Involvement in the Drug Development Process: Case Study of Potential Applications from an Online Peer Support Network.

PubMed

Anand, Amrutha; Brandwood, Helen Jane; Jameson Evans, Matt

2017-11-01

To date, social media has been used predominantly by the pharmaceutical industry to market products and to gather feedback and comments on products from consumers, a process termed social listening. However, social media has only been used cautiously in the drug development cycle, mainly because of regulations, restrictions on engagement with patients, or a lack of guidelines for social media use from regulatory bodies. Despite this cautious approach, there is a clear drive, from both the industry and consumers, for increased patient participation in various stages of the drug development process. The authors use the example of HealthUnlocked, one of the world's largest health networks, to illustrate the potential applications of online health communities as a means of increasing patient involvement at various stages of the drug development process. Having identified the willingness of the user population to be involved in research, numerous ways to engage users on the platform have been identified and explored. This commentary describes some of these approaches and reports how online health networks that encourage people to share their experiences in managing their health can, in turn, enable rapid patient engagement for clinical research within the constraints of industry regulation. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.

Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

NASA Astrophysics Data System (ADS)

Qiu, Feng; Dai, Guang; Zhang, Ying

According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.

Followers are not enough: a multifaceted approach to community detection in online social networks.

PubMed

Darmon, David; Omodei, Elisa; Garland, Joshua

2015-01-01

In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a 'community' as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of 'community.' In this paper we focus on three types of communities beyond follower-based structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure.

Online Collaborative Writing for ESL Learners Using Blogs and Feedback Checklists

ERIC Educational Resources Information Center

Grami, Grami Mohammad A.

2012-01-01

This paper reports on the experience of seven Saudi female ESL students who worked collaboratively in an interactive online writing environment over a period of four weeks. It chronicles their experiences with online writing tasks, documents their responses to online feedback, and examines their attempts to cope with different settings and…

Tracing the Attention of Moving Citizens

NASA Astrophysics Data System (ADS)

Wu, Lingfei; Wang, Cheng-Jun

2016-09-01

With the widespread use of mobile computing devices in contemporary society, our trajectories in the physical space and virtual world are increasingly closely connected. Using the anonymous smartphone data of 1 × 105 users in a major city of China, we study the interplay between online and offline human behaviors by constructing the mobility network (offline) and the attention network (online). Using the network renormalization technique, we find that they belong to two different classes: the mobility network is small-world, whereas the attention network is fractal. We then divide the city into different areas based on the features of the mobility network discovered under renormalization. Interestingly, this spatial division manifests the location-based online behaviors, for example shopping, dating, and taxi-requesting. Finally, we offer a geometric network model to help us understand the relationship between small-world and fractal networks.

Learners' Interpersonal Beliefs and Generated Feedback in an Online Role-Playing Peer-Feedback Activity: An Exploratory Study

ERIC Educational Resources Information Center

Ching, Yu-Hui; Hsu, Yu-Chang

2016-01-01

Peer feedback affords interaction and critical thinking opportunities for learners in online courses. However, various factors prevent learners from taking advantage of these promising benefits. This study explored learners' perceptions of the interpersonal factors in a role-playing peer-feedback activity, and examined the types of peer feedback…

A neural based intelligent flight control system for the NASA F-15 flight research aircraft

NASA Technical Reports Server (NTRS)

Urnes, James M.; Hoy, Stephen E.; Ladage, Robert N.; Stewart, James

1993-01-01

A flight control concept that can identify aircraft stability properties and continually optimize the aircraft flying qualities has been developed by McDonnell Aircraft Company under a contract with the NASA-Dryden Flight Research Facility. This flight concept, termed the Intelligent Flight Control System, utilizes Neural Network technology to identify the host aircraft stability and control properties during flight, and use this information to design on-line the control system feedback gains to provide continuous optimum flight response. This self-repairing capability can provide high performance flight maneuvering response throughout large flight envelopes, such as needed for the National Aerospace Plane. Moreover, achieving this response early in the vehicle's development schedule will save cost.

Delayed Instructional Feedback May Be More Effective, but Is This Contrary to Learners' Preferences?

ERIC Educational Resources Information Center

Lefevre, David; Cox, Benita

2017-01-01

This research investigates learners' preferences for the timing of feedback provided to multiple-choice questions within technology-based instruction, hitherto an area of little empirical attention. Digital materials are undergoing a period of renewed prominence within online learning and multiple-choice questions remain a common component. There…

Information diffusion in structured online social networks

NASA Astrophysics Data System (ADS)

Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

2015-05-01

Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

A comparison of classroom and online asynchronous problem-based learning for students undertaking statistics training as part of a Public Health Masters degree.

PubMed

de Jong, N; Verstegen, D M L; Tan, F E S; O'Connor, S J

2013-05-01

This case-study compared traditional, face-to-face classroom-based teaching with asynchronous online learning and teaching methods in two sets of students undertaking a problem-based learning module in the multilevel and exploratory factor analysis of longitudinal data as part of a Masters degree in Public Health at Maastricht University. Students were allocated to one of the two study variants on the basis of their enrolment status as full-time or part-time students. Full-time students (n = 11) followed the classroom-based variant and part-time students (n = 12) followed the online asynchronous variant which included video recorded lectures and a series of asynchronous online group or individual SPSS activities with synchronous tutor feedback. A validated student motivation questionnaire was administered to both groups of students at the start of the study and a second questionnaire was administered at the end of the module. This elicited data about student satisfaction with the module content, teaching and learning methods, and tutor feedback. The module coordinator and problem-based learning tutor were also interviewed about their experience of delivering the experimental online variant and asked to evaluate its success in relation to student attainment of the module's learning outcomes. Student examination results were also compared between the two groups. Asynchronous online teaching and learning methods proved to be an acceptable alternative to classroom-based teaching for both students and staff. Educational outcomes were similar for both groups, but importantly, there was no evidence that the asynchronous online delivery of module content disadvantaged part-time students in comparison to their full-time counterparts.

Information dynamics shape the sexual networks of Internet-mediated prostitution

PubMed Central

Rocha, Luis E. C.; Liljeros, Fredrik; Holme, Petter

2010-01-01

Like many other social phenomena, prostitution is increasingly coordinated over the Internet. The online behavior affects the offline activity; the reverse is also true. We investigated the reported sexual contacts between 6,624 anonymous escorts and 10,106 sex buyers extracted from an online community from its beginning and six years on. These sexual encounters were also graded and categorized (in terms of the type of sexual activities performed) by the buyers. From the temporal, bipartite network of posts, we found a full feedback loop in which high grades on previous posts affect the future commercial success of the sex worker, and vice versa. We also found a peculiar growth pattern in which the turnover of community members and sex workers causes a sublinear preferential attachment. There is, moreover, a strong geographic influence on network structure—the network is geographically clustered but still close to connected, the contacts consistent with the inverse-square law observed in trading patterns. We also found that the number of sellers scales sublinearly with city size, so this type of prostitution does not, comparatively speaking, benefit much from an increasing concentration of people. PMID:20231480

Online Social Networking, Sexual Risk and Protective Behaviors: Considerations for Clinicians and Researchers.

PubMed

Holloway, Ian W; Dunlap, Shannon; Del Pino, Homero E; Hermanstyne, Keith; Pulsipher, Craig; Landovitz, Raphael J

2014-09-01

Online social networking refers to the use of internet-based technologies that facilitate connection and communication between users. These platforms may be accessed via computer or mobile device (e.g., tablet, smartphone); communication between users may include linking of profiles, posting of text, photo and video content, instant messaging and email. This review provides an overview of recent research on the relationship between online social networking and sexual risk and protective behaviors with a focus on use of social networking sites (SNS) among young people and populations at high risk for sexually transmitted infections (STIs). While findings are mixed, the widespread use of SNS for sexual communication and partner seeking presents opportunities for the delivery and evaluation of public health interventions. Results of SNS-based interventions to reduce sexual risk are synthesized in order to offer hands-on advice for clinicians and researchers interested in engaging patients and study participants via online social networking.

Reinforcement-learning-based dual-control methodology for complex nonlinear discrete-time systems with application to spark engine EGR operation.

PubMed

Shih, Peter; Kaul, Brian C; Jagannathan, S; Drallmeier, James A

2008-08-01

A novel reinforcement-learning-based dual-control methodology adaptive neural network (NN) controller is developed to deliver a desired tracking performance for a class of complex feedback nonlinear discrete-time systems, which consists of a second-order nonlinear discrete-time system in nonstrict feedback form and an affine nonlinear discrete-time system, in the presence of bounded and unknown disturbances. For example, the exhaust gas recirculation (EGR) operation of a spark ignition (SI) engine is modeled by using such a complex nonlinear discrete-time system. A dual-controller approach is undertaken where primary adaptive critic NN controller is designed for the nonstrict feedback nonlinear discrete-time system whereas the secondary one for the affine nonlinear discrete-time system but the controllers together offer the desired performance. The primary adaptive critic NN controller includes an NN observer for estimating the states and output, an NN critic, and two action NNs for generating virtual control and actual control inputs for the nonstrict feedback nonlinear discrete-time system, whereas an additional critic NN and an action NN are included for the affine nonlinear discrete-time system by assuming the state availability. All NN weights adapt online towards minimization of a certain performance index, utilizing gradient-descent-based rule. Using Lyapunov theory, the uniformly ultimate boundedness (UUB) of the closed-loop tracking error, weight estimates, and observer estimates are shown. The adaptive critic NN controller performance is evaluated on an SI engine operating with high EGR levels where the controller objective is to reduce cyclic dispersion in heat release while minimizing fuel intake. Simulation and experimental results indicate that engine out emissions drop significantly at 20% EGR due to reduction in dispersion in heat release thus verifying the dual-control approach.

A general framework for a collaborative water quality knowledge and information network.

PubMed

Dalcanale, Fernanda; Fontane, Darrell; Csapo, Jorge

2011-03-01

Increasing knowledge about the environment has brought about a better understanding of the complexity of the issues, and more information publicly available has resulted into a steady shift from centralized decision making to increasing levels of participatory processes. The management of that information, in turn, is becoming more complex. One of the ways to deal with the complexity is the development of tools that would allow all players, including managers, researchers, educators, stakeholders and the civil society, to be able to contribute to the information system, in any level they are inclined to do so. In this project, a search for the available technology for collaboration, methods of community filtering, and community-based review was performed and the possible implementation of these tools to create a general framework for a collaborative "Water Quality Knowledge and Information Network" was evaluated. The main goals of the network are to advance water quality education and knowledge; encourage distribution and access to data; provide networking opportunities; allow public perceptions and concerns to be collected; promote exchange of ideas; and, give general, open, and free access to information. A reference implementation was made available online and received positive feedback from the community, which also suggested some possible improvements.

A General Framework for a Collaborative Water Quality Knowledge and Information Network

NASA Astrophysics Data System (ADS)

Dalcanale, Fernanda; Fontane, Darrell; Csapo, Jorge

2011-03-01

Increasing knowledge about the environment has brought about a better understanding of the complexity of the issues, and more information publicly available has resulted into a steady shift from centralized decision making to increasing levels of participatory processes. The management of that information, in turn, is becoming more complex. One of the ways to deal with the complexity is the development of tools that would allow all players, including managers, researchers, educators, stakeholders and the civil society, to be able to contribute to the information system, in any level they are inclined to do so. In this project, a search for the available technology for collaboration, methods of community filtering, and community-based review was performed and the possible implementation of these tools to create a general framework for a collaborative "Water Quality Knowledge and Information Network" was evaluated. The main goals of the network are to advance water quality education and knowledge; encourage distribution and access to data; provide networking opportunities; allow public perceptions and concerns to be collected; promote exchange of ideas; and, give general, open, and free access to information. A reference implementation was made available online and received positive feedback from the community, which also suggested some possible improvements.

MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

NASA Astrophysics Data System (ADS)

Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

PRN: a preprint service for catalyzing R-fMRI and neuroscience related studies

PubMed Central

Yan, Chao-gan; Li, Qingyang; Gao, Lei

2015-01-01

Sharing drafts of scientific manuscripts on preprint hosting services for early exposure and pre-publication feedback is a well-accepted practice in fields such as physics, astronomy, or mathematics. The field of neuroscience, however, has yet to adopt the preprint model. A reason for this reluctance might partly be the lack of central preprint services for the field of neuroscience. To address this issue, we announce the launch of Preprints of the R-fMRI Network (PRN), a community funded preprint hosting service. PRN provides free-submission and free hosting of manuscripts for resting state functional magnetic resonance imaging (R-fMRI) and neuroscience related studies. Submitted articles are openly discussed and receive feedback from readers and a panel of invited consultants from the R-fMRI Network. All manuscripts and feedback are freely accessible online with citable permanent URL for open-access. The goal of PRN is to supplement the peer reviewed journal publication system – by more rapidly communicating the latest research achievements throughout the world. We hope PRN would help the field to embrace the preprint model and thus further accelerate R-fMRI and neuroscience related studies, eventually enhancing human mental health. PMID:25844159

The Use of Online Corrective Feedback in Academic Writing by L1 Malay Learners

ERIC Educational Resources Information Center

Yoke, Soo Kum; Rajendran, Cecilia Bai; Sain, Noridah; Kamaludin, Puteri Nur Hidayah; Nawi, Sofwah Md; Yusof, Suhaili

2013-01-01

Conventional corrective feedback has been widely practiced but has been said to be tedious, stressful and time consuming. As such, the focus of this study is to investigate the use of an alternative method to giving corrective feedback namely, an online corrective feedback through e-mail. In order to examine if this innovative form of corrective…

Experiences of Users from Online Grocery Stores

NASA Astrophysics Data System (ADS)

Freeman, Mark

Grocery shopping, traditionally considered as the pinnacle of the self-service industry, is used as the case study in this chapter. As the Internet has become widely used by many segments of the population, the opportunity to shop online for groceries has been presented to consumers. This chapter considers issues that need to be addressed to make online grocery shopping systems more usable for these consumers, based on feedback from individuals who participated in a study of user interactions with Australian online grocery stores.

Tracing the Attention of Moving Citizens

PubMed Central

Wu, Lingfei; Wang, Cheng-Jun

2016-01-01

With the widespread use of mobile computing devices in contemporary society, our trajectories in the physical space and virtual world are increasingly closely connected. Using the anonymous smartphone data of 1 × 105 users in a major city of China, we study the interplay between online and offline human behaviors by constructing the mobility network (offline) and the attention network (online). Using the network renormalization technique, we find that they belong to two different classes: the mobility network is small-world, whereas the attention network is fractal. We then divide the city into different areas based on the features of the mobility network discovered under renormalization. Interestingly, this spatial division manifests the location-based online behaviors, for example shopping, dating, and taxi-requesting. Finally, we offer a geometric network model to help us understand the relationship between small-world and fractal networks. PMID:27608929

Effects of Online Augmented Kinematic and Perceptual Feedback on Treatment of Speech Movements in Apraxia of Speech

PubMed Central

McNeil, M.R.; Katz, W.F.; Fossett, T.R.D.; Garst, D.M.; Szuminsky, N.J.; Carter, G.; Lim, K.Y.

2010-01-01

Apraxia of speech (AOS) is a motor speech disorder characterized by disturbed spatial and temporal parameters of movement. Research on motor learning suggests that augmented feedback may provide a beneficial effect for training movement. This study examined the effects of the presence and frequency of online augmented visual kinematic feedback (AVKF) and clinician-provided perceptual feedback on speech accuracy in 2 adults with acquired AOS. Within a single-subject multiple-baseline design, AVKF was provided using electromagnetic midsagittal articulography (EMA) in 2 feedback conditions (50 or 100%). Articulator placement was specified for speech motor targets (SMTs). Treated and baselined SMTs were in the initial or final position of single-syllable words, in varying consonant-vowel or vowel-consonant contexts. SMTs were selected based on each participant's pre-assessed erred productions. Productions were digitally recorded and online perceptual judgments of accuracy (including segment and intersegment distortions) were made. Inter- and intra-judge reliability for perceptual accuracy was high. Results measured by visual inspection and effect size revealed positive acquisition and generalization effects for both participants. Generalization occurred across vowel contexts and to untreated probes. Results of the frequency manipulation were confounded by presentation order. Maintenance of learned and generalized effects were demonstrated for 1 participant. These data provide support for the role of augmented feedback in treating speech movements that result in perceptually accurate speech production. Future investigations will explore the independent contributions of each feedback type (i.e. kinematic and perceptual) in producing efficient and effective training of SMTs in persons with AOS. PMID:20424468

Analysis of Feedback Processes in Online Group Interaction: A Methodological Model

ERIC Educational Resources Information Center

Espasa, Anna; Guasch, Teresa; Alvarez, Ibis M.

2013-01-01

The aim of this article is to present a methodological model to analyze students' group interaction to improve their essays in online learning environments, based on asynchronous and written communication. In these environments teacher and student scaffolds for discussion are essential to promote interaction. One of these scaffolds can be the…

Online Self-Assessment Materials: Do These Make a Difference to Student Learning?

ERIC Educational Resources Information Center

Peat, Mary

2000-01-01

Examines the use of Web-based online self-assessment in a large first-year biology class at the University of Sydney (Australia). Discusses a more student-centered focus to aid lifelong learning; collaborative learning; suitable and timely feedback; the use of Bloom's taxonomy; and student evaluations of self-assessment modules. (LRW)

A last updating evolution model for online social networks

NASA Astrophysics Data System (ADS)

Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

2013-05-01

As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.

Disseminating Innovations in Teaching Value-Based Care Through an Online Learning Network.

PubMed

Gupta, Reshma; Shah, Neel T; Moriates, Christopher; Wallingford, September; Arora, Vineet M

2017-08-01

A national imperative to provide value-based care requires new strategies to teach clinicians about high-value care. We developed a virtual online learning network aimed at disseminating emerging strategies in teaching value-based care. The online Teaching Value in Health Care Learning Network includes monthly webinars that feature selected innovators, online discussion forums, and a repository for sharing tools. The learning network comprises clinician-educators and health system leaders across North America. We conducted a cross-sectional online survey of all webinar presenters and the active members of the network, and we assessed program feasibility. Six months after the program launched, there were 277 learning community members in 22 US states. Of the 74 active members, 50 (68%) completed the evaluation. Active members represented independently practicing physicians and trainees in 7 specialties, nurses, educators, and health system leaders. Nearly all speakers reported that the learning network provided them with a unique opportunity to connect with a different audience and achieve greater recognition for their work. Of the members who were active in the learning network, most reported that strategies gleaned from the network were helpful, and some adopted or adapted these innovations at their home institutions. One year after the program launched, the learning network had grown to 364 total members. The learning network helped participants share and implement innovations to promote high-value care. The model can help disseminate innovations in emerging areas of health care transformation, and is sustainable without ongoing support after a period of start-up funding.

The Effect of Central American Smoke Aerosols on the Air Quality and Climate over the Southeastern United States: First Results from RAMS-AROMA

NASA Astrophysics Data System (ADS)

Wang, J.; Christopher, S. A.; Nair, U. S.; Reid, J.; Prins, E. M.; Szykman, J.

2004-12-01

Observation shows that smoke aerosols from biomass burning activities in Central America can be transported to the Southeastern United States (SEUS). In this study, the Regional Atmospheric Modeling System - Assimilation and Radiation Online Modeling of Aerosols (RAMS-AROMA) is used to investigate the effect of transported smoke aerosols on climate and air quality over the SEUS. AROMA is an aerosol transport model with capabilities of online integration of aerosol radiation effects and online assimilation of satellite-derived aerosol and emission products. It is assembled within the RAMS, so two-way interactions between aerosol fields and other meteorology fields are achieved simultaneously during each model time step. RAMS-AROMA is a unique tool that can be used to examine the aerosol radiative impacts on the surface energy budget and atmospheric heating rate and to investigate how atmospheric thermal and dynamical processes respond to such impacts and consequently affect the aerosol distribution (so called feedbacks). First results regarding air quality effects and radiative forcing of transported smoke aerosols will be presented from RAMS-AROMA based on assimilation of smoke emission products from the Fire Locating and Modeling of Burning Emissions (FLAMBE) project and aerosol optical thickness data derived from the MODIS instrument on the Terra and Aqua satellites. Comparisons with PM2.5 data collected from the EPA observation network and the aerosol optical thickness data from the DOE Atmosphere Radiation Measurements in the Southern Great Plains (ARM SGP) showed that RAMS-AROMA can predict the timing and spatial distribution of smoke events very well, with an accuracy useful for air quality forecasts. The smoke radiative effects on the surface temperature and atmospheric heating rate as well as their feedbacks will also be discussed.

Online social networking by patients with diabetes: a qualitative evaluation of communication with Facebook.

PubMed

Greene, Jeremy A; Choudhry, Niteesh K; Kilabuk, Elaine; Shrank, William H

2011-03-01

Several disease-specific information exchanges now exist on Facebook and other online social networking sites. These new sources of knowledge, support, and engagement have become important for patients living with chronic disease, yet the quality and content of the information provided in these digital arenas are poorly understood. To qualitatively evaluate the content of communication in Facebook communities dedicated to diabetes. We identified the 15 largest Facebook groups focused on diabetes management. For each group, we downloaded the 15 most recent "wall posts" and the 15 most recent discussion topics from the 10 largest groups. Four hundred eighty unique users were identified in a series of 690 comments from wall posts and discussion topics. Posts were abstracted and aggregated into a database. Two investigators evaluated the posts, developed a thematic coding scheme, and applied codes to the data. Patients with diabetes, family members, and their friends use Facebook to share personal clinical information, to request disease-specific guidance and feedback, and to receive emotional support. Approximately two-thirds of posts included unsolicited sharing of diabetes management strategies, over 13% of posts provided specific feedback to information requested by other users, and almost 29% of posts featured an effort by the poster to provide emotional support to others as members of a community. Approximately 27% of posts featured some type of promotional activity, generally presented as testimonials advertising non-FDA approved, "natural" products. Clinically inaccurate recommendations were infrequent, but were usually associated with promotion of a specific product or service. Thirteen percent of posts contained requests for personal information from Facebook participants. Facebook provides a forum for reporting personal experiences, asking questions, and receiving direct feedback for people living with diabetes. However, promotional activity and personal data collection are also common, with no accountability or checks for authenticity.

Synchronization of Lienard-Type Oscillators in Uniform Electrical Networks

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

Sinha, Mohit; Dorfler, Florian; Johnson, Brian B.

2016-08-01

This paper presents a condition for global asymptotic synchronization of Lienard-type nonlinear oscillators in uniform LTI electrical networks with series R-L circuits modeling interconnections. By uniform electrical networks, we mean that the per-unit-length impedances are identical for the interconnecting lines. We derive conditions for global asymptotic synchronization for a particular feedback architecture where the derivative of the oscillator output current supplements the innate current feedback induced by simply interconnecting the oscillator to the network. Our proof leverages a coordinate transformation to a set of differential coordinates that emphasizes signal differences and the particular form of feedback permits the formulation ofmore » a quadratic Lyapunov function for this class of networks. This approach is particularly interesting since synchronization conditions are difficult to obtain by means of quadratic Lyapunov functions when only current feedback is used and for networks composed of series R-L circuits. Our synchronization condition depends on the algebraic connectivity of the underlying network, and reiterates the conventional wisdom from Lyapunov- and passivity-based arguments that strong coupling is required to ensure synchronization.« less

Video diaries on social media: Creating online communities for geoscience research and education

NASA Astrophysics Data System (ADS)

Tong, V.

2013-12-01

Making video clips is an engaging way to learn and teach geoscience. As smartphones become increasingly common, it is relatively straightforward for students to produce ';video diaries' by recording their research and learning experience over the course of a science module. Instead of keeping the video diaries for themselves, students may use the social media such as Facebook for sharing their experience and thoughts. There are some potential benefits to link video diaries and social media in pedagogical contexts. For example, online comments on video clips offer useful feedback and learning materials to the students. Students also have the opportunity to engage in geoscience outreach by producing authentic scientific contents at the same time. A video diary project was conducted to test the pedagogical potential of using video diaries on social media in the context of geoscience outreach, undergraduate research and teaching. This project formed part of a problem-based learning module in field geophysics at an archaeological site in the UK. The project involved i) the students posting video clips about their research and problem-based learning in the field on a daily basis; and ii) the lecturer building an online outreach community with partner institutions. In this contribution, I will discuss the implementation of the project and critically evaluate the pedagogical potential of video diaries on social media. My discussion will focus on the following: 1) Effectiveness of video diaries on social media; 2) Student-centered approach of producing geoscience video diaries as part of their research and problem-based learning; 3) Learning, teaching and assessment based on video clips and related commentaries posted on Facebook; and 4) Challenges in creating and promoting online communities for geoscience outreach through the use of video diaries. I will compare the outcomes from this study with those from other pedagogical projects with video clips on geoscience, and evaluate the concept of ';networked public engagement' based on online video diaries.

Using Case-Based Reasoning to Improve the Quality of Feedback Provided by Automated Assessment Systems for Programming Exercises

ERIC Educational Resources Information Center

Kyrilov, Angelo

2017-01-01

Information technology is now ubiquitous in higher education institutions worldwide. More than 85% of American universities use e-learning systems to supplement traditional classroom activities. An obvious benefit of these online tools is their ability to automatically grade exercises submitted by students and provide immediate feedback. Most of…

Experimental Evidence on the Effectiveness of Automated Essay Scoring in Teacher Education Cases

ERIC Educational Resources Information Center

Riedel, Eric; Dexter, Sara L.; Scharber, Cassandra; Doering, Aaron

2006-01-01

Research on computer-based writing evaluation has only recently focused on the potential for providing formative feedback rather than summative assessment. This study tests the impact of an automated essay scorer (AES) that provides formative feedback on essay drafts written as part of a series of online teacher education case studies. Seventy…

Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study.

PubMed

Saleh, Soha; Yarossi, Mathew; Manuweera, Thushini; Adamovich, Sergei; Tunik, Eugene

2017-01-01

Mirror visual feedback (MVF) is potentially a powerful tool to facilitate recovery of disordered movement and stimulate activation of under-active brain areas due to stroke. The neural mechanisms underlying MVF have therefore been a focus of recent inquiry. Although it is known that sensorimotor areas can be activated via mirror feedback, the network interactions driving this effect remain unknown. The aim of the current study was to fill this gap by using dynamic causal modeling to test the interactions between regions in the frontal and parietal lobes that may be important for modulating the activation of the ipsilesional motor cortex during mirror visual feedback of unaffected hand movement in stroke patients. Our intent was to distinguish between two theoretical neural mechanisms that might mediate ipsilateral activation in response to mirror-feedback: transfer of information between bilateral motor cortices versus recruitment of regions comprising an action observation network which in turn modulate the motor cortex. In an event-related fMRI design, fourteen chronic stroke subjects performed goal-directed finger flexion movements with their unaffected hand while observing real-time visual feedback of the corresponding (veridical) or opposite (mirror) hand in virtual reality. Among 30 plausible network models that were tested, the winning model revealed significant mirror feedback-based modulation of the ipsilesional motor cortex arising from the contralesional parietal cortex, in a region along the rostral extent of the intraparietal sulcus. No winning model was identified for the veridical feedback condition. We discuss our findings in the context of supporting the latter hypothesis, that mirror feedback-based activation of motor cortex may be attributed to engagement of a contralateral (contralesional) action observation network. These findings may have important implications for identifying putative cortical areas, which may be targeted with non-invasive brain stimulation as a means of potentiating the effects of mirror training.

The SUNY biomedical communication network: six years of progress in on-line bibiographic retrieval.

PubMed Central

Egeland, J

1975-01-01

The SUNY Biomedical Communication Network became operational in 1968 as the first on-line bibliograhpic retrieval service for biomedical literature. Since 1968, the SUNY/BCN has grown in size from nine to thirty-two medical and university libraries and has expanded its data base coverage to include the ERIC and Psychological Abstracts data bases in addition to the full ten-year retrospective MEDLARS data base. Aside from the continuous provision of an on-line searching system, the SUNY experience over the last six years has yielded valuable information in the following areas of: (1) monograph indexing and retrieval, (2) shared cataloging, (3) user interaction and education in on-line systems, and (4) member participation in Network policy-making processes. The continued success of the SUNY/BCN is evidence that it is possible to provide a high quality on-line bibliographic retrieval system at cost to academic institutions. SUNY's success in this effort is the result of centralized resource sharing and effective regional networking, combined with thoughtful planning by user advisory committees. PMID:1173557

Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

PubMed

Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

2007-07-01

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

The concurrent and longitudinal relationships between adolescents' use of social network sites and their social self-esteem.

PubMed

Valkenburg, Patti M; Koutamanis, Maria; Vossen, Helen G M

2017-11-01

The first aim of this study was to investigate the concurrent and longitudinal relationships between adolescents' use of social network sites (SNSs) and their social self-esteem. The second aim was to investigate whether the valence of the feedback that adolescents receive on SNSs can explain these relationships. We conducted a three-wave panel study among 852 pre- and early adolescents (10-15 years old). In line with earlier research, we found significant concurrent correlations between adolescents' SNS use and their social self-esteem in all three data waves. The longitudinal results only partly confirmed these concurrent findings: Adolescents' initial SNS use did not significantly influence their social self-esteem in subsequent years. In contrast, their initial social self-esteem consistently influenced their SNS use in subsequent years. The valence of online feedback from close friends and acquaintances explained the concurrent relationship between SNS use and social self-esteem, but not the longitudinal relationship. Results are discussed in terms of their methodological and theoretical implications.

Error correcting mechanisms during antisaccades: contribution of online control during primary saccades and offline control via secondary saccades.

PubMed

Bedi, Harleen; Goltz, Herbert C; Wong, Agnes M F; Chandrakumar, Manokaraananthan; Niechwiej-Szwedo, Ewa

2013-01-01

Errors in eye movements can be corrected during the ongoing saccade through in-flight modifications (i.e., online control), or by programming a secondary eye movement (i.e., offline control). In a reflexive saccade task, the oculomotor system can use extraretinal information (i.e., efference copy) online to correct errors in the primary saccade, and offline retinal information to generate a secondary corrective saccade. The purpose of this study was to examine the error correction mechanisms in the antisaccade task. The roles of extraretinal and retinal feedback in maintaining eye movement accuracy were investigated by presenting visual feedback at the spatial goal of the antisaccade. We found that online control for antisaccade is not affected by the presence of visual feedback; that is whether visual feedback is present or not, the duration of the deceleration interval was extended and significantly correlated with reduced antisaccade endpoint error. We postulate that the extended duration of deceleration is a feature of online control during volitional saccades to improve their endpoint accuracy. We found that secondary saccades were generated more frequently in the antisaccade task compared to the reflexive saccade task. Furthermore, we found evidence for a greater contribution from extraretinal sources of feedback in programming the secondary "corrective" saccades in the antisaccade task. Nonetheless, secondary saccades were more corrective for the remaining antisaccade amplitude error in the presence of visual feedback of the target. Taken together, our results reveal a distinctive online error control strategy through an extension of the deceleration interval in the antisaccade task. Target feedback does not improve online control, rather it improves the accuracy of secondary saccades in the antisaccade task.

Error Correcting Mechanisms during Antisaccades: Contribution of Online Control during Primary Saccades and Offline Control via Secondary Saccades

PubMed Central

Bedi, Harleen; Goltz, Herbert C.; Wong, Agnes M. F.; Chandrakumar, Manokaraananthan; Niechwiej-Szwedo, Ewa

2013-01-01

Errors in eye movements can be corrected during the ongoing saccade through in-flight modifications (i.e., online control), or by programming a secondary eye movement (i.e., offline control). In a reflexive saccade task, the oculomotor system can use extraretinal information (i.e., efference copy) online to correct errors in the primary saccade, and offline retinal information to generate a secondary corrective saccade. The purpose of this study was to examine the error correction mechanisms in the antisaccade task. The roles of extraretinal and retinal feedback in maintaining eye movement accuracy were investigated by presenting visual feedback at the spatial goal of the antisaccade. We found that online control for antisaccade is not affected by the presence of visual feedback; that is whether visual feedback is present or not, the duration of the deceleration interval was extended and significantly correlated with reduced antisaccade endpoint error. We postulate that the extended duration of deceleration is a feature of online control during volitional saccades to improve their endpoint accuracy. We found that secondary saccades were generated more frequently in the antisaccade task compared to the reflexive saccade task. Furthermore, we found evidence for a greater contribution from extraretinal sources of feedback in programming the secondary “corrective” saccades in the antisaccade task. Nonetheless, secondary saccades were more corrective for the remaining antisaccade amplitude error in the presence of visual feedback of the target. Taken together, our results reveal a distinctive online error control strategy through an extension of the deceleration interval in the antisaccade task. Target feedback does not improve online control, rather it improves the accuracy of secondary saccades in the antisaccade task. PMID:23936308

The Effects of Facilitating Feedback on Online Learners' Cognitive Engagement: Evidence from the Asynchronous Online Discussion

ERIC Educational Resources Information Center

Guo, Wenge; Chen, Ye; Lei, Jing; Wen, Yan

2014-01-01

With a large-scale online K-12 teacher professional development course as the research context, this study examined the effects of facilitating feedback on online learners' cognitive engagement using quasi-experiment method. A total of 1,540 discussion messages from 110 learners (65 in the experimental group and 45 in the control group) were both…

Optimizing Dynamical Network Structure for Pinning Control

NASA Astrophysics Data System (ADS)

Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo

2016-04-01

Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.

Ontology-based topic clustering for online discussion data

NASA Astrophysics Data System (ADS)

Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

2013-03-01

With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.

Blending Formal and Informal Learning Networks for Online Learning

ERIC Educational Resources Information Center

Czerkawski, Betül C.

2016-01-01

With the emergence of social software and the advance of web-based technologies, online learning networks provide invaluable opportunities for learning, whether formal or informal. Unlike top-down, instructor-centered, and carefully planned formal learning settings, informal learning networks offer more bottom-up, student-centered participatory…

Real-time individualized training vectors for experiential learning.

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

Willis, Matt; Tucker, Eilish Marie; Raybourn, Elaine Marie

2011-01-01

Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD)more » project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.« less

Output feedback control of a quadrotor UAV using neural networks.

PubMed

Dierks, Travis; Jagannathan, Sarangapani

2010-01-01

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

Followers Are Not Enough: A Multifaceted Approach to Community Detection in Online Social Networks

PubMed Central

2015-01-01

In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a ‘community’ as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of ‘community.’ In this paper we focus on three types of communities beyond follower-based structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure. PMID:26267868

The Online Social Networking of Cyberspace: A Study on the Development of an Online Social Network Project and the Sport Industry's Perception of Its Relative Advantage

ERIC Educational Resources Information Center

Liptrap, Timothy John

2011-01-01

This exploratory case study examined online social networking (OSN), and the perceptions of Sport Marketing students and sport industry professional as to the relative advantage of the OSN tools in the marketplace. The conceptual framework for this study was based on Boyer's (1990) concepts of Scholarship of Teaching and Learning (SoTL), and the…

Reinforced communication and social navigation: Remember your friends and remember yourself

NASA Astrophysics Data System (ADS)

Mirshahvalad, A.; Rosvall, M.

2011-09-01

In social systems, people communicate with each other and form groups based on their interests. The pattern of interactions, the network, and the ideas that flow on the network naturally evolve together. Researchers use simple models to capture the feedback between changing network patterns and ideas on the network, but little is understood about the role of past events in the feedback process. Here, we introduce a simple agent-based model to study the coupling between peoples’ ideas and social networks, and better understand the role of history in dynamic social networks. We measure how information about ideas can be recovered from information about network structure and, the other way around, how information about network structure can be recovered from information about ideas. We find that it is, in general, easier to recover ideas from the network structure than vice versa.

From sparse to dense and from assortative to disassortative in online social networks

PubMed Central

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-01-01

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks. PMID:24798703

From sparse to dense and from assortative to disassortative in online social networks.

PubMed

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-05-06

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.

The Long-Term Benefits of Positive Self-Presentation via Profile Pictures, Number of Friends and the Initiation of Relationships on Facebook for Adolescents' Self-Esteem and the Initiation of Offline Relationships.

PubMed

Metzler, Anna; Scheithauer, Herbert

2017-01-01

Social networking sites are a substantial part of adolescents' daily lives. By using a longitudinal approach the current study examined the impact of (a) positive self-presentation, (b) number of friends, and (c) the initiation of online relationships on Facebook on adolescents' self-esteem and their initiation of offline relationships, as well as the mediating role of positive feedback. Questionnaire data were obtained from 217 adolescents (68% girls, mean age 16.7 years) in two waves. Adolescents' positive self-presentation and number of friends were found to be related to a higher frequency of receiving positive feedback, which in turn was negatively associated with self-esteem. However, the number of Facebook friends had a positive impact on self-esteem, and the initiation of online relationships positively influenced the initiation of offline relationships over time, demonstrating that Facebook may be a training ground for increasing adolescents' social skills. Implications and suggestions for future research are provided.

The Long-Term Benefits of Positive Self-Presentation via Profile Pictures, Number of Friends and the Initiation of Relationships on Facebook for Adolescents’ Self-Esteem and the Initiation of Offline Relationships

PubMed Central

Metzler, Anna; Scheithauer, Herbert

2017-01-01

Social networking sites are a substantial part of adolescents’ daily lives. By using a longitudinal approach the current study examined the impact of (a) positive self-presentation, (b) number of friends, and (c) the initiation of online relationships on Facebook on adolescents’ self-esteem and their initiation of offline relationships, as well as the mediating role of positive feedback. Questionnaire data were obtained from 217 adolescents (68% girls, mean age 16.7 years) in two waves. Adolescents’ positive self-presentation and number of friends were found to be related to a higher frequency of receiving positive feedback, which in turn was negatively associated with self-esteem. However, the number of Facebook friends had a positive impact on self-esteem, and the initiation of online relationships positively influenced the initiation of offline relationships over time, demonstrating that Facebook may be a training ground for increasing adolescents’ social skills. Implications and suggestions for future research are provided. PMID:29187827

Teaching Quality Evaluation: Online vs Manually, Facts and Myths

ERIC Educational Resources Information Center

Esmael, Salman

2017-01-01

Aim/Purpose: This study aimed to examine whether there is a difference between manual feedback and online feedback with regard to feedback quality, respondents' percentage, reliability and the amount of verbal comments written by students. Background: The quality of teaching is an important component of academic work. There are various methods for…

Factors Predicting Online Graduate Students' Responsiveness to Feedback from Their Professors

ERIC Educational Resources Information Center

Breslin, Mary R.

2012-01-01

College students act on their professors' feedback less often and less completely than their professors would like. The problem this study addressed is that the relative predictive value of factors concerning graduate students in online courses acting on their professors' feedback is unknown. By focusing on graduate students in…

Does Feedback Influence Student Postings to Online Discussions?

ERIC Educational Resources Information Center

Meyer, Katrina A.

2007-01-01

Feedback theory proposes that feedback influences the behavior of a system and its parts and that is governed by rules. This exploratory study attempts to test this theory in a graduate-level class on leadership theory. Twelve students were asked to participate in five online discussions, each lasting one week. The questions for each discussion…

An Evaluation of the Interactive Query Expansion in an Online Library Catalogue with a Graphical User Interface.

ERIC Educational Resources Information Center

Hancock-Beaulieu, Micheline; And Others

1995-01-01

An online library catalog was used to evaluate an interactive query expansion facility based on relevance feedback for the Okapi, probabilistic, term weighting, retrieval system. A graphical user interface allowed searchers to select candidate terms extracted from relevant retrieved items to reformulate queries. Results suggested that the…

Students' Feedback of mDPBL Approach and the Learning Impact towards Computer Networks Teaching and Learning

ERIC Educational Resources Information Center

Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

2018-01-01

This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…

Why people continue to play online games: in search of critical design factors to increase customer loyalty to online contents.

PubMed

Choi, Dongseong; Kim, Jinwoo

2004-02-01

As people increasingly play online games, numerous new features have been proposed to increase players' log-on time at online gaming sites. However, few studies have investigated why people continue to play certain online games or which design features are most closely related to the amount of time spent by players at particular online gaming sites. This study proposes a theoretical model using the concepts of customer loyalty, flow, personal interaction, and social interaction to explain why people continue to play online network games. The study then conducts a large-scale survey to validate the model. Finally, it analyzes current online games to identify design features that are closely related to the theoretical concepts. The results indicate that people continue to play online games if they have optimal experiences while playing the games. This optimal experience can be attained if the player has effective personal interaction with the system or pleasant social interactions with other people connected to the Internet. Personal interaction can be facilitated by providing appropriate goals, operators and feedback; social interaction can be facilitated through appropriate communication places and tools. This paper ends with the implications of applying the study results to other domains such as e-commerce and cyber communities.

Learning feedback and feedforward control in a mirror-reversed visual environment.

PubMed

Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi; Diedrichsen, Jörn

2015-10-01

When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. Copyright © 2015 the American Physiological Society.

Learning feedback and feedforward control in a mirror-reversed visual environment

PubMed Central

Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi

2015-01-01

When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. PMID:26245313

Planning for the next generation of public health advocates: evaluation of an online advocacy mentoring program.

PubMed

O'Connell, Emily; Stoneham, Melissa; Saunders, Julie

2016-04-01

Issue addressed Despite being viewed as a core competency for public health professionals, public health advocacy lacks a prominent place in the public health literature and receives minimal coverage in university curricula. The Public Health Advocacy Institute of Western Australia (PHAIWA) sought to fill this gap by establishing an online e-mentoring program for public health professionals to gain knowledge through skill-based activities and engaging in a mentoring relationship with an experienced public health advocate. This study is a qualitative evaluation of the online e-mentoring program. Methods Semi-structured interviews were conducted with program participants at the conclusion of the 12-month program to examine program benefits and determine the perceived contribution of individual program components to overall advocacy outcomes. Results Increased mentee knowledge, skills, level of confidence and experience, and expanded public health networks were reported. Outcomes were dependent on participants' level of commitment, time and location barriers, mentoring relationship quality, adaptability to the online format and the relevance of activities for application to participants' workplace context. Program facilitators had an important role through the provision of timely feedback and maintaining contact with participants. Conclusion An online program that combines public health advocacy content via skill-based activities with mentoring from an experienced public health advocate is a potential strategy to build advocacy capacity in the public health workforce. So what? Integrating advocacy as a core component of professional development programs will help counteract current issues surrounding hesitancy by public health professionals to proactively engage in advocacy, and ensure that high quality, innovative and effective advocacy leadership continues in the Australian public health workforce.

Immediate detailed feedback to test-enhanced learning: an effective online educational tool.

PubMed

Wojcikowski, Ken; Kirk, Leslie

2013-11-01

Test-enhanced learning has gained popularity because it is an effective way to increase retention of knowledge; provided the student receives the correct answer soon after the test is taken. To determine whether detailed feedback provided to test-enhanced learning questions is an effective online educational tool for improving performance on complex biomedical information exams. A series of online multiple choice tests were developed to test knowledge of biomedical information that students were expected to know after each patient-case. Following submission of the student answers, one cohort (n = 52) received answers only while the following year, a second cohort (n = 51) received the answers with detailed feedback explaining why each answer was correct or incorrect. Students in both groups progressed through the series of online tests with little assessor intervention. Students receiving the answers along with the explanations within their feedback performed significantly better in the final biomedical information exam than those students receiving correct answers only. This pilot study found that the detailed feedback to test-enhanced learning questions is an important online learning tool. The increase in student performance in the complex biomedical information exam in this study suggests that detailed feedback should be investigated not only for increasing knowledge, but also be investigated for its effect on retention and application of knowledge.

Online Social Networking, Sexual Risk and Protective Behaviors: Considerations for Clinicians and Researchers

PubMed Central

Holloway, Ian W.; Dunlap, Shannon; del Pino, Homero E.; Hermanstyne, Keith; Pulsipher, Craig; Landovitz, Raphael J.

2014-01-01

Online social networking refers to the use of internet-based technologies that facilitate connection and communication between users. These platforms may be accessed via computer or mobile device (e.g., tablet, smartphone); communication between users may include linking of profiles, posting of text, photo and video content, instant messaging and email. This review provides an overview of recent research on the relationship between online social networking and sexual risk and protective behaviors with a focus on use of social networking sites (SNS) among young people and populations at high risk for sexually transmitted infections (STIs). While findings are mixed, the widespread use of SNS for sexual communication and partner seeking presents opportunities for the delivery and evaluation of public health interventions. Results of SNS-based interventions to reduce sexual risk are synthesized in order to offer hands-on advice for clinicians and researchers interested in engaging patients and study participants via online social networking. PMID:25642408

Learning in depth with the bespoke rubric-supported online poster presentation

NASA Astrophysics Data System (ADS)

Lajevardipour, Alireza; Wood, Andrew

2017-08-01

In our course of Biomedical Imaging, we introduced a research project as an assignment that included an online poster presentation. To assess the assignment, an adjusted criteria sheet was created, where it facilitated providing students with an effective feedback linked to particular criteria. Students are expected to produce a scientific poster to present the result of their investigation and upload it to an online discussion board. In addition, they are required to read their colleagues' works and provide peer-feedback by asking quality questions about principles and results, also on-line. Subtle distribution of marks in the rubric balances focus between preparing poster and providing peer-feedbacks.

Does Posting Facebook Status Updates Increase or Decrease Loneliness? An Online Social Networking Experiment

PubMed Central

Deters, Fenne große; Mehl, Matthias R.

2013-01-01

Online social networking is a pervasive but empirically understudied phenomenon. Strong public opinions on its consequences exist but are backed up by little empirical evidence and almost no causally-conclusive, experimental research. The current study tested the psychological effects of posting status updates on Facebook using an experimental design. For one week, participants in the experimental condition were asked to post more than they usually do, whereas participants in the control condition received no instructions. Participants added a lab “Research Profile” as a Facebook friend allowing for the objective documentation of protocol compliance, participants’ status updates, and friends’ responses. Results revealed (1) that the experimentally-induced increase in status updating activity reduced loneliness, (2) that the decrease in loneliness was due to participants feeling more connected to their friends on a daily basis and (3) that the effect of posting on loneliness was independent of direct social feedback (i.e. responses) by friends. PMID:24224070

BIDDSAT: visualizing the content of biodiversity data publishers in the Global Biodiversity Information Facility network.

PubMed

Otegui, Javier; Ariño, Arturo H

2012-08-15

In any data quality workflow, data publishers must become aware of issues in their data so these can be corrected. User feedback mechanisms provide one avenue, while global assessments of datasets provide another. To date, there is no publicly available tool to allow both biodiversity data institutions sharing their data through the Global Biodiversity Information Facility network and its potential users to assess datasets as a whole. Contributing to bridge this gap both for publishers and users, we introduce BIoDiversity DataSets Assessment Tool, an online tool that enables selected diagnostic visualizations on the content of data publishers and/or their individual collections. The online application is accessible at http://www.unav.es/unzyec/mzna/biddsat/ and is supported by all major browsers. The source code is licensed under the GNU GPLv3 license (http://www.gnu.org/licenses/gpl-3.0.txt) and is available at https://github.com/jotegui/BIDDSAT.

Managing Trust in Online Social Networks

NASA Astrophysics Data System (ADS)

Bhuiyan, Touhid; Josang, Audun; Xu, Yue

In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Zhang, Huaguang; Lin, Chong

2016-01-01

This paper focuses on the problem of adaptive neural network (NN) control for a class of nonlinear nonstrict-feedback systems via output feedback. A novel adaptive NN backstepping output-feedback control approach is first proposed for nonlinear nonstrict-feedback systems. The monotonicity of system bounding functions and the structure character of radial basis function (RBF) NNs are used to overcome the difficulties that arise from nonstrict-feedback structure. A state observer is constructed to estimate the immeasurable state variables. By combining adaptive backstepping technique with approximation capability of radial basis function NNs, an output-feedback adaptive NN controller is designed through backstepping approach. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. Two examples are used to illustrate the effectiveness of the proposed approach.

Students Reflecting on Test Performance and Feedback: An On-Line Approach

ERIC Educational Resources Information Center

Fyfe, Georgina; Fyfe, Sue; Meyer, Jan; Ziman, Mel; Sanders, Kathy; Hill, Julie

2014-01-01

Undergraduate students accessing on-line tests in Human Biology in three Western Australian universities were asked to complete an on-line post-test reflective survey about their perceptions of their test performance in light of automated feedback. The survey allowed pre-determined choices and comment text boxes relating to students' perceptions…

What Makes Learners Share Feedback or Not in an Online Community for Education

ERIC Educational Resources Information Center

Budu, Joseph

2018-01-01

Some higher education institutions create online communities to achieve engagement between teachers and learners. Unfortunately, some members seem to prefer sharing feedback via offline means instead of doing so in the online community. From qualitative data collected via flashcards, this article has found that this preference is largely due to…

How Does Early Feedback in an Online Programming Course Change Problem Solving?

ERIC Educational Resources Information Center

Ebrahimi, Alireza

2012-01-01

How does early feedback change the programming problem solving in an online environment and help students choose correct approaches? This study was conducted in a sample of students learning programming in an online course entitled Introduction to C++ and OOP (Object Oriented Programming) using the ANGEL learning management system platform. My…

The Antecedents, Objects, and Consequents of User Trust in Location-Based Social Networks

ERIC Educational Resources Information Center

Russo, Paul

2012-01-01

Online social networks provide rich opportunities to interact with friends and other online community members. At the same time, the addition of emerging location-sharing technologies--which broadcast a user's location online, including who they are with and what is happening nearby--is creating new dimensions to the types of interactions…

An information spreading model based on online social networks

NASA Astrophysics Data System (ADS)

Wang, Tao; He, Juanjuan; Wang, Xiaoxia

2018-01-01

Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

Geographies of an Online Social Network.

PubMed

Lengyel, Balázs; Varga, Attila; Ságvári, Bence; Jakobi, Ákos; Kertész, János

2015-01-01

How is online social media activity structured in the geographical space? Recent studies have shown that in spite of earlier visions about the "death of distance", physical proximity is still a major factor in social tie formation and maintenance in virtual social networks. Yet, it is unclear, what are the characteristics of the distance dependence in online social networks. In order to explore this issue the complete network of the former major Hungarian online social network is analyzed. We find that the distance dependence is weaker for the online social network ties than what was found earlier for phone communication networks. For a further analysis we introduced a coarser granularity: We identified the settlements with the nodes of a network and assigned two kinds of weights to the links between them. When the weights are proportional to the number of contacts we observed weakly formed, but spatially based modules resemble to the borders of macro-regions, the highest level of regional administration in the country. If the weights are defined relative to an uncorrelated null model, the next level of administrative regions, counties are reflected.

Geographies of an Online Social Network

PubMed Central

Lengyel, Balázs; Varga, Attila; Ságvári, Bence; Jakobi, Ákos; Kertész, János

2015-01-01

How is online social media activity structured in the geographical space? Recent studies have shown that in spite of earlier visions about the “death of distance”, physical proximity is still a major factor in social tie formation and maintenance in virtual social networks. Yet, it is unclear, what are the characteristics of the distance dependence in online social networks. In order to explore this issue the complete network of the former major Hungarian online social network is analyzed. We find that the distance dependence is weaker for the online social network ties than what was found earlier for phone communication networks. For a further analysis we introduced a coarser granularity: We identified the settlements with the nodes of a network and assigned two kinds of weights to the links between them. When the weights are proportional to the number of contacts we observed weakly formed, but spatially based modules resemble to the borders of macro-regions, the highest level of regional administration in the country. If the weights are defined relative to an uncorrelated null model, the next level of administrative regions, counties are reflected. PMID:26359668

Development of and feedback on a fully automated virtual reality system for online training in weight management skills.

PubMed

Thomas, J Graham; Spitalnick, Josh S; Hadley, Wendy; Bond, Dale S; Wing, Rena R

2015-01-01

Virtual reality (VR) technology can provide a safe environment for observing, learning, and practicing use of behavioral weight management skills, which could be particularly useful in enhancing minimal contact online weight management programs. The Experience Success (ES) project developed a system for creating and deploying VR scenarios for online weight management skills training. Virtual environments populated with virtual actors allow users to experiment with implementing behavioral skills via a PC-based point and click interface. A culturally sensitive virtual coach guides the experience, including planning for real-world skill use. Thirty-seven overweight/obese women provided feedback on a test scenario focused on social eating situations. They reported that the scenario gave them greater skills, confidence, and commitment for controlling eating in social situations. © 2014 Diabetes Technology Society.

Development of and Feedback on a Fully Automated Virtual Reality System for Online Training in Weight Management Skills

PubMed Central

Spitalnick, Josh S.; Hadley, Wendy; Bond, Dale S.; Wing, Rena R.

2014-01-01

Virtual reality (VR) technology can provide a safe environment for observing, learning, and practicing use of behavioral weight management skills, which could be particularly useful in enhancing minimal contact online weight management programs. The Experience Success (ES) project developed a system for creating and deploying VR scenarios for online weight management skills training. Virtual environments populated with virtual actors allow users to experiment with implementing behavioral skills via a PC-based point and click interface. A culturally sensitive virtual coach guides the experience, including planning for real-world skill use. Thirty-seven overweight/obese women provided feedback on a test scenario focused on social eating situations. They reported that the scenario gave them greater skills, confidence, and commitment for controlling eating in social situations. PMID:25367014

Executive Summaries: CIL '90.

ERIC Educational Resources Information Center

Elsweiler, John A., Jr.; And Others

1990-01-01

Presents summaries of 12 papers presented at the 1990 Computers in Libraries Conference. Topics discussed include online searching; microcomputer-based serials management; microcomputer-based workstations; online public access catalogs (OPACs); multitype library networking; CD-ROM searches; locally mounted online databases; collection evaluation;…

Modulation of dynamic modes by interplay between positive and negative feedback loops in gene regulatory networks

NASA Astrophysics Data System (ADS)

Wang, Liu-Suo; Li, Ning-Xi; Chen, Jing-Jia; Zhang, Xiao-Peng; Liu, Feng; Wang, Wei

2018-04-01

A positive and a negative feedback loop can induce bistability and oscillation, respectively, in biological networks. Nevertheless, they are frequently interlinked to perform more elaborate functions in many gene regulatory networks. Coupled positive and negative feedback loops may exhibit either oscillation or bistability depending on the intensity of the stimulus in some particular networks. It is less understood how the transition between the two dynamic modes is modulated by the positive and negative feedback loops. We developed an abstract model of such systems, largely based on the core p53 pathway, to explore the mechanism for the transformation of dynamic behaviors. Our results show that enhancing the positive feedback may promote or suppress oscillations depending on the strength of both feedback loops. We found that the system oscillates with low amplitudes in response to a moderate stimulus and switches to the on state upon a strong stimulus. When the positive feedback is activated much later than the negative one in response to a strong stimulus, the system exhibits long-term oscillations before switching to the on state. We explain this intriguing phenomenon using quasistatic approximation. Moreover, early switching to the on state may occur when the system starts from a steady state in the absence of stimuli. The interplay between the positive and negative feedback plays a key role in the transitions between oscillation and bistability. Of note, our conclusions should be applicable only to some specific gene regulatory networks, especially the p53 network, in which both oscillation and bistability exist in response to a certain type of stimulus. Our work also underscores the significance of transient dynamics in determining cellular outcome.

Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning.

PubMed

Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai

2014-07-01

In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Managing Written and Oral Negative Feedback in a Synchronous Online Teaching Situation

ERIC Educational Resources Information Center

Guichon, Nicolas; Betrancourt, Mireille; Prie, Yannick

2012-01-01

This case study focuses on the feedback that is provided by tutors to learners in the course of synchronous online teaching. More specifically, we study how trainee tutors used the affordances of Visu, an experimental web videoconferencing system, to provide negative feedback. Visu features classical functionalities such as video and chat, and it…

From "Hello" to Higher-Order Thinking: The Effect of Coaching and Feedback on Online Chats

ERIC Educational Resources Information Center

Stein, David S.; Wanstreet, Constance E.; Slagle, Paula; Trinko, Lynn A.; Lutz, Michelle

2013-01-01

This exploratory study examined the effect of a coaching and feedback intervention in teaching presence and social presence on higher-order thinking in an online community of inquiry. Coaching occurred before each chat, and feedback was provided immediately afterwards. The findings suggest that over time, the frequency of higher-order thinking…

Enhancing the Assessment Experience: Improving Student Perceptions, Engagement and Understanding Using Online Video Feedback

ERIC Educational Resources Information Center

West, John; Turner, Will

2016-01-01

Individualised video screencasts with accompanying narration were used to provide assessment feedback to a large number (n = 299) of first-year Bachelor of Education students at Edith Cowan University in Western Australia. An anonymous online survey revealed that nearly three times as many respondents (61%) preferred video feedback to written…

Attitudes towards Online Feedback on Writing: Why Students Mistrust the Learning Potential of Models

ERIC Educational Resources Information Center

Strobl, Carola

2015-01-01

This exploratory study sheds new light on students' perceptions of online feedback types for a complex writing task, summary writing from spoken input in a foreign language (L2), and investigates how these correlate with their actual learning to write. Students tend to favour clear-cut, instructivist rather than constructivist feedback, and guided…

A Comparison of Text, Voice, and Screencasting Feedback to Online Students

ERIC Educational Resources Information Center

Orlando, John

2016-01-01

The emergence of simple video and voice recording software has allowed faculty to deliver online course content in a variety of rich formats. But most faculty are still using traditional text comments for feedback to students. The author launched a study comparing student and faculty perceptions of text, voice, and screencasting feedback. The…

Health on the Web: Randomised Controlled Trial of Online Screening and Brief Alcohol Intervention Delivered in a Workplace Setting

PubMed Central

Khadjesari, Zarnie; Freemantle, Nick; Linke, Stuart; Hunter, Rachael; Murray, Elizabeth

2014-01-01

Background Alcohol misuse in England costs around £7.3 billion (US$12.2 billion) annually from lost productivity and absenteeism. Delivering brief alcohol interventions to employees as part of a health check may be acceptable, particularly with online delivery which can provide privacy for this stigmatised behaviour. Research to support this approach is limited and methodologically weak. The aim was to determine the effectiveness of online screening and personalised feedback on alcohol consumption, delivered in a workplace as part of a health check. Methods and Findings This two-group online individually randomised controlled trial recruited employees from a UK-based private sector organisation (approx. 100,000 employees). 3,375 employees completed the online health check in the three week recruitment period. Of these, 1,330 (39%) scored five or more on the AUDIT-C (indicating alcohol misuse) and were randomised to receive personalised feedback on their alcohol intake, alongside feedback on other health behaviours (n = 659), or to receive feedback on all health behaviours except alcohol intake (n = 671). Participants were mostly male (75%), with a median age of 48 years and half were in managerial positions (55%). Median Body Mass Index was 26, 12% were smokers, median time undertaking moderate/vigorous physical activity a week was 173 minutes and median fruit and vegetable consumption was three portions a day. Eighty percent (n = 1,066) of participants completed follow-up questionnaires at three months. An intention to treat analysis found no difference between experimental groups for past week drinking (primary outcome) (5.6% increase associated with the intervention (95% CI −4.7% to 16.9%; p = .30)), AUDIT (measure of alcohol-related harm) and health utility (EQ-5D). Conclusions There was no evidence to support the use of personalised feedback within an online health check for reducing alcohol consumption among employees in this organisation. Further research is needed on how to engage a larger proportion of employees in screening. Trial Registration International Standard Randomised Controlled Trial Number Register ISRCTN50658915 PMID:25409454

Closed-loop control of a fragile network: application to seizure-like dynamics of an epilepsy model

PubMed Central

Ehrens, Daniel; Sritharan, Duluxan; Sarma, Sridevi V.

2015-01-01

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Closed-loop therapy could therefore entail detecting when the network goes unstable, and then stimulating with an exogenous current to stabilize the network. In this study, a non-linear stochastic model of a neuronal network was used to simulate both seizure and non-seizure activity. In particular, synaptic weights between neurons were chosen such that the network's fixed point is stable during non-seizure periods, and a subset of these connections (the most fragile) were perturbed to make the same fixed point unstable to model seizure events; and, the model randomly transitions between these two modes. The goal of this study was to measure spike train observations from this epileptic network and then apply a feedback controller that (i) detects when the network goes unstable, and then (ii) applies a state-feedback gain control input to the network to stabilize it. The stability detector is based on a 2-state (stable, unstable) hidden Markov model (HMM) of the network, and detects the transition from the stable mode to the unstable mode from using the firing rate of the most fragile node in the network (which is the output of the HMM). When the unstable mode is detected, a state-feedback gain is applied to generate a control input to the fragile node bringing the network back to the stable mode. Finally, when the network is detected as stable again, the feedback control input is switched off. High performance was achieved for the stability detector, and feedback control suppressed seizures within 2 s after onset. PMID:25784851

Convergence and objective functions of some fault/noise-injection-based online learning algorithms for RBF networks.

PubMed

Ho, Kevin I-J; Leung, Chi-Sing; Sum, John

2010-06-01

In the last two decades, many online fault/noise injection algorithms have been developed to attain a fault tolerant neural network. However, not much theoretical works related to their convergence and objective functions have been reported. This paper studies six common fault/noise-injection-based online learning algorithms for radial basis function (RBF) networks, namely 1) injecting additive input noise, 2) injecting additive/multiplicative weight noise, 3) injecting multiplicative node noise, 4) injecting multiweight fault (random disconnection of weights), 5) injecting multinode fault during training, and 6) weight decay with injecting multinode fault. Based on the Gladyshev theorem, we show that the convergence of these six online algorithms is almost sure. Moreover, their true objective functions being minimized are derived. For injecting additive input noise during training, the objective function is identical to that of the Tikhonov regularizer approach. For injecting additive/multiplicative weight noise during training, the objective function is the simple mean square training error. Thus, injecting additive/multiplicative weight noise during training cannot improve the fault tolerance of an RBF network. Similar to injective additive input noise, the objective functions of other fault/noise-injection-based online algorithms contain a mean square error term and a specialized regularization term.

Nursing Librarians Cultivating Evidence-Based Practice Through an Asynchronous Online Course.

PubMed

Mears, Kim; Blake, Lindsay

2017-09-01

In response to a request from the Nursing Shared Governance Evidence-Based Practice Council, librarians created an online evidence-based practice (EBP) continuing education course for clinical nurses. The curriculum was adapted from a previously created face-to-face course and was offered online through a learning management system. Although many nurses registered for the course, only a small sample was able to complete all modules. Feedback revealed that nurses appreciated the ease of online use, but they experienced technical barriers. Overall, nurses completing the course agreed that all learning objectives were met. An online asynchronous course for nurses is a viable option for teaching EBP, but hospital computer limitations must be taken into account to allow for participants' full immersion into the material. J Contin Educ Nurs. 2017;48(9):420-424. Copyright 2017, SLACK Incorporated.

Predicting the global spread range via small subnetworks

NASA Astrophysics Data System (ADS)

Sun, Jiachen; Dong, Junyou; Ma, Xiao; Feng, Ling; Hu, Yanqing

2017-04-01

Modern online social network platforms are replacing traditional media due to their effectiveness in both spreading information and communicating opinions. One of the key problems in these online platforms is to predict the global spread range of any given information. Due to its gigantic size as well as time-varying dynamics, an online social network's global structure, however, is usually inaccessible to most researchers. Thus, it raises the very important issue of how to use solely small subnetworks to predict the global influence. In this paper, based on percolation theory, we show that the global spread range can be predicted well from only two small subnetworks. We test our methods in an artificial network and three empirical online social networks, such as the full Sina Weibo network with 99546027 nodes.

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation

PubMed Central

Kwak, Doyeon

2017-01-01

It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks. PMID:28542367

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

PubMed

Kwak, Doyeon; Kim, Wonjoon

2017-01-01

It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study

NASA Astrophysics Data System (ADS)

Pfeil, Thomas; Jordan, Jakob; Tetzlaff, Tom; Grübl, Andreas; Schemmel, Johannes; Diesmann, Markus; Meier, Karlheinz

2016-04-01

High-level brain function, such as memory, classification, or reasoning, can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware constitutes a fast and energy-efficient substrate for the implementation of such neural computing architectures in technical applications and neuroscientific research. The functional performance of neural networks is often critically dependent on the level of correlations in the neural activity. In finite networks, correlations are typically inevitable due to shared presynaptic input. Recent theoretical studies have shown that inhibitory feedback, abundant in biological neural networks, can actively suppress these shared-input correlations and thereby enable neurons to fire nearly independently. For networks of spiking neurons, the decorrelating effect of inhibitory feedback has so far been explicitly demonstrated only for homogeneous networks of neurons with linear subthreshold dynamics. Theory, however, suggests that the effect is a general phenomenon, present in any system with sufficient inhibitory feedback, irrespective of the details of the network structure or the neuronal and synaptic properties. Here, we investigate the effect of network heterogeneity on correlations in sparse, random networks of inhibitory neurons with nonlinear, conductance-based synapses. Emulations of these networks on the analog neuromorphic-hardware system Spikey allow us to test the efficiency of decorrelation by inhibitory feedback in the presence of hardware-specific heterogeneities. The configurability of the hardware substrate enables us to modulate the extent of heterogeneity in a systematic manner. We selectively study the effects of shared input and recurrent connections on correlations in membrane potentials and spike trains. Our results confirm that shared-input correlations are actively suppressed by inhibitory feedback also in highly heterogeneous networks exhibiting broad, heavy-tailed firing-rate distributions. In line with former studies, cell heterogeneities reduce shared-input correlations. Overall, however, correlations in the recurrent system can increase with the level of heterogeneity as a consequence of diminished effective negative feedback.

Video-based peer feedback through social networking for robotic surgery simulation: a multicenter randomized controlled trial.

PubMed

Carter, Stacey C; Chiang, Alexander; Shah, Galaxy; Kwan, Lorna; Montgomery, Jeffrey S; Karam, Amer; Tarnay, Christopher; Guru, Khurshid A; Hu, Jim C

2015-05-01

To examine the feasibility and outcomes of video-based peer feedback through social networking to facilitate robotic surgical skill acquisition. The acquisition of surgical skills may be challenging for novel techniques and/or those with prolonged learning curves. Randomized controlled trial involving 41 resident physicians performing the Tubes (Da Vinci Intuitive Surgical, Sunnyvale, CA) simulator exercise with versus without peer feedback of video-recorded performance through a social networking Web page. Data collected included simulator exercise score, time to completion, and comfort and satisfaction with robotic surgery simulation. There were no baseline differences between the intervention group (n = 20) and controls (n = 21). The intervention group showed improvement in mean scores from session 1 to sessions 2 and 3 (60.7 vs 75.5, P < 0.001, and 60.7 vs 80.1, P < 0.001, respectively). The intervention group scored significantly higher than controls at sessions 2 and 3 (75.5 vs 59.6, P = 0.009, and 80.1 vs 65.9, P = 0.019, respectively). The mean time (seconds) to complete the task was shorter for the intervention group than for controls during sessions 2 and 3 (217.4 vs 279.0, P = 0.004, and 201.4 vs 261.9, P = 0.006, respectively). At the study conclusion, feedback subjects were more comfortable with robotic surgery than controls (90% vs 62%, P = 0.021) and expressed greater satisfaction with the learning experience (100% vs 67%, P = 0.014). Of the intervention subjects, 85% found that peer feedback was useful and 100% found it effective. Video-based peer feedback through social networking appears to be an effective paradigm for surgical education and accelerates the robotic surgery learning curve during simulation.

What do the Numbers Say? The Influence of Motivation and Peer Feedback on Students' Behaviour in Online Discussions

ERIC Educational Resources Information Center

Xie, Kui

2013-01-01

Students' non-posting behaviour in online discussions is often neglected in educational research. However, it can be a potential indicator of student learning. This study examined the relationships between motivation, peer feedback and students’ posting and non-posting behaviours in online discussions in a distance learning class. Fifty-seven…

Predictive Effects of Online Peer Feedback Types on Performance Quality

ERIC Educational Resources Information Center

Yu, Fu-Yun; Wu, Chun-Ping

2013-01-01

This study examined the individual and combined predictive effects of two types of feedback (i.e., quantitative ratings and descriptive comments) in online peer-assessment learning systems on the quality of produced work. A total of 233 students participated in the study for six weeks. An online learning system that allows students to contribute…

A Community of Inquiry-Based Framework for Civic Education at Universitas Terbuka, Indonesia

ERIC Educational Resources Information Center

Setiani, Made Yudhi; MacKinnon, Allan M.

2015-01-01

This study focused on the civic education course at Universitas Terbuka (UT). Its purpose was to design a new approach for the online tutorial for the course by analyzing the literature related to online and distance education and investigating participant feedback on the current offering of the course and tutorial, which is a compulsory course in…

Process Evaluation of the Boost-A™ Transition Planning Program for Adolescents on the Autism Spectrum: A Strengths-Based Approach

ERIC Educational Resources Information Center

Hatfield, Megan; Falkmer, Marita; Falkmer, Torbjörn; Ciccarelli, Marina

2018-01-01

A process evaluation was conducted to determine the effectiveness, usability, and barriers and facilitators related to the Better OutcOmes & Successful Transitions for Autism (BOOST-A™), an online transition planning program. Adolescents on the autism spectrum (n = 33) and their parents (n = 39) provided feedback via an online questionnaire.…

Neurocognitive therapeutics: from concept to application in the treatment of negative attention bias.

PubMed

Schnyer, David M; Beevers, Christopher G; deBettencourt, Megan T; Sherman, Stephanie M; Cohen, Jonathan D; Norman, Kenneth A; Turk-Browne, Nicholas B

2015-01-01

There is growing interest in the use of neuroimaging for the direct treatment of mental illness. Here, we present a new framework for such treatment, neurocognitive therapeutics. What distinguishes neurocognitive therapeutics from prior approaches is the use of precise brain-decoding techniques within a real-time feedback system, in order to adapt treatment online and tailor feedback to individuals' needs. We report an initial feasibility study that uses this framework to alter negative attention bias in a small number of patients experiencing significant mood symptoms. The results are consistent with the promise of neurocognitive therapeutics to improve mood symptoms and alter brain networks mediating attentional control. Future work should focus on optimizing the approach, validating its effectiveness, and expanding the scope of targeted disorders.

Practical Guidelines for Qualitative Research Using Online Forums

PubMed Central

Im, Eun-Ok; Chee, Wonshik

2012-01-01

With an increasing number of Internet research in general, the number of qualitative Internet studies has recently increased. Online forums are one of the most frequently used qualitative Internet research methods. Despite an increasing number of online forum studies, very few articles have been written to provide practical guidelines to conduct an online forum as a qualitative research method. In this paper, practical guidelines in using an online forum as a qualitative research method are proposed based on three previous online forum studies. First, the three studies are concisely described. Practical guidelines are proposed based on nine idea categories related to issues in the three studies: (a) a fit with research purpose and questions; (b) logistics; (c) electronic versus conventional informed consent process; (d) structure and functionality of online forums; (e) interdisciplinary team; (f) screening methods; (g) languages; (h) data analysis methods; and (i) getting participants’ feedback. PMID:22918135

Practical guidelines for qualitative research using online forums.

PubMed

Im, Eun-Ok; Chee, Wonshik

2012-11-01

With an increasing number of Internet research in general, the number of qualitative Internet studies has recently increased. Online forums are one of the most frequently used qualitative Internet research methods. Despite an increasing number of online forum studies, very few articles have been written to provide practical guidelines to conduct an online forum as a qualitative research method. In this article, practical guidelines in using an online forum as a qualitative research method are proposed based on three previous online forum studies. First, the three studies are concisely described. Practical guidelines are proposed based on nine idea categories related to issues in the three studies: (a) a fit with research purpose and questions, (b) logistics, (c) electronic versus conventional informed consent process, (d) structure and functionality of online forums, (e) interdisciplinary team, (f) screening methods, (g) languages, (h) data analysis methods, and (i) getting participants' feedback.

Effectiveness of an Asynchronous Online Module on University Students' Understanding of the Bohr Model of the Hydrogen Atom

NASA Astrophysics Data System (ADS)

Farina, William J.; Bodzin, Alec M.

2017-12-01

Web-based learning is a growing field in education, yet empirical research into the design of high quality Web-based university science instruction is scarce. A one-week asynchronous online module on the Bohr Model of the atom was developed and implemented guided by the knowledge integration framework. The unit design aligned with three identified metaprinciples of science learning: making science accessible, making thinking visible, and promoting autonomy. Students in an introductory chemistry course at a large east coast university completed either an online module or traditional classroom instruction. Data from 99 students were analyzed and results showed significant knowledge growth in both online and traditional formats. For the online learning group, findings revealed positive student perceptions of their learning experiences, highly positive feedback for online science learning, and an interest amongst students to learn chemistry within an online environment.

Network feedback regulates motor output across a range of modulatory neuron activity

PubMed Central

Spencer, Robert M.

2016-01-01

Modulatory projection neurons alter network neuron synaptic and intrinsic properties to elicit multiple different outputs. Sensory and other inputs elicit a range of modulatory neuron activity that is further shaped by network feedback, yet little is known regarding how the impact of network feedback on modulatory neurons regulates network output across a physiological range of modulatory neuron activity. Identified network neurons, a fully described connectome, and a well-characterized, identified modulatory projection neuron enabled us to address this issue in the crab (Cancer borealis) stomatogastric nervous system. The modulatory neuron modulatory commissural neuron 1 (MCN1) activates and modulates two networks that generate rhythms via different cellular mechanisms and at distinct frequencies. MCN1 is activated at rates of 5–35 Hz in vivo and in vitro. Additionally, network feedback elicits MCN1 activity time-locked to motor activity. We asked how network activation, rhythm speed, and neuron activity levels are regulated by the presence or absence of network feedback across a physiological range of MCN1 activity rates. There were both similarities and differences in responses of the two networks to MCN1 activity. Many parameters in both networks were sensitive to network feedback effects on MCN1 activity. However, for most parameters, MCN1 activity rate did not determine the extent to which network output was altered by the addition of network feedback. These data demonstrate that the influence of network feedback on modulatory neuron activity is an important determinant of network output and feedback can be effective in shaping network output regardless of the extent of network modulation. PMID:27030739

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

PubMed

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

Online matchmaking: It's not just for dating sites anymore! Connecting the Climate Voices Science Speakers Network to Educators

NASA Astrophysics Data System (ADS)

Wegner, K.; Herrin, S.; Schmidt, C.

2015-12-01

Scientists play an integral role in the development of climate literacy skills - for both teachers and students alike. By partnering with local scientists, teachers can gain valuable insights into the science practices highlighted by the Next Generation Science Standards (NGSS), as well as a deeper understanding of cutting-edge scientific discoveries and local impacts of climate change. For students, connecting to local scientists can provide a relevant connection to climate science and STEM skills. Over the past two years, the Climate Voices Science Speakers Network (climatevoices.org) has grown to a robust network of nearly 400 climate science speakers across the United States. Formal and informal educators, K-12 students, and community groups connect with our speakers through our interactive map-based website and invite them to meet through face-to-face and virtual presentations, such as webinars and podcasts. But creating a common language between scientists and educators requires coaching on both sides. In this presentation, we will present the "nitty-gritty" of setting up scientist-educator collaborations, as well as the challenges and opportunities that arise from these partnerships. We will share the impact of these collaborations through case studies, including anecdotal feedback and metrics.

Online Matchmaking: It's Not Just for Dating Sites Anymore! Connecting the Climate Voices Science Speakers Network to Educators

NASA Technical Reports Server (NTRS)

Wegner, Kristin; Herrin, Sara; Schmidt, Cynthia

2015-01-01

Scientists play an integral role in the development of climate literacy skills - for both teachers and students alike. By partnering with local scientists, teachers can gain valuable insights into the science practices highlighted by the Next Generation Science Standards (NGSS), as well as a deeper understanding of cutting-edge scientific discoveries and local impacts of climate change. For students, connecting to local scientists can provide a relevant connection to climate science and STEM skills. Over the past two years, the Climate Voices Science Speakers Network (climatevoices.org) has grown to a robust network of nearly 400 climate science speakers across the United States. Formal and informal educators, K-12 students, and community groups connect with our speakers through our interactive map-based website and invite them to meet through face-to-face and virtual presentations, such as webinars and podcasts. But creating a common language between scientists and educators requires coaching on both sides. In this presentation, we will present the "nitty-gritty" of setting up scientist-educator collaborations, as well as the challenges and opportunities that arise from these partnerships. We will share the impact of these collaborations through case studies, including anecdotal feedback and metrics.

User preferences for a text message-based smoking cessation intervention.

PubMed

Bock, Beth C; Heron, Kristin E; Jennings, Ernestine G; Magee, Joshua C; Morrow, Kathleen M

2013-04-01

Younger adults are more likely to smoke and less likely to seek treatment than older smokers. They are also frequent users of communication technology. In the current study, we conducted focus groups to obtain feedback about preferences for a text message-based smoking cessation program from potential users. Participants (N = 21, M age = 25.6 years, age range = 20-33 years) were current or recently quit smokers (M cigarettes/day = 12.8) who used text messaging. Participants completed questionnaires and participated in a 2-hour focus group. Focus groups were conducted using an a priori semistructured interview guide to promote discussion of the content and functionality of the intervention. Major themes from analysis of the focus groups included support for the acceptability of a text-based cessation program, suggestions for a more technologically broad-based program, and adjustments to the program structure. Participants recommended including social networking functions, user control of program output through an online profile, and text message features to promote interaction with the system. Interestingly, many participants suggested the program should begin on individuals' identified quit day, challenging the procedures used in most cessation programs, which begin by preparing participants for a future quit date. Overall, younger adult smokers appear to be interested in participating in a smoking cessation program that uses text messages and web-based elements. Qualitative feedback regarding the perceived optimal features and structure of a technology-based intervention challenged traditional methods of implementing smoking cessation interventions and will inform the development of future programs.

Research and Teaching: Exploring the Use of an Online Quiz Game to Provide Formative Feedback in a Large-Enrollment, Introductory Biochemistry Course

ERIC Educational Resources Information Center

Milner, Rachel; Parrish, Jonathan; Wright, Adrienne; Gnarpe, Judy; Keenan, Louanne

2015-01-01

In a large-enrollment, introductory biochemistry course for nonmajors, the authors provide students with formative feedback through practice questions in PDF format. Recently, they investigated possible benefits of providing the practice questions via an online game (Brainspan). Participants were randomly assigned to either the online game group…

Online Formative Assessments in a Digital Signal Processing Course: Effects of Feedback Type and Content Difficulty on Students Learning Achievements

ERIC Educational Resources Information Center

Petrovic, J.; Pale, P.; Jeren, B.

2017-01-01

This study aimed to investigate the effects of using online formative assessments on students' learning achievements. Using a quasi-experimental study design with one control group (no formative assessments available), and two experimental groups receiving feedback in available online formative assessments (knowledge of the correct response--KCR,…

Effects of Online Sensory Feedback Restriction during the Training on Immediate and Long-Term Learning on a Finger Opposition Tapping Task

ERIC Educational Resources Information Center

Piemonte, Maria Elisa Pimentel; Kopczynski, Marcos Cammarosano; Voos, Mariana Callil; Miranda, Camila Souza; Oliveira, Tatiana de Paula

2015-01-01

Background: Online sensory feedback has been considered fundamental for motor learning. The sensory inputs experienced in previous attempts can be processed and compared to allow the online refinement of subsequent attempts, resulting on performance improvement. However, numerous studies have provided direct and indirect evidence that learning new…

Improved methods in neural network-based adaptive output feedback control, with applications to flight control

NASA Astrophysics Data System (ADS)

Kim, Nakwan

Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

Characterizing Communication Networks in a Web-Based Classroom: Cognitive Styles and Linguistic Behavior of Self-Organizing Groups in Online Discussions

ERIC Educational Resources Information Center

Vercellone-Smith, Pamela; Jablokow, Kathryn; Friedel, Curtis

2012-01-01

In this study, we explore the cognitive style profiles and linguistic patterns of self-organizing groups within a web-based graduate education course to determine how cognitive preferences and individual behaviors influence the patterns of information exchange and the formation of communication hierarchies in an online classroom. Network analysis…

Adaptive control of nonlinear system using online error minimum neural networks.

PubMed

Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

2016-11-01

In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Simulating Social Networks of Online Communities: Simulation as a Method for Sociability Design

NASA Astrophysics Data System (ADS)

Ang, Chee Siang; Zaphiris, Panayiotis

We propose the use of social simulations to study and support the design of online communities. In this paper, we developed an Agent-Based Model (ABM) to simulate and study the formation of social networks in a Massively Multiplayer Online Role Playing Game (MMORPG) guild community. We first analyzed the activities and the social network (who-interacts-with-whom) of an existing guild community to identify its interaction patterns and characteristics. Then, based on the empirical results, we derived and formalized the interaction rules, which were implemented in our simulation. Using the simulation, we reproduced the observed social network of the guild community as a means of validation. The simulation was then used to examine how various parameters of the community (e.g. the level of activity, the number of neighbors of each agent, etc) could potentially influence the characteristic of the social networks.

The Influence of Adult Learners' Self-Directed Learning Readiness and Network Literacy on Online Learning Effectiveness: A Study of Civil Servants in Taiwan

ERIC Educational Resources Information Center

Lai, Horng-Ji

2011-01-01

This study examined the effect of civil servants' Self-Directed Learning Readiness (SDLR) and network literacy on their online learning effectiveness in a web-based training program. Participants were 283 civil servants enrolled in an asynchronous online learning program through an e-learning portal provided by the Regional Civil Service…

A Randomized Controlled Trial Testing the Efficacy of a Brief Online Alcohol Intervention for High School Seniors.

PubMed

Doumas, Diana M; Esp, Susan; Flay, Brian; Bond, Laura

2017-09-01

The purpose of this randomized controlled study was to examine the efficacy of a brief, web-based personalized feedback intervention (the eCHECKUP TO GO) on alcohol use and alcohol-related consequences among high school seniors. Participants (n = 221) were high school seniors randomized by class period to either a brief, web-based personalized feedback intervention (the eCHECKUP TO GO) or an assessment-only control group. Participants completed online surveys at baseline and at a 6-week follow-up. Students participating in the eCHECKUP TO GO intervention reported a significant reduction in weekly drinking quantity, peak drinking quantity, and frequency of drinking to intoxication relative to those in the control group. Intervention effects were moderated by high-risk status (one or more episodes of heavy episodic drinking in the past 2 weeks reported at baseline) such that intervention effects were significant for high-risk students only. Results for alcohol-related consequences were not significant. Providing a brief, web-based personalized feedback intervention in the school setting is a promising approach for reducing problem alcohol use among high school seniors who report recent heavy episodic drinking.

Developing young adults' representational competence through infographic-based science news reporting

NASA Astrophysics Data System (ADS)

Gebre, Engida H.; Polman, Joseph L.

2016-12-01

This study presents descriptive analysis of young adults' use of multiple representations in the context of science news reporting. Across one semester, 71 high school students, in a socioeconomically diverse suburban secondary school in Midwestern United States, participated in activities of researching science topics of their choice and producing infographic-based science news for possible online publication. An external editor reviewed their draft infographics and provided comments for subsequent revision. Students also provided peer feedback to the draft version of infographics using an online commentary tool. We analysed the nature of representations students used as well as the comments from peer and the editor feedback. Results showed both students' capabilities and challenges in learning with representations in this context. Students frequently rely on using certain kinds of representations that are depictive in nature, and supporting their progress towards using more abstract representations requires special attention and identifying learning gaps. Results also showed that students were able to determine representational adequacy in the context of providing peer feedback. The study has implication for research and instruction using infographics as expressive tools to support learning.

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

NASA Astrophysics Data System (ADS)

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-10-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

Network feedback regulates motor output across a range of modulatory neuron activity.

PubMed

Spencer, Robert M; Blitz, Dawn M

2016-06-01

Modulatory projection neurons alter network neuron synaptic and intrinsic properties to elicit multiple different outputs. Sensory and other inputs elicit a range of modulatory neuron activity that is further shaped by network feedback, yet little is known regarding how the impact of network feedback on modulatory neurons regulates network output across a physiological range of modulatory neuron activity. Identified network neurons, a fully described connectome, and a well-characterized, identified modulatory projection neuron enabled us to address this issue in the crab (Cancer borealis) stomatogastric nervous system. The modulatory neuron modulatory commissural neuron 1 (MCN1) activates and modulates two networks that generate rhythms via different cellular mechanisms and at distinct frequencies. MCN1 is activated at rates of 5-35 Hz in vivo and in vitro. Additionally, network feedback elicits MCN1 activity time-locked to motor activity. We asked how network activation, rhythm speed, and neuron activity levels are regulated by the presence or absence of network feedback across a physiological range of MCN1 activity rates. There were both similarities and differences in responses of the two networks to MCN1 activity. Many parameters in both networks were sensitive to network feedback effects on MCN1 activity. However, for most parameters, MCN1 activity rate did not determine the extent to which network output was altered by the addition of network feedback. These data demonstrate that the influence of network feedback on modulatory neuron activity is an important determinant of network output and feedback can be effective in shaping network output regardless of the extent of network modulation. Copyright © 2016 the American Physiological Society.

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

PubMed

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

Characterization of Combustion Dynamics, Detection, and Prevention of an Unstable Combustion State Based on a Complex-Network Theory

NASA Astrophysics Data System (ADS)

Gotoda, Hiroshi; Kinugawa, Hikaru; Tsujimoto, Ryosuke; Domen, Shohei; Okuno, Yuta

2017-04-01

Complex-network theory has attracted considerable attention for nearly a decade, and it enables us to encompass our understanding of nonlinear dynamics in complex systems in a wide range of fields, including applied physics and mechanical, chemical, and electrical engineering. We conduct an experimental study using a pragmatic online detection methodology based on complex-network theory to prevent a limiting unstable state such as blowout in a confined turbulent combustion system. This study introduces a modified version of the natural visibility algorithm based on the idea of a visibility limit to serve as a pragmatic online detector. The average degree of the modified version of the natural visibility graph allows us to detect the onset of blowout, resulting in online prevention.

Popular Social Media as a Tool for Enhancing Community-Based End-of-Life Care Education for Healthcare Professionals: A Formative Study

ERIC Educational Resources Information Center

Hirakawa, Yoshihisa; Uemura, Mayu Yasuda; Chiang, Chifa; Aoyama, Atsuko

2018-01-01

The purpose of this study is twofold: to assess the acceptance and usefulness of Nagoya University Small Private Online Courses, which is an online end-of-life care educational program through popular social media designed to supplement traditional end-of-life care education among healthcare professionals and to get constructive feedback with the…

"Picturing Them Right in Front of Me": Guidelines for Implementing Video Communication in Online and Blended Learning

ERIC Educational Resources Information Center

West, Richard E.; Jay, Jason; Armstrong, Matt; Borup, Jered

2017-01-01

We provide actionable strategies that teachers can follow when implementing asynchronous video communication and feedback in their own courses. These strategies are based on our own research over many years in the use of asynchronous video in online teaching, as well as our review of the literature, and are provided to foster greater discussion on…

Information filtering on coupled social networks.

PubMed

Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui

2014-01-01

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.

'Silk Road', the virtual drug marketplace: a single case study of user experiences.

PubMed

Van Hout, Marie Claire; Bingham, Tim

2013-09-01

The online promotion of 'drug shopping' and user information networks is of increasing public health and law enforcement concern. An online drug marketplace called 'Silk Road' has been operating on the 'Deep Web' since February 2011 and was designed to revolutionise contemporary drug consumerism. A single case study approach explored a 'Silk Road' user's motives for online drug purchasing, experiences of accessing and using the website, drug information sourcing, decision making and purchasing, outcomes and settings for use, and perspectives around security. The participant was recruited following a lengthy relationship building phase on the 'Silk Road' chat forum. The male participant described his motives, experiences of purchasing processes and drugs used from 'Silk Road'. Consumer experiences on 'Silk Road' were described as 'euphoric' due to the wide choice of drugs available, relatively easy once navigating the Tor Browser (encryption software) and using 'Bitcoins' for transactions, and perceived as safer than negotiating illicit drug markets. Online researching of drug outcomes, particularly for new psychoactive substances was reported. Relationships between vendors and consumers were described as based on cyber levels of trust and professionalism, and supported by 'stealth modes', user feedback and resolution modes. The reality of his drug use was described as covert and solitary with psychonautic characteristics, which contrasted with his membership, participation and feelings of safety within the 'Silk Road' community. 'Silk Road' as online drug marketplace presents an interesting displacement away from 'traditional' online and street sources of drug supply. Member support and harm reduction ethos within this virtual community maximises consumer decision-making and positive drug experiences, and minimises potential harms and consumer perceived risks. Future research is necessary to explore experiences and backgrounds of other users. Copyright © 2013 Elsevier B.V. All rights reserved.

Effect of Temperature on Synthetic Positive and Negative Feedback Gene Networks

NASA Astrophysics Data System (ADS)

Charlebois, Daniel A.; Marshall, Sylvia; Balazsi, Gabor

Synthetic biological systems are built and tested under well controlled laboratory conditions. How altering the environment, such as the ambient temperature affects their function is not well understood. To address this question for synthetic gene networks with positive and negative feedback, we used mathematical modeling coupled with experiments in the budding yeast Saccharomyces cerevisiae. We found that cellular growth rates and gene expression dose responses change significantly at temperatures above and below the physiological optimum for yeast. Gene expression distributions for the negative feedback-based circuit changed from unimodal to bimodal at high temperature, while the bifurcation point of the positive feedback circuit shifted up with temperature. These results demonstrate that synthetic gene network function is context-dependent. Temperature effects should thus be tested and incorporated into their design and validation for real-world applications. NSERC Postdoctoral Fellowship (Grant No. PDF-453977-2014).

Robust consensus control with guaranteed rate of convergence using second-order Hurwitz polynomials

NASA Astrophysics Data System (ADS)

Fruhnert, Michael; Corless, Martin

2017-10-01

This paper considers homogeneous networks of general, linear time-invariant, second-order systems. We consider linear feedback controllers and require that the directed graph associated with the network contains a spanning tree and systems are stabilisable. We show that consensus with a guaranteed rate of convergence can always be achieved using linear state feedback. To achieve this, we provide a new and simple derivation of the conditions for a second-order polynomial with complex coefficients to be Hurwitz. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. Based on the conditions found, methods to compute feedback gains are proposed. We show that gains can be chosen such that consensus is achieved robustly over a variety of communication structures and system dynamics. We also consider the use of static output feedback.

CPG-inspired workspace trajectory generation and adaptive locomotion control for quadruped robots.

PubMed

Liu, Chengju; Chen, Qijun; Wang, Danwei

2011-06-01

This paper deals with the locomotion control of quadruped robots inspired by the biological concept of central pattern generator (CPG). A control architecture is proposed with a 3-D workspace trajectory generator and a motion engine. The workspace trajectory generator generates adaptive workspace trajectories based on CPGs, and the motion engine realizes joint motion imputes. The proposed architecture is able to generate adaptive workspace trajectories online by tuning the parameters of the CPG network to adapt to various terrains. With feedback information, a quadruped robot can walk through various terrains with adaptive joint control signals. A quadruped platform AIBO is used to validate the proposed locomotion control system. The experimental results confirm the effectiveness of the proposed control architecture. A comparison by experiments shows the superiority of the proposed method against the traditional CPG-joint-space control method.

Predictive Effects of the Quality of Online Peer-Feedback Provided and Received on Primary School Students' Quality of Question-Generation

ERIC Educational Resources Information Center

Yu, Fu-Yun; Wu, Chun-Ping

2016-01-01

The research objectives of this study were to examine the individual and combined predictive effects of the quality of online peer-feedback provided and received on primary school students' quality of question-generation. A correlational study was adopted, and performance data from 213 fifth-grade students engaged in online question-generation and…

State feedback control design for Boolean networks.

PubMed

Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang

2016-08-26

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.

Incorporating user perspectives in the design of an online intervention tool for people with visible differences: face IT.

PubMed

Bessell, Alyson; Clarke, Alex; Harcourt, Diana; Moss, Tim P; Rumsey, Nichola

2010-10-01

Individuals with visible differences can experience social anxiety in relation to their appearance. Social skills-based psychosocial interventions have to date shown only limited effectiveness at addressing their concerns. To incorporate user perspectives in the development of an online psychosocial intervention, known as Face IT. Study one consisted of a needs assessment with 12 individuals with a visible difference and six health professionals in order to identify the difficulties experienced by those with visible difference and obtain feedback on the proposed content of Face IT. The findings demonstrated support for the social skills model and the use of an online intervention. Study two consisted of an empirical usability evaluation of Face IT with 14 potential users and 14 health professionals. Based on feedback from the participants, changes were made to the graphics and navigation of the programme. The clinical content has been made more acceptable. The findings indicate support for the importance of social skills-based psychosocial interventions for addressing the needs of those with a visible difference, and have allowed modifications to be made to Face IT ahead of a randomized controlled trial of effectiveness.

Incorporation of feedback during beat synchronization is an index of neural maturation and reading skills.

PubMed

Woodruff Carr, Kali; Fitzroy, Ahren B; Tierney, Adam; White-Schwoch, Travis; Kraus, Nina

2017-01-01

Speech communication involves integration and coordination of sensory perception and motor production, requiring precise temporal coupling. Beat synchronization, the coordination of movement with a pacing sound, can be used as an index of this sensorimotor timing. We assessed adolescents' synchronization and capacity to correct asynchronies when given online visual feedback. Variability of synchronization while receiving feedback predicted phonological memory and reading sub-skills, as well as maturation of cortical auditory processing; less variable synchronization during the presence of feedback tracked with maturation of cortical processing of sound onsets and resting gamma activity. We suggest the ability to incorporate feedback during synchronization is an index of intentional, multimodal timing-based integration in the maturing adolescent brain. Precision of temporal coding across modalities is important for speech processing and literacy skills that rely on dynamic interactions with sound. Synchronization employing feedback may prove useful as a remedial strategy for individuals who struggle with timing-based language learning impairments. Copyright © 2016 Elsevier Inc. All rights reserved.

Who Networks? The Social Psychology of Virtual Communities

DTIC Science & Technology

2004-06-01

virtual life: the open side - characterized by communities of interest, civil society movements, virtual “states,” and 4 online gaming communities...network of people hailing from Sicily. Sometimes the offline/ online similari- ties mesh even more, as when a gaming society in a small Swedish town...Commercially owned and regulated graphics-based Massively Multi- Player Gaming Communities (EverQuest, The Matrix Online ®, etc.) • UseNET

Effectiveness of Key Knowledge Spreader Identification in Online Communities of Practice: A Simulation Study from Network Perspective

ERIC Educational Resources Information Center

Cao, Yu

2017-01-01

With the rapid development of online communities of practice (CoPs), how to identify key knowledge spreader (KKS) in online CoPs has grown up to be a hot issue. In this paper, we construct a network with variable clustering based on Holme-Kim model to represent CoPs, a simple dynamics of knowledge sharing is considered. Kendall's Tau coefficient…

Improving health care professionals' feedback on communication skills: development of an on-line resource.

PubMed

Harrison, Gill; Hayden, Sheila; Cook, Viv; Cushing, Annie

2012-09-01

This project aimed to develop an open-access on-line resource to assist health care professionals in providing effective feedback on patient-centered clinical and communication skills. The collaborative nature of the development of this learning resource is outlined and evaluation of its use is discussed. An inter-professional team of teaching staff from two London Universities employed a researcher to interview experienced clinical and academic health care professionals and gather examples of difficult feedback situations. Material was used to develop short video clips illustrating some common challenges in giving feedback on clinical and communication skills. Initial evaluation following use of the scenarios in workshops was undertaken by means of a "talking wall" technique. Evaluation indicated that the resource enhanced the learning experience by providing realistic and challenging scenarios to focus discussion. Inter-professional working and piloting the use of the video scenarios in workshops enabled the improvement and refinement of an on-line staff development resource on feedback. The on-line resource is now available as an open access learning tool, with eight scenarios and guidelines for providing effective feedback in the academic or clinical setting. It can be used for self-study or as part of a group training session. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting

PubMed Central

Ghazali, Rozaida; Herawan, Tutut

2016-01-01

Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network. PMID:27959927

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

PubMed

Waheeb, Waddah; Ghazali, Rozaida; Herawan, Tutut

2016-01-01

Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

Exploratory Study on the Patterns of Online Interaction and Knowledge Co-Construction in Project-Based Learning

ERIC Educational Resources Information Center

Heo, Heeok; Lim, Kyu Yon; Kim, Youngsoo

2010-01-01

This study aims to investigate the patterns and the quality of online interaction during project-based learning (PjBL) on both micro and macro levels. To achieve this purpose, PjBL was implemented with online group activities in an undergraduate course. Social network analysis (SNA) and content analysis were employed to analyze online interaction…

Feedback Regulation and Its Efficiency in Biochemical Networks

NASA Astrophysics Data System (ADS)

Kobayashi, Tetsuya J.; Yokota, Ryo; Aihara, Kazuyuki

2016-03-01

Intracellular biochemical networks fluctuate dynamically due to various internal and external sources of fluctuation. Dissecting the fluctuation into biologically relevant components is important for understanding how a cell controls and harnesses noise and how information is transferred over apparently noisy intracellular networks. While substantial theoretical and experimental advancement on the decomposition of fluctuation was achieved for feedforward networks without any loop, we still lack a theoretical basis that can consistently extend such advancement to feedback networks. The main obstacle that hampers is the circulative propagation of fluctuation by feedback loops. In order to define the relevant quantity for the impact of feedback loops for fluctuation, disentanglement of the causally interlocked influences between the components is required. In addition, we also lack an approach that enables us to infer non-perturbatively the influence of the feedback to fluctuation in the same way as the dual reporter system does in the feedforward networks. In this work, we address these problems by extending the work on the fluctuation decomposition and the dual reporter system. For a single-loop feedback network with two components, we define feedback loop gain as the feedback efficiency that is consistent with the fluctuation decomposition for feedforward networks. Then, we clarify the relation of the feedback efficiency with the fluctuation propagation in an open-looped FF network. Finally, by extending the dual reporter system, we propose a conjugate feedback and feedforward system for estimating the feedback efficiency non-perturbatively only from the statistics of the system.

Evolution of a Patient Information Management System in a Local Area Network Environment at Loyola University of Chicago Medical Center

PubMed Central

Price, Ronald N; Chandrasekhar, Arcot J; Tamirisa, Balaji

1990-01-01

The Department of Medicine at Loyola University Medical Center (LUMC) of Chicago has implemented a local area network (LAN) based Patient Information Management System (PIMS) as part of its integrated departmental database management system. PIMS consists of related database applications encompassing demographic information, current medications, problem lists, clinical data, prior events, and on-line procedure results. Integration into the existing departmental database system permits PIMS to capture and manipulate data in other departmental applications. Standardization of clinical data is accomplished through three data tables that verify diagnosis codes, procedures codes and a standardized set of clinical data elements. The modularity of the system, coupled with standardized data formats, allowed the development of a Patient Information Protocol System (PIPS). PIPS, a userdefinable protocol processor, provides physicians with individualized data entry or review screens customized for their specific research protocols or practice habits. Physician feedback indicates that the PIMS/PIPS combination enhances their ability to collect and review specific patient information by filtering large amount of clinical data.

Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

NASA Astrophysics Data System (ADS)

Meng, Su; Chen, Jie; Sun, Jian

2017-10-01

This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

Teens Engaged in Collaborative Health: The Feasibility and Acceptability of an Online Skill-Building Intervention for Adolescents at Risk for Depression.

PubMed

Lattie, Emily G; Ho, Joyce; Sargent, Elizabeth; Tomasino, Kathryn N; Smith, J D; Brown, C Hendricks; Mohr, David C

2017-06-01

There is an ongoing need for effective and accessible preventive interventions for adolescent depression and substance abuse. This paper reports on a field trial of an online indicated preventive intervention, ProjectTECH, which is based on cognitive-behavioral therapy (CBT) techniques. The study aims to gather information about the feasibility and acceptability of this program. Secondary aims of this study were to examine the impact of the program on depression symptoms, perceived stress, positive affect, and substance use and to compare differences between groups that were led by a peer versus those that were led by a licensed clinician. High school students (n = 39) were recruited primarily through social media advertisements, and assigned to four groups of 8-12 individuals to collaboratively participate in an 8 week peer network-based online preventive intervention which were led by a trained peer guide or a licensed clinician. Participants were provided with didactic lessons, CBT-based mood management tools, and peer networking features, and completed quantitative and qualitative feedback at baseline, midpoint, end of intervention, and 1 month follow up. The program attracted and retained users primarily from social media and was used frequently by many of the participants (system login M = 25.62, SD = 16.58). Participants rated the program as usable, and offered several suggestions for improving the program, including allowing for further personalization by the individual user, and including more prompts to engage with the social network. From baseline to end of intervention, significant decreases were observed in depressive symptoms and perceived stress ( p 's < .05). Significant increases in positive affect were observed from baseline to midpoint ( p < .05) and no changes were observed in substance use, although the rate of substance use was low in this sample. While this study had low power to detect group differences, no consistent differences were observed between participants in a peer-led group and those in a clinician-led group. Results of this study indicates that ProjectTECH, an indicated preventive intervention for high school-aged adolescents, demonstrates both feasibility, acceptability, and short-term, longitudinal psychological benefits for participants. Future iterations of the program may benefit from close attention to user interface design and the continued use of trained peer support guides.

Design and Promotion Strategy of Marketing Platform of Aquatic Auction based on Internet

NASA Astrophysics Data System (ADS)

Peng, Jianliang

For the online trade and promotion of aquatic products and related materials through the network between supply and demand, the design content and effective promotional strategies of aquatic auctions online marketing platform is proposed in this paper. Design elements involve the location of customer service, the basic function of the platform including the purchase of general orders, online auctions, information dissemination, and recommendation of fine products, human services, and payment preferences. Based on network and mobile e-commerce transaction support, the auction platform makes the transaction of aquatic products well in advance. The results are important practical value for the design and application of online marketing platform of aquatic auction.

Combining the Formative with the Summative: The Development of a Two-Stage Online Test to Encourage Engagement and Provide Personal Feedback in Large Classes

ERIC Educational Resources Information Center

Voelkel, Susanne

2013-01-01

The aim of this action research project was to improve student learning by encouraging more "time on task" and to improve self-assessment and feedback through the introduction of weekly online tests in a Year 2 lecture module in biological sciences. Initially voluntary online tests were offered to students and those who participated…

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

NASA Astrophysics Data System (ADS)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

The ESID Online Database network.

PubMed

Guzman, D; Veit, D; Knerr, V; Kindle, G; Gathmann, B; Eades-Perner, A M; Grimbacher, B

2007-03-01

Primary immunodeficiencies (PIDs) belong to the group of rare diseases. The European Society for Immunodeficiencies (ESID), is establishing an innovative European patient and research database network for continuous long-term documentation of patients, in order to improve the diagnosis, classification, prognosis and therapy of PIDs. The ESID Online Database is a web-based system aimed at data storage, data entry, reporting and the import of pre-existing data sources in an enterprise business-to-business integration (B2B). The online database is based on Java 2 Enterprise System (J2EE) with high-standard security features, which comply with data protection laws and the demands of a modern research platform. The ESID Online Database is accessible via the official website (http://www.esid.org/). Supplementary data are available at Bioinformatics online.

Realizing actual feedback control of complex network

NASA Astrophysics Data System (ADS)

Tu, Chengyi; Cheng, Yuhua

2014-06-01

In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems.

Effects on Student Achievement in General Chemistry following Participation in an Online Preparatory Course: ChemPrep, a Voluntary, Self-Paced, Online Introduction to Chemistry

ERIC Educational Resources Information Center

Botch, Beatrice; Day, Roberta; Vining, William; Stewart, Barbara; Rath, Kenneth; Peterfreund, Alan; Hart, David

2007-01-01

ChemPrep was developed to be a stand-alone preparatory short-course to help students succeed in general chemistry. It is Web-based and delivered using the OWL system. Students reported that the ChemPrep materials (short information pages, parameterized questions with detailed feedback, tutorials, and answers to questions through the OWL message…

Resumption of dynamism in damaged networks of coupled oscillators

NASA Astrophysics Data System (ADS)

Kundu, Srilena; Majhi, Soumen; Ghosh, Dibakar

2018-05-01

Deterioration in dynamical activities may come up naturally or due to environmental influences in a massive portion of biological and physical systems. Such dynamical degradation may have outright effect on the substantive network performance. This requires us to provide some proper prescriptions to overcome undesired circumstances. In this paper, we present a scheme based on external feedback that can efficiently revive dynamism in damaged networks of active and inactive oscillators and thus enhance the network survivability. Both numerical and analytical investigations are performed in order to verify our claim. We also provide a comparative study on the effectiveness of this mechanism for feedbacks to the inactive group or to the active group only. Most importantly, resurrection of dynamical activity is realized even in time-delayed damaged networks, which are considered to be less persistent against deterioration in the form of inactivity in the oscillators. Furthermore, prominence in our approach is substantiated by providing evidence of enhanced network persistence in complex network topologies taking small-world and scale-free architectures, which makes the proposed remedy quite general. Besides the study in the network of Stuart-Landau oscillators, affirmative influence of external feedback has been justified in the network of chaotic Rössler systems as well.

Online tuning of impedance matching circuit for long pulse inductively coupled plasma source operation—An alternate approach

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

Sudhir, Dass; Bandyopadhyay, M., E-mail: mainak@ter-india.org; Chakraborty, A.

2014-01-15

Impedance matching circuit between radio frequency (RF) generator and the plasma load, placed between them, determines the RF power transfer from RF generator to the plasma load. The impedance of plasma load depends on the plasma parameters through skin depth and plasma conductivity or resistivity. Therefore, for long pulse operation of inductively coupled plasmas, particularly for high power (∼100 kW or more) where plasma load condition may vary due to different reasons (e.g., pressure, power, and thermal), online tuning of impedance matching circuit is necessary through feedback. In fusion grade ion source operation, such online methodology through feedback is notmore » present but offline remote tuning by adjusting the matching circuit capacitors and tuning the driving frequency of the RF generator between the ion source operation pulses is envisaged. The present model is an approach for remote impedance tuning methodology for long pulse operation and corresponding online impedance matching algorithm based on RF coil antenna current measurement or coil antenna calorimetric measurement may be useful in this regard.« less

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

PubMed

Zenke, Friedemann; Ganguli, Surya

2018-06-01

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

Information Filtering on Coupled Social Networks

PubMed Central

Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui

2014-01-01

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks. PMID:25003525

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

A cloud-based forensics tracking scheme for online social network clients.

PubMed

Lin, Feng-Yu; Huang, Chien-Cheng; Chang, Pei-Ying

2015-10-01

In recent years, with significant changes in the communication modes, most users are diverted to cloud-based applications, especially online social networks (OSNs), which applications are mostly hosted on the outside and available to criminals, enabling them to impede criminal investigations and intelligence gathering. In the virtual world, how the Law Enforcement Agency (LEA) identifies the "actual" identity of criminal suspects, and their geolocation in social networks, is a major challenge to current digital investigation. In view of this, this paper proposes a scheme, based on the concepts of IP location and network forensics, which aims to develop forensics tracking on OSNs. According to our empirical analysis, the proposed mechanism can instantly trace the "physical location" of a targeted service resource identifier (SRI), when the target client is using online social network applications (Facebook, Twitter, etc.), and can analyze the probable target client "identity" associatively. To the best of our knowledge, this is the first individualized location method and architecture developed and evaluated in OSNs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

On the interaction structure of linear multi-input feedback control systems. M.S. Thesis; [problem solving, lattices (mathematics)

NASA Technical Reports Server (NTRS)

Wong, P. K.

1975-01-01

The closely-related problems of designing reliable feedback stabilization strategy and coordinating decentralized feedbacks are considered. Two approaches are taken. A geometric characterization of the structure of control interaction (and its dual) was first attempted and a concept of structural homomorphism developed based on the idea of 'similarity' of interaction pattern. The idea of finding classes of individual feedback maps that do not 'interfere' with the stabilizing action of each other was developed by identifying the structural properties of nondestabilizing and LQ-optimal feedback maps. Some known stability properties of LQ-feedback were generalized and some partial solutions were provided to the reliable stabilization and decentralized feedback coordination problems. A concept of coordination parametrization was introduced, and a scheme for classifying different modes of decentralization (information, control law computation, on-line control implementation) in control systems was developed.

A Framework for Engineering Stress Resilient Plants Using Genetic Feedback Control and Regulatory Network Rewiring.

PubMed

Foo, Mathias; Gherman, Iulia; Zhang, Peijun; Bates, Declan G; Denby, Katherine J

2018-05-23

Crop disease leads to significant waste worldwide, both pre- and postharvest, with subsequent economic and sustainability consequences. Disease outcome is determined both by the plants' response to the pathogen and by the ability of the pathogen to suppress defense responses and manipulate the plant to enhance colonization. The defense response of a plant is characterized by significant transcriptional reprogramming mediated by underlying gene regulatory networks, and components of these networks are often targeted by attacking pathogens. Here, using gene expression data from Botrytis cinerea-infected Arabidopsis plants, we develop a systematic approach for mitigating the effects of pathogen-induced network perturbations, using the tools of synthetic biology. We employ network inference and system identification techniques to build an accurate model of an Arabidopsis defense subnetwork that contains key genes determining susceptibility of the plant to the pathogen attack. Once validated against time-series data, we use this model to design and test perturbation mitigation strategies based on the use of genetic feedback control. We show how a synthetic feedback controller can be designed to attenuate the effect of external perturbations on the transcription factor CHE in our subnetwork. We investigate and compare two approaches for implementing such a controller biologically-direct implementation of the genetic feedback controller, and rewiring the regulatory regions of multiple genes-to achieve the network motif required to implement the controller. Our results highlight the potential of combining feedback control theory with synthetic biology for engineering plants with enhanced resilience to environmental stress.

Autoshaping and automaintenance: a neural-network approach.

PubMed

Burgos, José E

2007-07-01

This article presents an interpretation of autoshaping, and positive and negative automaintenance, based on a neural-network model. The model makes no distinction between operant and respondent learning mechanisms, and takes into account knowledge of hippocampal and dopaminergic systems. Four simulations were run, each one using an A-B-A design and four instances of feedfoward architectures. In A, networks received a positive contingency between inputs that simulated a conditioned stimulus (CS) and an input that simulated an unconditioned stimulus (US). Responding was simulated as an output activation that was neither elicited by nor required for the US. B was an omission-training procedure. Response directedness was defined as sensory feedback from responding, simulated as a dependence of other inputs on responding. In Simulation 1, the phenomena were simulated with a fully connected architecture and maximally intense response feedback. The other simulations used a partially connected architecture without competition between CS and response feedback. In Simulation 2, a maximally intense feedback resulted in substantial autoshaping and automaintenance. In Simulation 3, eliminating response feedback interfered substantially with autoshaping and automaintenance. In Simulation 4, intermediate autoshaping and automaintenance resulted from an intermediate response feedback. Implications for the operant-respondent distinction and the behavior-neuroscience relation are discussed.

Autoshaping and Automaintenance: A Neural-Network Approach

PubMed Central

Burgos, José E

2007-01-01

This article presents an interpretation of autoshaping, and positive and negative automaintenance, based on a neural-network model. The model makes no distinction between operant and respondent learning mechanisms, and takes into account knowledge of hippocampal and dopaminergic systems. Four simulations were run, each one using an A-B-A design and four instances of feedfoward architectures. In A, networks received a positive contingency between inputs that simulated a conditioned stimulus (CS) and an input that simulated an unconditioned stimulus (US). Responding was simulated as an output activation that was neither elicited by nor required for the US. B was an omission-training procedure. Response directedness was defined as sensory feedback from responding, simulated as a dependence of other inputs on responding. In Simulation 1, the phenomena were simulated with a fully connected architecture and maximally intense response feedback. The other simulations used a partially connected architecture without competition between CS and response feedback. In Simulation 2, a maximally intense feedback resulted in substantial autoshaping and automaintenance. In Simulation 3, eliminating response feedback interfered substantially with autoshaping and automaintenance. In Simulation 4, intermediate autoshaping and automaintenance resulted from an intermediate response feedback. Implications for the operant–respondent distinction and the behavior–neuroscience relation are discussed. PMID:17725055

QUEST: Eliminating Online Supervised Learning for Efficient Classification Algorithms.

PubMed

Zwartjes, Ardjan; Havinga, Paul J M; Smit, Gerard J M; Hurink, Johann L

2016-10-01

In this work, we introduce QUEST (QUantile Estimation after Supervised Training), an adaptive classification algorithm for Wireless Sensor Networks (WSNs) that eliminates the necessity for online supervised learning. Online processing is important for many sensor network applications. Transmitting raw sensor data puts high demands on the battery, reducing network life time. By merely transmitting partial results or classifications based on the sampled data, the amount of traffic on the network can be significantly reduced. Such classifications can be made by learning based algorithms using sampled data. An important issue, however, is the training phase of these learning based algorithms. Training a deployed sensor network requires a lot of communication and an impractical amount of human involvement. QUEST is a hybrid algorithm that combines supervised learning in a controlled environment with unsupervised learning on the location of deployment. Using the SITEX02 dataset, we demonstrate that the presented solution works with a performance penalty of less than 10% in 90% of the tests. Under some circumstances, it even outperforms a network of classifiers completely trained with supervised learning. As a result, the need for on-site supervised learning and communication for training is completely eliminated by our solution.

ERD-based online brain-machine interfaces (BMI) in the context of neurorehabilitation: optimizing BMI learning and performance.

PubMed

Soekadar, Surjo R; Witkowski, Matthias; Mellinger, Jürgen; Ramos, Ander; Birbaumer, Niels; Cohen, Leonardo G

2011-10-01

Event-related desynchronization (ERD) of sensori-motor rhythms (SMR) can be used for online brain-machine interface (BMI) control, but yields challenges related to the stability of ERD and feedback strategy to optimize BMI learning.Here, we compared two approaches to this challenge in 20 right-handed healthy subjects (HS, five sessions each, S1-S5) and four stroke patients (SP, 15 sessions each, S1-S15). ERD was recorded from a 275-sensor MEG system. During daily training,motor imagery-induced ERD led to visual and proprioceptive feedback delivered through an orthotic device attached to the subjects' hand and fingers. Group A trained with a heterogeneous reference value (RV) for ERD detection with binary feedback and Group B with a homogenous RV and graded feedback (10 HS and 2 SP in each group). HS in Group B showed better BMI performance than Group A (p < 0.001) and improved BMI control from S1 to S5 (p = 0.012) while Group A did not. In spite of the small n, SP in Group B showed a trend for a higher BMI performance (p = 0.06) and learning was significantly better (p < 0.05). Using a homogeneous RV and graded feedback led to improved modulation of ipsilesional activity resulting in superior BMI learning relative to use of a heterogeneous RV and binary feedback.

Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval

ERIC Educational Resources Information Center

Khribi, Mohamed Koutheair; Jemni, Mohamed; Nasraoui, Olfa

2009-01-01

In this paper, we describe an automatic personalization approach aiming to provide online automatic recommendations for active learners without requiring their explicit feedback. Recommended learning resources are computed based on the current learner's recent navigation history, as well as exploiting similarities and dissimilarities among…

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

DTIC Science & Technology

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

Modeling online social signed networks

NASA Astrophysics Data System (ADS)

Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

2018-04-01

People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

Clinic Versus Online Social Network–Delivered Lifestyle Interventions: Protocol for the Get Social Noninferiority Randomized Controlled Trial

PubMed Central

Wang, Monica L; Waring, Molly E; Jake-Schoffman, Danielle E; Oleski, Jessica L; Michaels, Zachary; Goetz, Jared M; Lemon, Stephenie C; Ma, Yunsheng

2017-01-01

Background Online social networks may be a promising modality to deliver lifestyle interventions by reducing cost and burden. Although online social networks have been integrated as one component of multimodality lifestyle interventions, no randomized trials to date have compared a lifestyle intervention delivered entirely via online social network with a traditional clinic-delivered intervention. Objective This paper describes the design and methods of a noninferiority randomized controlled trial, testing (1) whether a lifestyle intervention delivered entirely through an online social network would produce weight loss that would not be appreciably worse than that induced by a traditional clinic-based lifestyle intervention among overweight and obese adults and (2) whether the former would do so at a lower cost. Methods Adults with body mass index (BMI) between 27 and 45 kg/m2 (N=328) will be recruited from the communities in central Massachusetts. These overweight or obese adults will be randomized to two conditions: a lifestyle intervention delivered entirely via the online social network Twitter (Get Social condition) and an in-person group-based lifestyle intervention (Traditional condition) among overweight and obese adults. Measures will be obtained at baseline, 6 months, and 12 months after randomization. The primary noninferiority outcome is percentage weight loss at 12 months. Secondary noninferiority outcomes include dietary intake and moderate intensity physical activity at 12 months. Our secondary aim is to compare the conditions on cost. Exploratory outcomes include treatment retention, acceptability, and burden. Finally, we will explore predictors of weight loss in the online social network condition. Results The final wave of data collection is expected to conclude in June 2019. Data analysis will take place in the months following and is expected to be complete in September 2019. Conclusions Findings will extend the literature by revealing whether delivering a lifestyle intervention via an online social network is an effective alternative to the traditional modality of clinic visits, given the former might be more scalable and feasible to implement in settings that cannot support clinic-based models. Trial Registration ClinicalTrials.gov NCT02646618; https://clinicaltrials.gov/ct2/show/NCT02646618 (Archived by WebCite at http://www.webcitation.org/6v20waTFW) PMID:29229591

Viewing geometry determines the contribution of binocular vision to the online control of grasping.

PubMed

Keefe, Bruce D; Watt, Simon J

2017-12-01

Binocular vision is often assumed to make a specific, critical contribution to online visual control of grasping by providing precise information about the separation between digits and object. This account overlooks the 'viewing geometry' typically encountered in grasping, however. Separation of hand and object is rarely aligned precisely with the line of sight (the visual depth dimension), and analysis of the raw signals suggests that, for most other viewing angles, binocular feedback is less precise than monocular feedback. Thus, online grasp control relying selectively on binocular feedback would not be robust to natural changes in viewing geometry. Alternatively, sensory integration theory suggests that different signals contribute according to their relative precision, in which case the role of binocular feedback should depend on viewing geometry, rather than being 'hard-wired'. We manipulated viewing geometry, and assessed the role of binocular feedback by measuring the effects on grasping of occluding one eye at movement onset. Loss of binocular feedback resulted in a significantly less extended final slow-movement phase when hand and object were separated primarily in the frontoparallel plane (where binocular information is relatively imprecise), compared to when they were separated primarily along the line of sight (where binocular information is relatively precise). Consistent with sensory integration theory, this suggests the role of binocular (and monocular) vision in online grasp control is not a fixed, 'architectural' property of the visuo-motor system, but arises instead from the interaction of viewer and situation, allowing robust online control across natural variations in viewing geometry.

Discovery of Information Diffusion Process in Social Networks

NASA Astrophysics Data System (ADS)

Kim, Kwanho; Jung, Jae-Yoon; Park, Jonghun

Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

Online Self-Assessment with Feedback and Metacognitive Knowledge

ERIC Educational Resources Information Center

Ibabe, Izaskun; Jauregizar, Joana

2010-01-01

The present work describes an experience of educational innovation in a university context. Its aim was to determine the relationship between students' frequency of use of online self-assessment with feedback and their final performance on the course, taking into account both learners' motivation and perceived usefulness of these resources for…

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world. PMID:26528176

When Educational Resources Are Open

ERIC Educational Resources Information Center

Breck, Judy

2007-01-01

This article is a partial look at what the future of education might be if educational resources become open online. Intertwingularity is discussed as a general term for what OER will do online. Predictions about an open education future are based on nine quotations from books by popular writers about our networked age. When the network mechanisms…

Local Spatial Obesity Analysis and Estimation Using Online Social Network Sensors.

PubMed

Sun, Qindong; Wang, Nan; Li, Shancang; Zhou, Hongyi

2018-03-15

Recently, the online social networks (OSNs) have received considerable attentions as a revolutionary platform to offer users massive social interaction among users that enables users to be more involved in their own healthcare. The OSNs have also promoted increasing interests in the generation of analytical, data models in health informatics. This paper aims at developing an obesity identification, analysis, and estimation model, in which each individual user is regarded as an online social network 'sensor' that can provide valuable health information. The OSN-based obesity analytic model requires each sensor node in an OSN to provide associated features, including dietary habit, physical activity, integral/incidental emotions, and self-consciousness. Based on the detailed measurements on the correlation of obesity and proposed features, the OSN obesity analytic model is able to estimate the obesity rate in certain urban areas and the experimental results demonstrate a high success estimation rate. The measurements and estimation experimental findings created by the proposed obesity analytic model show that the online social networks could be used in analyzing the local spatial obesity problems effectively. Copyright © 2018. Published by Elsevier Inc.

They all do it, will you? Event-related potential evidence of herding behavior in online peer-to-peer lending.

PubMed

Yu, Haihong; Dan, MengHan; Ma, Qingguo; Jin, Jia

2018-05-14

As herding is a typical characteristic of human behavior, many researchers have found the existence of herding behavior in online peer-to-peer lending through empirical surveys. However, the underlying neural basis of this phenomenon is still unclear. In the current study, we studied the neural activities of herding at decision-making stage and feedback stage using event-related potentials (ERPs). Our results showed that at decision-making stage, larger error related negativity (ERN) amplitude was induced under low-proportion conditions than that of high-proportion conditions. Meanwhile, during feedback stage, negative feedback elicited larger feedback related negativity (FRN) amplitude than that of positive feedback under low-proportion conditions, however, there was no significant FRN difference under high-proportion conditions. The current study suggests that herding behavior in online peer-to-peer lending is related to individual's risk perception and is possible to avoid negative emotions brought by failed investments. Copyright © 2018 Elsevier B.V. All rights reserved.

Measuring Medical Student Preference: A Comparison of Classroom Versus Online Instruction for Teaching Pubmed*EC

PubMed Central

Schimming, Laura M.

2008-01-01

Objective: The research analyzed evaluation data to assess medical student satisfaction with the learning experience when required PubMed training is offered entirely online. Methods: A retrospective study analyzed skills assessment scores and student feedback forms from 455 first-year medical students who completed PubMed training either through classroom sessions or an online tutorial. The class of 2006 (n = 99) attended traditional librarian-led sessions in a computer classroom. The classes of 2007 (n = 120), 2008 (n = 121), and 2009 (n = 115) completed the training entirely online through a self-paced tutorial. PubMed skills assessment scores and student feedback about the training were compared for all groups. Results: As evidenced by open-ended comments about the training, students who took the online tutorial were equally or more satisfied with the learning experience than students who attended classroom sessions, with the classes of 2008 and 2009 reporting greater satisfaction (P<0.001) than the other 2 groups. The mean score on the PubMed skills assessment (91%) was the same for all groups of students. Conclusions: Student satisfaction improved and PubMed assessment scores did not change when instruction was offered online to first-year medical students. Comments from the students who received online training suggest that the increased control and individual engagement with the web-based content led to their satisfaction with the online tutorial. PMID:18654658

Adaptive and Maladaptive Means of Using Facebook: A Qualitative Pilot Study to Inform Suggestions for Development of a Future Intervention for Depression

PubMed Central

Tran, Tanya B.; Uebelacker, Lisa; Wenze, Susan J.; Collins, Caitlin; Broughton, Monica K.

2015-01-01

Existing literature examining the relation between social networking sites and mental health is primarily based on correlational methods and presents mixed findings. Many researchers neglect to examine the cognitive and behavioral processes used while online. This study’s qualitative approach strives to understand how individuals with elevated depressive symptoms may use Facebook following an interpersonal stressor. Participants’ narration of their Facebook use was coded. Common adaptive uses included using Facebook to seek social support, actively communicate, distract, recall positive memories, and reappraise negative thoughts. Maladaptive uses included engaging in social comparison, ruminating, and recalling negative memories. Feedback regarding development of a future intervention was also elicited. Suggestions included using Facebook to view positive, interesting, or meaningful information, distract, garner social support, and engage in social activities. Findings indicate that how one engages with Facebook after an interpersonal stressor may affect adjustment and may help to inform the development of a novel, Facebook-based intervention. PMID:26554330

Adaptive and Maladaptive Means of Using Facebook: A Qualitative Pilot Study to Inform Suggestions for Development of a Future Intervention for Depression.

PubMed

Tran, Tanya B; Uebelacker, Lisa; Wenze, Susan J; Collins, Caitlin; Broughton, Monica K

2015-11-01

Existing literature examining the relation between social networking sites and mental health is primarily based on correlational methods and presents mixed findings. Many researchers neglect to examine the cognitive and behavioral processes used while online. This study's qualitative approach strives to understand how individuals with elevated depressive symptoms may use Facebook following an interpersonal stressor. Participants' narration of their Facebook use was coded. Common adaptive uses included using Facebook to seek social support, actively communicate, distract, recall positive memories, and reappraise negative thoughts. Maladaptive uses included engaging in social comparison, ruminating, and recalling negative memories. Feedback regarding development of a future intervention was also elicited. Suggestions included using Facebook to view positive, interesting, or meaningful information, distract, garner social support, and engage in social activities. Findings indicate that how one engages with Facebook after an interpersonal stressor may affect adjustment and may help to inform the development of a novel, Facebook-based intervention.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Long, Theresa W.

1995-01-01

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Chaos synchronization in networks of semiconductor superlattices

NASA Astrophysics Data System (ADS)

Li, Wen; Aviad, Yaara; Reidler, Igor; Song, Helun; Huang, Yuyang; Biermann, Klaus; Rosenbluh, Michael; Zhang, Yaohui; Grahn, Holger T.; Kanter, Ido

2015-11-01

Chaos synchronization has been demonstrated as a useful building block for various tasks in secure communications, including a source of all-electronic ultrafast physical random number generators based on room temperature spontaneous chaotic oscillations in a DC-biased weakly coupled GaAs/Al0.45Ga0.55As semiconductor superlattice (SSL). Here, we experimentally demonstrate the emergence of several types of chaos synchronization, e.g. leader-laggard, face-to-face and zero-lag synchronization in network motifs of coupled SSLs consisting of unidirectional and mutual coupling as well as self-feedback coupling. Each type of synchronization clearly reflects the symmetry of the topology of its network motif. The emergence of a chaotic SSL without external feedback and synchronization among different structured SSLs open up the possibility for advanced secure multi-user communication methods based on large networks of coupled SSLs.

Sexual health promotion on social networking sites: a process evaluation of The FaceSpace Project.

PubMed

Nguyen, Phuong; Gold, Judy; Pedrana, Alisa; Chang, Shanton; Howard, Steve; Ilic, Olivia; Hellard, Margaret; Stoove, Mark

2013-07-01

This article reports findings from an evaluation of reach and engagement of The FaceSpace Project, a novel sexual health promotion project delivered through social networking sites that targeted young people aged 16-29 years. Multiple methods were used to evaluate project reach and engagement. The evaluation focussed on quantitative data (online usage statistics, online surveys), complemented by available qualitative data (project team meeting notes). The project reached 900 fans who were mostly between 18 and 34 years of age. The most successful ways of increasing audience reach were via Facebook advertisements and tagging photos of young people attending a music festival on the project Facebook page. Peaks in Facebook page interactions (comments and "likes") coincided with recruitment peaks and when videos were posted. However, video views varied greatly between postings. Feedback from the project team for increasing engagement in future social networking site interventions included having one centralized Facebook page and using episodic videos. This evaluation is among the first to assess the use of social networking sites for sexual health promotion and provides information to inform the implementation and evaluation of future projects using new media. Social networking sites offer great potential to reach and engage young people for sexual health promotion. However, further work is required to improve implementation and promote audience reach and engagement as well as to determine effectiveness of social networking sites in changing knowledge, attitudes, and behaviors. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Experiments with arbitrary networks in time-multiplexed delay systems

NASA Astrophysics Data System (ADS)

Hart, Joseph D.; Schmadel, Don C.; Murphy, Thomas E.; Roy, Rajarshi

2017-12-01

We report a new experimental approach using an optoelectronic feedback loop to investigate the dynamics of oscillators coupled on large complex networks with arbitrary topology. Our implementation is based on a single optoelectronic feedback loop with time delays. We use the space-time interpretation of systems with time delay to create large networks of coupled maps. Others have performed similar experiments using high-pass filters to implement the coupling; this restricts the network topology to the coupling of only a few nearest neighbors. In our experiment, the time delays and coupling are implemented on a field-programmable gate array, allowing the creation of networks with arbitrary coupling topology. This system has many advantages: the network nodes are truly identical, the network is easily reconfigurable, and the network dynamics occur at high speeds. We use this system to study cluster synchronization and chimera states in both small and large networks of different topologies.

Finding meaning in social media: content-based social network analysis of QuitNet to identify new opportunities for health promotion.

PubMed

Myneni, Sahiti; Cobb, Nathan K; Cohen, Trevor

2013-01-01

Unhealthy behaviors increase individual health risks and are a socioeconomic burden. Harnessing social influence is perceived as fundamental for interventions to influence health-related behaviors. However, the mechanisms through which social influence occurs are poorly understood. Online social networks provide the opportunity to understand these mechanisms as they digitally archive communication between members. In this paper, we present a methodology for content-based social network analysis, combining qualitative coding, automated text analysis, and formal network analysis such that network structure is determined by the content of messages exchanged between members. We apply this approach to characterize the communication between members of QuitNet, an online social network for smoking cessation. Results indicate that the method identifies meaningful theme-based social sub-networks. Modeling social network data using this method can provide us with theme-specific insights such as the identities of opinion leaders and sub-community clusters. Implications for design of targeted social interventions are discussed.

Recruiting migrants for health research through social network sites: an online survey among chinese migrants in australia.

PubMed

Hu, Jie; Wong, Kam Cheong; Wang, Zhiqiang

2015-04-27

Traditionally, postal surveys or face to face interviews are the main approaches for health researchers to obtain essential research data. However, with the prevalence of information technology and Internet, Web-based surveys are gaining popularity in health research. This study aims to report the process and outcomes of recruiting Chinese migrants through social network sites in Australia and to examine the sample characteristics of online recruitment by comparing the sample which was recruited by an online survey to a sample of Australian Chinese migrants collected by a postal survey. Descriptive analyses were performed to describe and compare the process and outcomes of online recruitment with postal survey questionnaires. Chi square tests and t tests were performed to assess the differences between the two samples for categorical and continuous variables respectively. In total, 473 Chinese migrants completed the online health survey from July to October 2013. Out of 426 participants recruited through the three Chinese social network sites in Australia, over 86.6% (369/426) were recruited within six weeks. Participants of the Web-based survey were younger, with a higher education level or had resided in Australia for less time compared to those recruited via a postal survey. However, there was no significant difference in gender, marital status, and professional occupation. The recruitment of Chinese migrants through social network sites in our online survey was feasible. Compared to a postal survey of Chinese migrants, the online survey attracted different group of Chinese migrants who may have diverse health needs and concerns. Our findings provided insightful information for researchers who are considering employing a Web-based approach to recruit migrants and ethnic minority participants.

Engineering Online and In-person Social Networks for Physical Activity: A Randomized Trial

PubMed Central

Rovniak, Liza S.; Kong, Lan; Hovell, Melbourne F.; Ding, Ding; Sallis, James F.; Ray, Chester A.; Kraschnewski, Jennifer L.; Matthews, Stephen A.; Kiser, Elizabeth; Chinchilli, Vernon M.; George, Daniel R.; Sciamanna, Christopher N.

2016-01-01

Background Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. Purpose To conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively-measured outcomes. Methods Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3% male, 83.4% overweight/obese) were randomized to 1 of 3 groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking, and prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Results Participants increased their MVPA by 21.0 mins/week, 95% CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Conclusions Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. Trial Registration Number NCT01142804 PMID:27405724

Application of Neural Networks for classification of Patau, Edwards, Down, Turner and Klinefelter Syndrome based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics.

PubMed

Catic, Aida; Gurbeta, Lejla; Kurtovic-Kozaric, Amina; Mehmedbasic, Senad; Badnjevic, Almir

2018-02-13

The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been investigated more extensively over the past few years. The reason for this is that ANNs are good approximates of complex functions, so classification can be performed without the need for explicitly defined input-output model. This engineering tool can be applied for optimization of existing methods for disease/syndrome classification. Cytogenetic and molecular analyses are the most frequent tests used in prenatal diagnostic for the early detection of Turner, Klinefelter, Patau, Edwards and Down syndrome. These procedures can be lengthy, repetitive; and often employ invasive techniques so a robust automated method for classifying and reporting prenatal diagnostics would greatly help the clinicians with their routine work. The database consisted of data collected from 2500 pregnant woman that came to the Institute of Gynecology, Infertility and Perinatology "Mehmedbasic" for routine antenatal care between January 2000 and December 2016. During first trimester all women were subject to screening test where values of maternal serum pregnancy-associated plasma protein A (PAPP-A) and free beta human chorionic gonadotropin (β-hCG) were measured. Also, fetal nuchal translucency thickness and the presence or absence of the nasal bone was observed using ultrasound. The architectures of linear feedforward and feedback neural networks were investigated for various training data distributions and number of neurons in hidden layer. Feedback neural network architecture out performed feedforward neural network architecture in predictive ability for all five aneuploidy prenatal syndrome classes. Feedforward neural network with 15 neurons in hidden layer achieved classification sensitivity of 92.00%. Classification sensitivity of feedback (Elman's) neural network was 99.00%. Average accuracy of feedforward neural network was 89.6% and for feedback was 98.8%. The results presented in this paper prove that an expert diagnostic system based on neural networks can be efficiently used for classification of five aneuploidy syndromes, covered with this study, based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics. Developed Expert System proved to be simple, robust, and powerful in properly classifying prenatal aneuploidy syndromes.

Decreasing Inappropriate Use of Antibiotics in Primary Care in Four Countries in South America—Cluster Randomized Controlled Trial

PubMed Central

Urbiztondo, Inés; Caballero, Lidia; Suarez, Miguel Angel; Olinisky, Monica

2017-01-01

High antibiotic prescribing and antimicrobial resistance in patients attending primary care have been reported in South America. Very few interventions targeting general practitioners (GPs) to decrease inappropriate antibiotic prescribing have been investigated in this region. This study assessed the effectiveness of online feedback on reducing antibiotic prescribing in patients with suspected respiratory tract infections (RTIs) attending primary care. The aim was to reduce antibiotic prescribing in patients with acute bronchitis and acute otitis media. Both are RTIs for which antibiotics have a very limited effect. A cluster randomized two-arm control trial was implemented. Healthcare centres from Bolivia, Argentina, Paraguay and Uruguay participating in the quality improvement program HAPPY AUDIT were randomly allocated to either intervention or control group. During ten consecutive weeks, GPs in the intervention group received evidence-based online feedback on the management of suspected RTIs. In patients with acute bronchitis, the intervention reduced the antibiotic prescribing rate from 71.6% to 56% (control group from 61.2% to 52%). In patients with acute otitis media, the intervention reduced the antibiotic prescribing from 94.8% to 86.2% (no change in the control group). In all RTIs, the intervention reduced antibiotic prescribing rate from 37.4% to 28.1% (control group from 29% to 27.2%). Online evidence-based feedback is effective for reducing antibiotic prescribing in patients with RTIs attending primary care in South America. PMID:29240687

Development of an Internet-Based Parent Training Intervention for Children with ASD

DTIC Science & Technology

2014-10-01

had mean pretests scores that were significantly lower than did individuals with master’s degrees, all three groups per- formed comparably on the...focus groups with 8-10 key stakeholders to gain feedback on the structural elements of the program. Focus group members will participate in two focus... groups , three months apart. In the first focus group , 9    we will obtain feedback on the structure of the online systems training and self-directed

A recurrent self-organizing neural fuzzy inference network.

PubMed

Juang, C F; Lin, C T

1999-01-01

A recurrent self-organizing neural fuzzy inference network (RSONFIN) is proposed in this paper. The RSONFIN is inherently a recurrent multilayered connectionist network for realizing the basic elements and functions of dynamic fuzzy inference, and may be considered to be constructed from a series of dynamic fuzzy rules. The temporal relations embedded in the network are built by adding some feedback connections representing the memory elements to a feedforward neural fuzzy network. Each weight as well as node in the RSONFIN has its own meaning and represents a special element in a fuzzy rule. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially in the RSONFIN. They are created on-line via concurrent structure identification (the construction of dynamic fuzzy if-then rules) and parameter identification (the tuning of the free parameters of membership functions). The structure learning together with the parameter learning forms a fast learning algorithm for building a small, yet powerful, dynamic neural fuzzy network. Two major characteristics of the RSONFIN can thus be seen: 1) the recurrent property of the RSONFIN makes it suitable for dealing with temporal problems and 2) no predetermination, like the number of hidden nodes, must be given, since the RSONFIN can find its optimal structure and parameters automatically and quickly. Moreover, to reduce the number of fuzzy rules generated, a flexible input partition method, the aligned clustering-based algorithm, is proposed. Various simulations on temporal problems are done and performance comparisons with some existing recurrent networks are also made. Efficiency of the RSONFIN is verified from these results.

Identifying the relationship between feedback provided in computer-assisted instructional modules, science self-efficacy, and academic achievement

NASA Astrophysics Data System (ADS)

Mazingo, Diann Etsuko

Feedback has been identified as a key variable in developing academic self-efficacy. The types of feedback can vary from a traditional, objectivist approach that focuses on minimizing learner errors to a more constructivist approach, focusing on facilitating understanding. The influx of computer-based courses, whether online or through a series of computer-assisted instruction (CAI) modules require that the current research of effective feedback techniques in the classroom be extended to computer environments in order to impact their instructional design. In this study, exposure to different types of feedback during a chemistry CAI module was studied in relation to science self-efficacy (SSE) and performance on an objective-driven assessment (ODA) of the chemistry concepts covered in the unit. The quantitative analysis consisted of two separate ANCOVAs on the dependent variables, using pretest as the covariate and group as the fixed factor. No significant differences were found for either variable between the three groups on adjusted posttest means for the ODA and SSE measures (.95F(2, 106) = 1.311, p = 0.274 and .95F(2, 106) = 1.080, p = 0.344, respectively). However, a mixed methods approach yielded valuable qualitative insights into why only one overall quantitative effect was observed. These findings are discussed in relation to the need to further refine the instruments and methods used in order to more fully explore the possibility that type of feedback might play a role in developing SSE, and consequently, improve academic performance in science. Future research building on this study may reveal significance that could impact instructional design practices for developing online and computer-based instruction.

A wearable biofeedback control system based body area network for freestyle swimming.

PubMed

Rui Li; Zibo Cai; WeeSit Lee; Lai, Daniel T H

2016-08-01

Wearable posture measurement units are capable of enabling real-time performance evaluation and providing feedback to end users. This paper presents a wearable feedback prototype designed for freestyle swimming with focus on trunk rotation measurement. The system consists of a nine-degree-of-freedom inertial sensor, which is built in a central data collection and processing unit, and two vibration motors for delivering real-time feedback. Theses devices form a fundamental body area network (BAN). In the experiment setup, four recreational swimmers were asked to do two sets of 4 x 25m freestyle swimming without and with feedback provided respectively. Results showed that real-time biofeedback mechanism improves swimmers kinematic performance by an average of 4.5% reduction in session time. Swimmers can gradually adapt to feedback signals, and the biofeedback control system can be employed in swimmers daily training for fitness maintenance.

Neural cryptography with feedback.

PubMed

Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

2004-04-01

Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

Online support to facilitate the reintegration of students with brain injury: trials and errors.

PubMed

Verburg, Geb; Borthwick, Burt; Bennett, Bill; Rumney, Peter

2003-01-01

The reintegration of students after acquired/traumatic brain injury (ABI/TBI) continues to be fraught with difficulties. Presented are (1) case studies exploring the potential of online support for teachers of students with ABI after returning from a paediatric rehabilitation centre; (2) results of Internet-based courses about reintegrating students with ABI; (3) outcomes of videoconferencing-based and Internet email-based support; (4) development of an online support process that uses Questions and Answers as a quick and immediate resource for teachers. The authors recommend that a collaborative process be instituted, in order to generate a relatively small number of high quality online resources about re-integrating students into their school and community. A second recommendation focuses on the development of online support network which may be text or email based or which may use videoconferencing over the Internet. Such networks allow students with ABI to maintain contact with their family and friends in the home community and facilitate their reintegration. An Internet-based support structure also allows professionals to provide consultation, collaboration and continuing input.

Social Networking Sites and Addiction: Ten Lessons Learned

PubMed Central

Kuss, Daria J.; Griffiths, Mark D.

2017-01-01

Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided. PMID:28304359

Social Networking Sites and Addiction: Ten Lessons Learned.

PubMed

Kuss, Daria J; Griffiths, Mark D

2017-03-17

Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided.

Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game.

PubMed

Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

2012-01-01

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.

Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, D.; Peng, Z. H.

2017-09-01

Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

Using virtual human technology to provide immediate feedback about participants' use of demographic cues and knowledge of their cue use.

PubMed

Wandner, Laura D; Letzen, Janelle E; Torres, Calia A; Lok, Benjamin; Robinson, Michael E

2014-11-01

Demographic characteristics have been found to influence pain management decisions, but limited focus has been placed on participants' reactions to feedback about their use of sex, race, or age to make these decisions. The present study aimed to examine the effects of providing feedback about the use of demographic cues to participants making pain management decisions. Participants (N = 107) viewed 32 virtual human patients with standardized levels of pain and provided ratings for virtual humans' pain intensity and their treatment decisions. Real-time lens model idiographic analyses determined participants' decision policies based on cues used. Participants were subsequently informed about cue use and completed feedback questions. Frequency analyses were conducted on responses to these questions. Between 7.4 and 89.4% of participants indicated awareness of their use of demographic or pain expression cues. Of those individuals, 26.9 to 55.5% believed this awareness would change their future clinical decisions, and 66.6 to 75.9% endorsed that their attitudes affect their imagined clinical practice. Between 66.6 and 79.1% of participants who used cues reported willingness to complete an online tutorial about pain across demographic groups. This study was novel because it provided participants feedback about their cue use. Most participants who used cues indicated willingness to participate in an online intervention, suggesting this technology's utility for modifying biases. This is the first study to make individuals aware of whether a virtual human's sex, race, or age influences their decision making. Findings suggest that a majority of the individuals who were made aware of their use of demographic cues would be willing to participate in an online intervention. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.

Deep and Surface Processing of Instructor's Feedback in an Online Course

ERIC Educational Resources Information Center

Huang, Kun; Ge, Xun; Law, Victor

2017-01-01

This study investigated the characteristics of deep and surface approaches to learning in online students' responses to instructor's qualitative feedback given to a multi-stage, ill-structured design project. Further, the study examined the relationships between approaches to learning and two learner characteristics: epistemic beliefs (EB) and…

An Investigation of Assessment and Feedback Practices in Fully Asynchronous Online Undergraduate Mathematics Courses

ERIC Educational Resources Information Center

Trenholm, Sven; Alcock, Lara; Robinson, Carol

2015-01-01

Research suggests it is difficult to learn mathematics in the fully asynchronous online (FAO) instructional modality, yet little is known about associated teaching and assessment practices. In this study, we investigate FAO mathematics assessment and feedback practices in particular consideration of both claims and findings that these practices…

Student and Instructor Responses to Emotional Motivational Feedback Messages in an Online Instructional Environment

ERIC Educational Resources Information Center

Sarsar, Firat

2017-01-01

The purpose of this study was to investigate the effectiveness of Emotional Motivational Feedback Message (EMFEM) in an online learning environment. This exploratory research was conducted using mixed method single case study design. Participants were 15 undergraduate students enrolled in an instructional technology course in a large state…

Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior.

PubMed

Althoff, Tim; Jindal, Pranav; Leskovec, Jure

2017-02-01

Many of today's most widely used computing applications utilize social networking features and allow users to connect, follow each other, share content, and comment on others' posts. However, despite the widespread adoption of these features, there is little understanding of the consequences that social networking has on user retention, engagement, and online as well as offline behavior. Here, we study how social networks influence user behavior in a physical activity tracking application. We analyze 791 million online and offline actions of 6 million users over the course of 5 years, and show that social networking leads to a significant increase in users' online as well as offline activities. Specifically, we establish a causal effect of how social networks influence user behavior. We show that the creation of new social connections increases user online in-application activity by 30%, user retention by 17%, and user offline real-world physical activity by 7% (about 400 steps per day). By exploiting a natural experiment we distinguish the effect of social influence of new social connections from the simultaneous increase in user's motivation to use the app and take more steps. We show that social influence accounts for 55% of the observed changes in user behavior, while the remaining 45% can be explained by the user's increased motivation to use the app. Further, we show that subsequent, individual edge formations in the social network lead to significant increases in daily steps. These effects diminish with each additional edge and vary based on edge attributes and user demographics. Finally, we utilize these insights to develop a model that accurately predicts which users will be most influenced by the creation of new social network connections.

Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior

PubMed Central

Althoff, Tim; Jindal, Pranav; Leskovec, Jure

2017-01-01

Many of today’s most widely used computing applications utilize social networking features and allow users to connect, follow each other, share content, and comment on others’ posts. However, despite the widespread adoption of these features, there is little understanding of the consequences that social networking has on user retention, engagement, and online as well as offline behavior. Here, we study how social networks influence user behavior in a physical activity tracking application. We analyze 791 million online and offline actions of 6 million users over the course of 5 years, and show that social networking leads to a significant increase in users’ online as well as offline activities. Specifically, we establish a causal effect of how social networks influence user behavior. We show that the creation of new social connections increases user online in-application activity by 30%, user retention by 17%, and user offline real-world physical activity by 7% (about 400 steps per day). By exploiting a natural experiment we distinguish the effect of social influence of new social connections from the simultaneous increase in user’s motivation to use the app and take more steps. We show that social influence accounts for 55% of the observed changes in user behavior, while the remaining 45% can be explained by the user’s increased motivation to use the app. Further, we show that subsequent, individual edge formations in the social network lead to significant increases in daily steps. These effects diminish with each additional edge and vary based on edge attributes and user demographics. Finally, we utilize these insights to develop a model that accurately predicts which users will be most influenced by the creation of new social network connections. PMID:28345078

Permissive norms and young adults' alcohol and marijuana use: the role of online communities.

PubMed

Stoddard, Sarah A; Bauermeister, Jose A; Gordon-Messer, Deborah; Johns, Michelle; Zimmerman, Marc A

2012-11-01

Young adults are increasingly interacting with their peer groups online through social networking sites. These online interactions may reinforce or escalate alcohol and other drug (AOD) use as a result of more frequent and continuous exposure to AOD promotive norms; however, the influence of young adults' virtual networks on AOD use remains untested. The purpose of this study was to examine the association between the presence of AOD use content in online social networking, perceived norms (online norms regarding AOD use and anticipated regret with AOD use postings), and alcohol and marijuana use in a sample of 18- to 24-year-olds. Using an adapted web version of respondent-driven sampling (webRDS), we recruited a sample of 18- to 24-year-olds (N = 3,448) in the United States. Using multivariate regression, we explored the relationship between past-30-day alcohol and marijuana use, online norms regarding AOD use, peer substance use, and online and offline peer support. Alcohol use was associated with more alcohol content online. Anticipated regret and online peer support were associated with less alcohol use. Anticipated regret was negatively associated with marijuana use. Peer AOD use was positively associated with both alcohol and marijuana use. Peers play an important role in young adult alcohol and marijuana use, whether online or in person. Our findings highlight the importance of promoting online network-based AOD prevention programs for young adults in the United States.

Development and Analyses of Privacy Management Models in Online Social Networks Based on Communication Privacy Management Theory

ERIC Educational Resources Information Center

Lee, Ki Jung

2013-01-01

Online social networks (OSNs), while serving as an emerging means of communication, promote various issues of privacy. Users of OSNs encounter diverse occasions that lead to invasion of their privacy, e.g., published conversation, public revelation of their personally identifiable information, and open boundary of distinct social groups within…

An Online Social Networking Approach to Reinforce Learning of Rocks and Minerals

ERIC Educational Resources Information Center

Kennelly, Patrick

2009-01-01

Numerous and varied methods are used in introductory Earth science and geology classes to help students learn about rocks and minerals, such as classroom lectures, laboratory specimen identification, and field trips. This paper reports on a method using online social networking. The choice of this forum was based on two criteria. First, many…

Roles of Course Facilitators, Learners, and Technology in the Flow of Information of a cMOOC

ERIC Educational Resources Information Center

Skrypnyk, Oleksandra; Joksimovic, Srec´ko; Kovanovic, Vitomir; Gas?evic, Dragan; Dawson, Shane

2015-01-01

Distributed Massive Open Online Courses (MOOCs) are based on the premise that online learning occurs through a network of interconnected learners. The teachers' role in distributed courses extends to forming such a network by facilitating communication that connects learners and their separate personal learning environments scattered around the…

Enabling Community Through Social Media

PubMed Central

Haythornthwaite, Caroline

2013-01-01

Background Social network analysis provides a perspective and method for inquiring into the structures that comprise online groups and communities. Traces from interaction via social media provide the opportunity for understanding how a community is formed and maintained online. Objective The paper aims to demonstrate how social network analysis provides a vocabulary and set of techniques for examining interaction patterns via social media. Using the case of the #hcsmca online discussion forum, this paper highlights what has been and can be gained by approaching online community from a social network perspective, as well as providing an inside look at the structure of the #hcsmca community. Methods Social network analysis was used to examine structures in a 1-month sample of Twitter messages with the hashtag #hcsmca (3871 tweets, 486 unique posters), which is the tag associated with the social media–supported group Health Care Social Media Canada. Network connections were considered present if the individual was mentioned, replied to, or had a post retweeted. Results Network analyses revealed patterns of interaction that characterized the community as comprising one component, with a set of core participants prominent in the network due to their connections with others. Analysis showed the social media health content providers were the most influential group based on in-degree centrality. However, there was no preferential attachment among people in the same professional group, indicating that the formation of connections among community members was not constrained by professional status. Conclusions Network analysis and visualizations provide techniques and a vocabulary for understanding online interaction, as well as insights that can help in understanding what, and who, comprises and sustains a network, and whether community emerges from a network of online interactions. PMID:24176835

Got Game? A Choice-Based Learning Assessment of Data Literacy and Visualization Skills

ERIC Educational Resources Information Center

Chin, Doris B.; Blair, Kristen P.; Schwartz, Daniel L.

2016-01-01

In partnership with both formal and informal learning institutions, researchers have been building a suite of online games, called choicelets, to serve as interactive assessments of learning skills, e.g. critical thinking or seeking feedback. Unlike more traditional assessments, which take a retrospective, knowledge-based view of learning,…

An approach to online network monitoring using clustered patterns

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

Kim, Jinoh; Sim, Alex; Suh, Sang C.

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

An approach to online network monitoring using clustered patterns

DOE PAGES

Kim, Jinoh; Sim, Alex; Suh, Sang C.; ...

2017-03-13

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

Dimensions and dynamics of citizen observatories: The case of online amateur weather networks

NASA Astrophysics Data System (ADS)

Gharesifard, Mohammad; Wehn, Uta; van der Zaag, Pieter

2016-04-01

Crowd-sourced environmental observations are being increasingly considered as having the potential to enhance the spatial and temporal resolution of current data streams from terrestrial and areal sensors. The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public (so-called citizen science) and has resulted in the formation of various online environmental citizen observatory networks. Online amateur weather networks are a particular example of such ICT-mediated citizen observatories as one of the oldest and most widely practiced citizen science activities. The objective of this paper is to introduce a conceptual framework that enables a systematic review of different dimensions of these mushrooming/expanding networks. These dimensions include the geographic scope and types of network participants; the network's establishment mechanism, revenue stream(s) and existing communication paradigm; efforts required by citizens and support offered by platform providers; and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run these networks, sustainability of the platforms, data ownership and level of transparency of each network. This framework is then utilized to perform a critical and normative review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) There are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks. (2) The revenue stream(s) of online amateur weather networks is one of the least discussed but most important dimensions that is crucial for the sustainability of these networks. (3) Although all of the networks included in this study have one or more explicit pattern of two-way communications, there is no sign (yet) of interactive information exchange among the triangle of weather observers, data aggregators and policy makers. KEYWORDS Citizen Science, Citizen Observatories, ICT-enabled citizen participation, online amateur weather networks

Online Help to End-Users in a Networked Environment.

ERIC Educational Resources Information Center

Meyer, Paul

1991-01-01

Discusses the need for online help for end-users based on experiences with an online public access catalog (OPAC) at the University of Cape Town libraries. The concept of end users is examined, the role of search intermediaries in information systems is explained, and online help and systems design is discussed. (LRW)

An optical-density-based feedback feeding method for ammonium concentration control in Spirulina platensis cultivation.

PubMed

Bao, Yilu; Wen, Shumei; Cong, Wei; Wu, Xia; Ning, Zhengxiang

2012-07-01

Cultivation of Spirulina platensis using ammonium salts or wastewater containing ammonium as alternative nitrogen sources is considered as a commercial way to reduce the production cost. In this research, by analyzing the relationship between biomass production and ammonium- N consumption in the fed-batch culture of Spirulina platensis using ammonium bicarbonate as a nitrogen nutrient source, an online adaptive control strategy based on optical density (OD) measurements for controlling ammonium feeding was presented. The ammonium concentration was successfully controlled between the cell growth inhibitory and limiting concentrations using this OD-based feedback feeding method. As a result, the maximum biomass concentration (2.98 g/l), productivity (0.237 g/l·d), nitrogen-to-cell conversion factor (7.32 gX/gN), and contents of protein (64.1%) and chlorophyll (13.4 mg/g) obtained by using the OD-based feedback feeding method were higher than those using the constant and variable feeding methods. The OD-based feedback feeding method could be recognized as an applicable way to control ammonium feeding and a benefit for Spirulina platensis cultivations.

Self-organizing radial basis function networks for adaptive flight control and aircraft engine state estimation

NASA Astrophysics Data System (ADS)

Shankar, Praveen

The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network based adaptive controller. While the fixed RBF network based controller which is tuned to compensate for control surface failures fails to achieve the same performance under modeling uncertainty and disturbances, the SORBFN is able to achieve good tracking convergence under all error conditions.

Ramp-integration technique for capacitance-type blade-tip clearance measurement

NASA Astrophysics Data System (ADS)

Sarma, Garimella R.; Barranger, John P.

The analysis of a proposed new technique for capacitance type blade tip clearance measurement is presented. The capacitance between the blade tip and a mounted capacitance electrode within a guard ring forms one of the feedback elements of a high speed operational amplifier. The differential equation governing the operational amplifier circuit is formulated and solved for two types of inputs to the amplifier - a constant voltage and a ramp. The resultant solution shows an output that contains a term that is proportional to the derivative of the product of the input voltage and the time constant of the feedback network. The blade tip clearance capacitance is obtained by subtracting the output of a balancing reference channel followed by integration. The proposed sampled data algorithm corrects for environmental effects and varying rotor speeds on-line, making the system suitable for turbine instrumentation. System requirements, block diagrams, and a typical application are included.

Ramp-integration technique for capacitance-type blade-tip clearance measurement

NASA Astrophysics Data System (ADS)

Sarma, G. R.; Barranger, J. P.

1986-05-01

The analysis of a proposed new technique for capacitance type blade tip clearance measurement is presented. The capacitance between the blade tip and a mounted capacitance electrode within a guard ring forms one of the feedback elements of a high speed operational amplifier. The differential equation governing the operational amplifier circuit is formulated and solved for two types of inputs to the amplifier - a constant voltage and a ramp. The resultant solutions shows an output that contains a term that is proportional to the derivative of the product of the input voltage and the time constant of the feedback network. The blade tip clearance capacitance is obtained by subtracting the output of a balancing reference channel followed by integration. The proposed sampled data algorithm corrects the environmental effects and varying rotor speeds on-line, making the system suitable for turbine instrumentation. System requirements, block diagrams, and typical application are included.

Ramp-integration technique for capacitance-type blade-tip clearance measurement

NASA Technical Reports Server (NTRS)

Sarma, Garimella R.; Barranger, John P.

1986-01-01

The analysis of a proposed new technique for capacitance type blade tip clearance measurement is presented. The capacitance between the blade tip and a mounted capacitance electrode within a guard ring forms one of the feedback elements of a high speed operational amplifier. The differential equation governing the operational amplifier circuit is formulated and solved for two types of inputs to the amplifier - a constant voltage and a ramp. The resultant solution shows an output that contains a term that is proportional to the derivative of the product of the input voltage and the time constant of the feedback network. The blade tip clearance capacitance is obtained by subtracting the output of a balancing reference channel followed by integration. The proposed sampled data algorithm corrects for environmental effects and varying rotor speeds on-line, making the system suitable for turbine instrumentation. System requirements, block diagrams, and a typical application are included.

Ramp-integration technique for capacitance-type blade-tip clearance measurement

NASA Technical Reports Server (NTRS)

Sarma, G. R.; Barranger, J. P.

1986-01-01

The analysis of a proposed new technique for capacitance type blade tip clearance measurement is presented. The capacitance between the blade tip and a mounted capacitance electrode within a guard ring forms one of the feedback elements of a high speed operational amplifier. The differential equation governing the operational amplifier circuit is formulated and solved for two types of inputs to the amplifier - a constant voltage and a ramp. The resultant solutions shows an output that contains a term that is proportional to the derivative of the product of the input voltage and the time constant of the feedback network. The blade tip clearance capacitance is obtained by subtracting the output of a balancing reference channel followed by integration. The proposed sampled data algorithm corrects the environmental effects and varying rotor speeds on-line, making the system suitable for turbine instrumentation. System requirements, block diagrams, and typical application are included.

Discovering latent commercial networks from online financial news articles

NASA Astrophysics Data System (ADS)

Xia, Yunqing; Su, Weifeng; Lau, Raymond Y. K.; Liu, Yi

2013-08-01

Unlike most online social networks where explicit links among individual users are defined, the relations among commercial entities (e.g. firms) may not be explicitly declared in commercial Web sites. One main contribution of this article is the development of a novel computational model for the discovery of the latent relations among commercial entities from online financial news. More specifically, a CRF model which can exploit both structural and contextual features is applied to commercial entity recognition. In addition, a point-wise mutual information (PMI)-based unsupervised learning method is developed for commercial relation identification. To evaluate the effectiveness of the proposed computational methods, a prototype system called CoNet has been developed. Based on the financial news articles crawled from Google finance, the CoNet system achieves average F-scores of 0.681 and 0.754 in commercial entity recognition and commercial relation identification, respectively. Our experimental results confirm that the proposed shallow natural language processing methods are effective for the discovery of latent commercial networks from online financial news.

Robust output feedback H∞ control for networked control systems based on the occurrence probabilities of time delays

NASA Astrophysics Data System (ADS)

Guo, Chenyu; Zhang, Weidong; Bao, Jie

2012-02-01

This article is concerned with the problem of robust H ∞ output feedback control for a kind of networked control systems with time-varying network-induced delays. Instead of using boundaries of time delays to represent all time delays, the occurrence probability of each time delay is considered in H∞ stability analysis and stabilisation. The problem addressed is the design of an output feedback controller such that, for all admissible uncertainties, the resulting closed-loop system is stochastically stable for the zero disturbance input and also simultaneously achieves a prescribed H∞ performance level. It is shown that less conservativeness is obtained. A set of linear matrix inequalities is given to solve the corresponding controller design problem. An example is provided to show the effectiveness and applicability of the proposed method.

The Network Classroom.

ERIC Educational Resources Information Center

Maule, R. William

1993-01-01

Discussion of the role of new computer communications technologies in education focuses on modern networking systems, including fiber distributed data interface and Integrated Services Digital Network; strategies for implementing networked-based communication; and public online information resources for the classroom, including Bitnet, Internet,…

Multi-Relational Characterization of Dynamic Social Network Communities

NASA Astrophysics Data System (ADS)

Lin, Yu-Ru; Sundaram, Hari; Kelliher, Aisling

The emergence of the mediated social web - a distributed network of participants creating rich media content and engaging in interactive conversations through Internet-based communication technologies - has contributed to the evolution of powerful social, economic and cultural change. Online social network sites and blogs, such as Facebook, Twitter, Flickr and LiveJournal, thrive due to their fundamental sense of "community". The growth of online communities offers both opportunities and challenges for researchers and practitioners. Participation in online communities has been observed to influence people's behavior in diverse ways ranging from financial decision-making to political choices, suggesting the rich potential for diverse applications. However, although studies on the social web have been extensive, discovering communities from online social media remains challenging, due to the interdisciplinary nature of this subject. In this article, we present our recent work on characterization of communities in online social media using computational approaches grounded on the observations from social science.

Stationary average consensus protocol for a class of heterogeneous high-order multi-agent systems with application for aircraft

NASA Astrophysics Data System (ADS)

Rezaei, Mohammad Hadi; Menhaj, Mohammad Bagher

2018-01-01

This paper investigates the stationary average consensus problem for a class of heterogeneous-order multi-agent systems. The goal is to bring the positions of agents to the average of their initial positions while letting the other states converge to zero. To this end, three different consensus protocols are proposed. First, based on the auxiliary variables information among the agents under switching directed networks and state-feedback control, a protocol is proposed whereby all the agents achieve stationary average consensus. In the second and third protocols, by resorting to only measurements of relative positions of neighbouring agents under fixed balanced directed networks, two control frameworks are presented with two strategies based on state-feedback and output-feedback control. Finally, simulation results are given to illustrate the effectiveness of the proposed protocols.

Elective Self-Care Course Emphasizing Critical Reasoning Principles

PubMed Central

2011-01-01

Objectives. To create, implement, and assess a self-directed online course based on 3 critical reasoning principles to develop pharmacy students’ skills in literature appraisal, content, metacognition, and assessment. Design. Students completed 3 assignments for the course: compile a literature appraisal on a healthcare topic; plan learning objectives and meta-cognitive skills for a learning module; and create a case-based online lesson with multi-structured feedback. Assessment. An online exit survey evaluated students’ perceptions regarding development of ACE (agency, collaboration, expertise) principles and preparation for competency. Students reported acquisition of ACE principles and noted improvements in their learning approaches, sense of responsibility for individual and community learning, skills, and confidence. Conclusions. An online elective course in self-care addressed practice standards for patient safety, maintenance of competency, and interprofessional education by emphasizing critical reasoning skills. PMID:22171110

Neural dynamic programming and its application to control systems

NASA Astrophysics Data System (ADS)

Seong, Chang-Yun

There are few general practical feedback control methods for nonlinear MIMO (multi-input-multi-output) systems, although such methods exist for their linear counterparts. Neural Dynamic Programming (NDP) is proposed as a practical design method of optimal feedback controllers for nonlinear MIMO systems. NDP is an offspring of both neural networks and optimal control theory. In optimal control theory, the optimal solution to any nonlinear MIMO control problem may be obtained from the Hamilton-Jacobi-Bellman equation (HJB) or the Euler-Lagrange equations (EL). The two sets of equations provide the same solution in different forms: EL leads to a sequence of optimal control vectors, called Feedforward Optimal Control (FOC); HJB yields a nonlinear optimal feedback controller, called Dynamic Programming (DP). DP produces an optimal solution that can reject disturbances and uncertainties as a result of feedback. Unfortunately, computation and storage requirements associated with DP solutions can be problematic, especially for high-order nonlinear systems. This dissertation presents an approximate technique for solving the DP problem based on neural network techniques that provides many of the performance benefits (e.g., optimality and feedback) of DP and benefits from the numerical properties of neural networks. We formulate neural networks to approximate optimal feedback solutions whose existence DP justifies. We show the conditions under which NDP closely approximates the optimal solution. Finally, we introduce the learning operator characterizing the learning process of the neural network in searching the optimal solution. The analysis of the learning operator provides not only a fundamental understanding of the learning process in neural networks but also useful guidelines for selecting the number of weights of the neural network. As a result, NDP finds---with a reasonable amount of computation and storage---the optimal feedback solutions to nonlinear MIMO control problems that would be very difficult to solve with DP. NDP was demonstrated on several applications such as the lateral autopilot logic for a Boeing 747, the minimum fuel control of a double-integrator plant with bounded control, the backward steering of a two-trailer truck, and the set-point control of a two-link robot arm.

Effects of Feedback in an Online Algebra Intervention

ERIC Educational Resources Information Center

Bokhove, Christian; Drijvers, Paul

2012-01-01

The design and arrangement of appropriate automatic feedback in digital learning environment is a widely recognized issue. In this article, we investigate the effect of feedback on the design and the results of a digital intervention for algebra. Three feedback principles guided the intervention: timing and fading, crises, and feedback variation.…

Evaluating the feasibility of using online software to collect patient information in a chiropractic practice-based research network.

PubMed

Kania-Richmond, Ania; Weeks, Laura; Scholten, Jeffrey; Reney, Mikaël

2016-03-01

Practice based research networks (PBRNs) are increasingly used as a tool for evidence based practice. We developed and tested the feasibility of using software to enable online collection of patient data within a chiropractic PBRN to support clinical decision making and research in participating clinics. To assess the feasibility of using online software to collect quality patient information. The study consisted of two phases: 1) Assessment of the quality of information provided, using a standardized form; and 2) Exploration of patients' perspectives and experiences regarding online information provision through semi-structured interviews. Data analysis was descriptive. Forty-five new patients were recruited. Thirty-six completed online forms, which were submitted by an appropriate person 100% of the time, with an error rate of less than 1%, and submitted in a timely manner 83% of the time. Twenty-one participants were interviewed. Overall, online forms were preferred given perceived security, ease of use, and enabling provision of more accurate information. Use of online software is feasible, provides high quality information, and is preferred by most participants. A pen-and-paper format should be available for patients with this preference and in case of technical difficulties.

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

Proprioceptive feedback and brain computer interface (BCI) based neuroprostheses.

PubMed

Ramos-Murguialday, Ander; Schürholz, Markus; Caggiano, Vittorio; Wildgruber, Moritz; Caria, Andrea; Hammer, Eva Maria; Halder, Sebastian; Birbaumer, Niels

2012-01-01

Brain computer interface (BCI) technology has been proposed for motor neurorehabilitation, motor replacement and assistive technologies. It is an open question whether proprioceptive feedback affects the regulation of brain oscillations and therefore BCI control. We developed a BCI coupled on-line with a robotic hand exoskeleton for flexing and extending the fingers. 24 healthy participants performed five different tasks of closing and opening the hand: (1) motor imagery of the hand movement without any overt movement and without feedback, (2) motor imagery with movement as online feedback (participants see and feel their hand, with the exoskeleton moving according to their brain signals, (3) passive (the orthosis passively opens and closes the hand without imagery) and (4) active (overt) movement of the hand and rest. Performance was defined as the difference in power of the sensorimotor rhythm during motor task and rest and calculated offline for different tasks. Participants were divided in three groups depending on the feedback receiving during task 2 (the other tasks were the same for all participants). Group 1 (n = 9) received contingent positive feedback (participants' sensorimotor rhythm (SMR) desynchronization was directly linked to hand orthosis movements), group 2 (n = 8) contingent "negative" feedback (participants' sensorimotor rhythm synchronization was directly linked to hand orthosis movements) and group 3 (n = 7) sham feedback (no link between brain oscillations and orthosis movements). We observed that proprioceptive feedback (feeling and seeing hand movements) improved BCI performance significantly. Furthermore, in the contingent positive group only a significant motor learning effect was observed enhancing SMR desynchronization during motor imagery without feedback in time. Furthermore, we observed a significantly stronger SMR desynchronization in the contingent positive group compared to the other groups during active and passive movements. To summarize, we demonstrated that the use of contingent positive proprioceptive feedback BCI enhanced SMR desynchronization during motor tasks.

A Review of Research Ethics in Internet-Based Research

ERIC Educational Resources Information Center

Convery, Ian; Cox, Diane

2012-01-01

Internet-based research methods can include: online surveys, web page content analysis, videoconferencing for online focus groups and/or interviews, analysis of "e-conversations" through social networking sites, email, chat rooms, discussion boards and/or blogs. Over the last ten years, an upsurge in internet-based research (IBR) has led…

Use of Online Sources of Information by Dental Practitioners: Findings from The Dental Practice-Based Research Network

PubMed Central

Funkhouser, Ellen; Agee, Bonita S.; Gordan, Valeria V.; Rindal, D. Brad; Fellows, Jeffrey L.; Qvist, Vibeke; McClelland, Jocelyn; Gilbert, Gregg H.

2013-01-01

Objectives Estimate the proportion of dental practitioners who use online sources of information for practice guidance. Methods From a survey of 657 dental practitioners in The Dental Practice Based Research Network, four indicators of online use for practice guidance were calculated: read journals online, obtained continuing education (CDE) through online sources, rated an online source as most influential, and reported frequently using an online source for guidance. Demographics, journals read, and use of various sources of information for practice guidance in terms of frequency and influence were ascertained for each. Results Overall, 21% (n=138) were classified into one of the four indicators of online use: 14% (n=89) rated an online source as most influential and 13% (n=87) reported frequently using an online source for guidance; few practitioners (5%, n=34) read journals online, fewer (3%, n=17) obtained CDE through online sources. Use of online information sources varied considerably by region and practice characteristics. In general, the 4 indicators represented practitioners with as many differences as similarities to each other and to offline users. Conclusion A relatively small proportion of dental practitioners use information from online sources for practice guidance. Variation exists regarding practitioners’ use of online source resources and how they rate the value of offline information sources for practice guidance. PMID:22994848

The eSGID Process: How to Improve Teaching and Learning in Online Graduate Courses

ERIC Educational Resources Information Center

O'Neal-Hixson, Kelly; Long, Jenny; Bock, Marjorie

2017-01-01

Small Group Instructional Diagnosis (SGID) is a feedback process to collect midterm feedback from students. The process uses small focus group student interviews to identify strengths of the course, areas of concern, and suggestions to address concerns. The purpose of this paper is to shares experiences using on online format of Small Group…

Distribution of Feedback among Teacher and Students in Online Collaborative Learning in Small Groups

ERIC Educational Resources Information Center

Coll, Cesar; Rochera, Maria Jose; de Gispert, Ines; Diaz-Barriga, Frida

2013-01-01

This study explores the characteristics and distribution of the feedback provided by the participants (a teacher and her students) in an activity organized inside a collaborative online learning environment. We analyse 853 submissions made by two groups of graduate students and their teacher (N1 = 629 & N2 = 224) involved in the collaborative…

Effectiveness of an Online Automated Evaluation and Feedback System in an Introductory Computer Literacy Course

ERIC Educational Resources Information Center

Varank, Ilhan; Erkoç, M. Fatih; Büyükimdat, Meryem Köskeroglu; Aktas, Mehmet; Yeni, Sabiha; Adigüzel, Tufan; Cömert, Zafer; Esgin, Esad

2014-01-01

The purpose of this study was to investigate the effectiveness of an online automated evaluation and feedback system that assessed students' word processing assignments prepared with Microsoft Office Word. The participants of the study were 119 undergraduate teacher education students, 86 of whom were female and 32 were male, enrolled in different…

Open and Anonymous Peer Review in a Digital Online Environment Compared in Academic Writing Context

ERIC Educational Resources Information Center

Razi, Salim

2016-01-01

This study compares the impact of "open" and "anonymous" peer feedback as an adjunct to teacher-mediated feedback in a digital online environment utilising data gathered on an academic writing course at a Turkish university. Students were divided into two groups with similar writing proficiencies. Students peer reviewed papers…

Online social networking technologies, HIV knowledge, and sexual risk and testing behaviors among homeless youth.

PubMed

Young, Sean D; Rice, Eric

2011-02-01

This study evaluates associations between online social networking and sexual health behaviors among homeless youth in Los Angeles. We analyzed survey data from 201 homeless youth accessing services at a Los Angeles agency. Multivariate (regression and logistic) models assessed whether use of (and topics discussed on) online social networking technologies affect HIV knowledge, sexual risk behaviors, and testing for sexually transmitted infections (STIs). One set of results suggests that using online social networks for partner seeking (compared to not using the networks for seeking partners) is associated with increased sexual risk behaviors. Supporting data suggest that (1) using online social networks to talk about safe sex is associated with an increased likelihood of having met a recent sex partner online, and (2) having online sex partners and talking to friends on online social networks about drugs and partying is associated with increased exchange sex. However, results also suggest that online social network usage is associated with increased knowledge and HIV/STI prevention among homeless youth: (1) using online social networks to talk about love and safe sex is associated with increased knowledge about HIV, (2) using the networks to talk about love is associated with decreased exchange sex, and (3) merely being a member of an online social network is associated with increased likelihood of having previously tested for STIs. Taken together, this study suggests that online social networking and the topics discussed on these networks can potentially increase and decrease sexual risk behaviors depending on how the networks are used. Developing sexual health services and interventions on online social networks could reduce sexual risk behaviors.

Contingencies of self-worth and social-networking-site behavior.

PubMed

Stefanone, Michael A; Lackaff, Derek; Rosen, Devan

2011-01-01

Social-networking sites like Facebook enable people to share a range of personal information with expansive groups of "friends." With the growing popularity of media sharing online, many questions remain regarding antecedent conditions for this behavior. Contingencies of self-worth afford a more nuanced approach to variable traits that affect self-esteem, and may help explain online behavior. A total of 311 participants completed an online survey measuring such contingencies and typical behaviors on Facebook. First, exploratory factor analyses revealed an underlying structure to the seven dimensions of self-worth. Public-based contingencies explained online photo sharing (β = 0.158, p < 0.01), while private-based contingencies demonstrated a negative relationship with time online (β = -0.186, p < 0.001). Finally, the appearance contingency for self-worth had the strongest relationship with the intensity of online photo sharing (β = 0.242), although no relationship was evident for time spent managing profiles.

Engineering Online and In-Person Social Networks for Physical Activity: A Randomized Trial.

PubMed

Rovniak, Liza S; Kong, Lan; Hovell, Melbourne F; Ding, Ding; Sallis, James F; Ray, Chester A; Kraschnewski, Jennifer L; Matthews, Stephen A; Kiser, Elizabeth; Chinchilli, Vernon M; George, Daniel R; Sciamanna, Christopher N

2016-12-01

Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. The purpose of this study was to conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively measured outcomes. Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3 % male, 83.4 % overweight/obese) were randomized to one of three groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking as well as prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Participants increased their MVPA by 21.0 min/week, 95 % CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. The trial was registered with the ClinicalTrials.gov (NCT01142804).

The Stratonovich formulation of quantum feedback network rules

NASA Astrophysics Data System (ADS)

Gough, John E.

2016-12-01

We express the rules for forming quantum feedback networks using the Stratonovich form of quantum stochastic calculus rather than the Itō or SLH (J. E. Gough and M. R. James, "Quantum feedback networks: Hamiltonian formulation," Commun. Math. Phys. 287, 1109 (2009), J. E. Gough and M. R. James, "The Series product and its application to quantum feedforward and feedback networks," IEEE Trans. Autom. Control 54, 2530 (2009)) form. Remarkably the feedback reduction rule implies that we obtain the Schur complement of the matrix of Stratonovich coupling operators where we short out the internal input/output coefficients.

Exploring the Neural Basis of Avatar Identification in Pathological Internet Gamers and of Self-Reflection in Pathological Social Network Users

PubMed Central

Leménager, Tagrid; Dieter, Julia; Hill, Holger; Hoffmann, Sabine; Reinhard, Iris; Beutel, Martin; Vollstädt-Klein, Sabine; Kiefer, Falk; Mann, Karl

2016-01-01

Background and aims Internet gaming addiction appears to be related to self-concept deficits and increased angular gyrus (AG)-related identification with one’s avatar. For increased social network use, a few existing studies suggest striatal-related positive social feedback as an underlying factor. However, whether an impaired self-concept and its reward-based compensation through the online presentation of an idealized version of the self are related to pathological social network use has not been investigated yet. We aimed to compare different stages of pathological Internet game and social network use to explore the neural basis of avatar and self-identification in addictive use. Methods About 19 pathological Internet gamers, 19 pathological social network users, and 19 healthy controls underwent functional magnetic resonance imaging while completing a self-retrieval paradigm, asking participants to rate the degree to which various self-concept-related characteristics described their self, ideal, and avatar. Self-concept-related characteristics were also psychometrically assessed. Results Psychometric testing indicated that pathological Internet gamers exhibited higher self-concept deficits generally, whereas pathological social network users exhibit deficits in emotion regulation only. We observed left AG hyperactivations in Internet gamers during avatar reflection and a correlation with symptom severity. Striatal hypoactivations during self-reflection (vs. ideal reflection) were observed in social network users and were correlated with symptom severity. Discussion and conclusion Internet gaming addiction appears to be linked to increased identification with one’s avatar, evidenced by high left AG activations in pathological Internet gamers. Addiction to social networks seems to be characterized by emotion regulation deficits, reflected by reduced striatal activation during self-reflection compared to during ideal reflection. PMID:27415603

Exploring the Neural Basis of Avatar Identification in Pathological Internet Gamers and of Self-Reflection in Pathological Social Network Users.

PubMed

Leménager, Tagrid; Dieter, Julia; Hill, Holger; Hoffmann, Sabine; Reinhard, Iris; Beutel, Martin; Vollstädt-Klein, Sabine; Kiefer, Falk; Mann, Karl

2016-09-01

Background and aims Internet gaming addiction appears to be related to self-concept deficits and increased angular gyrus (AG)-related identification with one's avatar. For increased social network use, a few existing studies suggest striatal-related positive social feedback as an underlying factor. However, whether an impaired self-concept and its reward-based compensation through the online presentation of an idealized version of the self are related to pathological social network use has not been investigated yet. We aimed to compare different stages of pathological Internet game and social network use to explore the neural basis of avatar and self-identification in addictive use. Methods About 19 pathological Internet gamers, 19 pathological social network users, and 19 healthy controls underwent functional magnetic resonance imaging while completing a self-retrieval paradigm, asking participants to rate the degree to which various self-concept-related characteristics described their self, ideal, and avatar. Self-concept-related characteristics were also psychometrically assessed. Results Psychometric testing indicated that pathological Internet gamers exhibited higher self-concept deficits generally, whereas pathological social network users exhibit deficits in emotion regulation only. We observed left AG hyperactivations in Internet gamers during avatar reflection and a correlation with symptom severity. Striatal hypoactivations during self-reflection (vs. ideal reflection) were observed in social network users and were correlated with symptom severity. Discussion and conclusion Internet gaming addiction appears to be linked to increased identification with one's avatar, evidenced by high left AG activations in pathological Internet gamers. Addiction to social networks seems to be characterized by emotion regulation deficits, reflected by reduced striatal activation during self-reflection compared to during ideal reflection.

Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study

PubMed Central

Choi, Jun-Ho; Lee, Jong-Seok

2016-01-01

Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods. PMID:26793137

Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study.

PubMed

Choi, Jun-Ho; Lee, Jong-Seok

2015-01-01

Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods.

Hybrid neural network for density limit disruption prediction and avoidance on J-TEXT tokamak

NASA Astrophysics Data System (ADS)

Zheng, W.; Hu, F. R.; Zhang, M.; Chen, Z. Y.; Zhao, X. Q.; Wang, X. L.; Shi, P.; Zhang, X. L.; Zhang, X. Q.; Zhou, Y. N.; Wei, Y. N.; Pan, Y.; J-TEXT team

2018-05-01

Increasing the plasma density is one of the key methods in achieving an efficient fusion reaction. High-density operation is one of the hot topics in tokamak plasmas. Density limit disruptions remain an important issue for safe operation. An effective density limit disruption prediction and avoidance system is the key to avoid density limit disruptions for long pulse steady state operations. An artificial neural network has been developed for the prediction of density limit disruptions on the J-TEXT tokamak. The neural network has been improved from a simple multi-layer design to a hybrid two-stage structure. The first stage is a custom network which uses time series diagnostics as inputs to predict plasma density, and the second stage is a three-layer feedforward neural network to predict the probability of density limit disruptions. It is found that hybrid neural network structure, combined with radiation profile information as an input can significantly improve the prediction performance, especially the average warning time ({{T}warn} ). In particular, the {{T}warn} is eight times better than that in previous work (Wang et al 2016 Plasma Phys. Control. Fusion 58 055014) (from 5 ms to 40 ms). The success rate for density limit disruptive shots is above 90%, while, the false alarm rate for other shots is below 10%. Based on the density limit disruption prediction system and the real-time density feedback control system, the on-line density limit disruption avoidance system has been implemented on the J-TEXT tokamak.

Evaluating the performance of vehicular platoon control under different network topologies of initial states

NASA Astrophysics Data System (ADS)

Li, Yongfu; Li, Kezhi; Zheng, Taixiong; Hu, Xiangdong; Feng, Huizong; Li, Yinguo

2016-05-01

This study proposes a feedback-based platoon control protocol for connected autonomous vehicles (CAVs) under different network topologies of initial states. In particularly, algebraic graph theory is used to describe the network topology. Then, the leader-follower approach is used to model the interactions between CAVs. In addition, feedback-based protocol is designed to control the platoon considering the longitudinal and lateral gaps simultaneously as well as different network topologies. The stability and consensus of the vehicular platoon is analyzed using the Lyapunov technique. Effects of different network topologies of initial states on convergence time and robustness of platoon control are investigated. Results from numerical experiments demonstrate the effectiveness of the proposed protocol with respect to the position and velocity consensus in terms of the convergence time and robustness. Also, the findings of this study illustrate the convergence time of the control protocol is associated with the initial states, while the robustness is not affected by the initial states significantly.

Consensus Algorithms for Networks of Systems with Second- and Higher-Order Dynamics

NASA Astrophysics Data System (ADS)

Fruhnert, Michael

This thesis considers homogeneous networks of linear systems. We consider linear feedback controllers and require that the directed graph associated with the network contains a spanning tree and systems are stabilizable. We show that, in continuous-time, consensus with a guaranteed rate of convergence can always be achieved using linear state feedback. For networks of continuous-time second-order systems, we provide a new and simple derivation of the conditions for a second-order polynomials with complex coefficients to be Hurwitz. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. Based on the conditions found, methods to compute feedback gains are proposed. We show that gains can be chosen such that consensus is achieved robustly over a variety of communication structures and system dynamics. We also consider the use of static output feedback. For networks of discrete-time second-order systems, we provide a new and simple derivation of the conditions for a second-order polynomials with complex coefficients to be Schur. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. We show that consensus can always be achieved for marginally stable systems and discretized systems. Simple conditions for consensus achieving controllers are obtained when the Laplacian eigenvalues are all real. For networks of continuous-time time-variant higher-order systems, we show that uniform consensus can always be achieved if systems are quadratically stabilizable. In this case, we provide a simple condition to obtain a linear feedback control. For networks of discrete-time higher-order systems, we show that constant gains can be chosen such that consensus is achieved for a variety of network topologies. First, we develop simple results for networks of time-invariant systems and networks of time-variant systems that are given in controllable canonical form. Second, we formulate the problem in terms of Linear Matrix Inequalities (LMIs). The condition found simplifies the design process and avoids the parallel solution of multiple LMIs. The result yields a modified Algebraic Riccati Equation (ARE) for which we present an equivalent LMI condition.

Epidemic mitigation via awareness propagation in communication networks: the role of time scales

NASA Astrophysics Data System (ADS)

Wang, Huijuan; Chen, Chuyi; Qu, Bo; Li, Daqing; Havlin, Shlomo

2017-07-01

The participation of individuals in multi-layer networks allows for feedback between network layers, opening new possibilities to mitigate epidemic spreading. For instance, the spread of a biological disease such as Ebola in a physical contact network may trigger the propagation of the information related to this disease in a communication network, e.g. an online social network. The information propagated in the communication network may increase the awareness of some individuals, resulting in them avoiding contact with their infected neighbors in the physical contact network, which might protect the population from the infection. In this work, we aim to understand how the time scale γ of the information propagation (speed that information is spread and forgotten) in the communication network relative to that of the epidemic spread (speed that an epidemic is spread and cured) in the physical contact network influences such mitigation using awareness information. We begin by proposing a model of the interaction between information propagation and epidemic spread, taking into account the relative time scale γ. We analytically derive the average fraction of infected nodes in the meta-stable state for this model (i) by developing an individual-based mean-field approximation (IBMFA) method and (ii) by extending the microscopic Markov chain approach (MMCA). We show that when the time scale γ of the information spread relative to the epidemic spread is large, our IBMFA approximation is better compared to MMCA near the epidemic threshold, whereas MMCA performs better when the prevalence of the epidemic is high. Furthermore, we find that an optimal mitigation exists that leads to a minimal fraction of infected nodes. The optimal mitigation is achieved at a non-trivial relative time scale γ, which depends on the rate at which an infected individual becomes aware. Contrary to our intuition, information spread too fast in the communication network could reduce the mitigation effect. Finally, our finding has been validated in the real-world two-layer network obtained from the location-based social network Brightkite.

Urban Mobility and Location-Based Social Networks: Social, Economic and Environmental Incentives

ERIC Educational Resources Information Center

Zhang, Ke

2016-01-01

Location-based social networks (LBSNs) have recently attracted the interest of millions of users who can now not only connect and interact with their friends--as it also happens in traditional online social networks--but can also voluntarily share their whereabouts in real time. A location database is the backbone of a location-based social…

A cost-effective measurement-device-independent quantum key distribution system for quantum networks

NASA Astrophysics Data System (ADS)

Valivarthi, Raju; Zhou, Qiang; John, Caleb; Marsili, Francesco; Verma, Varun B.; Shaw, Matthew D.; Nam, Sae Woo; Oblak, Daniel; Tittel, Wolfgang

2017-12-01

We experimentally realize a measurement-device-independent quantum key distribution (MDI-QKD) system. It is based on cost-effective and commercially available hardware such as distributed feedback lasers and field-programmable gate arrays that enable time-bin qubit preparation and time-tagging, and active feedback systems that allow for compensation of time-varying properties of photons after transmission through deployed fiber. We examine the performance of our system, and conclude that its design does not compromise performance. Our demonstration paves the way for MDI-QKD-based quantum networks in star-type topology that extend over more than 100 km distance.

Improving Teach Astronomy: A Survey of Instructors

NASA Astrophysics Data System (ADS)

Wenger, Matthew; Riabokin, Malanka; Impey, Chris David

2018-01-01

Teach Astronomy is a website that provides educational resources for introductory astronomy. The motivation behind constructing this site was to provide quality online educational tools for use as a primary or supplementary instructional resource for teachers and students. The website provides an online textbook, glossary, podcasts and video summaries of concepts. As the popularity of online courses steadily increases, so does the demand for robust online educational resources. In order to cater to our users, our team conducted a survey of the instructors that use Teach Astronomy site for feedback for use in updating and streamlining the website content. The survey collected feedback regarding functionality of each of the website tools, in which courses the site was being used, and the motivation of the instructors use of our site. The overwhelming majority of responses indicate that instructors use the website as a class textbook in introductory astronomy courses for non-science majors, and instructors also generally tended to agree that the site content was comprehensive and lucid. One interesting result of the survey is to cluster topics in a way that is consistent with different levels of instruction (i.e. grouping middle-school level content and university level content distinctly). Our team will use this feedback to improve the Teach Astronomy website and maintain it as a high-quality, free online resource. We will also continue to gather feedback from instructors to ensure that the Teach Astronomy website stays current and remains a valuable online resource for instructors around the country.

A continually online-trained neural network controller for brushless DC motor drives

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

Rubaai, A.; Kotaru, R.; Kankam, M.D.

2000-04-01

In this paper, a high-performance controller with simultaneous online identification and control is designed for brushless dc motor drives. The dynamics of the motor/load are modeled online, and controlled using two different neural network based identification and control schemes, as the system is in operation. In the first scheme, an attempt is made to control the rotor angular speed, utilizing a single three-hidden-layer network. The second scheme attempts to control the stator currents, using a predetermined control law as a function of the estimated states. This schemes incorporates three multilayered feedforward neural networks that are online trained, using the Levenburg-Marquadtmore » training algorithm. The control of the direct and quadrature components of the stator current successfully tracked a wide variety of trajectories after relatively short online training periods. The control strategy adapts to the uncertainties of the motor/load dynamics and, in addition, learns their inherent nonlinearities. Simulation results illustrated that a neurocontroller used in conjunction with adaptive control schemes can result in a flexible control device which may be utilized in a wide range of environments.« less

Modeling gene regulatory network motifs using statecharts

PubMed Central

2012-01-01

Background Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks. For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs. Results We present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal. We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation. Conclusions We present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed. PMID:22536967

UK policy on social networking sites and online health: From informed patient to informed consumer?

PubMed Central

Hunt, Daniel; Koteyko, Nelya; Gunter, Barrie

2015-01-01

Background Social networking sites offer new opportunities for communication between and amongst health care professionals, patients and members of the public. In doing so, they have the potential to facilitate public access to health care information, peer-support networks, health policy fora and online consultations. Government policies and guidance from professional organisations have begun to address the potential of these technologies in the domain of health care and the responsibilities they entail for their users. Objective Adapting a discourse analytic framework for the analysis of policy documents, this review paper critically examines discussions of social networking sites in recent government and professional policy documents. It focuses particularly on who these organisations claim should use social media, for what purposes, and what the anticipated outcomes of use will be for patients and the organisations themselves. Conclusion Recent policy documents have configured social media as a new means with which to harvest patient feedback on health care encounters and communicate health care service information with which patients and the general public can be ‘empowered’ to make responsible decisions. In orienting to social media as a vehicle for enabling consumer choice, these policies encourage the marketization of health information through a greater role for non-profit and commercial organisations in the eHealth domain. At the same time, current policy largely overlooks the role of social media in mediating ongoing support and self-management for patients with long-term conditions. PMID:29942541

Design of a Model-Based Online Management Information System for Interlibrary Loan Networks.

ERIC Educational Resources Information Center

Rouse, Sandra H.; Rouse, William B.

1979-01-01

Discusses the design of a model-based management information system in terms of mathematical/statistical, information processing, and human factors issues and presents a prototype system for interlibrary loan networks. (Author/CWM)

Mittag-Leffler synchronization of delayed fractional-order bidirectional associative memory neural networks with discontinuous activations: state feedback control and impulsive control schemes.

PubMed

Ding, Xiaoshuai; Cao, Jinde; Zhao, Xuan; Alsaadi, Fuad E

2017-08-01

This paper is concerned with the drive-response synchronization for a class of fractional-order bidirectional associative memory neural networks with time delays, as well as in the presence of discontinuous activation functions. The global existence of solution under the framework of Filippov for such networks is firstly obtained based on the fixed-point theorem for condensing map. Then the state feedback and impulsive controllers are, respectively, designed to ensure the Mittag-Leffler synchronization of these neural networks and two new synchronization criteria are obtained, which are expressed in terms of a fractional comparison principle and Razumikhin techniques. Numerical simulations are presented to validate the proposed methodologies.

Converting Student Support Services to Online Delivery.

ERIC Educational Resources Information Center

Brigham, David E.

2001-01-01

Uses a systems framework to analyze the creation of student support services for distance education at Regents College: electronic advising, electronic peer network, online course database, online bookstore, virtual library, and alumni services website. Addresses the issues involved in converting distance education programs from print-based and…

Nonlinear filter based decision feedback equalizer for optical communication systems.

PubMed

Han, Xiaoqi; Cheng, Chi-Hao

2014-04-07

Nonlinear impairments in optical communication system have become a major concern of optical engineers. In this paper, we demonstrate that utilizing a nonlinear filter based Decision Feedback Equalizer (DFE) with error detection capability can deliver a better performance compared with the conventional linear filter based DFE. The proposed algorithms are tested in simulation using a coherent 100 Gb/sec 16-QAM optical communication system in a legacy optical network setting.

Participatory surveillance of diabetes device safety: a social media-based complement to traditional FDA reporting.

PubMed

Mandl, Kenneth D; McNabb, Marion; Marks, Norman; Weitzman, Elissa R; Kelemen, Skyler; Eggleston, Emma M; Quinn, Maryanne

2014-01-01

Malfunctions or poor usability of devices measuring glucose or delivering insulin are reportable to the FDA. Manufacturers submit 99.9% of these reports. We test online social networks as a complementary source to traditional FDA reporting of device-related adverse events. Participatory surveillance of members of a non-profit online social network, TuDiabetes.org, from October 2011 to September 2012. Subjects were volunteers from a group within TuDiabetes, actively engaged online in participatory surveillance. They used the free TuAnalyze app, a privacy-preserving method to report detailed clinical information, available through the network. Network members were polled about finger-stick blood glucose monitors, continuous glucose monitors, and insulin delivery devices, including insulin pumps and insulin pens. Of 549 participants, 75 reported device-related adverse events, nearly half (48.0%) requiring intervention from another person to manage the event. Only three (4.0%) of these were reported by participants to the FDA. All TuAnalyze reports contained outcome information compared with 22% of reports to the FDA. Hypoglycemia and hyperglycemia were experienced by 48.0% and 49.3% of participants, respectively. Members of an online community readily engaged in participatory surveillance. While polling distributed online populations does not yield generalizable, denominator-based rates, this approach can characterize risk within online communities using a bidirectional communication channel that enables reach-back and intervention. Engagement of distributed communities in social networks is a viable complementary approach to traditional public health surveillance for adverse events related to medical devices. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

JGME-ALiEM Hot Topics in Medical Education Online Journal Club: An Analysis of a Virtual Discussion About Resident Teachers.

PubMed

Sherbino, Jonathan; Joshi, Nikita; Lin, Michelle

2015-09-01

In health professionals' education, senior learners play a key role in the teaching of junior colleagues. We describe an online discussion about residents as teachers to highlight the topic and the online journal club medium. In January 2015, the Journal of Graduate Medical Education (JGME) and the Academic Life in Emergency Medicine blog facilitated an open-access, online, weeklong journal club on the JGME article "What Makes a Great Resident Teacher? A Multicenter Survey of Medical Students Attending an Internal Medicine Conference." Social media platforms used to promote asynchronous discussions included a blog, a video discussion via Google Hangouts on Air, and Twitter. We performed a thematic analysis of the discussion. Web analytics were captured as a measure of impact. The blog post garnered 1324 page views from 372 cities in 42 countries. Twitter was used to endorse discussion points, while blog comments provided opinions or responded to an issue. The discussion focused on why resident feedback was devalued by medical students. Proposed explanations included feedback not being labeled as such, the process of giving delivery, the source of feedback, discrepancies with self-assessment, and threats to medical student self-image. The blog post resulted in a crowd-sourced repository of resident teacher resources. An online journal club provides a novel discussion forum across multiple social media platforms to engage authors, content experts, and the education community. Crowd-sourced analysis of the resident teacher role suggests that resident feedback to medical students is important, and barriers to student acceptance of feedback can be overcome.

Efficacy of a Web-Based, Tailored, Alcohol Prevention/Intervention Program for College Students: 3-Month Follow-Up

ERIC Educational Resources Information Center

Bingham, C. Raymond; Barretto, Andrea Ippel; Walton, Maureen A.; Bryant, Christopher M.; Shope, Jean T.; Raghunathan, Trivellore E.

2011-01-01

This study presents the results of an efficacy evaluation of a web-based brief motivational alcohol prevention/intervention program called "Michigan Prevention and Alcohol Safety for Students" (M-PASS). Four on-line sessions providing individually-tailored feedback were delivered to first-year college students over 9 weeks. Non- and…

EELAB: an innovative educational resource in occupational medicine.

PubMed

Zhou, A Y; Dodman, J; Hussey, L; Sen, D; Rayner, C; Zarin, N; Agius, R

2017-07-01

Postgraduate education, training and clinical governance in occupational medicine (OM) require easily accessible yet rigorous, research and evidence-based tools based on actual clinical practice. To develop and evaluate an online resource helping physicians develop their OM skills using their own cases of work-related ill-health (WRIH). WRIH data reported by general practitioners (GPs) to The Health and Occupation Research (THOR) network were used to identify common OM clinical problems, their reported causes and management. Searches were undertaken for corresponding evidence-based and audit guidelines. A web portal entitled Electronic, Experiential, Learning, Audit and Benchmarking (EELAB) was designed to enable access to interactive resources preferably by entering data about actual cases. EELAB offered disease-specific online learning and self-assessment, self-audit of clinical management against external standards and benchmarking against their peers' practices as recorded in the research database. The resource was made available to 250 GPs and 224 occupational physicians in UK as well as postgraduate OM students for evaluation. Feedback was generally very favourable with physicians reporting their EELAB use for case-based assignments. Comments such as those suggesting a wider range of clinical conditions have guided further improvement. External peer-reviewed evaluation resulted in accreditation by the Royal College of GPs and by the Faculties of OM (FOM) of London and of Ireland. This innovative resource has been shown to achieve education, self-audit and benchmarking objectives, based on the participants' clinical practice and an extensive research database. © The Author 2017. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Reinforcement-learning-based output-feedback control of nonstrict nonlinear discrete-time systems with application to engine emission control.

PubMed

Shih, Peter; Kaul, Brian C; Jagannathan, Sarangapani; Drallmeier, James A

2009-10-01

A novel reinforcement-learning-based output adaptive neural network (NN) controller, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility function and control inputs. All NN weights adapt online toward minimization of a performance index, utilizing the gradient-descent-based rule, in contrast with iteration-based adaptive-critic schemes. Lyapunov functions are used to show the stability of the closed-loop tracking error, weights, and observer estimates. Separation and certainty equivalence principles, persistency of excitation condition, and linearity in the unknown parameter assumption are not needed. Experimental results on a spark ignition (SI) engine operating lean at an equivalence ratio of 0.75 show a significant (25%) reduction in cyclic dispersion in heat release with control, while the average fuel input changes by less than 1% compared with the uncontrolled case. Consequently, oxides of nitrogen (NO(x)) drop by 30%, and unburned hydrocarbons drop by 16% with control. Overall, NO(x)'s are reduced by over 80% compared with stoichiometric levels.

Online social networks—Paradise of computer viruses

NASA Astrophysics Data System (ADS)

Fan, W.; Yeung, K. H.

2011-01-01

Online social network services have attracted more and more users in recent years. So the security of social networks becomes a critical problem. In this paper, we propose a virus propagation model based on the application network of Facebook, which is the most popular among these social network service providers. We also study the virus propagation with an email virus model and compare the behaviors of a virus spreading on Facebook with the original email network. It is found that Facebook provides the same chance for a virus spreading while it gives a platform for application developers. And a virus will spread faster in the Facebook network if users of Facebook spend more time on it.

Off-lexicon online Arabic handwriting recognition using neural network

NASA Astrophysics Data System (ADS)

Yahia, Hamdi; Chaabouni, Aymen; Boubaker, Houcine; Alimi, Adel M.

2017-03-01

This paper highlights a new method for online Arabic handwriting recognition based on graphemes segmentation. The main contribution of our work is to explore the utility of Beta-elliptic model in segmentation and features extraction for online handwriting recognition. Indeed, our method consists in decomposing the input signal into continuous part called graphemes based on Beta-Elliptical model, and classify them according to their position in the pseudo-word. The segmented graphemes are then described by the combination of geometric features and trajectory shape modeling. The efficiency of the considered features has been evaluated using feed forward neural network classifier. Experimental results using the benchmarking ADAB Database show the performance of the proposed method.

Human-Centered Development of an Online Social Network for Metabolic Syndrome Management.

PubMed

Núñez-Nava, Jefersson; Orozco-Sánchez, Paola A; López, Diego M; Ceron, Jesus D; Alvarez-Rosero, Rosa E

2016-01-01

According to the International Diabetes Federation (IDF), a quarter of the world's population has Metabolic Syndrome (MS). To develop (and assess the users' degree of satisfaction of) an online social network for patients who suffer from Metabolic Syndrome, based on the recommendations and requirements of the Human-Centered Design. Following the recommendations of the ISO 9241-210 for Human-Centered Design (HCD), an online social network was designed to promote physical activity and healthy nutrition. In order to guarantee the active participation of the users during the development of the social network, a survey, an in-depth interview, a focal group, and usability tests were carried out with people suffering from MS. The study demonstrated how the different activities, recommendations, and requirements of the ISO 9241-210 are integrated into a traditional software development process. Early usability tests demonstrated that the user's acceptance and the effectiveness and efficiency of the social network are satisfactory.

The Effect of Online Peer Feedback on the Academic Writing Ability of Iranian EFL Learners

ERIC Educational Resources Information Center

Moradi, Mohammad Reza; Karimpour, Zahra

2012-01-01

This paper reports an exploratory study of 60 English as a foreign language (EFL) student's experiences of online peer feedback in an essay writing course at Islamic Azad University, Dezful Branch. They were required to comment on their peers' writing essays using the checklist to whom had been made available, but in different ways. The groups…

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks

PubMed Central

Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

2015-01-01

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns. PMID:26291608

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.

PubMed

Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

2015-08-01

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns.

Beauty premium: Event-related potentials evidence of how physical attractiveness matters in online peer-to-peer lending.

PubMed

Jin, Jia; Fan, Bonai; Dai, Shenyi; Ma, Qingguo

2017-02-15

Although it is well known that attractiveness-based impressions affect the labor market, election outcomes and many other social activities, little is known about the role physical attractiveness plays in financial transactions. With the development of online finance, peer-to-peer lending has become one of the most important ways in which businesses or individuals raise capital. However, because of information asymmetry, the lender must decide whether or not to lend money to a stranger based on limited information, resulting in their decision being influenced by many other factors. In the current study, we investigated how potential borrowers' facial attractiveness influenced lenders' attitudes toward borrowers' repayment behavior at the brain level by using event-related potentials. At the priming stage, photos of attractive borrowers induced smaller N200 amplitude than photos of unattractive borrowers. Meanwhile, at the feedback stage, compared with the condition of repaying on time, breach of repayment from unattractive borrowers induced larger feedback-related negativity (FRN) amplitude, which was a frontal-central negative deflection and would be enhanced by the unexpected outcome. Furthermore, smaller P300 amplitude was also elicited by the condition of not repaying on time. These differences in the FRN and P300 amplitudes were not observed between negative and positive feedback from attractive borrowers. Therefore, our findings suggest that the beauty premium phenomenon is present in online peer-to-peer lending and that lenders were more tolerant toward attractive borrowers' dishonest behavior. Copyright © 2017 Elsevier B.V. All rights reserved.

Learner Perceptions of Online Peer Pronunciation Feedback through P-Check

ERIC Educational Resources Information Center

Yonesaka, Suzanne M.

2017-01-01

Receiving adequate pronunciation feedback is an ongoing challenge for L2 learners. Although instructors are the most important source of corrective pronunciation feedback (Szpyra, 2014; Timson, 2007), L2 learners can also benefit from peer pronunciation feedback (Lord, 2008; Kim & Yoon, 2014; Roccamo, 2015). This paper examines Japanese…

Evaluating Preference for Graphic Feedback on Correct versus Incorrect Performance

ERIC Educational Resources Information Center

Sigurdsson, Sigurdur O.; Ring, Brandon M.

2013-01-01

The current study evaluated preferences of undergraduate students for graphic feedback on percentage of incorrect performance versus feedback on percentage of correct performance. A total of 108 participants were enrolled in the study and received graphic feedback on performance on 12 online quizzes. One half of participants received graphic…

Online Variational Bayesian Filtering-Based Mobile Target Tracking in Wireless Sensor Networks

PubMed Central

Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

2014-01-01

The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer–Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying. PMID:25393784

Dynamic topographical pattern classification of multichannel prefrontal NIRS signals: II. Online differentiation of mental arithmetic and rest

NASA Astrophysics Data System (ADS)

Schudlo, Larissa C.; Chau, Tom

2014-02-01

Objective. Near-infrared spectroscopy (NIRS) has recently gained attention as a modality for brain-computer interfaces (BCIs), which may serve as an alternative access pathway for individuals with severe motor impairments. For NIRS-BCIs to be used as a real communication pathway, reliable online operation must be achieved. Yet, only a limited number of studies have been conducted online to date. These few studies were carried out under a synchronous paradigm and did not accommodate an unconstrained resting state, precluding their practical clinical implication. Furthermore, the potentially discriminative power of spatiotemporal characteristics of activation has yet to be considered in an online NIRS system. Approach. In this study, we developed and evaluated an online system-paced NIRS-BCI which was driven by a mental arithmetic activation task and accommodated an unconstrained rest state. With a dual-wavelength, frequency domain near-infrared spectrometer, measurements were acquired over nine sites of the prefrontal cortex, while ten able-bodied participants selected letters from an on-screen scanning keyboard via intentionally controlled brain activity (using mental arithmetic). Participants were provided dynamic NIR topograms as continuous visual feedback of their brain activity as well as binary feedback of the BCI's decision (i.e. if the letter was selected or not). To classify the hemodynamic activity, temporal features extracted from the NIRS signals and spatiotemporal features extracted from the dynamic NIR topograms were used in a majority vote combination of multiple linear classifiers. Main results. An overall online classification accuracy of 77.4 ± 10.5% was achieved across all participants. The binary feedback was found to be very useful during BCI use, while not all participants found value in the continuous feedback provided. Significance. These results demonstrate that mental arithmetic is a potent mental task for driving an online system-paced NIRS-BCI. BCI feedback that reflects the classifier's decision has the potential to improve user performance. The proposed system can provide a framework for future online NIRS-BCI development and testing.

Adaptive optimal stochastic state feedback control of resistive wall modes in tokamaks

NASA Astrophysics Data System (ADS)

Sun, Z.; Sen, A. K.; Longman, R. W.

2006-01-01

An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least-square method with exponential forgetting factor and covariance resetting is used to identify (experimentally determine) the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used.

Adaptive Optimal Stochastic State Feedback Control of Resistive Wall Modes in Tokamaks

NASA Astrophysics Data System (ADS)

Sun, Z.; Sen, A. K.; Longman, R. W.

2007-06-01

An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least square method with exponential forgetting factor and covariance resetting is used to identify the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used.

Social media for lifelong learning.

PubMed

Kind, Terry; Evans, Yolanda

2015-04-01

Learning is ongoing, and can be considered a social activity. In this paper we aim to provide a review of the use of social media for lifelong learning. We start by defining lifelong learning, drawing upon principles of continuous professional development and adult learning theory. We searched Embase and MEDLINE from 2004-2014 for search terms relevant to social media and learning. We describe examples of lifelong learners using social media in medical education and healthcare that have been reported in the peer-reviewed literature. Medical or other health professions students may have qualities consistent with being a lifelong learner, yet once individuals move beyond structured learning environments they will need to recognize their own gaps in knowledge and skills over time and be motivated to fill them, thereby incorporating lifelong learning principles into their day-to-day practice. Engagement with social media can parallel engagement in the learning process over time, to the extent that online social networking fosters feedback and collaboration. The use of social media and online networking platforms are a key way to continuously learn in today's information sharing society. Additional research is needed, particularly rigorous studies that extend beyond learner satisfaction to knowledge, behaviour change, and outcomes.

Beyond the online catalog: developing an academic information system in the sciences.

PubMed Central

Crawford, S; Halbrook, B; Kelly, E; Stucki, L

1987-01-01

The online public access catalog consists essentially of a machine-readable database with network capabilities. Like other computer-based information systems, it may be continuously enhanced by the addition of new capabilities and databases. It may also become a gateway to other information networks. This paper reports the evolution of the Bibliographic Access and Control System (BACS) of Washington University in end-user searching, current awareness services, information management, and administrative functions. Ongoing research and development and the future of the online catalog are also discussed. PMID:3315052

Beyond the online catalog: developing an academic information system in the sciences.

PubMed

Crawford, S; Halbrook, B; Kelly, E; Stucki, L

1987-07-01

The online public access catalog consists essentially of a machine-readable database with network capabilities. Like other computer-based information systems, it may be continuously enhanced by the addition of new capabilities and databases. It may also become a gateway to other information networks. This paper reports the evolution of the Bibliographic Access and Control System (BACS) of Washington University in end-user searching, current awareness services, information management, and administrative functions. Ongoing research and development and the future of the online catalog are also discussed.

An investigation of assessment and feedback practices in fully asynchronous online undergraduate mathematics courses

NASA Astrophysics Data System (ADS)

Trenholm, Sven; Alcock, Lara; Robinson, Carol

2015-11-01

Research suggests it is difficult to learn mathematics in the fully asynchronous online (FAO) instructional modality, yet little is known about associated teaching and assessment practices. In this study, we investigate FAO mathematics assessment and feedback practices in particular consideration of both claims and findings that these practices have a powerful influence on learning. A survey questionnaire was constructed and completed by 70 FAO undergraduate mathematics instructors, mostly from the USA, who were each asked to detail their assessment and feedback practices in a single FAO mathematics course. Alongside these questions, participants also answered the 16-item version of the Approaches to Teaching Inventory. In addition, a novel feedback framework was also created and used to examine how feedback practices may be related to participants' approaches to teaching. Results show that assessment and feedback practices are varied and complex: in particular, we found there was not a simple emphasis on summative assessment instruments, nor a concomitant expectation these would always be invigilated. Though richer assessment feedback appears to be emphasized, evidence suggests this feedback may not be primarily directed at advancing student learning. Moreover, we found evidence of a reliance on computer--human interactions (e.g. via computer-assisted assessment systems) and further evidence of a decline in human interactions, suggesting a dynamic that is both consistent with current online learning theory and claims FAO mathematics courses are becoming commodified. Several avenues for further research are suggested.

47 CFR 64.2010 - Safeguards on the disclosure of customer proprietary network information.

Code of Federal Regulations, 2013 CFR

2013-10-01

... authenticate a customer prior to disclosing CPNI based on customer-initiated telephone contact, online account... customer. (c) Online access to CPNI. A telecommunications carrier must authenticate a customer without the... customer online access to CPNI related to a telecommunications service account. Once authenticated, the...

47 CFR 64.2010 - Safeguards on the disclosure of customer proprietary network information.

Code of Federal Regulations, 2012 CFR

2012-10-01

... authenticate a customer prior to disclosing CPNI based on customer-initiated telephone contact, online account... customer. (c) Online access to CPNI. A telecommunications carrier must authenticate a customer without the... customer online access to CPNI related to a telecommunications service account. Once authenticated, the...

47 CFR 64.2010 - Safeguards on the disclosure of customer proprietary network information.

Code of Federal Regulations, 2014 CFR

2014-10-01

... authenticate a customer prior to disclosing CPNI based on customer-initiated telephone contact, online account... customer. (c) Online access to CPNI. A telecommunications carrier must authenticate a customer without the... customer online access to CPNI related to a telecommunications service account. Once authenticated, the...

Developing a Curriculum to Promote Professionalism for Medical Students Using Social Media: Pilot of a Workshop and Blog-Based Intervention

PubMed Central

O'Hagan, Thomas; Chisolm, Margaret S

2015-01-01

Background As the use of social media (SM) tools becomes increasingly widespread, medical trainees need guidance on applying principles of professionalism to their online behavior. Objective To develop a curriculum to improve knowledge and skills regarding professionalism of SM use by medical students. Methods This project was conducted in 3 phases: (1) a needs assessment was performed via a survey of medical students regarding SM use, rationale for and frequency of use, and concerns; (2) a workshop-format curriculum was designed and piloted for preclinical students to gain foundational knowledge of online professionalism; and (3) a complementary longitudinal SM-based curriculum was designed and piloted for clinical students to promote both medical humanism and professionalism. Results A total of 72 medical students completed the survey (response rate 30%). Among the survey respondents, 71/72 (99%) reported visiting social networking sites, with 55/72 (76%) reporting daily visits. Privacy of personal information (62/72, 86%) and mixing of personal/professional identities (49/72, 68%) were the students’ most commonly endorsed concerns regarding SM use. The workshop-format curriculum was evaluated qualitatively via participant feedback. Of the 120 students who participated in the workshop, 91 completed the post workshop evaluation (response rate 76%), with 56 positive comments and 54 suggestions for improvement. The workshop was experienced by students as enjoyable, thought provoking, informative, and relevant. Suggestions for improvement included adjustments to timing, format, and content of the workshop. The SM-based curriculum was evaluated by a small-scale pilot of 11 students, randomized to the intervention group (participation in faculty-moderated blog) or the control group. Outcomes were assessed quantitatively and qualitatively via personal growth scales, participant feedback, and analysis of blog themes. There was a trend toward improvement in total personal growth scores among those students in the blog group from 3.65 (0.47) to 4.11 (0.31) (mean [SD]) with no change observed for the students in the control group (3.89 [0.11] before and after evaluation). Themes relevant to humanism and professionalism were observed in the blog discussion. Conclusions Most medical students surveyed reported using SM and identified privacy and personal-professional boundaries as areas of concern. The workshop format and SM-based curricula were well-received by students whose formative feedback will inform the refinement and further development of efforts to promote professionalism among medical students. PMID:27731846

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Negative feedback in ants: crowding results in less trail pheromone deposition

PubMed Central

Czaczkes, Tomer J.; Grüter, Christoph; Ratnieks, Francis L. W.

2013-01-01

Crowding in human transport networks reduces efficiency. Efficiency can be increased by appropriate control mechanisms, which are often imposed externally. Ant colonies also have distribution networks to feeding sites outside the nest and can experience crowding. However, ants do not have external controllers or leaders. Here, we report a self-organized negative feedback mechanism, based on local information, which downregulates the production of recruitment signals in crowded parts of a network by Lasius niger ants. We controlled crowding by manipulating trail width and the number of ants on a trail, and observed a 5.6-fold reduction in the number of ants depositing trail pheromone from least to most crowded conditions. We also simulated crowding by placing glass beads covered in nest-mate cuticular hydrocarbons on the trail. After 10 bead encounters over 20 cm, forager ants were 45 per cent less likely to deposit pheromone. The mechanism of negative feedback reported here is unusual in that it acts by downregulating the production of a positive feedback signal, rather than by direct inhibition or the production of an inhibitory signal. PMID:23365196

Disseminating educational innovations in health care practice: training versus social networks.

PubMed

Jippes, Erik; Achterkamp, Marjolein C; Brand, Paul L P; Kiewiet, Derk Jan; Pols, Jan; van Engelen, Jo M L

2010-05-01

Improvements and innovation in health service organization and delivery have become more and more important due to the gap between knowledge and practice, rising costs, medical errors, and the organization of health care systems. Since training and education is widely used to convey and distribute innovative initiatives, we examined the effect that following an intensive Teach-the-Teacher training had on the dissemination of a new structured competency-based feedback technique of assessing clinical competencies among medical specialists in the Netherlands. We compared this with the effect of the structure of the social network of medical specialists, specifically the network tie strength (strong ties versus weak ties). We measured dissemination of the feedback technique by using a questionnaire filled in by Obstetrics & Gynecology and Pediatrics residents (n=63). Data on network tie strength was gathered with a structured questionnaire given to medical specialists (n=81). Social network analysis was used to compose the required network coefficients. We found a strong effect for network tie strength and no effect for the Teach-the-Teacher training course on the dissemination of the new structured feedback technique. This paper shows the potential that social networks have for disseminating innovations in health service delivery and organization. Further research is needed into the role and structure of social networks on the diffusion of innovations between departments and the various types of innovations involved. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game

PubMed Central

Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

2012-01-01

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior. PMID:22496771

Examining the Relationship between Online Social Capital and Ehealth Literacy: Implications for Instagram Use for Chronic Disease Prevention among College Students

ERIC Educational Resources Information Center

Paige, Samantha R.; Stellefson, Michael; Chaney, Beth H.; Chaney, Don J.; Alber, Julia M.; Chappell, Chelsea; Barry, Adam E.

2017-01-01

Background: College students actively seek online health information and use Instagram, an image- and video-based social networking website, to build social networks grounded in trust and behavioral norms (social capital), which have the potential to prevent chronic disease. Purpose: This study aimed to (1) examine how intensity of Instagram use…

Router Agent Technology for Policy-Based Network Management

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston

2011-01-01

This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

An Internet-Based Radiology Course in Medical School: Comparison of Academic Performance of Students on Campus Versus Those With Absenteeism Due to Residency Interviews.

PubMed

Alexander, Andrew George; Deas, Deborah; Lyons, Paul Eric

2018-05-18

Imaging and its optimal use are imperative to the practice of medicine, yet many students don't receive a formal education in radiology. Concurrently, students look for ways to take time away from medical school for residency interviewing. Web-based instruction provides an opportunity to combine these imperatives using online modalities. A largely Web-based course in radiology during the 4th year of medical school was evaluated both for its acceptance to students who needed to be away from campus for interviews, and its effectiveness on a nationally administered standardized test. All students were placed into a structured program utilizing online videos, online modules, online textbook assignments, and live interactive online lectures. Over half of the course could be completed away from campus. The Alliance of Medical Student Educators in Radiology test exam bank was used as a final exam to evaluate medical knowledge. Positive student feedback included the freedom to travel for interviews, hands-on ultrasound training, interactive teaching sessions, and quality Web-based learning modules. Negative feedback included taking quizzes in-person, a perceived outdated online textbook, and physically shadowing hospital technicians. Most students elected to take the course during the interview months of October through January. The Alliance of Medical Student Educators in Radiology final exam results (70.5%) were not significantly different than the national cohort (70%) who took the course in-person. Test scores from students taking the course during interview travel months were not significantly different from students who took the course before (P=.30) or after (P=.34) the interview season. Students desire to learn radiology and often choose to do so when they need to be away from campus during the fall of their 4th year of study to accomplish their residency interviews. Web-based education in radiology allows students' interview traveling and radiology course objectives to be successfully met without adversely affecting the outcomes on a nationally normed examination in radiology. A curriculum that includes online content and live Web-based teleconference access to faculty can accomplish both imperatives. ©Andrew George Alexander, Deborah Deas, Paul Eric Lyons. Originally published in JMIR Medical Education (http://mededu.jmir.org), 18.05.2018.

Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity

PubMed Central

Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan

2016-01-01

What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. PMID:26824331

Link prediction in multiplex online social networks

NASA Astrophysics Data System (ADS)

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

Link prediction in multiplex online social networks.

PubMed

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

Assess and Invest: Faculty Feedback on Library Tutorials

ERIC Educational Resources Information Center

Appelt, Kristina M.; Pendell, Kimberly

2010-01-01

Communication and collaboration with faculty are increasingly important in the development of both curriculum-integrated and stand-alone "just in time" library tutorials. In the final developmental stages of the Evidence-Based Practice online tutorials, faculty members were asked to provide input during structured faculty feedback…

Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies

PubMed Central

Zheng, Shuai; Ghasemzadeh, Nima; Hayek, Salim S; Quyyumi, Arshed A

2017-01-01

Background Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. Objective Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. Methods A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. Results Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports—each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. Conclusions IDEAL-X adopts a unique online machine learning–based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable. PMID:28487265

Are They Using My Feedback? The Extent of Students' Feedback Use Has a Large Impact on Subsequent Academic Performance

ERIC Educational Resources Information Center

Zimbardi, Kirsten; Colthorpe, Kay; Dekker, Andrew; Engstrom, Craig; Bugarcic, Andrea; Worthy, Peter; Victor, Ruban; Chunduri, Prasad; Lluka, Lesley; Long, Phil

2017-01-01

Feedback is known to have a large influence on student learning gains, and the emergence of online tools has greatly enhanced the opportunity for delivering timely, expressive, digital feedback and for investigating its learning impacts. However, to date there have been no large quantitative investigations of the feedback provided by large teams…

Online contributions of auditory feedback to neural activity in avian song control circuitry

PubMed Central

Sakata, Jon T.; Brainard, Michael S.

2008-01-01

Birdsong, like human speech, relies critically on auditory feedback to provide information about the quality of vocalizations. Although the importance of auditory feedback to vocal learning is well established, whether and how feedback signals influence vocal premotor circuitry has remained obscure. Previous studies in singing birds have not detected changes to vocal premotor activity following perturbations of auditory feedback, leading to the hypothesis that contributions of feedback to vocal plasticity might rely on ‘offline’ processing. Here, we recorded single and multi-unit activity in the premotor nucleus HVC of singing Bengalese finches in response to feedback perturbations that are known to drive plastic changes in song. We found that transient feedback perturbation caused reliable decreases in HVC activity at short latencies (20-80 ms). Similar changes to HVC activity occurred in awake, non-singing finches when the bird’s own song was played back with auditory perturbations that simulated those experienced by singing birds. These data indicate that neurons in avian vocal premotor circuitry are rapidly influenced by perturbations of auditory feedback and support the possibility that feedback information in HVC contributes online to the production and plasticity of vocalizations. PMID:18971480

Intra-operative feedback and dynamic compensation for image-guided robotic focal ultrasound surgery.

PubMed

Chauhan, S; Amir, H; Chen, G; Hacker, A; Michel, M S; Koehrmann, K U

2008-11-01

This paper describes a non-invasive remote temperature measurement technique integrated with a biomechatronic surgery system devised in our laboratory and named FUSBOT (Focal Ultrasound Surgery RoBOT). FUSBOTs use High-Intensity Focused Ultrasound (HIFU) for ablation of cancers/tumors and targets accessible through various soft-tissue acoustic windows in the human body. The focused ultrasound beam parameters are chosen so that biologically significant temperature rises are achieved only within the focal volume. In this paper, FUSBOT(BS), a customized system for breast surgery, is taken as a representative example to demonstrate the implementation and the results of non-invasive feedback during ablation. An 8-axis PC-based controller controls various sub-sections of the system within a safe constrained work envelope. Temperature is a prime target parameter in ablative procedures, and it is of paramount importance that means should be devised for its measurement and control in order to design optimal dose protocols and judge the efficacy of FUS systems. A customized sensory interface is devised and integrated with FUSBOT(BS), and dedicated software algorithms are embedded for surgical planning based on real-time guidance and feedback. Variations in the physical parameters of the tissue interacting with the incident modality are used as surgical feedback. The use of real-time ultrasound imaging and data processed from various sensors to deduce lesion position and thermal feedback during surgery, as integrated with the robotic system for online surgical planning, is described. Dynamic registration algorithms are developed for compensation and re-registration of the robotic end-effector with respect to the target, and representative empirical outcomes for lesion tracking and online temperature estimation in various biological tissues are presented.

Student Practice Evaluation Form-Revised Edition online comment bank: development and reliability analysis.

PubMed

Rodger, Sylvia; Turpin, Merrill; Copley, Jodie; Coleman, Allison; Chien, Chi-Wen; Caine, Anne-Maree; Brown, Ted

2014-08-01

The reliable evaluation of occupational therapy students completing practice education placements along with provision of appropriate feedback is critical for both students and for universities from a quality assurance perspective. This study describes the development of a comment bank for use with an online version of the Student Practice Evaluation Form-Revised Edition (SPEF-R Online) and investigates its reliability. A preliminary bank of 109 individual comments (based on previous students' placement performance) was developed via five stages. These comments reflected all 11 SPEF-R domains. A purpose-designed online survey was used to examine the reliability of the comment bank. A total of 37 practice educators returned surveys, 31 of which were fully completed. Participants were asked to rate each individual comment using the five-point SPEF-R rating scale. One hundred and two of 109 comments demonstrated satisfactory agreement with their respective default ratings that were determined by the development team. At each domain level, the intra-class correlation coefficients (ranging between 0.86 and 0.96) also demonstrated good to excellent inter-rater reliability. There were only seven items that required rewording prior to inclusion in the final SPEF-R Online comment bank. The development of the SPEF-R Online comment bank offers a source of reliable comments (consistent with the SPEF-R rating scale across different domains) and aims to assist practice educators in providing reliable and timely feedback to students in a user-friendly manner. © 2014 Occupational Therapy Australia.

A feedback-based secure path approach for wireless sensor network data collection.

PubMed

Mao, Yuxin; Wei, Guiyi

2010-01-01

The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

Digital Literacy in the Medical Curriculum: A Course With Social Media Tools and Gamification.

PubMed

Mesko, Bertalan; Győrffy, Zsuzsanna; Kollár, János

2015-10-01

The profession of practicing medicine is based on communication, and as social media and other digital technologies play a major role in today's communication, digital literacy must be included in the medical curriculum. The value of social media has been demonstrated several times in medicine and health care, therefore it is time to prepare medical students for the conditions they will have to face when they graduate. The aim of our study was to design a new e-learning-based curriculum and test it with medical students. An elective course was designed to teach students how to use the Internet, with a special emphasis on social media. An e-learning platform was also made available and students could access material about using digital technologies on the online platforms they utilized the most. All students filled in online surveys before and after the course in order to provide feedback about the curriculum. Over a 3-year period, 932 students completed the course. The course did not increase the number of hours spent online but aimed at making that time more efficient and useful. Based on the responses of students, they found the information provided by the curriculum useful for their studies and future practices. A well-designed course, improved by constant evaluation-based feedback, can be suitable for preparing students for the massive use of the Internet, social media platforms, and digital technologies. New approaches must be applied in modern medical education in order to teach students new skills. Such curriculums that put emphasis on reaching students on the online channels they use in their studies and everyday lives introduce them to the world of empowered patients and prepare them to deal with the digital world.

Digital Literacy in the Medical Curriculum: A Course With Social Media Tools and Gamification

PubMed Central

Győrffy, Zsuzsanna; Kollár, János

2015-01-01

Background The profession of practicing medicine is based on communication, and as social media and other digital technologies play a major role in today’s communication, digital literacy must be included in the medical curriculum. The value of social media has been demonstrated several times in medicine and health care, therefore it is time to prepare medical students for the conditions they will have to face when they graduate. Objective The aim of our study was to design a new e-learning-based curriculum and test it with medical students. Method An elective course was designed to teach students how to use the Internet, with a special emphasis on social media. An e-learning platform was also made available and students could access material about using digital technologies on the online platforms they utilized the most. All students filled in online surveys before and after the course in order to provide feedback about the curriculum. Results Over a 3-year period, 932 students completed the course. The course did not increase the number of hours spent online but aimed at making that time more efficient and useful. Based on the responses of students, they found the information provided by the curriculum useful for their studies and future practices. Conclusions A well-designed course, improved by constant evaluation-based feedback, can be suitable for preparing students for the massive use of the Internet, social media platforms, and digital technologies. New approaches must be applied in modern medical education in order to teach students new skills. Such curriculums that put emphasis on reaching students on the online channels they use in their studies and everyday lives introduce them to the world of empowered patients and prepare them to deal with the digital world. PMID:27731856

Regular network model for the sea ice-albedo feedback in the Arctic.

PubMed

Müller-Stoffels, Marc; Wackerbauer, Renate

2011-03-01

The Arctic Ocean and sea ice form a feedback system that plays an important role in the global climate. The complexity of highly parameterized global circulation (climate) models makes it very difficult to assess feedback processes in climate without the concurrent use of simple models where the physics is understood. We introduce a two-dimensional energy-based regular network model to investigate feedback processes in an Arctic ice-ocean layer. The model includes the nonlinear aspect of the ice-water phase transition, a nonlinear diffusive energy transport within a heterogeneous ice-ocean lattice, and spatiotemporal atmospheric and oceanic forcing at the surfaces. First results for a horizontally homogeneous ice-ocean layer show bistability and related hysteresis between perennial ice and perennial open water for varying atmospheric heat influx. Seasonal ice cover exists as a transient phenomenon. We also find that ocean heat fluxes are more efficient than atmospheric heat fluxes to melt Arctic sea ice.

Support for Online Calibration in the ALICE HLT Framework

NASA Astrophysics Data System (ADS)

Krzewicki, Mikolaj; Rohr, David; Zampolli, Chiara; Wiechula, Jens; Gorbunov, Sergey; Chauvin, Alex; Vorobyev, Ivan; Weber, Steffen; Schweda, Kai; Shahoyan, Ruben; Lindenstruth, Volker; ALICE Collaboration

2017-10-01

The ALICE detector employs sub detectors sensitive to environmental conditions such as pressure and temperature, e.g. the time projection chamber (TPC). A precise reconstruction of particle trajectories requires precise calibration of these detectors. Performing the calibration in real time in the HLT improves the online reconstruction and potentially renders certain offline calibration steps obsolete, speeding up offline physics analysis. For LHC Run 3, starting in 2020 when data reduction will rely on reconstructed data, online calibration becomes a necessity. In order to run the calibration online, the HLT now supports the processing of tasks that typically run offline. These tasks run massively in parallel on all HLT compute nodes and their output is gathered and merged periodically. The calibration results are both stored offline for later use and fed back into the HLT chain via a feedback loop in order to apply calibration information to the online track reconstruction. Online calibration and feedback loop are subject to certain time constraints in order to provide up-to-date calibration information and they must not interfere with ALICE data taking. Our approach to run these tasks in asynchronous processes enables us to separate them from normal data taking in a way that makes it failure resilient. We performed a first test of online TPC drift time calibration under real conditions during the heavy-ion run in December 2015. We present an analysis and conclusions of this first test, new improvements and developments based on this, as well as our current scheme to commission this for production use.

Acceptability and perceptions of end-users towards an online sports-health surveillance system

PubMed Central

Barboza, Saulo Delfino; Bolling, Caroline Silveira; Nauta, Joske; van Mechelen, Willem; Verhagen, Evert

2017-01-01

Aim To describe the acceptability and the perceptions of athletes and staff members (ie, end-users) towards an online sports-health surveillance system. Methods A pilot study with a mixed-methods approach was pursued. Descriptive analysis was conducted to present the adherence of judo (n=34), swimming (n=21) and volleyball (n=14) athletes to an online registration of their sport exposure and any health complaints between April 2014 and January 2015. End-users’ perceptions towards the system were investigated qualitatively with semistructured interviews (n=21). Qualitative analysis was based on the constant comparative method using principles of the grounded theory. Results The response rates of judo, swimming and volleyball athletes were 50% (SD 23), 61% (SD 27) and 56% (SD 25), respectively. Most athletes found it simple to register their sport exposure and health complaints online; however, personal communication was still preferred for this purpose. The system facilitated the communication between medical and trainer staff, who were able to identify in the system reports health complaints from athletes that were not necessarily communicated face-to-face. Therefore, staff members reported that they were able to intervene earlier to prevent minor health complaints from becoming severe health problems. However, staff members expected higher adherence of athletes to the online follow-ups, and athletes expected to receive feedback on their inputs to the system. Conclusion An online system can be used in sporting settings complementary to regular strategies for monitoring athletes’ health. However, providing feedback on athletes’ inputs is important to maintain their adherence to such an online system. PMID:29071115

Evaluating the feasibility of using online software to collect patient information in a chiropractic practice-based research network

PubMed Central

Kania-Richmond, Ania; Weeks, Laura; Scholten, Jeffrey; Reney, Mikaël

2016-01-01

Background: Practice based research networks (PBRNs) are increasingly used as a tool for evidence based practice. We developed and tested the feasibility of using software to enable online collection of patient data within a chiropractic PBRN to support clinical decision making and research in participating clinics. Purpose: To assess the feasibility of using online software to collect quality patient information. Methods: The study consisted of two phases: 1) Assessment of the quality of information provided, using a standardized form; and 2) Exploration of patients’ perspectives and experiences regarding online information provision through semi-structured interviews. Data analysis was descriptive. Results: Forty-five new patients were recruited. Thirty-six completed online forms, which were submitted by an appropriate person 100% of the time, with an error rate of less than 1%, and submitted in a timely manner 83% of the time. Twenty-one participants were interviewed. Overall, online forms were preferred given perceived security, ease of use, and enabling provision of more accurate information. Conclusions: Use of online software is feasible, provides high quality information, and is preferred by most participants. A pen-and-paper format should be available for patients with this preference and in case of technical difficulties. PMID:27069272

The Types and Effects of Peer Native Speakers' Feedback on CMC

ERIC Educational Resources Information Center

Diez-Bedmar, Maria Belen; Perez-Paredes, Pascual

2012-01-01

Online collaborative writing tasks are frequently undertaken in forums and wikis. Variation between these two communication modes has yet to be examined, particularly type of feedback and its effects. We investigated the type of feedback and the impact of English native-speakers' feedback on Spanish peers' discourse restructuring in the context of…

Exploring Student Perceptions of Audiovisual Feedback via Screencasting in Online Courses

ERIC Educational Resources Information Center

Mathieson, Kathleen

2012-01-01

Using Moore's (1993) theory of transactional distance as a framework, this action research study explored students' perceptions of audiovisual feedback provided via screencasting as a supplement to text-only feedback. A crossover design was employed to ensure that all students experienced both text-only and text-plus-audiovisual feedback and to…

Enhancing the Impact of Formative Feedback on Student Learning through an Online Feedback System

ERIC Educational Resources Information Center

Hatziapostolou, Thanos; Paraskakis, Iraklis

2010-01-01

Formative feedback is instrumental in the learning experience of a student. It can be effective in promoting learning if it is timely, personal, manageable, motivational, and in direct relation with assessment criteria. Despite its importance, however, research suggests that students are discouraged from engaging in the feedback process primarily…

Analysis of Peer Review Comments: QM Recommendations and Feedback Intervention Theory

ERIC Educational Resources Information Center

Schwegler, Andria F.; Altman, Barbara W.

2015-01-01

Because feedback is a critical component of the continuous improvement cycle of the Quality Matters (QM) peer review process, the present research analyzed the feedback that peer reviewers provided to course developers after a voluntary, nonofficial QM peer review of online courses. Previous research reveals that the effects of feedback on…

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness.

PubMed

Balatsoukas, Panos; Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John

2015-06-11

Social network technologies have become part of health education and wider health promotion—either by design or happenstance. Social support, peer pressure, and information sharing in online communities may affect health behaviors. If there are positive and sustained effects, then social network technologies could increase the effectiveness and efficiency of many public health campaigns. Social media alone, however, may be insufficient to promote health. Furthermore, there may be unintended and potentially harmful consequences of inaccurate or misleading health information. Given these uncertainties, there is a need to understand and synthesize the evidence base for the use of online social networking as part of health promoting interventions to inform future research and practice. Our aim was to review the research on the integration of expert-led health promotion interventions with online social networking in order to determine the extent to which the complementary benefits of each are understood and used. We asked, in particular, (1) How is effectiveness being measured and what are the specific problems in effecting health behavior change?, and (2) To what extent is the designated role of social networking grounded in theory? The narrative synthesis approach to literature review was used to analyze the existing evidence. We searched the indexed scientific literature using keywords associated with health promotion and social networking. The papers included were only those making substantial study of both social networking and health promotion—either reporting the results of the intervention or detailing evidence-based plans. General papers about social networking and health were not included. The search identified 162 potentially relevant documents after review of titles and abstracts. Of these, 42 satisfied the inclusion criteria after full-text review. Six studies described randomized controlled trials (RCTs) evaluating the effectiveness of online social networking within health promotion interventions. Most of the trials investigated the value of a "social networking condition" in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks.

Social media users have different experiences, motivations, and quality of life.

PubMed

Campisi, Jay; Folan, Denis; Diehl, Grace; Kable, Timothy; Rademeyer, Candice

2015-08-30

While the number of individuals participating in internet-based social networks has continued to rise, it is unclear how participating in social networks might influence quality of life (QOL). Individuals differ in their experiences, motivations for, and amount of time using internet-based social networks, therefore, we examined if individuals differing in social network user experiences, motivations and frequency of social network also differed in self-reported QOL. Two-hundred and thirty-seven individuals (aged 18-65) were recruited online using the online platform Mechanical Turk (MTurk). All participants completed a web-based survey examining social network use and the World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-Bref) to assess QOL. Individuals who reported positive associations with the use of social networks demonstrated higher QOL while those reporting negative associates demonstrated lower QOL. Moreover, individuals using social networks to stay connected to friends demonstrated higher QOL while those using social networking for dating purposes reported lower QOL. Frequency of social network use did not relate to QOL. These results suggest that QOL differs among social network users. Thus, participating in social networking may be a way to either promote or detract from QOL. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

On-line integration of computer controlled diagnostic devices and medical information systems in undergraduate medical physics education for physicians.

PubMed

Hanus, Josef; Nosek, Tomas; Zahora, Jiri; Bezrouk, Ales; Masin, Vladimir

2013-01-01

We designed and evaluated an innovative computer-aided-learning environment based on the on-line integration of computer controlled medical diagnostic devices and a medical information system for use in the preclinical medical physics education of medical students. Our learning system simulates the actual clinical environment in a hospital or primary care unit. It uses a commercial medical information system for on-line storage and processing of clinical type data acquired during physics laboratory classes. Every student adopts two roles, the role of 'patient' and the role of 'physician'. As a 'physician' the student operates the medical devices to clinically assess 'patient' colleagues and records all results in an electronic 'patient' record. We also introduced an innovative approach to the use of supportive education materials, based on the methods of adaptive e-learning. A survey of student feedback is included and statistically evaluated. The results from the student feedback confirm the positive response of the latter to this novel implementation of medical physics and informatics in preclinical education. This approach not only significantly improves learning of medical physics and informatics skills but has the added advantage that it facilitates students' transition from preclinical to clinical subjects. Copyright © 2011 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Loop Mirror Laser Neural Network with a Fast Liquid-Crystal Display

NASA Astrophysics Data System (ADS)

Mos, Evert C.; Schleipen, Jean J. H. B.; de Waardt, Huug; Khoe, Djan G. D.

1999-07-01

In our laser neural network (LNN) all-optical threshold action is obtained by application of controlled optical feedback to a laser diode. Here an extended experimental LNN is presented with as many as 32 neurons and 12 inputs. In the setup we use a fast liquid-crystal display to implement an optical matrix vector multiplier. This display, based on ferroelectric liquid-crystal material, enables us to present 125 training examples s to the LNN. To maximize the optical feedback efficiency of the setup, a loop mirror is introduced. We use a -rule learning algorithm to train the network to perform a number of functions toward the application area of telecommunication data switching.

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

Blended shared control utilizing online identification : Regulating grasping forces of a surrogate surgical grasper.

PubMed

Stephens, Trevor K; Kong, Nathan J; Dockter, Rodney L; O'Neill, John J; Sweet, Robert M; Kowalewski, Timothy M

2018-06-01

Surgical robots are increasingly common, yet routine tasks such as tissue grasping remain potentially harmful with high occurrences of tissue crush injury due to the lack of force feedback from the grasper. This work aims to investigate whether a blended shared control framework which utilizes real-time identification of the object being grasped as part of the feedback may help address the prevalence of tissue crush injury in robotic surgeries. This work tests the proposed shared control framework and tissue identification algorithm on a custom surrogate surgical robotic grasping setup. This scheme utilizes identification of the object being grasped as part of the feedback to regulate to a desired force. The blended shared control is arbitrated between human and an implicit force controller based on a computed confidence in the identification of the grasped object. The online identification is performed using least squares based on a nonlinear tissue model. Testing was performed on five silicone tissue surrogates. Twenty grasps were conducted, with half of the grasps performed under manual control and half of the grasps performed with the proposed blended shared control, to test the efficacy of the control scheme. The identification method resulted in an average of 95% accuracy across all time samples of all tissue grasps using a full leave-grasp-out cross-validation. There was an average convergence time of [Formula: see text] ms across all training grasps for all tissue surrogates. Additionally, there was a reduction in peak forces induced during grasping for all tissue surrogates when applying blended shared control online. The blended shared control using online identification more successfully regulated grasping forces to the desired target force when compared with manual control. The preliminary work on this surrogate setup for surgical grasping merits further investigation on real surgical tools and with real human tissues.

The National Map Customer Requirements: Findings from Interviews and Surveys

USGS Publications Warehouse

Sugarbaker, Larry; Coray, Kevin E.; Poore, Barbara

2009-01-01

The purpose of this study was to receive customer feedback and to understand data and information requirements for The National Map. This report provides results and findings from interviews and surveys and will guide policy and operations decisions about data and information requirements leading to the development of a 5-year strategic plan for the National Geospatial Program. These findings are based on feedback from approximately 2,200 customers between February and August 2008. The U.S. Geological Survey (USGS) conducted more than 160 interviews with 200 individuals. The American Society for Photogrammetry and Remote Sensing (ASPRS) and the International Map Trade Association (IMTA) surveyed their memberships and received feedback from over 400 members. The Environmental Systems Research Institute (ESRI) received feedback from over 1,600 of its U.S.-based software users through an online survey sent to customers attending the ESRI International User Conference in the summer of 2008. The results of these surveys were shared with the USGS and have been included in this report.

Beyond Traditional Literacy Instruction: Toward an Account-Based Literacy Training Curriculum in Libraries

ERIC Educational Resources Information Center

Cirella, David

2012-01-01

A diverse group, account-based services include a wide variety of sites commonly used by patrons, including online shopping sites, social networks, photo- and video-sharing sites, banking and financial sites, government services, and cloud-based storage. Whether or not a piece of information is obtainable online must be considered when creating…

Advancements in Curriculum and Assessment by the Use of IMMEX Technology in the Organic Laboratory

ERIC Educational Resources Information Center

Cox, Charles T., Jr.; Cooper, Melanie M.; Pease, Rebecca; Buchanan, Krystal; Hernandez-Cruz, Laura; Stevens, Ron; Picione, John; Holme, Thomas

2008-01-01

The use of web-based software and course management systems for the delivery of online assessments in the chemistry classroom is becoming more common. IMMEX software, like other web-based software, can be used for delivering assessments and providing feedback, but differs in that it offers additional features designed to give insights and promote…

Script Concordance Testing in Continuing Professional Development: Local or International Reference Panels?

ERIC Educational Resources Information Center

Pleguezuelos, E. M.; Hornos, E.; Dory, V.; Gagnon, R.; Malagrino, P.; Brailovsky, C. A.; Charlin, B.

2013-01-01

Context: The PRACTICUM Institute has developed large-scale international programs of on-line continuing professional development (CPD) based on self-testing and feedback using the Practicum Script Concordance Test© (PSCT). Aims: To examine the psychometric consequences of pooling the responses of panelists from different countries (composite…

Teachers' Perceptions Based on Tenure Status and Gender about Principals' Supervision

ERIC Educational Resources Information Center

Range, Bret G.; Finch, Kim; Young, Suzanne; Hvidston, David J.

2014-01-01

This descriptive study assessed teachers' attitudes about their formative supervision and the observational ability of principals through the constructs of teacher tenure status and gender. In sum, 255 teachers responded to an online survey indicating teachers' desired feedback focused on classroom climate, student engagement, and instructional…

Towards Real-Time Speech Emotion Recognition for Affective E-Learning

ERIC Educational Resources Information Center

Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2016-01-01

This paper presents the voice emotion recognition part of the FILTWAM framework for real-time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving Learning Through Webcams And Microphones) intends to offer timely and appropriate online feedback based upon learner's vocal intonations and facial expressions in order…

Online particle detection with Neural Networks based on topological calorimetry information

NASA Astrophysics Data System (ADS)

Ciodaro, T.; Deva, D.; de Seixas, J. M.; Damazio, D.

2012-06-01

This paper presents the latest results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction using the ATLAS calorimetry information (energy measurements). The extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time by 59%. Also, the total memory necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount.

Assessing Online Learning

ERIC Educational Resources Information Center

Comeaux, Patricia, Ed.

2004-01-01

Students in traditional as well as online classrooms need more than grades from their instructors--they also need meaningful feedback to help bridge their academic knowledge and skills with their daily lives. With the increasing number of online learning classrooms, the question of how to consistently assess online learning has become increasingly…

JGME-ALiEM Hot Topics in Medical Education Online Journal Club: An Analysis of a Virtual Discussion About Resident Teachers

PubMed Central

Sherbino, Jonathan; Joshi, Nikita; Lin, Michelle

2015-01-01

Background  In health professionals' education, senior learners play a key role in the teaching of junior colleagues. Objective  We describe an online discussion about residents as teachers to highlight the topic and the online journal club medium. Methods  In January 2015, the Journal of Graduate Medical Education (JGME) and the Academic Life in Emergency Medicine blog facilitated an open-access, online, weeklong journal club on the JGME article “What Makes a Great Resident Teacher? A Multicenter Survey of Medical Students Attending an Internal Medicine Conference.” Social media platforms used to promote asynchronous discussions included a blog, a video discussion via Google Hangouts on Air, and Twitter. We performed a thematic analysis of the discussion. Web analytics were captured as a measure of impact. Results  The blog post garnered 1324 page views from 372 cities in 42 countries. Twitter was used to endorse discussion points, while blog comments provided opinions or responded to an issue. The discussion focused on why resident feedback was devalued by medical students. Proposed explanations included feedback not being labeled as such, the process of giving delivery, the source of feedback, discrepancies with self-assessment, and threats to medical student self-image. The blog post resulted in a crowd-sourced repository of resident teacher resources. Conclusions  An online journal club provides a novel discussion forum across multiple social media platforms to engage authors, content experts, and the education community. Crowd-sourced analysis of the resident teacher role suggests that resident feedback to medical students is important, and barriers to student acceptance of feedback can be overcome. PMID:26457152

Hack-proof Synchronization Protocol for Multi-player Online Games

NASA Astrophysics Data System (ADS)

Fung, Yeung Siu; Lui, John C. S.

Modern multi-player online games are popular and attractive because they provide a sense of virtual world experience to users: players can interact with each other on the Internet but perceive a local area network responsiveness. To make this possible, most modern multi-player online games use similar networking architecture that aims to hide the effects of network latency, packet loss, and high variance of delay from players. Because real-time interactivity is a crucial feature from a player's point of view, any delay perceived by a player can affect his/her performance [16]. Therefore, the game client must be able to run and accept new user commands continuously regardless of the condition of the underlying communication channel, and that it will not stop responding because of waiting for update packets from other players. To make this possible, multi-player online games typically use protocols based on "dead-reckoning" [5, 6, 9] which allows loose synchronization between players.

Protecting posted genes: social networking and the limits of GINA.

PubMed

Soo-Jin Lee, Sandra; Borgelt, Emily

2014-01-01

The combination of decreased genotyping costs and prolific social media use is fueling a personal genetic testing industry in which consumers purchase and interact with genetic risk information online. Consumers and their genetic risk profiles are protected in some respects by the 2008 federal Genetic Information Nondiscrimination Act (GINA), which forbids the discriminatory use of genetic information by employers and health insurers; however, practical and technical limitations undermine its enforceability, given the everyday practices of online social networking and its impact on the workplace. In the Web 2.0 era, employers in most states can legally search about job candidates and employees online, probing social networking sites for personal information that might bear on hiring and employment decisions. We examine GINA's protections for online sharing of genetic information as well as its limitations, and propose policy recommendations to address current gaps that leave employees' genetic information vulnerable in a Web-based world.

Computer-Mediated Social Support for Physical Activity: A Content Analysis

ERIC Educational Resources Information Center

Stragier, Jeroen; Mechant, Peter; De Marez, Lieven; Cardon, Greet

2018-01-01

Purpose: Online fitness communities are a recent phenomenon experiencing growing user bases. They can be considered as online social networks in which recording, monitoring, and sharing of physical activity (PA) are the most prevalent practices. They have added a new dimension to the social experience of PA in which online peers function as…

Students' Informal Peer Feedback Networks

ERIC Educational Resources Information Center

Headington, Rita

2018-01-01

The nature and significance of students' informal peer feedback networks is an under-explored area. This paper offers the findings of a longitudinal investigation of the informal peer feedback networks of a cohort of student teachers [n = 105] across the three years of a UK primary education degree programme. It tracked the dynamic nature of these…

Online Databases for Taxonomy and Identification of Pathogenic Fungi and Proposal for a Cloud-Based Dynamic Data Network Platform

PubMed Central

Prakash, Peralam Yegneswaran; Irinyi, Laszlo; Halliday, Catriona; Chen, Sharon; Robert, Vincent

2017-01-01

ABSTRACT The increase in public online databases dedicated to fungal identification is noteworthy. This can be attributed to improved access to molecular approaches to characterize fungi, as well as to delineate species within specific fungal groups in the last 2 decades, leading to an ever-increasing complexity of taxonomic assortments and nomenclatural reassignments. Thus, well-curated fungal databases with substantial accurate sequence data play a pivotal role for further research and diagnostics in the field of mycology. This minireview aims to provide an overview of currently available online databases for the taxonomy and identification of human and animal-pathogenic fungi and calls for the establishment of a cloud-based dynamic data network platform. PMID:28179406

Interlocked positive and negative feedback network motifs regulate β-catenin activity in the adherens junction pathway

PubMed Central

Klinke, David J.; Horvath, Nicholas; Cuppett, Vanessa; Wu, Yueting; Deng, Wentao; Kanj, Rania

2015-01-01

The integrity of epithelial tissue architecture is maintained through adherens junctions that are created through extracellular homotypic protein–protein interactions between cadherin molecules. Cadherins also provide an intracellular scaffold for the formation of a multiprotein complex that contains signaling proteins, including β-catenin. Environmental factors and controlled tissue reorganization disrupt adherens junctions by cleaving the extracellular binding domain and initiating a series of transcriptional events that aim to restore tissue homeostasis. However, it remains unclear how alterations in cell adhesion coordinate transcriptional events, including those mediated by β-catenin in this pathway. Here were used quantitative single-cell and population-level in vitro assays to quantify the endogenous pathway dynamics after the proteolytic disruption of the adherens junctions. Using prior knowledge of isolated elements of the overall network, we interpreted these data using in silico model-based inference to identify the topology of the regulatory network. Collectively the data suggest that the regulatory network contains interlocked network motifs consisting of a positive feedback loop, which is used to restore the integrity of adherens junctions, and a negative feedback loop, which is used to limit β-catenin–induced gene expression. PMID:26224311

Delivering Faster Congestion Feedback with the Mark-Front Strategy

NASA Technical Reports Server (NTRS)

Liu, Chunlei; Jain, Raj

2001-01-01

Computer networks use congestion feedback from the routers and destinations to control the transmission load. Delivering timely congestion feedback is essential to the performance of networks. Reaction to the congestion can be more effective if faster feedback is provided. Current TCP/IP networks use timeout, duplicate Acknowledgement Packets (ACKs) and explicit congestion notification (ECN) to deliver the congestion feedback, each provides a faster feedback than the previous method. In this paper, we propose a markfront strategy that delivers an even faster congestion feedback. With analytical and simulation results, we show that mark-front strategy reduces buffer size requirement, improves link efficiency and provides better fairness among users. Keywords: Explicit Congestion Notification, mark-front, congestion control, buffer size requirement, fairness.

Online Advertising in Social Networks

NASA Astrophysics Data System (ADS)

Bagherjeiran, Abraham; Bhatt, Rushi P.; Parekh, Rajesh; Chaoji, Vineet

Online social networks offer opportunities to analyze user behavior and social connectivity and leverage resulting insights for effective online advertising. This chapter focuses on the role of social network information in online display advertising.