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 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

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…

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…

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.

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

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.

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

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;…

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.

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.

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…

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.

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.

Count Your Calories and Share Them: Health Benefits of Sharing mHealth Information on Social Networking Sites.

PubMed

Oeldorf-Hirsch, Anne; High, Andrew C; Christensen, John L

2018-04-23

This study investigates the relationship between sharing tracked mobile health (mHealth) information online, supportive communication, feedback, and health behavior. Based on the Integrated Theory of mHealth, our model asserts that sharing tracked health information on social networking sites benefits users' perceptions of their health because of the supportive communication they gain from members of their online social networks and that the amount of feedback people receive moderates these associations. Users of mHealth apps (N = 511) completed an online survey, and results revealed that both sharing tracked health information and receiving feedback from an online social network were positively associated with supportive communication. Network support both corresponded with improved health behavior and mediated the association between sharing health information and users' health behavior. As users received greater amounts of feedback from their online social networks, however, the association between sharing tracked health information and health behavior decreased. Theoretical implications for sharing tracked health information and practical implications for using mHealth apps are discussed.

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…

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…

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.

A game theory-based trust measurement model for social networks.

PubMed

Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong

2016-01-01

In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.

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.

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.

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

NASA Technical Reports Server (NTRS)

Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

2003-01-01

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

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.

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

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.

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.

Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

NASA Astrophysics Data System (ADS)

Tiwari, Shivendra N.; Padhi, Radhakant

2018-01-01

Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

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.

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

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.

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

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)

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.

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.

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.

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

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.

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).

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.

Fault-tolerant nonlinear adaptive flight control using sliding mode online learning.

PubMed

Krüger, Thomas; Schnetter, Philipp; Placzek, Robin; Vörsmann, Peter

2012-08-01

An expanded nonlinear model inversion flight control strategy using sliding mode online learning for neural networks is presented. The proposed control strategy is implemented for a small unmanned aircraft system (UAS). This class of aircraft is very susceptible towards nonlinearities like atmospheric turbulence, model uncertainties and of course system failures. Therefore, these systems mark a sensible testbed to evaluate fault-tolerant, adaptive flight control strategies. Within this work the concept of feedback linearization is combined with feed forward neural networks to compensate for inversion errors and other nonlinear effects. Backpropagation-based adaption laws of the network weights are used for online training. Within these adaption laws the standard gradient descent backpropagation algorithm is augmented with the concept of sliding mode control (SMC). Implemented as a learning algorithm, this nonlinear control strategy treats the neural network as a controlled system and allows a stable, dynamic calculation of the learning rates. While considering the system's stability, this robust online learning method therefore offers a higher speed of convergence, especially in the presence of external disturbances. The SMC-based flight controller is tested and compared with the standard gradient descent backpropagation algorithm in the presence of system failures. Copyright © 2012 Elsevier Ltd. All rights reserved.

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 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

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)

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…

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.

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.

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

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.

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...

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…

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%.

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 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.

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…

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.

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…

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

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

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.

Online social networking in people with psychosis: A systematic review.

PubMed

Highton-Williamson, Elizabeth; Priebe, Stefan; Giacco, Domenico

2015-02-01

Online social networking might facilitate the establishment of social contacts for people with psychosis, who are often socially isolated by the symptoms and consequences of their disorder. We carried out a systematic review exploring available evidence on the use of online social networking in people with psychosis. The review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Included studies examined the use of the online social networking by people with an a priori diagnosis of psychosis (inclusive of bipolar disorder). Data from included studies were extracted and narratively synthesised. A total of 11 studies, published between 2005 and 2013, reported data on online social networking in people with psychosis. People with psychosis seem to spend more time in chat rooms or playing online games than control groups. The use of other online tools, such as Facebook or communication through e-mail, is lower or the same than controls. Online social networking was used by patients with psychosis for establishing new relationships, maintaining relationships/reconnecting with people and online peer support. Online social networking, in the form of forums or online chats, could play a role in strategies aimed at enhancing social networks and reduce the risk of isolation in this population. © The Author(s) 2014.

Vaccine Hesitancy and Online Information: The Influence of Digital Networks.

PubMed

Getman, Rebekah; Helmi, Mohammad; Roberts, Hal; Yansane, Alfa; Cutler, David; Seymour, Brittany

2017-12-01

This article analyzes the digital childhood vaccination information network for vaccine-hesitant parents. The goal of this study was to explore the structure and influence of vaccine-hesitant content online by generating a database and network analysis of vaccine-relevant content. We used Media Cloud, a searchable big-data platform of over 550 million stories from 50,000 media sources, for quantitative and qualitative study of an online media sample based on keyword selection. We generated a hyperlink network map and measured indegree centrality of the sources and vaccine sentiment for a random sample of 450 stories. 28,122 publications from 4,817 sources met inclusion criteria. Clustered communities formed based on shared hyperlinks; communities tended to link within, not among, each other. The plurality of information was provaccine (46.44%, 95% confidence interval [39.86%, 53.20%]). The most influential sources were in the health community (National Institutes of Health, Centers for Disease Control and Prevention) or mainstream media ( New York Times); some user-generated sources also had strong influence and were provaccine (Wikipedia). The vaccine-hesitant community rarely interacted with provaccine content and simultaneously used primary provaccine content within vaccine-hesitant narratives. The sentiment of the overall conversation was consistent with scientific evidence. These findings demonstrate an online environment where scientific evidence online drives vaccine information outside of the vaccine-hesitant community but is also prominently used and misused within the robust vaccine-hesitant community. Future communication efforts should take current context into account; more information may not prevent vaccine hesitancy.

Developing Online Learning Resources: Big Data, Social Networks, and Cloud Computing to Support Pervasive Knowledge

ERIC Educational Resources Information Center

Anshari, Muhammad; Alas, Yabit; Guan, Lim Sei

2016-01-01

Utilizing online learning resources (OLR) from multi channels in learning activities promise extended benefits from traditional based learning-centred to a collaborative based learning-centred that emphasises pervasive learning anywhere and anytime. While compiling big data, cloud computing, and semantic web into OLR offer a broader spectrum of…

Applying social network analysis to understand the knowledge sharing behaviour of practitioners in a clinical online discussion forum.

PubMed

Stewart, Samuel Alan; Abidi, Syed Sibte Raza

2012-12-04

Knowledge Translation (KT) plays a vital role in the modern health care community, facilitating the incorporation of new evidence into practice. Web 2.0 tools provide a useful mechanism for establishing an online KT environment in which health practitioners share their practice-related knowledge and experiences with an online community of practice. We have implemented a Web 2.0 based KT environment--an online discussion forum--for pediatric pain practitioners across seven different hospitals in Thailand. The online discussion forum enabled the pediatric pain practitioners to share and translate their experiential knowledge to help improve the management of pediatric pain in hospitals. The goal of this research is to investigate the knowledge sharing dynamics of a community of practice through an online discussion forum. We evaluated the communication patterns of the community members using statistical and social network analysis methods in order to better understand how the online community engages to share experiential knowledge. Statistical analyses and visualizations provide a broad overview of the communication patterns within the discussion forum. Social network analysis provides the tools to delve deeper into the social network, identifying the most active members of the community, reporting the overall health of the social network, isolating the potential core members of the social network, and exploring the inter-group relationships that exist across institutions and professions. The statistical analyses revealed a network dominated by a single institution and a single profession, and found a varied relationship between reading and posting content to the discussion forum. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the center of the community in terms of facilitating communication. The group-level analysis suggests that there is strong interprofessional and interregional communication, but a dearth of non-nurse participants has been identified as a shortcoming. The results of the analysis suggest that the discussion forum is active and healthy, and that, though few, the interprofessional and interinstitutional ties are strong.

Leveraging social system networks in ubiquitous high-data-rate health systems.

PubMed

Massey, Tammara; Marfia, Gustavo; Stoelting, Adam; Tomasi, Riccardo; Spirito, Maurizio A; Sarrafzadeh, Majid; Pau, Giovanni

2011-05-01

Social system networks with high data rates and limited storage will discard data if the system cannot connect and upload the data to a central server. We address the challenge of limited storage capacity in mobile health systems during network partitions with a heuristic that achieves efficiency in storage capacity by modifying the granularity of the medical data during long intercontact periods. Patterns in the connectivity, reception rate, distance, and location are extracted from the social system network and leveraged in the global algorithm and online heuristic. In the global algorithm, the stochastic nature of the data is modeled with maximum likelihood estimation based on the distribution of the reception rates. In the online heuristic, the correlation between system position and the reception rate is combined with patterns in human mobility to estimate the intracontact and intercontact time. The online heuristic performs well with a low data loss of 2.1%-6.1%.

Fuzzy-rule-based Adaptive Resource Control for Information Sharing in P2P Networks

NASA Astrophysics Data System (ADS)

Wu, Zhengping; Wu, Hao

With more and more peer-to-peer (P2P) technologies available for online collaboration and information sharing, people can launch more and more collaborative work in online social networks with friends, colleagues, and even strangers. Without face-to-face interactions, the question of who can be trusted and then share information with becomes a big concern of a user in these online social networks. This paper introduces an adaptive control service using fuzzy logic in preference definition for P2P information sharing control, and designs a novel decision-making mechanism using formal fuzzy rules and reasoning mechanisms adjusting P2P information sharing status following individual users' preferences. Applications of this adaptive control service into different information sharing environments show that this service can provide a convenient and accurate P2P information sharing control for individual users in P2P networks.

Myths on Bi-direction Communication of Web 2.0 Based Social Networks: Is Social Network Truly Interactive?

DTIC Science & Technology

2011-03-10

more and more social interactions are happening on the on-line. Especially recent uptake of the social network sites (SNSs), such as Facebook (http...results give overviews on social interactions on a popular social network site . As each twitter account has different characteristics based on...the public and individuals post their private stories on their blogs and share their interests using social network sites . On the other hand, people

Algebraic and adaptive learning in neural control systems

NASA Astrophysics Data System (ADS)

Ferrari, Silvia

A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

Turning Archival Tapes into an Online “Cardless” Catalog

PubMed Central

Zuckerman, Alan E.; Ewens, Wilma A.; Cannard, Bonnie G.; Broering, Naomi C.

1982-01-01

Georgetown University has created an online card catalog based on machine readable cataloging records (MARC) loaded from archival tapes or online via the OCLC network. The system is programmed in MUMPS and uses the medical subject headings (MeSH) authority file created by the National Library of Medicine. The online catalog may be searched directly by library users and has eliminated the need for manual filing of catalog cards.

47 CFR 64.5110 - Safeguards on the disclosure of customer proprietary network information.

Code of Federal Regulations, 2013 CFR

2013-10-01

... disclosing CPNI based on a customer-initiated telephone contact, TRS call, point-to-point call, online...) of this section. (c) Online access to CPNI. A TRS provider shall authenticate a customer without the... customer online access to CPNI related to his or her TRS account. Once authenticated, the customer may only...

47 CFR 64.5110 - Safeguards on the disclosure of customer proprietary network information.

Code of Federal Regulations, 2014 CFR

2014-10-01

... disclosing CPNI based on a customer-initiated telephone contact, TRS call, point-to-point call, online...) of this section. (c) Online access to CPNI. A TRS provider shall authenticate a customer without the... customer online access to CPNI related to his or her TRS account. Once authenticated, the customer may only...

Online Learners' Navigational Patterns Based on Data Mining in Terms of Learning Achievement

ERIC Educational Resources Information Center

Keskin, Sinan; Sahin, Muhittin; Ozgur, Adem; Yurdugul, Halil

2016-01-01

The aim of this study is to determine navigational patterns of university students in a learning management system (LMS). It also investigates whether online learners' navigational behaviors differ in terms of their academic achievement (pass, fail). The data for the study comes from 65 third grade students enrolled in online Computer Network and…

An Analysis of Students Enrolled to an Undergraduate University Course Offered Also Online

ERIC Educational Resources Information Center

Scarabottolo, Nello

2016-01-01

This paper analyzes the main characteristics of the students enrolled to a three-years undergraduate course on Security of Computer Systems and Networks, offered in traditional, classroom based fashion as well as online at the University of Milan (Italy). This allows to compare classroom and online students from several points of view, and gives…

Drama and danger: the opportunities and challenges of promoting youth sexual health through online social networks.

PubMed

Veinot, Tiffany C; Campbell, Terrance R; Kruger, Daniel; Grodzinski, Alison; Franzen, Susan

2011-01-01

Social networks affect both exposure to sexually transmitted infections (STIs) and associated risk behavior. Networks may also play a role in disparities in STI/HIV rates among African American youth. Accordingly, there is growing interest in the potential of social network-based interventions to reduce STI/HIV incidence in this group. However, any youth-focused network intervention must grapple with the role of technologies in the social lives of young people. We report results of 12 focus groups with 94 youth from one economically depressed city with a high STI/HIV prevalence. We examined how youth use information and communication technologies (ICTs) in order to socialize with others, and how this aligns with their communication about sexuality and HIV/STIs. The study resulted in the generation of five themes: distraction, diversification, dramatization, danger management and dialogue. We consider implications of these findings for future development of online, social network-based HIV/STI prevention interventions for youth.

Drama and danger: The opportunities and challenges of promoting youth sexual health through online social networks

PubMed Central

Veinot, Tiffany C.; Campbell, Terrance R.; Kruger, Daniel; Grodzinski, Alison; Franzen, Susan

2011-01-01

Social networks affect both exposure to sexually transmitted infections (STIs) and associated risk behavior. Networks may also play a role in disparities in STI/HIV rates among African American youth. Accordingly, there is growing interest in the potential of social network-based interventions to reduce STI/HIV incidence in this group. However, any youth-focused network intervention must grapple with the role of technologies in the social lives of young people. We report results of 12 focus groups with 94 youth from one economically depressed city with a high STI/HIV prevalence. We examined how youth use information and communication technologies (ICTs) in order to socialize with others, and how this aligns with their communication about sexuality and HIV/STIs. The study resulted in the generation of five themes: distraction, diversification, dramatization, danger management and dialogue. We consider implications of these findings for future development of online, social network-based HIV/STI prevention interventions for youth. PMID:22195207

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID

PubMed Central

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-01-01

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm–neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS. PMID:29671822

Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

PubMed

Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

2018-04-19

Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

Social networking and online recruiting for HIV research: ethical challenges.

PubMed

Curtis, Brenda L

2014-02-01

Social networking sites and online advertising organizations provide HIV/AIDS researchers access to target populations, often reaching difficult-to-reach populations. However, this benefit to researchers raises many issues for the protections of prospective research participants. Traditional recruitment procedures have involved straightforward transactions between the researchers and prospective participants; online recruitment is a more complex and indirect form of communication involving many parties engaged in the collecting, aggregating, and storing of research participant data. Thus, increased access to online data has challenged the adequacy of current and established procedures for participants' protections, such as informed consent and privacy/confidentiality. Internet-based HIV/AIDS research recruitment and its ethical challenges are described, and research participant safeguards and best practices are outlined.

Social Networking and Online Recruiting for HIV Research: Ethical Challenges

PubMed Central

Curtis, Brenda L.

2015-01-01

Social networking sites and online advertising organizations provide HIV/AIDS researchers access to target populations, often reaching difficult-to-reach populations. However, this benefit to researchers raises many issues for the protections of prospective research participants. Traditional recruitment procedures have involved straightforward transactions between the researchers and prospective participants; online recruitment is a more complex and indirect form of communication involving many parties engaged in the collecting, aggregating, and storing of research participant data. Thus, increased access to online data has challenged the adequacy of current and established procedures for participants’ protections, such as informed consent and privacy/confidentiality. Internet-based HIV/AIDS research recruitment and its ethical challenges are described, and research participant safeguards and best practices are outlined. PMID:24572084

A prospective examination of online social network dynamics and smoking cessation

PubMed Central

Zhao, Kang; Papandonatos, George D.; Erar, Bahar; Wang, Xi; Amato, Michael S.; Cha, Sarah; Cohn, Amy M.; Pearson, Jennifer L.

2017-01-01

Introduction Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence. Method Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics. Results Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05). Conclusions This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors. PMID:28832621

Internet use, social networking, and HIV/AIDS risk for homeless adolescents.

PubMed

Rice, Eric; Monro, William; Barman-Adhikari, Anamika; Young, Sean D

2010-12-01

To examine the association between sexual health and internet use, including social networking websites such as MySpace and Facebook, among a sample of homeless adolescents at high risk of contracting HIV/AIDS. In 2009, a survey of internet use among 201 homeless adolescents was carried out. Multivariate logistic regression models assessed how patterns of use were associated with engaging in exchange sex (sex for money, drugs, or housing), recent HIV testing, and online partner-seeking behaviors. Among the surveyed adolescents, 96.5% reported internet use. Most youth accessed the internet at public libraries or youth service agencies. Increased time online and recent engagement in exchange sex were both positively associated with online partner-seeking. Youth connected to family members online were less likely to practice exchange sex and more likely to report a recent HIV test. Youth connected to street-based peers online were more likely to practice exchange sex, whereas youth connected to home-based peers online were more likely to report a recent HIV test. Although these data are preliminary, homeless youth need more access to the internet, as access facilitates connecting with family and home-based peers whose presence may reduce sexual risk-taking. Access, however, must be carefully monitored to prevent youth soliciting sex online. Copyright © 2010 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness

PubMed Central

Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John

2015-01-01

Background 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. Objective 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? Methods 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. Results 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. Conclusions 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. PMID:26068087

Dynamical behaviours and control measures of rumour-spreading model with consideration of network topology

NASA Astrophysics Data System (ADS)

Zhu, Linhe; Zhao, Hongyong

2017-07-01

A series of online rumours have seriously influenced the normal production and living of people. This paper aims to study the combined impact of psychological factor, propagation delay, network topology and control strategy on rumour diffusion over the online social networks. Based on an online social network, which is seen as a scale-free network, we model the spread of rumours by using a delayed SIS (Susceptible and Infected) epidemic-like model with consideration of psychological factor and network topology. First, through theoretical analysis, we illustrate the boundedness of the density of rumour-susceptible individuals and rumour-infected individuals. Second, we obtain the basic reproduction number R0 and prove the stability of the non-rumour equilibrium point and the rumour-spreading equilibrium point. Third, control strategies, such as uniform immunisation control, proportional immunisation control, targeted immunisation control and optimum control, are put forward to restrain rumour diffusion. Meanwhile, we have compared the differences of these control strategies. Finally, some representative numerical simulations are performed to verify the theoretical analysis results.

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.

Online Databases for Taxonomy and Identification of Pathogenic Fungi and Proposal for a Cloud-Based Dynamic Data Network Platform.

PubMed

Prakash, Peralam Yegneswaran; Irinyi, Laszlo; Halliday, Catriona; Chen, Sharon; Robert, Vincent; Meyer, Wieland

2017-04-01

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. Copyright © 2017 American Society for Microbiology.

Enhanced online convolutional neural networks for object tracking

NASA Astrophysics Data System (ADS)

Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

2018-04-01

In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

Information need in local government and online network system ; LOGON

NASA Astrophysics Data System (ADS)

Ohta, Masanori

Local Authorities Systems DEvelopment Center started the trial operation of LOcal Government information service On-line Network system (LOGON) in April of 1988. Considering the background of LOGON construction this paper introduces the present status of informationalization in municipalities and needs to network systems as well as information centers based on results of various types of research. It also compares database systems with communication by personal computers, both of which are typical communication forms, and investigates necessary functions of LOGON. The actual system functions, services and operation of LOGON and some problems occurred in the trial are discussed.

Considering a Twitter-Based Professional Learning Network in Literacy Education

ERIC Educational Resources Information Center

Colwell, Jamie; Hutchison, Amy C.

2018-01-01

This study explored how 26 preservice secondary content teachers perceived their experiences participating in and developing a Twitter-based professional learning network focused on disciplinary literacy. Participants completed blog reflections and anonymous online surveys to reflect on their experiences, which served as data for this study. A…

Doctoral Students' Identity Positioning in Networked Learning Environments

ERIC Educational Resources Information Center

Koole, Marguerite; Stack, Sara

2016-01-01

In this study, the authors explored identity positioning as perceived by doctoral learners in online, networked-learning environments. The study examined two distance doctoral programs at a Canadian university. It was a qualitative study based on methodologies involving open coding and discourse analysis. The social positioning cycle, based on…

Ontology- and graph-based similarity assessment in biological networks.

PubMed

Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-10-15

A standard systems-based approach to biomarker and drug target discovery consists of placing putative biomarkers in the context of a network of biological interactions, followed by different 'guilt-by-association' analyses. The latter is typically done based on network structural features. Here, an alternative analysis approach in which the networks are analyzed on a 'semantic similarity' space is reported. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment in biological networks. http://rosalind.infj.ulst.ac.uk/SimTrek.html francisco.azuaje@crp-sante.lu Supplementary data are available at Bioinformatics online.

Composition and structure of a large online social network in The Netherlands.

PubMed

Corten, Rense

2012-01-01

Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in The Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for The Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities.

Library Automation in the Netherlands and Pica.

ERIC Educational Resources Information Center

Bossers, Anton; Van Muyen, Martin

1984-01-01

Describes the Pica Library Automation Network (originally the Project for Integrated Catalogue Automation), which is based on a centralized bibliographic database. Highlights include the Pica conception of library automation, online shared cataloging system, circulation control system, acquisition system, and online Dutch union catalog with…

A Framework for Finding and Summarizing Product Defects, and Ranking Helpful Threads from Online Customer Forums through Machine Learning

ERIC Educational Resources Information Center

Jiao, Jian

2013-01-01

The Internet has revolutionized the way users share and acquire knowledge. As important and popular Web-based applications, online discussion forums provide interactive platforms for users to exchange information and report problems. With the rapid growth of social networks and an ever increasing number of Internet users, online forums have…

Neural network based online simultaneous policy update algorithm for solving the HJI equation in nonlinear H∞ control.

PubMed

Wu, Huai-Ning; Luo, Biao

2012-12-01

It is well known that the nonlinear H∞ state feedback control problem relies on the solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that has proven to be impossible to solve analytically. In this paper, a neural network (NN)-based online simultaneous policy update algorithm (SPUA) is developed to solve the HJI equation, in which knowledge of internal system dynamics is not required. First, we propose an online SPUA which can be viewed as a reinforcement learning technique for two players to learn their optimal actions in an unknown environment. The proposed online SPUA updates control and disturbance policies simultaneously; thus, only one iterative loop is needed. Second, the convergence of the online SPUA is established by proving that it is mathematically equivalent to Newton's method for finding a fixed point in a Banach space. Third, we develop an actor-critic structure for the implementation of the online SPUA, in which only one critic NN is needed for approximating the cost function, and a least-square method is given for estimating the NN weight parameters. Finally, simulation studies are provided to demonstrate the effectiveness of the proposed algorithm.

Utility-Based Link Recommendation in Social Networks

ERIC Educational Resources Information Center

Li, Zhepeng

2013-01-01

Link recommendation, which suggests links to connect currently unlinked users, is a key functionality offered by major online social networking platforms. Salient examples of link recommendation include "people you may know"' on Facebook and "who to follow" on Twitter. A social networking platform has two types of stakeholder:…

Effective seeding strategy in evolutionary prisoner's dilemma games on online social networks

NASA Astrophysics Data System (ADS)

Xu, Bo; Shi, Huibin; Wang, Jianwei; Huang, Yun

2015-04-01

This paper explores effective seeding strategies in prisoner's dilemma game (PDG) on online social networks, i.e. the optimal strategy to obtain global cooperation with minimum cost. Three distinct seeding strategies are compared by performing computer simulations on real online social network datasets. Our finding suggests that degree centrality seeding outperforms other strategies regardless of the initial payoff setting or network size. Celebrities of online social networks play key roles in preserving cooperation.

Identifying Gatekeepers in Online Learning Networks

ERIC Educational Resources Information Center

Gursakal, Necmi; Bozkurt, Aras

2017-01-01

The rise of the networked society has not only changed our perceptions but also the definitions, roles, processes and dynamics of online learning networks. From offline to online worlds, networks are everywhere and gatekeepers are an important entity in these networks. In this context, the purpose of this paper is to explore gatekeeping and…

Social and place-focused communities in location-based online social networks

NASA Astrophysics Data System (ADS)

Brown, Chloë; Nicosia, Vincenzo; Scellato, Salvatore; Noulas, Anastasios; Mascolo, Cecilia

2013-06-01

Thanks to widely available, cheap Internet access and the ubiquity of smartphones, millions of people around the world now use online location-based social networking services. Understanding the structural properties of these systems and their dependence upon users' habits and mobility has many potential applications, including resource recommendation and link prediction. Here, we construct and characterise social and place-focused graphs by using longitudinal information about declared social relationships and about users' visits to physical places collected from a popular online location-based social service. We show that although the social and place-focused graphs are constructed from the same data set, they have quite different structural properties. We find that the social and location-focused graphs have different global and meso-scale structure, and in particular that social and place-focused communities have negligible overlap. Consequently, group inference based on community detection performed on the social graph alone fails to isolate place-focused groups, even though these do exist in the network. By studying the evolution of tie structure within communities, we show that the time period over which location data are aggregated has a substantial impact on the stability of place-focused communities, and that information about place-based groups may be more useful for user-centric applications than that obtained from the analysis of social communities alone.

Demonstrating the use of web analytics and an online survey to understand user groups of a national network of river level data

NASA Astrophysics Data System (ADS)

Macleod, Christopher Kit; Braga, Joao; Arts, Koen; Ioris, Antonio; Han, Xiwu; Sripada, Yaji; van der Wal, Rene

2016-04-01

The number of local, national and international networks of online environmental sensors are rapidly increasing. Where environmental data are made available online for public consumption, there is a need to advance our understanding of the relationships between the supply of and the different demands for such information. Understanding how individuals and groups of users are using online information resources may provide valuable insights into their activities and decision making. As part of the 'dot.rural wikiRivers' project we investigated the potential of web analytics and an online survey to generate insights into the use of a national network of river level data from across Scotland. These sources of online information were collected alongside phone interviews with volunteers sampled from the online survey, and interviews with providers of online river level data; as part of a larger project that set out to help improve the communication of Scotland's online river data. Our web analytics analysis was based on over 100 online sensors which are maintained by the Scottish Environmental Protection Agency (SEPA). Through use of Google Analytics data accessed via the R Ganalytics package we assessed: if the quality of data provided by Google Analytics free service is good enough for research purposes; if we could demonstrate what sensors were being used, when and where; how the nature and pattern of sensor data may affect web traffic; and whether we can identify and profile these users based on information from traffic sources. Web analytics data consists of a series of quantitative metrics which capture and summarize various dimensions of the traffic to a certain web page or set of pages. Examples of commonly used metrics include the number of total visits to a site and the number of total page views. Our analyses of the traffic sources from 2009 to 2011 identified several different major user groups. To improve our understanding of how the use of this national network of river level data may provide insights into the interactions between individuals and their usage of hydrological information, we ran an online survey linked to the SEPA river level pages for one year. We collected over 2000 complete responses to the survey. The survey included questions on user activities and the importance of river level information for their activities; alongside questions on what additional information they used in their decision making e.g. precipitation, and when and what river pages they visited. In this presentation we will present results from our analysis of the web analytics and online survey, and the insights they provide to understanding user groups of this national network of river level data.

Online Social Networking Issues Within Academia and Pharmacy Education

PubMed Central

2008-01-01

Online social networking sites such as Facebook and MySpace are extremely popular as indicated by the numbers of members and visits to the sites. They allow students to connect with users with similar interests, build and maintain relationships with friends, and feel more connected with their campus. The foremost criticisms of online social networking are that students may open themselves to public scrutiny of their online personas and risk physical safety by revealing excessive personal information. This review outlines issues of online social networking in higher education by drawing upon articles in both the lay press and academic publications. New points for pharmacy educators to consider include the possible emergence of an “e-professionalism” concept; legal and ethical implications of using online postings in admission, discipline, and student safety decisions; how online personas may blend into professional life; and the responsibility for educating students about the risks of online social networking. PMID:18322572

Online social networking issues within academia and pharmacy education.

PubMed

Cain, Jeff

2008-02-15

Online social networking sites such as Facebook and MySpace are extremely popular as indicated by the numbers of members and visits to the sites. They allow students to connect with users with similar interests, build and maintain relationships with friends, and feel more connected with their campus. The foremost criticisms of online social networking are that students may open themselves to public scrutiny of their online personas and risk physical safety by revealing excessive personal information. This review outlines issues of online social networking in higher education by drawing upon articles in both the lay press and academic publications. New points for pharmacy educators to consider include the possible emergence of an "e-professionalism" concept; legal and ethical implications of using online postings in admission, discipline, and student safety decisions; how online personas may blend into professional life; and the responsibility for educating students about the risks of online social networking.

A Regularizer Approach for RBF Networks Under the Concurrent Weight Failure Situation.

PubMed

Leung, Chi-Sing; Wan, Wai Yan; Feng, Ruibin

2017-06-01

Many existing results on fault-tolerant algorithms focus on the single fault source situation, where a trained network is affected by one kind of weight failure. In fact, a trained network may be affected by multiple kinds of weight failure. This paper first studies how the open weight fault and the multiplicative weight noise degrade the performance of radial basis function (RBF) networks. Afterward, we define the objective function for training fault-tolerant RBF networks. Based on the objective function, we then develop two learning algorithms, one batch mode and one online mode. Besides, the convergent conditions of our online algorithm are investigated. Finally, we develop a formula to estimate the test set error of faulty networks trained from our approach. This formula helps us to optimize some tuning parameters, such as RBF width.

On-Line Databases in Mexico.

ERIC Educational Resources Information Center

Molina, Enzo

1986-01-01

Use of online bibliographic databases in Mexico is provided through Servicio de Consulta a Bancos de Informacion, a public service that provides information retrieval, document delivery, translation, technical support, and training services. Technical infrastructure is based on a public packet-switching network and institutional users may receive…

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

NASA Astrophysics Data System (ADS)

Song, Rui-Zhuo; Xiao, Wen-Dong; Wei, Qing-Lai

2014-05-01

We develop an online adaptive dynamic programming (ADP) based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

A bipartite fitness model for online music streaming services

NASA Astrophysics Data System (ADS)

Pongnumkul, Suchit; Motohashi, Kazuyuki

2018-01-01

This paper proposes an evolution model and an analysis of the behavior of music consumers on online music streaming services. While previous studies have observed power-law degree distributions of usage in online music streaming services, the underlying behavior of users has not been well understood. Users and songs can be described using a bipartite network where an edge exists between a user node and a song node when the user has listened that song. The growth mechanism of bipartite networks has been used to understand the evolution of online bipartite networks Zhang et al. (2013). Existing bipartite models are based on a preferential attachment mechanism László Barabási and Albert (1999) in which the probability that a user listens to a song is proportional to its current popularity. This mechanism does not allow for two types of real world phenomena. First, a newly released song with high quality sometimes quickly gains popularity. Second, the popularity of songs normally decreases as time goes by. Therefore, this paper proposes a new model that is more suitable for online music services by adding fitness and aging functions to the song nodes of the bipartite network proposed by Zhang et al. (2013). Theoretical analyses are performed for the degree distribution of songs. Empirical data from an online streaming service, Last.fm, are used to confirm the degree distribution of the object nodes. Simulation results show improvements from a previous model. Finally, to illustrate the application of the proposed model, a simplified royalty cost model for online music services is used to demonstrate how the changes in the proposed parameters can affect the costs for online music streaming providers. Managerial implications are also discussed.

Analyzing the Social Networks of High- and Low-Performing Students in Online Discussion Forums

ERIC Educational Resources Information Center

Ghadirian, Hajar; Salehi, Keyvan; Ayub, Ahmad Fauzi Mohd

2018-01-01

An ego network is an individual's social network relationships with core members. In this study, the ego network parameters in online discussion spaces of high- and low-performing students were compared. The extent to which students' ego networks changed over the course were also analyzed. Participation in 7 weeks of online discussions were…

Online and Offline Social Networks: Use of Social Networking Sites by Emerging Adults

ERIC Educational Resources Information Center

Subrahmanyam, Kaveri; Reich, Stephanie M.; Waechter, Natalia; Espinoza, Guadalupe

2008-01-01

Social networking sites (e.g., MySpace and Facebook) are popular online communication forms among adolescents and emerging adults. Yet little is known about young people's activities on these sites and how their networks of "friends" relate to their other online (e.g., instant messaging) and offline networks. In this study, college students…

Model-Free Adaptive Control for Unknown Nonlinear Zero-Sum Differential Game.

PubMed

Zhong, Xiangnan; He, Haibo; Wang, Ding; Ni, Zhen

2018-05-01

In this paper, we present a new model-free globalized dual heuristic dynamic programming (GDHP) approach for the discrete-time nonlinear zero-sum game problems. First, the online learning algorithm is proposed based on the GDHP method to solve the Hamilton-Jacobi-Isaacs equation associated with optimal regulation control problem. By setting backward one step of the definition of performance index, the requirement of system dynamics, or an identifier is relaxed in the proposed method. Then, three neural networks are established to approximate the optimal saddle point feedback control law, the disturbance law, and the performance index, respectively. The explicit updating rules for these three neural networks are provided based on the data generated during the online learning along the system trajectories. The stability analysis in terms of the neural network approximation errors is discussed based on the Lyapunov approach. Finally, two simulation examples are provided to show the effectiveness of the proposed method.

An on-line BCI for control of hand grasp sequence and holding using adaptive probabilistic neural network.

PubMed

Hazrati, Mehrnaz Kh; Erfanian, Abbas

2008-01-01

This paper presents a new EEG-based Brain-Computer Interface (BCI) for on-line controlling the sequence of hand grasping and holding in a virtual reality environment. The goal of this research is to develop an interaction technique that will allow the BCI to be effective in real-world scenarios for hand grasp control. Moreover, for consistency of man-machine interface, it is desirable the intended movement to be what the subject imagines. For this purpose, we developed an on-line BCI which was based on the classification of EEG associated with imagination of the movement of hand grasping and resting state. A classifier based on probabilistic neural network (PNN) was introduced for classifying the EEG. The PNN is a feedforward neural network that realizes the Bayes decision discriminant function by estimating probability density function using mixtures of Gaussian kernels. Two types of classification schemes were considered here for on-line hand control: adaptive and static. In contrast to static classification, the adaptive classifier was continuously updated on-line during recording. The experimental evaluation on six subjects on different days demonstrated that by using the static scheme, a classification accuracy as high as the rate obtained by the adaptive scheme can be achieved. At the best case, an average classification accuracy of 93.0% and 85.8% was obtained using adaptive and static scheme, respectively. The results obtained from more than 1500 trials on six subjects showed that interactive virtual reality environment can be used as an effective tool for subject training in BCI.

Online Network Influences on Emerging Adults’ Alcohol and Drug Use

PubMed Central

Cook, Stephanie H.; Gordon-Messer, Deborah; Zimmerman, Marc A.

2012-01-01

Researchers have reported that network characteristics are associated with substance use behavior. Considering that social interactions within online networks are increasingly common, we examined the relationship between online network characteristics and substance use in a sample of emerging adults (ages 18–24) from across the United States (N = 2,153; M = 21 years old; 47 % female; 70 % White). We used regression analyses to examine the relationship between online ego network characteristics (i.e., characteristics of individuals directly related to the focal participant plus the relationships shared among individuals within the online network) and alcohol use and substance use, respectively. Alcohol use was associated with network density (i.e., interconnectedness between individuals in a network), total number of peer ties, and a greater proportion of emotionally close ties. In sex-stratified models, density was related to alcohol use for males but not females. Drug use was associated with an increased number of peer ties, and the increased proportion of network members’ discussion and acceptance of drug use, respectively. We also found that online network density and total numbers of ties were associated with more personal drug use for males but not females. Conversely, we noted that social norms were related to increased drug use and this relationship was stronger for females than males. We discuss the implications of our findings for substance use and online network research. PMID:23212348

China's Chemical Information Online Service: ChI2Net.

ERIC Educational Resources Information Center

Naiyan, Yu; And Others

1997-01-01

Describes the Chemical Integrated Information Service Network (ChI2Net), a comprehensive online information service system which includes chemical, technical, economic, market, news, and management information based on computer and modern communication technology that was built by the China National Chemical Information Centre. (Author/LRW)

How Social Network Position Relates to Knowledge Building in Online Learning Communities

ERIC Educational Resources Information Center

Wang, Lu

2010-01-01

Social Network Analysis, Statistical Analysis, Content Analysis and other research methods were used to research online learning communities at Capital Normal University, Beijing. Analysis of the two online courses resulted in the following conclusions: (1) Social networks of the two online courses form typical core-periphery structures; (2)…

My Space or Yours?

ERIC Educational Resources Information Center

Barrett, Joanne

2006-01-01

Social networking is one of the latest trends to evolve out of the growing online community. Social networking sites gather data submitted by members that is then stored as user profiles. The data or profiles can then be shared among the members of the site. Membership can be free or fee-based. A typical social networking site provides members…

The Relationship Between Online Social Networking and Depression: A Systematic Review of Quantitative Studies.

PubMed

Baker, David A; Algorta, Guillermo Perez

2016-11-01

Online social networking sites (SNSs) such as Facebook, Twitter, and MySpace are used by billions of people every day to communicate and interact with others. There has been increasing interest in the potential impact of online social networking on wellbeing, with a broadening body of new research into factors associated with both positive and negative mental health outcomes such as depression. This systematic review of empirical studies (n = 30) adds to existing research in this field by examining current quantitative studies focused on the relationship between online social networking and symptoms of depression. The academic databases PsycINFO, Web of Science, CINAHL, MEDLINE, and EMBASE were searched systematically using terms related to online social networking and depression. Reporting quality was critically appraised and the findings discussed with reference to their wider implications. The findings suggest that the relationship between online social networking and symptoms of depression may be complex and associated with multiple psychological, social, behavioral, and individual factors. Furthermore, the impact of online social networking on wellbeing may be both positive and negative, highlighting the need for future research to determine the impact of candidate mediators and moderators underlying these heterogeneous outcomes across evolving networks.

Similarity between community structures of different online social networks and its impact on underlying community detection

NASA Astrophysics Data System (ADS)

Fan, W.; Yeung, K. H.

2015-03-01

As social networking services are popular, many people may register in more than one online social network. In this paper we study a set of users who have accounts of three online social networks: namely Foursquare, Facebook and Twitter. Community structure of this set of users may be reflected in these three online social networks. Therefore, high correlation between these reflections and the underlying community structure may be observed. In this work, community structures are detected in all three online social networks. Also, we investigate the similarity level of community structures across different networks. It is found that they show strong correlation with each other. The similarity between different networks may be helpful to find a community structure close to the underlying one. To verify this, we propose a method to increase the weights of some connections in networks. With this method, new networks are generated to assist community detection. By doing this, value of modularity can be improved and the new community structure match network's natural structure better. In this paper we also show that the detected community structures of online social networks are correlated with users' locations which are identified on Foursquare. This information may also be useful for underlying community detection.

Computer-Mediated Social Support for Physical Activity: A Content Analysis.

PubMed

Stragier, Jeroen; Mechant, Peter; De Marez, Lieven; Cardon, Greet

2018-02-01

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 virtual PA partners or supporters. However, research into seeking and receiving computer-mediated social support for PA is scarce. Our aim was to study to what extent using online fitness communities and sharing physical activities with online social networks results in receiving various types of online social support. Two databases, one containing physical activities logged with Strava and one containing physical activities logged with RunKeeper and shared on Twitter, were investigated for occurrence and type of social support, by means of a deductive content analysis. Results indicate that social support delivered through Twitter is not particularly extensive. On Strava, social support is significantly more prevalent. Especially esteem support, expressed as compliments for the accomplishment of an activity, is provided on both Strava and Twitter. The results demonstrate that social media have potential as a platform used for providing social support for PA, but differences among various social network sites can be substantial. Especially esteem support can be expected, in contrast to online health communities, where information support is more common.

Are Health Behavior Change Interventions That Use Online Social Networks Effective? A Systematic Review

PubMed Central

Lewis, Lucy K; Ferrar, Katia; Marshall, Simon; De Bourdeaudhuij, Ilse; Vandelanotte, Corneel

2014-01-01

Background The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change. Objective The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions. Methods Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where “population” included child or adult populations, including healthy and disease populations; “intervention” involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; “comparator” was either a control group or within subject in the case of pre-post study designs; “outcomes” included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and “study design” included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen’s d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized. Results A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from −0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity). Conclusions To date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided. PMID:24550083

Are health behavior change interventions that use online social networks effective? A systematic review.

PubMed

Maher, Carol A; Lewis, Lucy K; Ferrar, Katia; Marshall, Simon; De Bourdeaudhuij, Ilse; Vandelanotte, Corneel

2014-02-14

The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change. The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions. Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where "population" included child or adult populations, including healthy and disease populations; "intervention" involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; "comparator" was either a control group or within subject in the case of pre-post study designs; "outcomes" included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and "study design" included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen's d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized. A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from -0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity). To date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided.

Effects of Network Structure, Competition and Memory Time on Social Spreading Phenomena

NASA Astrophysics Data System (ADS)

Gleeson, James P.; O'Sullivan, Kevin P.; Baños, Raquel A.; Moreno, Yamir

2016-04-01

Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior that is analytically tractable and that can reproduce several characteristics of empirical micro-blogging data on hashtag usage, such as (time-dependent) heavy-tailed distributions of meme popularity. The presented framework constitutes a null model for social spreading phenomena that, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.

Online Social Networks - Opportunities for Empowering Cancer Patients.

PubMed

Mohammadzadeh, Zeinab; Davoodi, Somayeh; Ghazisaeidi, Marjan

2016-01-01

Online social network technologies have become important to health and apply in most health care areas. Particularly in cancer care, because it is a disease which involves many social aspects, online social networks can be very useful. Use of online social networks provides a suitable platform for cancer patients and families to present and share information about their medical conditions, address their educational needs, support decision making, and help to coping with their disease and improve their own outcomes. Like any other new technologies, online social networks, along with many benefits, have some negative effects such as violation of privacy and publication of incorrect information. However, if these effects are managed properly, they can empower patients to manage cancer through changing behavioral patterns and enhancing the quality of cancer patients lives This paper explains some application of online social networks in the cancer patient care process. It also covers advantages and disadvantages of related technologies.

Online social networking for radiology.

PubMed

Auffermann, William F; Chetlen, Alison L; Colucci, Andrew T; DeQuesada, Ivan M; Grajo, Joseph R; Heller, Matthew T; Nowitzki, Kristina M; Sherry, Steven J; Tillack, Allison A

2015-01-01

Online social networking services have changed the way we interact as a society and offer many opportunities to improve the way we practice radiology and medicine in general. This article begins with an introduction to social networking. Next, the latest advances in online social networking are reviewed, and areas where radiologists and clinicians may benefit from these new tools are discussed. This article concludes with several steps that the interested reader can take to become more involved in online social networking. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Online social networks that connect users to physical activity partners: a review and descriptive analysis.

PubMed

Nakhasi, Atul; Shen, Album Xiaotian; Passarella, Ralph Joseph; Appel, Lawrence J; Anderson, Cheryl Am

2014-06-16

The US Centers for Disease Control and Prevention have identified a lack of encouragement, support, or companionship from family and friends as a major barrier to physical activity. To overcome this barrier, online social networks are now actively leveraging principles of companion social support in novel ways. The aim was to evaluate the functionality, features, and usability of existing online social networks which seek to increase physical activity and fitness among users by connecting them to physical activity partners, not just online, but also face-to-face. In September 2012, we used 3 major databases to identify the website addresses for relevant online social networks. We conducted a Google search using 8 unique keyword combinations: the common keyword "find" coupled with 1 of 4 prefix terms "health," "fitness," "workout," or "physical" coupled with 1 of 2 stem terms "activity partners" or "activity buddies." We also searched 2 prominent technology start-up news sites, TechCrunch and Y Combinator, using 2 unique keyword combinations: the common keyword "find" coupled with 1 of 2 stem terms "activity partners" and "activity buddies." Sites were defined as online social health activity networks if they had the ability to (1) actively find physical activity partners or activities for the user, (2) offer dynamic, real-time tracking or sharing of social activities, and (3) provide virtual profiles to users. We excluded from our analysis sites that were not Web-based, publicly available, in English, or free. Of the 360 initial search results, we identified 13 websites that met our complete criteria of an online social health activity network. Features such as physical activity creation (13/13, 100%) and private messaging (12/13, 92%) appeared almost universally among these websites. However, integration with Web 2.0 technologies such as Facebook and Twitter (9/13, 69%) and the option of direct event joining (8/13, 62%) were not as universally present. Largely absent were more sophisticated features that would enable greater usability, such as interactive engagement prompts (3/13, 23%) and system-created best fit activities (3/13, 23%). Several major online social networks that connect users to physical activity partners currently exist and use standardized features to achieve their goals. Future research is needed to better understand how users utilize these features and how helpful they truly are.

Efficient Online Learning Algorithms Based on LSTM Neural Networks.

PubMed

Ergen, Tolga; Kozat, Suleyman Serdar

2017-09-13

We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

Social Work in a Digital Age: Ethical and Risk Management Challenges

ERIC Educational Resources Information Center

Reamer, Frederic G.

2013-01-01

Digital, online, and other electronic technology has transformed the nature of social work practice. Contemporary social workers can provide services to clients by using online counseling, telephone counseling, video counseling, cybertherapy (avatar therapy), self-guided Web-based interventions, electronic social networks, e-mail, and text…

Online Socialization through Social Software and Networks from an Educational Perspective

ERIC Educational Resources Information Center

Gülbahar, Yasemin

2015-01-01

The potential represented by the usage of Internet-based communication technologies in parallel with e-instruction is enabling learners to cooperate and collaborate throughout the world. However, an important dimension, namely the socialization of learners through online dialogues via e-mail, discussion forums, chats, blogs, wikis and virtual…

Why we need more than just randomized controlled trials to establish the effectiveness of online social networks for health behavior change.

PubMed

Vandelanotte, Corneel; Maher, Carol A

2015-01-01

Despite their popularity and potential to promote health in large populations, the effectiveness of online social networks (e.g., Facebook) to improve health behaviors has been somewhat disappointing. Most of the research examining the effectiveness of such interventions has used randomized controlled trials (RCTs). It is asserted that the modest outcomes may be due to characteristics specific to both online social networks and RCTs. The highly controlled nature of RCTs stifles the dynamic nature of online social networks. Alternative and ecologically valid research designs that evaluate online social networks in real-life conditions are needed to advance the science in this area.

Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

NASA Astrophysics Data System (ADS)

Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng

2013-01-01

Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.

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.

Power Grid Maintenance Scheduling Intelligence Arrangement Supporting System Based on Power Flow Forecasting

NASA Astrophysics Data System (ADS)

Xie, Chang; Wen, Jing; Liu, Wenying; Wang, Jiaming

With the development of intelligent dispatching, the intelligence level of network control center full-service urgent need to raise. As an important daily work of network control center, the application of maintenance scheduling intelligent arrangement to achieve high-quality and safety operation of power grid is very important. By analyzing the shortages of the traditional maintenance scheduling software, this paper designs a power grid maintenance scheduling intelligence arrangement supporting system based on power flow forecasting, which uses the advanced technologies in maintenance scheduling, such as artificial intelligence, online security checking, intelligent visualization techniques. It implements the online security checking of maintenance scheduling based on power flow forecasting and power flow adjusting based on visualization, in order to make the maintenance scheduling arrangement moreintelligent and visual.

Students' Participation in Social Networking Sites: Implications for Social Work Education

ERIC Educational Resources Information Center

Mukherjee, Dhrubodhi; Clark, Janet

2012-01-01

Social work students have few guidelines to help them evaluate the implication of their posted information on Internet-based social networking sites (SNSs). There is a national trend among employers of human services to cross-check publicly available online information on applicants. Based on data from a survey of 105 baccalaureate and master's…

Leveraging social media in the stem cell sector: exploring Twitter's potential as a vehicle for public information campaigns.

PubMed

McNutt, Kathleen; Zarzeczny, Amy

2017-10-01

Our aim in this project was to explore Twitter's potential as a vehicle for an online public information campaign (PIC) focused on providing evidence-based information about stem cell therapies and the market for unproven stem cell-based interventions. We designed an online, Twitter-based PIC using classic design principles and identified a set of target intermediaries (organizations with online influence) using a network governance approach. We tracked the PIC's dissemination over a 2-month period, and evaluated it using metrics from the #SMMStandards Conclave. Participation was limited but the PIC achieved some reach and engagement. Social media based online PICs appear to have potential but also face challenges. Future research is required to better understand how to most effectively maximize their strengths.

Online location of a break in water distribution systems

NASA Astrophysics Data System (ADS)

Liang, Jianwen; Xiao, Di; Zhao, Xinhua; Zhang, Hongwei

2003-08-01

Breaks often occur to urban water distribution systems under severely cold weather, or due to corrosion of pipes, deformation of ground, etc., and the breaks cannot easily be located, especially immediately after the events. This paper develops a methodology to locate a break in a water distribution system by monitoring water pressure online at some nodes in the water distribution system. For the purpose of online monitoring, supervisory control and data acquisition (SCADA) technology can well be used. A neural network-based inverse analysis method is constructed for locating the break based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water distribution system, and validated by using a set of data that have never been used in the training. It is found that the methodology provides a quick, effective, and practical way in which a break in a water distribution system can be located.

Online social networks for patient involvement and recruitment in clinical research.

PubMed

Ryan, Gemma Sinead

2013-01-01

To review current literature and discuss the potential of online social networking to engage patients and the public and recruit and retain participants in clinical research. Online social networking is becoming a large influence on people's daily lives. Clinical research faces several challenges, with an increasing need to engage with patients and the public and for studies to recruit and retain increasing numbers of participants, particularly in under-served, under-represented and hard to reach groups and communities. Searches were conducted using EMBASE, BNI, ERIC, CINAHL, PSYCHinfo online databases and Google Scholar to identify any grey or unpublished literature that may be available. Review methods This is a methodology paper. Online social networking is a successful, cost-effective and efficient method by which to target and recruit a wide range of communities, adolescents, young people and underserved populations into quantitative and qualitative research. Retention of participants in longitudinal studies could be improved using social networks such as Facebook. Evidence indicates that a mixed approach to recruitment using social networking and traditional methods is most effective. Further research is required to strengthen the evidence available, especially in dissemination of research through online social networks. Researchers should consider using online social networking as a method of engaging the public, and also for the recruitment and follow up of participants.

Data Quality in Online Health Social Networks for Chronic Diseases

ERIC Educational Resources Information Center

Venkatesan, Srikanth

2017-01-01

Can medical advice from other participants in online health social networks impact patient safety? What can we do alleviate this problem? How does the accuracy of information on such networks affect the patients?. There has been a significant increase , in recent years, in the use of online health social network sites as more patients seek to…

Problem formulation, metrics, open government, and on-line collaboration

NASA Astrophysics Data System (ADS)

Ziegler, C. R.; Schofield, K.; Young, S.; Shaw, D.

2010-12-01

Problem formulation leading to effective environmental management, including synthesis and application of science by government agencies, may benefit from collaborative on-line environments. This is illustrated by two interconnected projects: 1) literature-based evidence tools that support causal assessment and problem formulation, and 2) development of output, outcome, and sustainability metrics for tracking environmental conditions. Specifically, peer-production mechanisms allow for global contribution to science-based causal evidence databases, and subsequent crowd-sourced development of causal networks supported by that evidence. In turn, science-based causal networks may inform problem formulation and selection of metrics or indicators to track environmental condition (or problem status). Selecting and developing metrics in a collaborative on-line environment may improve stakeholder buy-in, the explicit relevance of metrics to planning, and the ability to approach problem apportionment or accountability, and to define success or sustainability. Challenges include contribution governance, data-sharing incentives, linking on-line interfaces to data service providers, and the intersection of environmental science and social science. Degree of framework access and confidentiality may vary by group and/or individual, but may ultimately be geared at demonstrating connections between science and decision making and supporting a culture of open government, by fostering transparency, public engagement, and collaboration.

"Supporting Early Career Women in the Geosciences through Online Peer-Mentoring: Lessons from the Earth Science Women's Network (ESWN)"

NASA Astrophysics Data System (ADS)

Holloway, T.; Hastings, M. G.; Barnes, R. T.; Fischer, E. V.; Wiedinmyer, C.; Rodriguez, C.; Adams, M. S.; Marin-Spiotta, E.

2014-12-01

The Earth Science Women's Network (ESWN) is an international peer-mentoring organization with over 2000 members, dedicated to career development and community for women across the geosciences. Since its formation in 2002, ESWN has supported the growth of a more diverse scientific community through a combination of online and in-person networking activities. Lessons learned related to online networking and community-building will be presented. ESWN serves upper-level undergraduates, graduate students, professionals in a range of environmental fields, scientists working in federal and state governments, post-doctoral researchers, and academic faculty and scientists. Membership includes women working in over 50 countries, although the majority of ESWN members work in the U.S. ESWN increases retention of women in the geosciences by enabling and supporting professional person-to-person connections. This approach has been shown to reduce feelings of isolation among our members and help build professional support systems critical to career success. In early 2013 ESWN transitioned online activities to an advanced social networking platform that supports discussion threads, group formation, and individual messaging. Prior to that, on-line activities operated through a traditional list-serve, hosted by the National Center for Atmospheric Research (NCAR). The new web center, http://eswnonline.org, serves as the primary forum for members to build connections, seek advice, and share resources. For example, members share job announcements, discuss issues of work-life balance, and organize events at professional conferences. ESWN provides a platform for problem-based mentoring, drawing from the wisdom of colleagues across a range of career stages.

Method and system for determining induction motor speed

DOEpatents

Parlos, Alexander G.; Bharadwaj, Raj M.

2004-03-30

A non-linear, semi-parametric neural network-based adaptive filter is utilized to determine the dynamic speed of a rotating rotor within an induction motor, without the explicit use of a speed sensor, such as a tachometer, is disclosed. The neural network-based filter is developed using actual motor current measurements, voltage measurements, and nameplate information. The neural network-based adaptive filter is trained using an estimated speed calculator derived from the actual current and voltage measurements. The neural network-based adaptive filter uses voltage and current measurements to determine the instantaneous speed of a rotating rotor. The neural network-based adaptive filter also includes an on-line adaptation scheme that permits the filter to be readily adapted for new operating conditions during operations.

Bridging online and offline social networks: Multiplex analysis

NASA Astrophysics Data System (ADS)

Filiposka, Sonja; Gajduk, Andrej; Dimitrova, Tamara; Kocarev, Ljupco

2017-04-01

We show that three basic actor characteristics, namely normalized reciprocity, three cycles, and triplets, can be expressed using an unified framework that is based on computing the similarity index between two sets associated with the actor: the set of her/his friends and the set of those considering her/him as a friend. These metrics are extended to multiplex networks and then computed for two friendship networks generated by collecting data from two groups of undergraduate students. We found that in offline communication strong and weak ties are (almost) equally presented, while in online communication weak ties are dominant. Moreover, weak ties are much less reciprocal than strong ties. However, across different layers of the multiplex network reciprocities are preserved, while triads (measured with normalized three cycles and triplets) are not significant.

Decentralized Online Social Networks

NASA Astrophysics Data System (ADS)

Datta, Anwitaman; Buchegger, Sonja; Vu, Le-Hung; Strufe, Thorsten; Rzadca, Krzysztof

Current Online social networks (OSN) are web services run on logically centralized infrastructure. Large OSN sites use content distribution networks and thus distribute some of the load by caching for performance reasons, nevertheless there is a central repository for user and application data. This centralized nature of OSNs has several drawbacks including scalability, privacy, dependence on a provider, need for being online for every transaction, and a lack of locality. There have thus been several efforts toward decentralizing OSNs while retaining the functionalities offered by centralized OSNs. A decentralized online social network (DOSN) is a distributed system for social networking with no or limited dependency on any dedicated central infrastructure. In this chapter we explore the various motivations of a decentralized approach to online social networking, discuss several concrete proposals and types of DOSN as well as challenges and opportunities associated with decentralization.

On-line training of recurrent neural networks with continuous topology adaptation.

PubMed

Obradovic, D

1996-01-01

This paper presents an online procedure for training dynamic neural networks with input-output recurrences whose topology is continuously adjusted to the complexity of the target system dynamics. This is accomplished by changing the number of the elements of the network hidden layer whenever the existing topology cannot capture the dynamics presented by the new data. The training mechanism is based on the suitably altered extended Kalman filter (EKF) algorithm which is simultaneously used for the network parameter adjustment and for its state estimation. The network consists of a single hidden layer with Gaussian radial basis functions (GRBF), and a linear output layer. The choice of the GRBF is induced by the requirements of the online learning. The latter implies the network architecture which permits only local influence of the new data point in order not to forget the previously learned dynamics. The continuous topology adaptation is implemented in our algorithm to avoid memory and computational problems of using a regular grid of GRBF'S which covers the network input space. Furthermore, we show that the resulting parameter increase can be handled "smoothly" without interfering with the already acquired information. If the target system dynamics are changing over time, we show that a suitable forgetting factor can be used to "unlearn" the no longer-relevant dynamics. The quality of the recurrent network training algorithm is demonstrated on the identification of nonlinear dynamic systems.

A generalized theory of preferential linking

NASA Astrophysics Data System (ADS)

Hu, Haibo; Guo, Jinli; Liu, Xuan; Wang, Xiaofan

2014-12-01

There are diverse mechanisms driving the evolution of social networks. A key open question dealing with understanding their evolution is: How do various preferential linking mechanisms produce networks with different features? In this paper we first empirically study preferential linking phenomena in an evolving online social network, find and validate the linear preference. We propose an analyzable model which captures the real growth process of the network and reveals the underlying mechanism dominating its evolution. Furthermore based on preferential linking we propose a generalized model reproducing the evolution of online social networks, and present unified analytical results describing network characteristics for 27 preference scenarios. We study the mathematical structure of degree distributions and find that within the framework of preferential linking analytical degree distributions can only be the combinations of finite kinds of functions which are related to rational, logarithmic and inverse tangent functions, and extremely complex network structure will emerge even for very simple sublinear preferential linking. This work not only provides a verifiable origin for the emergence of various network characteristics in social networks, but bridges the micro individuals' behaviors and the global organization of social networks.

Technology use and reasons to participate in online social networking websites for people living with HIV in the US

PubMed Central

Horvath, Keith J.; Danilenko, Gene P.; Williams, Mark L.; Simoni, Jane; Amico, K. Rivet; Oakes, J. Michael; Rosser, B.R. Simon

2012-01-01

It is unknown if online social networking technologies are already highly integrated among some people living with HIV (PLWH) or have yet to be adopted. To fill this gap in understanding, 312 PLWH (84% male, 69% white) residing in the US completed on online survey in 2009 of their patterns of social networking and mobile phone use. Twenty-two persons also participated in one of two online focus groups. Results showed that 76% of participants with lower adherence to HIV medication used social networking websites/features at least once a week. Their ideal online social networking health websites included one that facilitated socializing with others (45% of participants) and relevant informational content (22%), although privacy was a barrier to use (26%). Texting (81%), and to a lesser extent mobile web-access (51%), was widely used among participants. Results support the potential reach of online social networking and text messaging intervention approaches. PMID:22350832

Sex Differences in Virtual Network Characteristics and Sexual Risk Behavior among Emerging Adults

PubMed Central

Cook, Stephanie H.; Bauermeister, José A.; Zimmerman, Marc A.

2016-01-01

Emerging adults (EAs)ages 18 to 24 account for a large proportion of all sexually transmitted infections (STIs), HIV infections, and unintended pregnancies in the United States. Given the increased influence of online media on decision-making, we examined how EA online networks were associated with sexual risk behaviors. We used egocentric network data collected from EAs aged 18 to 24 years old across the United States (N=1,687) to examine how online norms (e.g., acceptance of HIV infections, other STIs, and pregnancy) and network characteristics (i.e., network size and density; ties' closeness, race, age, and sex similarities) were associated with participants' unprotected vaginal intercourse (UVI) in the last 30 days. Findings suggested that in male EAs, there was a strong association between sexual norms, structural characteristics, and sexual risk behavior compared to females. Researchers and practitioners may wish to address online peer norms and EAs' online network composition when developing online sexual risk prevention tools. PMID:28083447

Facebook and romantic relationships: intimacy and couple satisfaction associated with online social network use.

PubMed

Hand, Matthew M; Thomas, Donna; Buboltz, Walter C; Deemer, Eric D; Buyanjargal, Munkhsanaa

2013-01-01

Online social networks, such as Facebook, have gained immense popularity and potentially affect the way people build and maintain interpersonal relationships. The present study sought to examine time spent on online social networks, as it relates to intimacy and relationship satisfaction experienced in romantic relationships. Results did not find relationships between an individual's usage of online social networks and his/her perception of relationship satisfaction and intimacy. However, the study found a negative relationship between intimacy and the perception of a romantic partner's use of online social networks. This finding may allude to an attributional bias in which individuals are more likely to perceive a partner's usage as negative compared to their own usage. Additionally, it was found that intimacy mediates the relationship between online social network usage and overall relationship satisfaction, which suggests that the level of intimacy experienced in a relationship may serve as a buffer that protects the overall level of satisfaction.

Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

PubMed

Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

2017-03-01

A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Networked Learning: Design Considerations for Online Instructors

ERIC Educational Resources Information Center

Czerkawski, Betul C.

2016-01-01

The considerable increase in web-based knowledge networks in the past two decades is strongly influencing learning environments. Learning entails information retrieval, use, communication, and production, and is strongly enriched by socially mediated discussions, debates, and collaborative activities. It is becoming critical for educators to…

The Personal Learning Planner: Collaboration through Online Learning and Publication

ERIC Educational Resources Information Center

Gibson, David; Sherry, Lorraine; Havelock, Bruce

2007-01-01

This paper discusses the online Personal Learning Planner (PLP) project underway at the National Institute of Community Innovations (NICI), one of the partners in the Teacher Education Network (TEN), a 2000 PT3 Catalyst grantee. The Web-based PLP provides a standards-linked "portfolio space" for both works in progress and demonstration collections…

Learning online social support: an investigation of network information technology based on UTAUT.

PubMed

Lin, Chieh-Peng; Anol, Bhattacherjee

2008-06-01

Extending the unified theory of acceptance and use of technology (UTAUT) model, this study postulates a model of online social support. The model is empirically tested using data from undergraduates in Taiwan regarding their usage of instant messaging (IM). The test results indicate that all model paths are significant, except that the path between online social support and facilitating conditions is insignificant. This study offers limitations and implications.

Academics and Social Networking Sites: Benefits, Problems and Tensions in Professional Engagement with Online Networking

ERIC Educational Resources Information Center

Jordan, Katy; Weller, Martin

2018-01-01

The web has had a profound effect on the ways people interact, with online social networks arguably playing an important role in changing or augmenting how we connect with others. However, uptake of online social networking by the academic community varies, and needs to be understood. This paper presents an independent, novel analysis of a…

Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features

NASA Astrophysics Data System (ADS)

Bouboulis, Pantelis; Chouvardas, Symeon; Theodoridis, Sergios

2018-04-01

We present a novel diffusion scheme for online kernel-based learning over networks. So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS), is the need for updating a growing number of parameters as time iterations evolve. Besides complexity, this leads to an increased need of communication resources, in a distributed setting. In contrast, the proposed method approximates the solution as a fixed-size vector (of larger dimension than the input space) using Random Fourier Features. This paves the way to use standard linear combine-then-adapt techniques. To the best of our knowledge, this is the first time that a complete protocol for distributed online learning in RKHS is presented. Conditions for asymptotic convergence and boundness of the networkwise regret are also provided. The simulated tests illustrate the performance of the proposed scheme.

Methods for inferring health-related social networks among coworkers from online communication patterns.

PubMed

Matthews, Luke J; DeWan, Peter; Rula, Elizabeth Y

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network.

Methods for Inferring Health-Related Social Networks among Coworkers from Online Communication Patterns

PubMed Central

Matthews, Luke J.; DeWan, Peter; Rula, Elizabeth Y.

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network. PMID:23418436

"This Site Is Blocked": K-12 Teachers and the Challenge of Accessing Peer-to-Peer Networks for Education

ERIC Educational Resources Information Center

Ching, Cynthia Carter; Hursh, Anthony W.

2010-01-01

This article examines a little-discussed phenomenon in the study of both peer-to-peer collaborative networks and teaching with technology: that of teachers caught in the middle between open public networks as teaching resources and highly restrictive school policies regarding internet content and online access. Based on their experiences as…

Online People Tagging: Social (Mobile) Network(ing) Services and Work-Based Learning

ERIC Educational Resources Information Center

Cook, John; Pachler, Norbert

2012-01-01

Social and mobile technologies offer users unprecedented opportunities for communicating, interacting, sharing, meaning-making, content and context generation. And, these affordances are in constant flux driven by a powerful interplay between technological innovation and emerging cultural practices. Significantly, also, they are starting to…

Assessing the Validity of Automated Webcrawlers as Data Collection Tools to Investigate Online Child Sexual Exploitation.

PubMed

Westlake, Bryce; Bouchard, Martin; Frank, Richard

2017-10-01

The distribution of child sexual exploitation (CE) material has been aided by the growth of the Internet. The graphic nature and prevalence of the material has made researching and combating difficult. Although used to study online CE distribution, automated data collection tools (e.g., webcrawlers) have yet to be shown effective at targeting only relevant data. Using CE-related image and keyword criteria, we compare networks starting from CE websites to those from similar non-CE sexuality websites and dissimilar sports websites. Our results provide evidence that (a) webcrawlers have the potential to provide valid CE data, if the appropriate criterion is selected; (b) CE distribution is still heavily image-based suggesting images as an effective criterion; (c) CE-seeded networks are more hub-based and differ from non-CE-seeded networks on several website characteristics. Recommendations for improvements to reliable criteria selection are discussed.

Novel WRM-based architecture of hybrid PON featuring online access and full-fiber-fault protection for smart grid

NASA Astrophysics Data System (ADS)

Li, Xingfeng; Gan, Chaoqin; Liu, Zongkang; Yan, Yuqi; Qiao, HuBao

2018-01-01

In this paper, a novel architecture of hybrid PON for smart grid is proposed by introducing a wavelength-routing module (WRM). By using conventional optical passive components, a WRM with M ports is designed. The symmetry and passivity of the WRM makes it be easily integrated and very cheap in practice. Via the WRM, two types of network based on different ONU-interconnected manner can realize online access. Depending on optical switches and interconnecting fibers, full-fiber-fault protection and dynamic bandwidth allocation are realized in these networks. With the help of amplitude modulation, DPSK modulation and RSOA technology, wavelength triple-reuse is achieved. By means of injecting signals into left and right branches in access ring simultaneously, the transmission delay is decreased. Finally, the performance analysis and simulation of the network verifies the feasibility of the proposed architecture.

Crossing boundaries: the design of an interdisciplinary training program to improve care for the frail elderly.

PubMed

Kolomitro, Klodiana; Stockley, Denise; Egan, Rylan; MacDonald, Michelle L

2015-01-01

The Technology Evaluation in the Elderly Network (TVN) was funded in July 2012 under the Canadian Networks of Centres of Excellence program. This article highlights the development and preliminary evaluation of the TVN Interdisciplinary Training Program. This program is based on an experiential learning approach that crosses a multitude of disciplines including health sciences, law, social sciences, and ethical aspects of working with the frail elderly. Opportunities within the program include mentorship, interdisciplinary online collaborative projects, external placements, academic products, pre-grant submission, trainee-driven requirements, Network meetings, online modules/webinars, and most importantly active involvement with patients, families, and their support systems. The authors have 120 trainees from approximately 23 different disciplines including law, ethics, public policy, social work, and engineering engaged in the program. Based on our evaluation this program has been perceived as highly valuable by the participants and the community.

The Joint Fire Science Program Fire Exchange Network: Facilitating Knowledge Exchange About Wildland Fire Science Across the U.S.

NASA Astrophysics Data System (ADS)

York, A.; Blocksome, C.; Cheng, T.; Creighton, J.; Edwards, G.; Frederick, S.; Giardina, C. P.; Goebel, P. C.; Gucker, C.; Kobziar, L.; Lane, E.; Leis, S.; Long, A.; Maier, C.; Marschall, J.; McGowan-Stinski, J.; Mohr, H.; MontBlanc, E.; Pellant, M.; Pickett, E.; Seesholtz, D.; Skowronski, N.; Stambaugh, M. C.; Stephens, S.; Thode, A.; Trainor, S. F.; Waldrop, T.; Wolfson, B.; Wright, V.; Zedler, P.

2014-12-01

The Joint Fire Science Program's (JFSP) Fire Exchange Network is actively working to accelerate the awareness, understanding, and adoption of wildland fire science information by federal, tribal, state, local, and private stakeholders within ecologically similar regions. Our network of 15 regional exchanges provides timely, accurate, and regionally relevant science-based information to assist with fire management challenges. Regional activities, through which we engage fire and resource managers, scientists, and private landowners, include online newsletters and announcements, social media, regionally focused web-based clearinghouses of relevant science, field trips and demonstration sites, workshops and conferences, webinars and online training, and syntheses and fact sheets. Exchanges also help investigators design research that is relevant to regional management needs and assist with technology transfer to management audiences. This poster provides an introduction to and map of the regional exchanges.

From Dyadic Ties to Information Infrastructures: Care-Coordination between Patients, Providers, Students and Researchers

PubMed Central

Purkayastha, S.; Biswas, R.; Jai Ganesh, A.U.; Otero, P.

2015-01-01

Summary Objective To share how an effectual merging of local and online networks in low resource regions can supplement and strengthen the local practice of patient centered care through the use of an online digital infrastructure powered by all stakeholders in healthcare. User Driven Health Care offers the dynamic integration of patient values and evidence based solutions for improved medical communication in medical care. Introduction This paper conceptualizes patient care-coordination through the lens of engaged stakeholders using digital infrastructures tools to integrate information technology. We distinguish this lens from the prevalent conceptualization of dyadic ties between clinician-patient, patient-nurse, clinician-nurse, and offer the holistic integration of all stakeholder inputs, in the clinic and augmented by online communication in a multi-national setting. Methods We analyze an instance of the user-driven health care (UDHC), a network of providers, patients, students and researchers working together to help manage patient care. The network currently focuses on patients from LMICs, but the provider network is global in reach. We describe UDHC and its opportunities and challenges in care-coordination to reduce costs, bring equity, and improve care quality and share evidence. Conclusion UDHC has resulted in coordinated global based local care, affecting multiple facets of medical practice. Shared information resources between providers with disparate knowledge, results in better understanding by patients, unique and challenging cases for students, innovative community based research and discovery learning for all. PMID:26123908

From Dyadic Ties to Information Infrastructures: Care-Coordination between Patients, Providers, Students and Researchers. Contribution of the Health Informatics Education Working Group.

PubMed

Purkayastha, S; Price, A; Biswas, R; Jai Ganesh, A U; Otero, P

2015-08-13

To share how an effectual merging of local and online networks in low resource regions can supplement and strengthen the local practice of patient centered care through the use of an online digital infrastructure powered by all stakeholders in healthcare. User Driven Health Care offers the dynamic integration of patient values and evidence based solutions for improved medical communication in medical care. This paper conceptualizes patient care-coordination through the lens of engaged stakeholders using digital infrastructures tools to integrate information technology. We distinguish this lens from the prevalent conceptualization of dyadic ties between clinician-patient, patient-nurse, clinician-nurse, and offer the holistic integration of all stakeholder inputs, in the clinic and augmented by online communication in a multi-national setting. We analyze an instance of the user-driven health care (UDHC), a network of providers, patients, students and researchers working together to help manage patient care. The network currently focuses on patients from LMICs, but the provider network is global in reach. We describe UDHC and its opportunities and challenges in care-coordination to reduce costs, bring equity, and improve care quality and share evidence. UDHC has resulted in coordinated global based local care, affecting multiple facets of medical practice. Shared information resources between providers with disparate knowledge, results in better understanding by patients, unique and challenging cases for students, innovative community based research and discovery learning for all.

Online Identities and Social Networking

NASA Astrophysics Data System (ADS)

Maheswaran, Muthucumaru; Ali, Bader; Ozguven, Hatice; Lord, Julien

Online identities play a critical role in the social web that is taking shape on the Internet. Despite many technical proposals for creating and managing online identities, none has received widespread acceptance. Design and implementation of online identities that are socially acceptable on the Internet remains an open problem. This chapter discusses the interplay between online identities and social networking. Online social networks (OSNs) are growing at a rapid pace and has millions of members in them. While the recent trend is to create explicit OSNs such as Facebook and MySpace, we also have implicit OSNs such as interaction graphs created by email and instant messaging services. Explicit OSNs allow users to create profiles and use them to project their identities on the web. There are many interesting identity related issues in the context of social networking including how OSNs help and hinder the definition of online identities.

Examining the Relationship between Online Social Capital and eHealth Literacy: Implications for Instagram Use for Chronic Disease Prevention among College Students

PubMed Central

Stellefson, Michael; Chaney, Beth H.; Chaney, J. Don; 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 moderates the relationship between eHealth Literacy and online social capital in college students, and (2) discuss how Instagram can be used as a social awareness platform for chronic disease prevention among college students. Methods Hierarchical regression analyses were conducted to analyze web-based survey data from a random sample of college students (N=327). Results Online bridging social capital was associated with greater eHealth Literacy (P<.05) and intensity of Instagram use (P<.001), when controlling for socio-demographic variables. The relationship between eHealth Literacy and online bridging social capital was strongest among respondents’ with average (P<.01) and high (P<.01) intensity Instagram use, as compared to low Instagram intensity. Discussion High intensity of Instagram may strengthen college students’ low eHealth Literacy, especially when interacting with heterogeneous connections with weaker ties. Translation to Health Education Practice Health education specialists should continue to explore how college students’ intensity of Instagram use can be strengthened to build bridging online social capital, and ultimately prevent chronic disease. PMID:29152031

Examining the Relationship between Online Social Capital and eHealth Literacy: Implications for Instagram Use for Chronic Disease Prevention among College Students.

PubMed

Paige, Samantha R; Stellefson, Michael; Chaney, Beth H; Chaney, J Don; Alber, Julia M; Chappell, Chelsea; Barry, Adam E

2017-01-01

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. This study aimed to: (1) examine how intensity of Instagram use moderates the relationship between eHealth Literacy and online social capital in college students, and (2) discuss how Instagram can be used as a social awareness platform for chronic disease prevention among college students. Hierarchical regression analyses were conducted to analyze web-based survey data from a random sample of college students ( N =327). Online bridging social capital was associated with greater eHealth Literacy ( P <.05) and intensity of Instagram use ( P <.001), when controlling for socio-demographic variables. The relationship between eHealth Literacy and online bridging social capital was strongest among respondents' with average ( P <.01) and high ( P <.01) intensity Instagram use, as compared to low Instagram intensity. High intensity of Instagram may strengthen college students' low eHealth Literacy, especially when interacting with heterogeneous connections with weaker ties. Health education specialists should continue to explore how college students' intensity of Instagram use can be strengthened to build bridging online social capital, and ultimately prevent chronic disease.

Addiction to Internet Use, Online Gaming, and Online Social Networking Among Young Adults in China, Singapore, and the United States.

PubMed

Tang, Catherine So-Kum; Koh, Yee Woen; Gan, YiQun

2017-11-01

The current study investigated the rates of addictions to Internet use, online gaming, and online social networking as well as their associations with depressive symptoms among young adults in China, Singapore, and the United States. A total of 3267 undergraduate students were recruited. Psychological instruments were used to assess various Internet-related addictions and depressive symptoms. Male students were more addicted to Internet and online gaming whereas female students were more addicted to online social networking. Compared with students in the United States, Chinese and Singaporean students were more addicted to Internet use and online social networking but less to online gaming. The odds of depression among students with addiction to various Internet-related addictions were highest in China. Internet-related addiction is a new public health concern of young adults, especially in the Asia-Pacific regions. It is found to associate with depressive symptoms. Strategies should address this phenomenon with attention to specific needs of gender and region while managing mood disturbances.

Massively Open Online Course for Educators (MOOC-Ed) Network Dataset

ERIC Educational Resources Information Center

Kellogg, Shaun; Edelmann, Achim

2015-01-01

This paper presents the Massively Open Online Course for Educators (MOOC-Ed) network dataset. It entails information on two online communication networks resulting from two consecutive offerings of the MOOC called "The Digital Learning Transition in K-12 Schools" in spring and fall 2013. The courses were offered to educators from the USA…

The Social Network Classroom

NASA Astrophysics Data System (ADS)

Bunus, Peter

Online social networking is an important part in the everyday life of college students. Despite the increasing popularity of online social networking among students and faculty members, its educational benefits are largely untested. This paper presents our experience in using social networking applications and video content distribution websites as a complement of traditional classroom education. In particular, the solution has been based on effective adaptation, extension and integration of Facebook, Twitter, Blogger YouTube and iTunes services for delivering educational material to students on mobile platforms like iPods and 3 rd generation mobile phones. The goals of the proposed educational platform, described in this paper, are to make the learning experience more engaging, to encourage collaborative work and knowledge sharing among students, and to provide an interactive platform for the educators to reach students and deliver lecture material in a totally new way.

Role Modelling in MOOC Discussion Forums

ERIC Educational Resources Information Center

Hecking, Tobias; Chounta, Irene-Angelica; Hoppe, H. Ulrich

2017-01-01

To further develop rich and expressive ways of modelling roles of contributors in discussion forums of online courses, particularly in MOOCs, networks of forum users are analyzed based on the relations of information-giving and information-seeking. Specific connection patterns that appear in the information exchange networks of forum users are…

Effectiveness of Simulation in a Hybrid and Online Networking Course.

ERIC Educational Resources Information Center

Cameron, Brian H.

2003-01-01

Reports on a study that compares the performance of students enrolled in two sections of a Web-based computer networking course: one utilizing a simulation package and the second utilizing a static, graphical software package. Analysis shows statistically significant improvements in performance in the simulation group compared to the…

Natural Language Video Description using Deep Recurrent Neural Networks

DTIC Science & Technology

2015-11-23

records who says what, but lacks tim- ing information. Movie scripts typically include names of all characters and most movies loosely follow the...and Jürgen Schmidhuber. A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks. In Proc. 9th Int

Dueling Data

ERIC Educational Resources Information Center

Cesarini, Paul

2008-01-01

What is network neutrality? The basic premise is that people should have the right to access online, in a free and unfettered manner, any type of content that is not illegal, based on the predetermined speed they are paying their Internet-service provider (ISP) for each month. That is, with network neutrality, the content becomes irrelevant. The…

Get Networked and Spy Your Languages

ERIC Educational Resources Information Center

Rico, Mercedes; Ferreira, Paula; Dominguez, Eva M.; Coppens, Julian

2012-01-01

Our proposal describes ISPY, a multilateral European K2 language project based on the development of an Online Networking Platform for Language Learning (http://www.ispy-project.com/). Supported by the Lifelong Learning European Programme, the platform aims to help young adults across Europe, secondary and vocational school programs, learn a new…

Social Facilitation Effects by Pedagogical Conversational Agent: Lexical Network Analysis in an Online Explanation Task

ERIC Educational Resources Information Center

Hayashi, Yugo

2015-01-01

The present study investigates web-based learning activities of undergraduate students who generate explanations about a key concept taught in a large-scale classroom. The present study used an online system with Pedagogical Conversational Agent (PCA), asked to explain about the key concept from different points and provided suggestions and…

Comparing the Social Knowledge Construction Behavioral Patterns of Problem-Based Online Asynchronous Discussion in E/M-Learning Environments

ERIC Educational Resources Information Center

Lan, Yu-Feng; Tsai, Pei-Wei; Yang, Shih-Hsien; Hung, Chun-Ling

2012-01-01

In recent years, researchers have conducted various studies on applying wireless networking technology and mobile devices in education settings. However, research on behavioral patterns in learners' online asynchronous discussions with mobile devices is limited. The purposes of this study are to develop a mobile learning system, mobile interactive…

Reflective Outcomes of Convergent and Divergent Group Tasking in the Online Learning Environment

ERIC Educational Resources Information Center

Hawkes, Mark

2007-01-01

Using collaborative critical reflection as an index, this study examines the asynchronous and face-to-face discourse of 28 suburban Chicago elementary teachers developing problem based learning (PBL) curriculum. Statistical analysis of the corpus produced by the 2 mediums shows that the asynchronous online network emerges as the medium of choice…

Correlates of consumer trust in online health information: findings from the health information national trends survey.

PubMed

Ye, Yinjiao

2011-01-01

The past few decades have witnessed a dramatic increase in consumers seeking health information online. However, the quality of such information remains questionable, and the trustworthiness of online health information has become a hot topic, whereas little attention has been paid to how consumers evaluate online health information credibility. This study builds on theoretical perspectives of trust such as personal-capital-based, social-capital-based, and transfer-based, and it examines various correlates of consumer trust in online health information. The author analyzed the 2007 Health Information National Trends Survey data (N = 7,674). Results showed that consumer trust in online health information did not correlate with personal capital such as income, education, and health status. Social capital indicated by visiting social networking Web sites was not associated with trust in online health information either. Nevertheless, trust in online health information transferred from traditional mass media and government health agencies to the Internet, and it varied by such information features as easiness to locate and to understand. Age appeared to be a key factor in understanding the correlates of trust in online health information. Theoretical and empirical implications of the results are discussed.

Identifying web usage behavior of bank customers

NASA Astrophysics Data System (ADS)

Araya, Sandro; Silva, Mariano; Weber, Richard

2002-03-01

The bank Banco Credito e Inversiones (BCI) started its virtual bank in 1996 and its registered customers perform currently more than 10,000 Internet transactions daily, which typically cause les than 10% of traditional transaction costs. Since most of the customers are still not registered for online banking, one of the goals of the virtual bank is to increase then umber of registered customers. Objective of the presented work was to identify customers who are likely to perform online banking but still do not use this medium for their transactions. This objective has been reached by determining profiles of registered customers who perform many transactions online. Based on these profiles the bank's Data Warehouse is explored for twins of these heavy users that are still not registered for online banking. We applied clustering in order to group the registered customers into five classes. One of these classes contained almost 30% of all registered customers and could clearly be identified as class of heavy users. Next a neural network assigned online customers to the previously found five classes. Applying the network trained on online customers to all the bank customers identified twins of heavy users that, however had not performed online transactions so far. A mailing to these candidates informing about the advantages of online banking doubled the number of registrations compared to previous campaigns.

Empirical analysis of online social networks in the age of Web 2.0

NASA Astrophysics Data System (ADS)

Fu, Feng; Liu, Lianghuan; Wang, Long

2008-01-01

Today the World Wide Web is undergoing a subtle but profound shift to Web 2.0, to become more of a social web. The use of collaborative technologies such as blogs and social networking site (SNS) leads to instant online community in which people communicate rapidly and conveniently with each other. Moreover, there are growing interest and concern regarding the topological structure of these new online social networks. In this paper, we present empirical analysis of statistical properties of two important Chinese online social networks-a blogging network and an SNS open to college students. They are both emerging in the age of Web 2.0. We demonstrate that both networks possess small-world and scale-free features already observed in real-world and artificial networks. In addition, we investigate the distribution of topological distance. Furthermore, we study the correlations between degree (in/out) and degree (in/out), clustering coefficient and degree, popularity (in terms of number of page views) and in-degree (for the blogging network), respectively. We find that the blogging network shows disassortative mixing pattern, whereas the SNS network is an assortative one. Our research may help us to elucidate the self-organizing structural characteristics of these online social networks embedded in technical forms.

Control of magnetic bearing systems via the Chebyshev polynomial-based unified model (CPBUM) neural network.

PubMed

Jeng, J T; Lee, T T

2000-01-01

A Chebyshev polynomial-based unified model (CPBUM) neural network is introduced and applied to control a magnetic bearing systems. First, we show that the CPBUM neural network not only has the same capability of universal approximator, but also has faster learning speed than conventional feedforward/recurrent neural network. It turns out that the CPBUM neural network is more suitable in the design of controller than the conventional feedforward/recurrent neural network. Second, we propose the inverse system method, based on the CPBUM neural networks, to control a magnetic bearing system. The proposed controller has two structures; namely, off-line and on-line learning structures. We derive a new learning algorithm for each proposed structure. The experimental results show that the proposed neural network architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

PubMed Central

Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

2017-01-01

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks. PMID:28932180

Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.

PubMed

Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

2017-01-01

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

Three Eras in Global Tobacco Control: How Global Governance Processes Influenced Online Tobacco Control Networking.

PubMed

Wipfli, Heather; Chu, Kar-Hai; Lancaster, Molly; Valente, Thomas

2016-01-01

Online networks can serve as a platform to diffuse policy innovations and enhance global health governance. This study focuses on how shifts in global health governance may influence related online networks. We compare social network metrics (average degree centrality [AVGD], density [D] and clustering coefficient [CC]) of Globalink, an online network of tobacco control advocates, across three eras in global tobacco control governance; pre-Framework Convention on Tobacco Control (FCTC) policy transfer (1992-1998), global regime formation through the FCTC negotiations (1999-2005), and philanthropic funding through the Bloomberg Initiative (2006-2012). Prior to 1999, Globalink was driven by a handful of high-income countries (AVGD=1.908 D=0.030, CC=0.215). The FCTC negotiations (1999-2005) corresponded with a rapid uptick in the number of countries represented within Globalink and new members were most often brought into the network through relationships with regional neighbors (AVGD=2.824, D=0.021, CC=0.253). Between 2006 and 2012, the centrality of the US in the network increases significantly (AVGD=3.414, D=0.023, CC=0.310). The findings suggest that global institutionalization through WHO, as with the FCTC, can lead to the rapid growth of decentralized online networks. Alternatively, private initiatives, such as the Bloomberg Initiative, can lead to clustering in which a single source of information gains increasing influence over an online network.

Effects of Digital Footprint on Career Management: Evidence from Social Media in Business Education

NASA Astrophysics Data System (ADS)

Benson, Vladlena; Filippaios, Fragkiskos

As online social media gain immense popularity among Internet users, we would like to explore the implication of social networking on career management. This paper links social capital theories and the impact of online social networks on ties between individuals in social and business uses. Social media contributes to building up individual digital footprint, or Internet content linked to individual names. We then propose a typology of the digital footprint based on the evidence from a survey of business students. Discussion of the implications of the study and arising research questions conclude the article.

Aerial robot intelligent control method based on back-stepping

NASA Astrophysics Data System (ADS)

Zhou, Jian; Xue, Qian

2018-05-01

The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

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.

Security clustering algorithm based on reputation in hierarchical peer-to-peer network

NASA Astrophysics Data System (ADS)

Chen, Mei; Luo, Xin; Wu, Guowen; Tan, Yang; Kita, Kenji

2013-03-01

For the security problems of the hierarchical P2P network (HPN), the paper presents a security clustering algorithm based on reputation (CABR). In the algorithm, we take the reputation mechanism for ensuring the security of transaction and use cluster for managing the reputation mechanism. In order to improve security, reduce cost of network brought by management of reputation and enhance stability of cluster, we select reputation, the historical average online time, and the network bandwidth as the basic factors of the comprehensive performance of node. Simulation results showed that the proposed algorithm improved the security, reduced the network overhead, and enhanced stability of cluster.

RELM: developing a serious game to teach evidence-based medicine in an academic health sciences setting.

PubMed

Gleason, Ann Whitney

2015-01-01

Gaming as a means of delivering online education continues to gain in popularity. Online games provide an engaging and enjoyable way of learning. Gaming is especially appropriate for case-based teaching, and provides a conducive environment for adult independent learning. With funding from the National Network of Libraries of Medicine, Pacific Northwest Region (NN/LM PNR), the University of Washington (UW) Health Sciences Library, and the UW School of Medicine are collaborating to create an interactive, self-paced online game that teaches players to employ the steps in practicing evidence-based medicine. The game encourages life-long learning and literacy skills and could be used for providing continuing medical education.

Understanding the Perceptions of Network Gatekeepers on Bandwidth and Online Video Streams in Ahmadu Bello University, Nigeria

ERIC Educational Resources Information Center

Odigie, Imoisili Ojeime; Gbaje, Ezra Shiloba

2017-01-01

Online video streaming is a learning technology used in today's world and reliant on the availability of bandwidth. This research study sought to understand the perceptions of network gatekeepers about bandwidth and online video streams in Ahmadu Bello University, Nigeria. To achieve this, the interpretive paradigm and the Network Gatekeeping…

Professional Online Presence and Learning Networks: Educating for Ethical Use of Social Media

ERIC Educational Resources Information Center

Forbes, Dianne

2017-01-01

In a teacher education context, this study considers the use of social media for building a professional online presence and learning network. This article provides an overview of uses of social media in teacher education, presents a case study of key processes in relation to professional online presence and learning networks, and highlights…

Sailor: Maryland's Online Public Information Network. Sailor Network Assessment Final Report: Findings and Future Sailor Network Development.

ERIC Educational Resources Information Center

Bertot, John Carlo; McClure, Charles R.

This report describes the results of an assessment of Sailor, Maryland's Online Public Information Network, which provides statewide Internet connection to 100% of Maryland public libraries. The concept of a "statewide networked environment" includes information services, products, hardware and software, telecommunications…

Online monitoring of seismic damage in water distribution systems

NASA Astrophysics Data System (ADS)

Liang, Jianwen; Xiao, Di; Zhao, Xinhua; Zhang, Hongwei

2004-07-01

It is shown that water distribution systems can be damaged by earthquakes, and the seismic damages cannot easily be located, especially immediately after the events. Earthquake experiences show that accurate and quick location of seismic damage is critical to emergency response of water distribution systems. This paper develops a methodology to locate seismic damage -- multiple breaks in a water distribution system by monitoring water pressure online at limited positions in the water distribution system. For the purpose of online monitoring, supervisory control and data acquisition (SCADA) technology can well be used. A neural network-based inverse analysis method is constructed for locating the seismic damage based on the variation of water pressure. The neural network is trained by using analytically simulated data from the water distribution system, and validated by using a set of data that have never been used in the training. It is found that the methodology provides an effective and practical way in which seismic damage in a water distribution system can be accurately and quickly located.

Experimental demonstration of the real-time online fault monitoring technique for chaos-based passive optical networks

NASA Astrophysics Data System (ADS)

Dou, Xinyu; Yin, Hongxi; Yue, Hehe; Jin, Yu; Shen, Jing; Li, Lin

2015-09-01

In this paper, a real-time online fault monitoring technique for chaos-based passive optical networks (PONs) is proposed and experimentally demonstrated. The fault monitoring is performed by the chaotic communication signal. The proof-of-concept experiments are demonstrated for two PON structures, i.e., wavelength-division-multiplexing (WDM) PON and Ethernet PON (EPON), respectively. For WDM PON, two monitoring approaches are investigated, one deploying a chaotic optical time domain reflectometry (OTDR) for each transmitter, and the other using only one tunable chaotic OTDR. The experimental results show that the faults at beyond 20 km from the OLT can be detected and located. The spatial resolution of the tunable chaotic OTDR is an order of magnitude of centimeter. Meanwhile, the monitoring process can operate in parallel with the chaotic optical secure communications. The proposed technique has benefits of real-time, online, precise fault location, and simple realization, which will significantly reduce the cost of operation, administration and maintenance (OAM) of PON.

Building addiction recovery capital through online participation in a recovery community.

PubMed

Bliuc, Ana-Maria; Best, David; Iqbal, Muhammad; Upton, Katie

2017-11-01

This study examines how online participation in a community of recovery contributes to personal journeys of recovery. It investigates whether recovery capital building - as indicated by increased levels and quality of online social interactions - and markers of positive identity development predict retention in a recovery program designed around fostering community involvement for early stage recovery addicts. It was predicted that online participation on the group's Facebook page and positive identity development are associated to retention in the program. To map how participants interact online, social network analysis (SNA) based on naturally occurring online data (N = 609) on the Facebook page of a recovery community was conducted. Computerised linguistic analyses evaluated sentiment of the textual data (capturing social identity markers). Linear regression analyses evaluated whether indicators of recovery capital predict program retention. To illustrate the findings in the context of the specific recovery community, presented are two case studies of key participants who moved from the periphery to the centre of the social network. By conducting in-depth interviews with these participants, personal experiences of engagement in the online community of group members who have undergone the most significant changes since joining the community are explored. Retention in the program was determined by a) the number of comment 'likes' and all 'likes' received on the Facebook page; b) position in the social network (degree of centrality); and c) linguistic content around group identity and achievement. Positive online interactions between members of recovery communities support the recovery process through helping participants to develop recovery capital that binds them to groups supportive of positive change. Copyright © 2017 Elsevier Ltd. All rights reserved.

Differences in Friendship Networks and Experiences of Cyberbullying Among Korean and Australian Adolescents.

PubMed

Lee, Jee Young; Kwon, Yeji; Yang, Soeun; Park, Sora; Kim, Eun-Mee; Na, Eun-Yeong

2017-01-01

Cyberbullying is one of the negative consequences of online social interaction. The digital environment enables adolescents to engage in online social interaction beyond the traditional physical boundaries of families, neighborhoods, and schools. The authors examined connections to friendship networks in both online and offline settings are related to their experiences as victims, perpetrators, and bystanders of cyberbullying. A comparative face-to-face survey of adolescents (12-15-year-olds) was conducted in Korea (n = 520) and Australia (n = 401). The results reveal that online networks are partially related to cyberbullying in both countries, showing the size of social network sites was significantly correlated with experience cyberbullying among adolescents in both countries. However there were cultural differences in the impact of friendship networks on cyberbullying. The size of the online and offline networks has a stronger impact on the cyberbullying experiences in Korea than it does in Australia. In particular, the number of friends in cliques was positively related to both bullying and victimization in Korea.

Caring in the Information Age: Personal Online Networks to Improve Caregiver Support.

PubMed

Piraino, Emily; Byrne, Kerry; Heckman, George A; Stolee, Paul

2017-06-01

It is becoming increasingly important to find ways for caregivers and service providers to collaborate. This study explored the potential for improving care and social support through shared online network use by family caregivers and service providers in home care. This qualitative study was guided by Rogers' Theory of Diffusion of Innovations [NY: Free Press; 1995], and involved focus group and individual interviews of service providers (n = 31) and family caregivers (n = 4). Interview transcriptions were analyzed using descriptive, topic, and analytic coding, followed by thematic analysis. The network was identified as presenting an opportunity to fill communication gaps presented by other modes of communication and further enhance engagement with families. Barriers included time limitations and policy-related restrictions, privacy, security, and information ownership. Online networks may help address longstanding home-care issues around communication and information-sharing. The success of online networks in home care requires support from care partners. Future research should pilot the use of online networks in home care using barrier and facilitator considerations from this study.

Test and Evaluation of the Malicious Activity Simulation Tool (MAST) in a Local Area Network (LAN) Running the Common PC Operating System Environment (COMPOSE)

DTIC Science & Technology

2013-09-01

Malicious Activity Simulation Tool MMORPG Massively Multiplayer Online Role-Playing Game MMS Mission Management Server MOA Memorandum of Agreement MS...conferencing, and massively multiplayer online role- playing games (MMORPG). During all of these Internet-based exchanges and transactions, the Internet user...In its 2011 Internet Crime Report, the Internet Crime Complaint Center (IC3) stated there were more than 300,000 complaints of online criminal

Craving Facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits.

PubMed

Hormes, Julia M; Kearns, Brianna; Timko, C Alix

2014-12-01

To assess disordered online social networking use via modified diagnostic criteria for substance dependence, and to examine its association with difficulties with emotion regulation and substance use. Cross-sectional survey study targeting undergraduate students. Associations between disordered online social networking use, internet addiction, deficits in emotion regulation and alcohol use problems were examined using univariate and multivariate analyses of covariance. A large University in the Northeastern United States. Undergraduate students (n = 253, 62.8% female, 60.9% white, age mean = 19.68, standard deviation = 2.85), largely representative of the target population. The response rate was 100%. Disordered online social networking use, determined via modified measures of alcohol abuse and dependence, including DSM-IV-TR diagnostic criteria for alcohol dependence, the Penn Alcohol Craving Scale and the Cut-down, Annoyed, Guilt, Eye-opener (CAGE) screen, along with the Young Internet Addiction Test, Alcohol Use Disorders Identification Test, Acceptance and Action Questionnaire-II, White Bear Suppression Inventory and Difficulties in Emotion Regulation Scale. Disordered online social networking use was present in 9.7% [n = 23; 95% confidence interval (5.9, 13.4)] of the sample surveyed, and significantly and positively associated with scores on the Young Internet Addiction Test (P < 0.001), greater difficulties with emotion regulation (P = 0.003) and problem drinking (P = 0.03). The use of online social networking sites is potentially addictive. Modified measures of substance abuse and dependence are suitable in assessing disordered online social networking use. Disordered online social networking use seems to arise as part of a cluster of symptoms of poor emotion regulation skills and heightened susceptibility to both substance and non-substance addiction. © 2014 Society for the Study of Addiction.

Networked Instructional Chemistry: Using Technology To Teach Chemistry

NASA Astrophysics Data System (ADS)

Smith, Stanley; Stovall, Iris

1996-10-01

Networked multimedia microcomputers provide new ways to help students learn chemistry and to help instructors manage the learning environment. This technology is used to replace some traditional laboratory work, collect on-line experimental data, enhance lectures and quiz sections with multimedia presentations, provide prelaboratory training for beginning nonchemistry- major organic laboratory, provide electronic homework for organic chemistry students, give graduate students access to real NMR data for analysis, and provide access to molecular modeling tools. The integration of all of these activities into an active learning environment is made possible by a client-server network of hundreds of computers. This requires not only instructional software but also classroom and course management software, computers, networking, and room management. Combining computer-based work with traditional course material is made possible with software management tools that allow the instructor to monitor the progress of each student and make available an on-line gradebook so students can see their grades and class standing. This client-server based system extends the capabilities of the earlier mainframe-based PLATO system, which was used for instructional computing. This paper outlines the components of a technology center used to support over 5,000 students per semester.

Experimental demonstration of software defined data center optical networks with Tbps end-to-end tunability

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Zhang, Jie; Ji, Yuefeng; Li, Hui; Wang, Huitao; Ge, Chao

2015-10-01

The end-to-end tunability is important to provision elastic channel for the burst traffic of data center optical networks. Then, how to complete the end-to-end tunability based on elastic optical networks? Software defined networking (SDN) based end-to-end tunability solution is proposed for software defined data center optical networks, and the protocol extension and implementation procedure are designed accordingly. For the first time, the flexible grid all optical networks with Tbps end-to-end tunable transport and switch system have been online demonstrated for data center interconnection, which are controlled by OpenDayLight (ODL) based controller. The performance of the end-to-end tunable transport and switch system has been evaluated with wavelength number tuning, bit rate tuning, and transmit power tuning procedure.

Online and Social Networking Interventions for the Treatment of Depression in Young People: A Systematic Review

PubMed Central

Goodall, Joanne; Hetrick, Sarah E; Parker, Alexandra G; Gilbertson, Tamsyn; Amminger, G. Paul; Davey, Christopher G; McGorry, Patrick D; Gleeson, John; Alvarez-Jimenez, Mario

2014-01-01

Background Major depression accounts for the greatest burden of all diseases globally. The peak onset of depression occurs between adolescence and young adulthood, and for many individuals, depression displays a relapse-remitting and increasingly severe course. Given this, the development of cost-effective, acceptable, and population-focused interventions for depression is critical. A number of online interventions (both prevention and acute phase) have been tested in young people with promising results. As these interventions differ in content, clinician input, and modality, it is important to identify key features (or unhelpful functions) associated with treatment outcomes. Objective A systematic review of the research literature was undertaken. The review was designed to focus on two aspects of online intervention: (1) standard approaches evaluating online intervention content in randomized controlled designs (Section 1), and (2) second-generation online interventions and services using social networking (eg, social networking sites and online support groups) in any type of research design (Section 2). Methods Two specific literature searches were undertaken. There was no date range specified. The Section 1 search, which focused on randomized controlled trials, included only young people (12-25 years) and yielded 101 study abstracts, of which 15 met the review inclusion criteria. The Section 2 search, which included all study design types and was not restricted in terms of age, yielded 358 abstracts, of which 22 studies met the inclusion criteria. Information about the studies and their findings were extracted and tabulated for review. Results The 15 studies identified in Section 1 described 10 trials testing eight different online interventions, all of which were based on a cognitive behavioral framework. All but one of the eight identified studies reported positive results; however, only five of the 15 studies used blinded interviewer administered outcomes with most trials using self-report data. Studies varied significantly in presentation of intervention content, treatment dose, and dropout. Only two studies included moderator or clinician input. Results for Section 2 were less consistent. None of the Section 2 studies reported controlled or randomized designs. With the exception of four studies, all included participants were younger than 25 years of age. Eight of the 16 social networking studies reported positive results for depression-related outcomes. The remaining studies were either mixed or negative. Findings for online support groups tended to be more positive; however, noteworthy risks were identified. Conclusions Online interventions with a broad cognitive behavioral focus appear to be promising in reducing depression symptomology in young people. Further research is required into the effectiveness of online interventions delivering cognitive behavioral subcomponents, such as problem-solving therapy. Evidence for the use of social networking is less compelling, although limited by a lack of well-designed studies and social networking interventions. A range of future social networking therapeutic opportunities are highlighted. PMID:25226790

Online and social networking interventions for the treatment of depression in young people: a systematic review.

PubMed

Rice, Simon M; Goodall, Joanne; Hetrick, Sarah E; Parker, Alexandra G; Gilbertson, Tamsyn; Amminger, G Paul; Davey, Christopher G; McGorry, Patrick D; Gleeson, John; Alvarez-Jimenez, Mario

2014-09-16

Major depression accounts for the greatest burden of all diseases globally. The peak onset of depression occurs between adolescence and young adulthood, and for many individuals, depression displays a relapse-remitting and increasingly severe course. Given this, the development of cost-effective, acceptable, and population-focused interventions for depression is critical. A number of online interventions (both prevention and acute phase) have been tested in young people with promising results. As these interventions differ in content, clinician input, and modality, it is important to identify key features (or unhelpful functions) associated with treatment outcomes. A systematic review of the research literature was undertaken. The review was designed to focus on two aspects of online intervention: (1) standard approaches evaluating online intervention content in randomized controlled designs (Section 1), and (2) second-generation online interventions and services using social networking (eg, social networking sites and online support groups) in any type of research design (Section 2). Two specific literature searches were undertaken. There was no date range specified. The Section 1 search, which focused on randomized controlled trials, included only young people (12-25 years) and yielded 101 study abstracts, of which 15 met the review inclusion criteria. The Section 2 search, which included all study design types and was not restricted in terms of age, yielded 358 abstracts, of which 22 studies met the inclusion criteria. Information about the studies and their findings were extracted and tabulated for review. The 15 studies identified in Section 1 described 10 trials testing eight different online interventions, all of which were based on a cognitive behavioral framework. All but one of the eight identified studies reported positive results; however, only five of the 15 studies used blinded interviewer administered outcomes with most trials using self-report data. Studies varied significantly in presentation of intervention content, treatment dose, and dropout. Only two studies included moderator or clinician input. Results for Section 2 were less consistent. None of the Section 2 studies reported controlled or randomized designs. With the exception of four studies, all included participants were younger than 25 years of age. Eight of the 16 social networking studies reported positive results for depression-related outcomes. The remaining studies were either mixed or negative. Findings for online support groups tended to be more positive; however, noteworthy risks were identified. Online interventions with a broad cognitive behavioral focus appear to be promising in reducing depression symptomology in young people. Further research is required into the effectiveness of online interventions delivering cognitive behavioral subcomponents, such as problem-solving therapy. Evidence for the use of social networking is less compelling, although limited by a lack of well-designed studies and social networking interventions. A range of future social networking therapeutic opportunities are highlighted.

Words Analysis of Online Chinese News Headlines about Trending Events: A Complex Network Perspective

PubMed Central

Li, Huajiao; Fang, Wei; An, Haizhong; Huang, Xuan

2015-01-01

Because the volume of information available online is growing at breakneck speed, keeping up with meaning and information communicated by the media and netizens is a new challenge both for scholars and for companies who must address public relations crises. Most current theories and tools are directed at identifying one website or one piece of online news and do not attempt to develop a rapid understanding of all websites and all news covering one topic. This paper represents an effort to integrate statistics, word segmentation, complex networks and visualization to analyze headlines’ keywords and words relationships in online Chinese news using two samples: the 2011 Bohai Bay oil spill and the 2010 Gulf of Mexico oil spill. We gathered all the news headlines concerning the two trending events in the search results from Baidu, the most popular Chinese search engine. We used Simple Chinese Word Segmentation to segment all the headlines into words and then took words as nodes and considered adjacent relations as edges to construct word networks both using the whole sample and at the monthly level. Finally, we develop an integrated mechanism to analyze the features of words’ networks based on news headlines that can account for all the keywords in the news about a particular event and therefore track the evolution of news deeply and rapidly. PMID:25807376

A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.

PubMed

Qiao, Ning; Mostafa, Hesham; Corradi, Federico; Osswald, Marc; Stefanini, Fabio; Sumislawska, Dora; Indiveri, Giacomo

2015-01-01

Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks, with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm(2), and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities.

Words analysis of online Chinese news headlines about trending events: a complex network perspective.

PubMed

Li, Huajiao; Fang, Wei; An, Haizhong; Huang, Xuan

2015-01-01

Because the volume of information available online is growing at breakneck speed, keeping up with meaning and information communicated by the media and netizens is a new challenge both for scholars and for companies who must address public relations crises. Most current theories and tools are directed at identifying one website or one piece of online news and do not attempt to develop a rapid understanding of all websites and all news covering one topic. This paper represents an effort to integrate statistics, word segmentation, complex networks and visualization to analyze headlines' keywords and words relationships in online Chinese news using two samples: the 2011 Bohai Bay oil spill and the 2010 Gulf of Mexico oil spill. We gathered all the news headlines concerning the two trending events in the search results from Baidu, the most popular Chinese search engine. We used Simple Chinese Word Segmentation to segment all the headlines into words and then took words as nodes and considered adjacent relations as edges to construct word networks both using the whole sample and at the monthly level. Finally, we develop an integrated mechanism to analyze the features of words' networks based on news headlines that can account for all the keywords in the news about a particular event and therefore track the evolution of news deeply and rapidly.

Online social network data as sociometric markers.

PubMed

Binder, Jens F; Buglass, Sarah L; Betts, Lucy R; Underwood, Jean D M

2017-10-01

Data from online social networks carry enormous potential for psychological research, yet their use and the ethical implications thereof are currently hotly debated. The present work aims to outline in detail the unique information richness of this data type and, in doing so, to support researchers when deciding on ethically appropriate ways of collecting, storing, publishing, and sharing data from online sources. Focusing on the very nature of social networks, their structural characteristics, and depth of information, we provide a detailed and accessible account of the challenges associated with data management and data storage. In particular, the general nonanonymity of network data sets is discussed, and an approach is developed to quantify the level of uniqueness that a particular online network bestows upon the individual maintaining it. Using graph enumeration techniques, we show that comparatively sparse information on a network is suitable as a sociometric marker that allows for the identification of an individual from the global population of online users. The impossibility of anonymizing specific types of network data carries implications for ethical guidelines and research practice. At the same time, network uniqueness opens up opportunities for novel research in psychology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Micro-level dynamics of the online information propagation: A user behavior model based on noisy spiking neurons.

PubMed

Lymperopoulos, Ilias N; Ioannou, George D

2016-10-01

We develop and validate a model of the micro-level dynamics underlying the formation of macro-level information propagation patterns in online social networks. In particular, we address the dynamics at the level of the mechanism regulating a user's participation in an online information propagation process. We demonstrate that this mechanism can be realistically described by the dynamics of noisy spiking neurons driven by endogenous and exogenous, deterministic and stochastic stimuli representing the influence modulating one's intention to be an information spreader. Depending on the dynamically changing influence characteristics, time-varying propagation patterns emerge reflecting the temporal structure, strength, and signal-to-noise ratio characteristics of the stimulation driving the online users' information sharing activity. The proposed model constitutes an overarching, novel, and flexible approach to the modeling of the micro-level mechanisms whereby information propagates in online social networks. As such, it can be used for a comprehensive understanding of the online transmission of information, a process integral to the sociocultural evolution of modern societies. The proposed model is highly adaptable and suitable for the study of the propagation patterns of behavior, opinions, and innovations among others. Copyright © 2016 Elsevier Ltd. All rights reserved.

Emotion regulation in bereavement: searching for and finding emotional support in social network sites

NASA Astrophysics Data System (ADS)

Döveling, Katrin

2015-04-01

In an age of rising impact of online communication in social network sites (SNS), emotional interaction is neither limited nor restricted by time or space. Bereavement extends to the anonymity of cyberspace. What role does virtual interaction play in SNS in dealing with the basic human emotion of grief caused by the loss of a beloved person? The analysis laid out in this article provides answers in light of an interdisciplinary perspective on online bereavement. Relevant lines of research are scrutinized. After laying out the theoretical spectrum for the study, hypotheses based on a prior in-depth qualitative content analysis of 179 postings in three different German online bereavement platforms are proposed and scrutinized in a quantitative content analysis (2127 postings from 318 users). Emotion regulation patterns in SNS and similarities as well as differences in online bereavement of children, adolescents and adults are revealed. Large-scale quantitative findings into central motives, patterns, and restorative effects of online shared bereavement in regulating distress, fostering personal empowerment, and engendering meaning are presented. The article closes with implications for further analysis in memorialization practices.

Essential elements of online information networks on invasive alien species

USGS Publications Warehouse

Simpson, A.; Sellers, E.; Grosse, A.; Xie, Y.

2006-01-01

In order to be effective, information must be placed in the proper context and organized in a manner that is logical and (preferably) standardized. Recently, invasive alien species (IAS) scientists have begun to create online networks to share their information concerning IAS prevention and control. At a special networking session at the Beijing International Symposium on Biological Invasions, an online Eastern Asia-North American IAS Information Network (EA-NA Network) was proposed. To prepare for the development of this network, and to provide models for other regional collaborations, we compare four examples of global, regional, and national online IAS information networks: the Global Invasive Species Information Network, the Invasives Information Network of the Inter-American Biodiversity Information Network, the Chinese Species Information System, and the Invasive Species Information Node of the US National Biological Information Infrastructure. We conclude that IAS networks require a common goal, dedicated leaders, effective communication, and broad endorsement, in order to obtain sustainable, long-term funding and long-term stability. They need to start small, use the experience of other networks, partner with others, and showcase benefits. Global integration and synergy among invasive species networks will succeed with contributions from both the top-down and the bottom-up. ?? 2006 Springer.

Social Features of Online Networks: The Strength of Intermediary Ties in Online Social Media

PubMed Central

Grabowicz, Przemyslaw A.; Ramasco, José J.; Moro, Esteban; Pujol, Josep M.; Eguiluz, Victor M.

2012-01-01

An increasing fraction of today's social interactions occur using online social media as communication channels. Recent worldwide events, such as social movements in Spain or revolts in the Middle East, highlight their capacity to boost people's coordination. Online networks display in general a rich internal structure where users can choose among different types and intensity of interactions. Despite this, there are still open questions regarding the social value of online interactions. For example, the existence of users with millions of online friends sheds doubts on the relevance of these relations. In this work, we focus on Twitter, one of the most popular online social networks, and find that the network formed by the basic type of connections is organized in groups. The activity of the users conforms to the landscape determined by such groups. Furthermore, Twitter's distinction between different types of interactions allows us to establish a parallelism between online and offline social networks: personal interactions are more likely to occur on internal links to the groups (the weakness of strong ties); events transmitting new information go preferentially through links connecting different groups (the strength of weak ties) or even more through links connecting to users belonging to several groups that act as brokers (the strength of intermediary ties). PMID:22247773

Promote Digital Citizenship through School-Based Social Networking

ERIC Educational Resources Information Center

Winn, Matthew R.

2012-01-01

Just as participation in social networking has grown, so has media coverage of inappropriate activity online. Teacher-student relationships and cyberbullying are just a few of the stories that seem to make the news on a regular basis. For educators, this is particularly troubling, considering how few students know what is appropriate when using…

Shaping Networked Theatre: Experience Architectures, Behaviours and Creative Pedagogies

ERIC Educational Resources Information Center

Sutton, Paul

2012-01-01

Since 2006 the UK based applied theatre company C&T has been using its experience and expertise in mixing drama, learning and digital media to create a new online utility for shaping collaborative educational drama experiences. C&T describes this practice as "Networked Theatre". This article describes both the motivations for…

Correlation between Academic and Skills-Based Tests in Computer Networks

ERIC Educational Resources Information Center

Buchanan, William

2006-01-01

Computing-related programmes and modules have many problems, especially related to large class sizes, large-scale plagiarism, module franchising, and an increased requirement from students for increased amounts of hands-on, practical work. This paper presents a practical computer networks module which uses a mixture of online examinations and a…

Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics

PubMed Central

Lee, Sandra Soo-Jin; Vernez, Simone L.; Ormond, K.E.; Granovetter, Mark

2013-01-01

Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Methods: Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. Results: 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Conclusion: Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities. PMID:25562728

Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics.

PubMed

Lee, Sandra Soo-Jin; Vernez, Simone L; Ormond, K E; Granovetter, Mark

2013-10-14

Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities.

Three Eras in Global Tobacco Control: How Global Governance Processes Influenced Online Tobacco Control Networking

PubMed Central

Wipfli, Heather; Chu, Kar-Hai; Lancaster, Molly; Valente, Thomas

2017-01-01

Online networks can serve as a platform to diffuse policy innovations and enhance global health governance. This study focuses on how shifts in global health governance may influence related online networks. We compare social network metrics (average degree centrality [AVGD], density [D] and clustering coefficient [CC]) of Globalink, an online network of tobacco control advocates, across three eras in global tobacco control governance; pre-Framework Convention on Tobacco Control (FCTC) policy transfer (1992–1998), global regime formation through the FCTC negotiations (1999–2005), and philanthropic funding through the Bloomberg Initiative (2006–2012). Prior to 1999, Globalink was driven by a handful of high-income countries (AVGD=1.908 D=0.030, CC=0.215). The FCTC negotiations (1999–2005) corresponded with a rapid uptick in the number of countries represented within Globalink and new members were most often brought into the network through relationships with regional neighbors (AVGD=2.824, D=0.021, CC=0.253). Between 2006 and 2012, the centrality of the US in the network increases significantly (AVGD=3.414, D=0.023, CC=0.310). The findings suggest that global institutionalization through WHO, as with the FCTC, can lead to the rapid growth of decentralized online networks. Alternatively, private initiatives, such as the Bloomberg Initiative, can lead to clustering in which a single source of information gains increasing influence over an online network. PMID:28596813

Online professional networks for physicians: risk management.

PubMed

Hyman, Jon L; Luks, Howard J; Sechrest, Randale

2012-05-01

The rapidly developing array of online physician-only communities represents a potential extraordinary advance in the availability of educational and informational resources to physicians. These online communities provide physicians with a new range of controls over the information they process, but use of this social media technology carries some risk. The purpose of this review was to help physicians manage the risks of online professional networking and discuss the potential benefits that may come with such networks. This article explores the risks and benefits of physicians engaging in online professional networking with peers and provides suggestions on risk management. Through an Internet search and literature review, we scrutinized available case law, federal regulatory code, and guidelines of conduct from professional organizations and consultants. We reviewed the OrthoMind.com site as a case example because it is currently the only online social network exclusively for orthopaedic surgeons. Existing case law suggests potential liability for orthopaedic surgeons who engage with patients on openly accessible social network platforms. Current society guidelines in both the United States and Britain provide sensible rules that may mitigate such risks. However, the overall lack of a strong body of legal opinions, government regulations as well as practical experience for most surgeons limit the suitability of such platforms. Closed platforms that are restricted to validated orthopaedic surgeons may limit these downside risks and hence allow surgeons to collaborate with one another both as clinicians and practice owners. Educating surgeons about the pros and cons of participating in these networking platforms is helping them more astutely manage risks and optimize benefits. This evolving online environment of professional interaction is one of few precedents, but the application of risk management strategies that physicians use in daily practice carries over into the online community. This participation should foster ongoing dialogue as new guidelines emerge. This will allow today's orthopaedic surgeon to feel more comfortable with online professional networks and better understand how to make an informed decision regarding their proper use.

"I like talking to people on the computer": Outcomes of a home-based intervention to develop social media skills in youth with disabilities living in rural communities.

PubMed

Raghavendra, Parimala; Hutchinson, Claire; Grace, Emma; Wood, Denise; Newman, Lareen

2018-05-01

To investigate the effectiveness of a home-based social media use intervention to enhance the social networks of rural youth with disabilities. Participants were nine youth (mean age = 17.0 years) with disabilities from two rural Australian communities. The intervention consisted of providing appropriate assistive technology and social media training on individualised goals. Using mixed methods, quantitative (a single group pre-post) and qualitative (interviews with participants and their carers) measures were used to examine outcomes of training, individual experiences of the intervention, and changes to online social networks. Participants increased their performance and satisfaction with performance on social media problem areas post-intervention; paired t-tests showed statistical significance at p < .001. There was also a significant increase in the number of online communication partners; Wilcoxon Signed Ranks showed statistical significance at p < .05. The interviews highlighted increased social participation, independence and improvements to literacy. Ongoing parental concerns regarding cyber safety and inappropriate online content were noted. The findings suggest that social media training is a feasible method for increasing social networks among rural-based youth with disabilities. To sustain ongoing benefits, parents need knowledge and training in integrating assistive technology and social media. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fast Flux Watch: A mechanism for online detection of fast flux networks.

PubMed

Al-Duwairi, Basheer N; Al-Hammouri, Ahmad T

2014-07-01

Fast flux networks represent a special type of botnets that are used to provide highly available web services to a backend server, which usually hosts malicious content. Detection of fast flux networks continues to be a challenging issue because of the similar behavior between these networks and other legitimate infrastructures, such as CDNs and server farms. This paper proposes Fast Flux Watch (FF-Watch), a mechanism for online detection of fast flux agents. FF-Watch is envisioned to exist as a software agent at leaf routers that connect stub networks to the Internet. The core mechanism of FF-Watch is based on the inherent feature of fast flux networks: flux agents within stub networks take the role of relaying client requests to point-of-sale websites of spam campaigns. The main idea of FF-Watch is to correlate incoming TCP connection requests to flux agents within a stub network with outgoing TCP connection requests from the same agents to the point-of-sale website. Theoretical and traffic trace driven analysis shows that the proposed mechanism can be utilized to efficiently detect fast flux agents within a stub network.

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Reinforcement learning controller design for affine nonlinear discrete-time systems using online approximators.

PubMed

Yang, Qinmin; Jagannathan, Sarangapani

2012-04-01

In this paper, reinforcement learning state- and output-feedback-based adaptive critic controller designs are proposed by using the online approximators (OLAs) for a general multi-input and multioutput affine unknown nonlinear discretetime systems in the presence of bounded disturbances. The proposed controller design has two entities, an action network that is designed to produce optimal signal and a critic network that evaluates the performance of the action network. The critic estimates the cost-to-go function which is tuned online using recursive equations derived from heuristic dynamic programming. Here, neural networks (NNs) are used both for the action and critic whereas any OLAs, such as radial basis functions, splines, fuzzy logic, etc., can be utilized. For the output-feedback counterpart, an additional NN is designated as the observer to estimate the unavailable system states, and thus, separation principle is not required. The NN weight tuning laws for the controller schemes are also derived while ensuring uniform ultimate boundedness of the closed-loop system using Lyapunov theory. Finally, the effectiveness of the two controllers is tested in simulation on a pendulum balancing system and a two-link robotic arm system.

A General Bayesian Network Approach to Analyzing Online Game Item Values and Its Influence on Consumer Satisfaction and Purchase Intention

NASA Astrophysics Data System (ADS)

Lee, Kun Chang; Park, Bong-Won

Many online game users purchase game items with which to play free-to-play games. Because of a lack of research into which there is no specified framework for categorizing the values of game items, this study proposes four types of online game item values based on an analysis of literature regarding online game characteristics. It then proposes to investigate how online game users perceive satisfaction and purchase intention from the proposed four types of online game item values. Though regression analysis has been used frequently to answer this kind of research question, we propose a new approach, a General Bayesian Network (GBN), which can be performed in an understandable way without sacrificing predictive accuracy. Conventional techniques, such as regression analysis, do not provide significant explanation for this kind of problem because they are fixed to a linear structure and are limited in explaining why customers are likely to purchase game items and if they are satisfied with their purchases. In contrast, the proposed GBN provides a flexible underlying structure based on questionnaire survey data and offers robust decision support on this kind of research question by identifying its causal relationships. To illustrate the validity of GBN in solving the research question in this study, 327 valid questionnaires were analyzed using GBN with what-if and goal-seeking approaches. The experimental results were promising and meaningful in comparison with regression analysis results.

Development of on-line monitoring system for Nuclear Power Plant (NPP) using neuro-expert, noise analysis, and modified neural networks

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

Subekti, M.; Center for Development of Reactor Safety Technology, National Nuclear Energy Agency of Indonesia, Puspiptek Complex BO.80, Serpong-Tangerang, 15340; Ohno, T.

2006-07-01

The neuro-expert has been utilized in previous monitoring-system research of Pressure Water Reactor (PWR). The research improved the monitoring system by utilizing neuro-expert, conventional noise analysis and modified neural networks for capability extension. The parallel method applications required distributed architecture of computer-network for performing real-time tasks. The research aimed to improve the previous monitoring system, which could detect sensor degradation, and to perform the monitoring demonstration in High Temperature Engineering Tested Reactor (HTTR). The developing monitoring system based on some methods that have been tested using the data from online PWR simulator, as well as RSG-GAS (30 MW research reactormore » in Indonesia), will be applied in HTTR for more complex monitoring. (authors)« less

Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

PubMed

Ammenwerth, Elske; Hackl, Werner O

2017-01-01

Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

An Incentive-based Online Optimization Framework for Distribution Grids

DOE PAGES

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun; ...

2017-10-09

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

An Incentive-based Online Optimization Framework for Distribution Grids

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

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

An experimental study of the Online Information Paradox: Does en-route information improve road network performance?

PubMed

Wijayaratna, Kasun P; Dixit, Vinayak V; Denant-Boemont, Laurent; Waller, S Travis

2017-01-01

This study investigates the empirical presence of a theoretical transportation paradox, defined as the "Online Information Paradox" (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network.

A neural net approach to space vehicle guidance

NASA Technical Reports Server (NTRS)

Caglayan, Alper K.; Allen, Scott M.

1990-01-01

The space vehicle guidance problem is formulated using a neural network approach, and the appropriate neural net architecture for modeling optimum guidance trajectories is investigated. In particular, an investigation is made of the incorporation of prior knowledge about the characteristics of the optimal guidance solution into the neural network architecture. The online classification performance of the developed network is demonstrated using a synthesized network trained with a database of optimum guidance trajectories. Such a neural-network-based guidance approach can readily adapt to environment uncertainties such as those encountered by an AOTV during atmospheric maneuvers.

"Newbies" and "Celebrities": Detecting Social Roles in an Online Network of Teachers via Participation Patterns

ERIC Educational Resources Information Center

Smith Risser, H.; Bottoms, SueAnn

2014-01-01

The advent of social networking tools allows teachers to create online networks and share information. While some virtual networks have a formal structure and defined boundaries, many do not. These unstructured virtual networks are difficult to study because they lack defined boundaries and a formal structure governing leadership roles and the…

On-line Tool Wear Detection on DCMT070204 Carbide Tool Tip Based on Noise Cutting Audio Signal using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Prasetyo, T.; Amar, S.; Arendra, A.; Zam Zami, M. K.

2018-01-01

This study develops an on-line detection system to predict the wear of DCMT070204 tool tip during the cutting process of the workpiece. The machine used in this research is CNC ProTurn 9000 to cut ST42 steel cylinder. The audio signal has been captured using the microphone placed in the tool post and recorded in Matlab. The signal is recorded at the sampling rate of 44.1 kHz, and the sampling size of 1024. The recorded signal is 110 data derived from the audio signal while cutting using a normal chisel and a worn chisel. And then perform signal feature extraction in the frequency domain using Fast Fourier Transform. Feature selection is done based on correlation analysis. And tool wear classification was performed using artificial neural networks with 33 input features selected. This artificial neural network is trained with back propagation method. Classification performance testing yields an accuracy of 74%.

Digital divide 2.0: the role of social networking sites in seeking health information online from a longitudinal perspective.

PubMed

Feng, Yang; Xie, Wenjing

2015-01-01

Adopting a longitudinal angle, this study analyzed data from the Pew Internet's Health Tracking Survey in 2006, 2008, and 2010 to identify potential communication inequalities in social networking site use. Results showed that with the growing role of social networking site use in predicting people's likelihood of seeking health information online, the socioeconomic and demographic factors that contributed to the disparities in social networking site use could also lead to disparities in seeking health information online. Also, results indicated that people are more likely to seek heath-related information online if they or their close family or friends have a chronic disease situation.

Network public opinion space sentiment tendency analyze based on recurrent convolution neural network

NASA Astrophysics Data System (ADS)

Zhang, Gaowei; Xu, Lingyu; Wang, Lei

2018-04-01

The purpose of this chapter is to analyze the investor's psychological characteristics and investment decision-making behavior characteristics, to study the investor sentiment under the network public opinion, and then analyze from three aspects: First, investor sentiment analysis and how to spread in the online media; The influence mechanism of investor's emotion on the stock market and its effect; the third one is to measure the investor's emotion based on the degree of attention, trying hard to sort out the internal relations between the investor's sentiment and the network public opinion and the stock market, in order to lay the theoretical foundation of this article.

Learning Communities via the Internet a la Epic Learning: You Can Lead the Horses to Water, but You Cannot Get Them To Drink.

ERIC Educational Resources Information Center

Orey, Michael; Koenecke, Lynne; Crozier, Jane

2003-01-01

Describes learning experiences of three students enrolled in a training company's Web-based course on network administration that included a variety of online technologies, including a live virtual classroom, coaches, chat, and bulletin boards, to try and develop an online learning community. Concludes that learners must be taught how to form…

Flexible Learning in a Workplace Model: Blended a Motivation to a Lifelong Learner in a Social Network Environment

ERIC Educational Resources Information Center

Na-songkhla, Jaitip

2011-01-01

This paper presents a model of learning in a workplace, in which an online course provides flexibility for staff to learn at their convenient hours. A motivation was brought into an account of the success of learning in a workplace program, based upon Behaviorist learning approach--an online mentor and an accumulated learning activities score was…

Invited Commentary: Evolution of Social Networks, Health, and the Role of Epidemiology.

PubMed

Aiello, Allison E

2017-06-01

Almost 40 years ago, Berkman and Syme demonstrated that social networks were related to the risk of early mortality (Am J Epidemiol. 1979;109(2):186-204). Their study was highly innovative because they directly measured and quantified social networks in a large prospective population-based survey with mortality follow-up. The results of the study showed robust network gradients, whereby those with fewer networks and weaker social ties had significantly higher mortality rates. The important influence of social networks that Berkman and Syme noted many years ago is likely to heighten in the future, as demographic characteristics shift and individuals become more inclined to socialize through online platforms instead of real-world interactions. Berkman and Syme's research in 1979 continues to play a key role in shaping recent efforts to uncover the influence of social networks on health. Looking back on their findings may help epidemiologists better understand the importance of both online and offline networks for population health today. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Fuzzy Modelling for Human Dynamics Based on Online Social Networks

PubMed Central

Cuenca-Jara, Jesus; Valdes-Vela, Mercedes; Skarmeta, Antonio F.

2017-01-01

Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities. PMID:28837120

Fuzzy Modelling for Human Dynamics Based on Online Social Networks.

PubMed

Cuenca-Jara, Jesus; Terroso-Saenz, Fernando; Valdes-Vela, Mercedes; Skarmeta, Antonio F

2017-08-24

Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities.

On-line Monitoring Device for High-voltage Switch Cabinet Partial Discharge Based on Pulse Current Method

NASA Astrophysics Data System (ADS)

Y Tao, S.; Zhang, X. Z.; Cai, H. W.; Li, P.; Feng, Y.; Zhang, T. C.; Li, J.; Wang, W. S.; Zhang, X. K.

2017-12-01

The pulse current method for partial discharge detection is generally applied in type testing and other off-line tests of electrical equipment at delivery. After intensive analysis of the present situation and existing problems of partial discharge detection in switch cabinets, this paper designed the circuit principle and signal extraction method for partial discharge on-line detection based on a high-voltage presence indicating systems (VPIS), established a high voltage switch cabinet partial discharge on-line detection circuit based on the pulse current method, developed background software integrated with real-time monitoring, judging and analyzing functions, carried out a real discharge simulation test on a real-type partial discharge defect simulation platform of a 10KV switch cabinet, and verified the sensitivity and validity of the high-voltage switch cabinet partial discharge on-line monitoring device based on the pulse current method. The study presented in this paper is of great significance for switch cabinet maintenance and theoretical study on pulse current method on-line detection, and has provided a good implementation method for partial discharge on-line monitoring devices for 10KV distribution network equipment.

On-line diagnosis of sequential systems, 2

NASA Technical Reports Server (NTRS)

Sundstrom, R. J.

1974-01-01

The theory and techniques applicable to the on-line diagnosis of sequential systems, were investigated. A complete model for the study of on-line diagnosis is developed. First an appropriate class of system models is formulated which can serve as a basis for a theoretical study of on-line diagnosis. Then notions of realization, fault, fault-tolerance and diagnosability are formalized which have meaningful interpretations in the the context of on-line diagnosis. The diagnosis of systems which are structurally decomposed and are represented as a network of smaller systems is studied. The fault set considered is the set of faults which only affect one component system is the network. A characterization of those networks which can be diagnosed using a purely combinational detector is achieved. A technique is given which can be used to realize any network by a network which is diagnosable in the above sense. Limits are found on the amount of redundancy involved in any such technique.

Social Networking: Developing Intercultural Competence and Fostering Autonomous Learning

ERIC Educational Resources Information Center

Vurdien, Ruby

2014-01-01

With the emergence of Web 2.0, the incorporation of internet-based social networking tools is becoming increasingly popular in the foreign language classes of today. This form of social interaction provides students with the opportunity to express and share their views with their peers, and to create profiles as well as online communities of…

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

TimeXNet Web: Identifying cellular response networks from diverse omics time-course data.

PubMed

Tan, Phit Ling; López, Yosvany; Nakai, Kenta; Patil, Ashwini

2018-05-14

Condition-specific time-course omics profiles are frequently used to study cellular response to stimuli and identify associated signaling pathways. However, few online tools allow users to analyze multiple types of high-throughput time-course data. TimeXNet Web is a web server that extracts a time-dependent gene/protein response network from time-course transcriptomic, proteomic or phospho-proteomic data, and an input interaction network. It classifies the given genes/proteins into time-dependent groups based on the time of their highest activity and identifies the most probable paths connecting genes/proteins in consecutive groups. The response sub-network is enriched in activated genes/proteins and contains novel regulators that do not show any observable change in the input data. Users can view the resultant response network and analyze it for functional enrichment. TimeXNet Web supports the analysis of high-throughput data from multiple species by providing high quality, weighted protein-protein interaction networks for 12 model organisms. http://txnet.hgc.jp/. ashwini@hgc.jp. Supplementary data are available at Bioinformatics online.

Using a Social Network Strategy to Distribute HIV Self-Test Kits to African American and Latino MSM.

PubMed

Lightfoot, Marguerita A; Campbell, Chadwick K; Moss, Nicholas; Treves-Kagan, Sarah; Agnew, Emily; Kang Dufour, Mi-Suk; Scott, Hyman; Sa'id, Aria M; Lippman, Sheri A

2018-05-04

Men who have sex with men (MSM) continue to be disproportionately impacted globally by the HIV epidemic. Studies suggest that HIV Self-testing (HIVST) is highly acceptable among MSM. Social network strategies to increase testing are effective in reaching MSM, particularly MSM of color, who may not otherwise test. We tested a social-network based strategy to distribute HIVST kits to African American and Latino MSM. This study was conducted in Alameda County, California a large, urban/suburban county with an HIV epidemic mirroring the national HIV epidemic. From January 2016 to March 2017, 30 AAMSM, LMSM, and Transgender women were trained as peer recruiters and asked to distribute five self-test kits to MSM social network members and support those who test positive in linking to care. Testers completed an online survey following their test. We compared peer-distributed HIVST testing outcomes to outcomes from Alameda County's targeted, community-based HIV testing programs using chi-squared tests. Peers distributed HIVST to 143 social and sexual network members, of whom 110 completed the online survey. Compared to MSM who utilized the County's sponsored testing programs, individuals reached through the peer-based self-testing strategy were significantly more likely to have never tested for HIV (3.51% vs. 0.41%, p<0.01) and to report a positive test result (6.14% vs 1.49%, p<0.01). Findings suggest that a network-based strategy for self-test distribution is a promising intervention to increase testing uptake and reduce undiagnosed infections among African American and Latino MSM.

Reduced kernel recursive least squares algorithm for aero-engine degradation prediction

NASA Astrophysics Data System (ADS)

Zhou, Haowen; Huang, Jinquan; Lu, Feng

2017-10-01

Kernel adaptive filters (KAFs) generate a linear growing radial basis function (RBF) network with the number of training samples, thereby lacking sparseness. To deal with this drawback, traditional sparsification techniques select a subset of original training data based on a certain criterion to train the network and discard the redundant data directly. Although these methods curb the growth of the network effectively, it should be noted that information conveyed by these redundant samples is omitted, which may lead to accuracy degradation. In this paper, we present a novel online sparsification method which requires much less training time without sacrificing the accuracy performance. Specifically, a reduced kernel recursive least squares (RKRLS) algorithm is developed based on the reduced technique and the linear independency. Unlike conventional methods, our novel methodology employs these redundant data to update the coefficients of the existing network. Due to the effective utilization of the redundant data, the novel algorithm achieves a better accuracy performance, although the network size is significantly reduced. Experiments on time series prediction and online regression demonstrate that RKRLS algorithm requires much less computational consumption and maintains the satisfactory accuracy performance. Finally, we propose an enhanced multi-sensor prognostic model based on RKRLS and Hidden Markov Model (HMM) for remaining useful life (RUL) estimation. A case study in a turbofan degradation dataset is performed to evaluate the performance of the novel prognostic approach.

Characterizing interactions in online social networks during exceptional events

NASA Astrophysics Data System (ADS)

Omodei, Elisa; De Domenico, Manlio; Arenas, Alex

2015-08-01

Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.

A Qualitative Study to Examine Feasibility and Design of an Online Social Networking Intervention to Increase Physical Activity in Teenage Girls.

PubMed

Van Kessel, Gisela; Kavanagh, Madeleine; Maher, Carol

2016-01-01

Online social networks present wide-reaching and flexible platforms through which to deliver health interventions to targeted populations. This study used a social marketing approach to explore teenage girls' perceptions of physical activity and the potential use of online social networks to receive a physical activity intervention. Six focus groups were conducted with 19 Australian teenage girls (ages 13 to 18 years) with varying levels of physical activity and socioeconomic status. A semi-structured format was used, with groups discussion transcribed verbatim. Content analysis identified emergent themes, with triangulation and memos used to ensure accuracy. Physical activity was most appealing when it emphasised sport, exercise and fitness, along with opportunities for socialisation with friends and self-improvement. Participants were receptive to delivery of a physical activity intervention via online social networks, with Facebook the most widely reported site. Participants commonly accessed online social networks via mobile devices and particularly smartphones. Undesirable features included promotion of physical activity in terms of walking; use of cartoon imagery; use of humour; and promotion of the intervention via schools, each of which were considered "uncool". Participants noted that their parents were likely to be supportive of them using an online social networking physical activity intervention, particularly if not promoted as a weight loss intervention. This study identified key features likely to increase the feasibility and retention of an online social networking physical activity intervention for teenage girls. Guidelines for the design of interventions for teenage girls are provided for future applications.

A Qualitative Study to Examine Feasibility and Design of an Online Social Networking Intervention to Increase Physical Activity in Teenage Girls

PubMed Central

Van Kessel, Gisela; Kavanagh, Madeleine; Maher, Carol

2016-01-01

Background Online social networks present wide-reaching and flexible platforms through which to deliver health interventions to targeted populations. This study used a social marketing approach to explore teenage girls’ perceptions of physical activity and the potential use of online social networks to receive a physical activity intervention. Methods Six focus groups were conducted with 19 Australian teenage girls (ages 13 to 18 years) with varying levels of physical activity and socioeconomic status. A semi-structured format was used, with groups discussion transcribed verbatim. Content analysis identified emergent themes, with triangulation and memos used to ensure accuracy. Results Physical activity was most appealing when it emphasised sport, exercise and fitness, along with opportunities for socialisation with friends and self-improvement. Participants were receptive to delivery of a physical activity intervention via online social networks, with Facebook the most widely reported site. Participants commonly accessed online social networks via mobile devices and particularly smartphones. Undesirable features included promotion of physical activity in terms of walking; use of cartoon imagery; use of humour; and promotion of the intervention via schools, each of which were considered “uncool”. Participants noted that their parents were likely to be supportive of them using an online social networking physical activity intervention, particularly if not promoted as a weight loss intervention. Conclusion This study identified key features likely to increase the feasibility and retention of an online social networking physical activity intervention for teenage girls. Guidelines for the design of interventions for teenage girls are provided for future applications. PMID:26934191

Trust and Online Reputation Systems

NASA Astrophysics Data System (ADS)

Kwan, Ming; Ramachandran, Deepak

Web 2.0 technologies provide organizations with unprecedented opportunities to expand and solidify relationships with their customers, partners, and employees—while empowering firms to define entirely new business models focused on sharing information in online collaborative environments. Yet, in and of themselves, these technologies cannot ensure productive online interactions. Leading enterprises that are experimenting with social networks and online communities are already discovering this fact and along with it, the importance of establishing trust as the foundation for online collaboration and transactions. Just as today's consumers must feel secure to bank, exchange personal information and purchase products and services online; participants in Web 2.0 initiatives will only accept the higher levels of risk and exposure inherent in e-commerce and Web collaboration in an environment of trust. Indeed, only by attending to the need to cultivate online trust with customers, partners and employees will enterprises ever fully exploit the expanded business potential posed by Web 2.0. But developing online trust is no easy feat. While various preliminary attempts have occurred, no definitive model for establishing or measuring it has yet been established. To that end, nGenera has identified three, distinct dimensions of online trust: reputation (quantitative-based); relationship (qualitative-based) and process (system-based). When considered together, they form a valuable model for understanding online trust and a toolbox for cultivating it to support Web 2.0 initiatives.

Boundedness and convergence of online gradient method with penalty for feedforward neural networks.

PubMed

Zhang, Huisheng; Wu, Wei; Liu, Fei; Yao, Mingchen

2009-06-01

In this brief, we consider an online gradient method with penalty for training feedforward neural networks. Specifically, the penalty is a term proportional to the norm of the weights. Its roles in the method are to control the magnitude of the weights and to improve the generalization performance of the network. By proving that the weights are automatically bounded in the network training with penalty, we simplify the conditions that are required for convergence of online gradient method in literature. A numerical example is given to support the theoretical analysis.

[Violence in social networks: an exploration of the online expressions of teens from marginalized areas of Greater Buenos Aires].

PubMed

Linne, Joaquín Walter; Angilletta, María Florencia

2016-01-01

This paper explores the online expressions of violence perpetrated or experienced by adolescents from marginalized areas of Greater Buenos Aires, Argentina. Using a qualitative methodology, four specific events were examined: threats, "bondis" [fights], cyberbullying and displays of mourning. To do so, 20 in-depth interviews and 3,000 virtual observations of profiles in the social network Facebook were carried out. Among the main results, it was seen that most expressions of violence are part of an offline-online dynamic. Empirical evidence is also offered based upon which it can be affirmed that the expressions of violence of these teenagers are developed around the culture of "aguante" [fierce loyalty]. The article ponders the extent to which, in the iconic platform of the option "like," these expressions are implicitly functional to the social network or, to the contrary, or whether they allow displacements and significant reappropriations on the part of users. New questions arise about the use of these tools by adolescents from marginalized areas and the need for more complex approaches to examine these phenomena.

Privacy in Social Networks: A Survey

NASA Astrophysics Data System (ADS)

Zheleva, Elena; Getoor, Lise

In this chapter, we survey the literature on privacy in social networks. We focus both on online social networks and online affiliation networks. We formally define the possible privacy breaches and describe the privacy attacks that have been studied. We present definitions of privacy in the context of anonymization together with existing anonymization techniques.

Networked Participatory Scholarship: Emergent Techno-Cultural Pressures toward Open and Digital Scholarship in Online Networks

ERIC Educational Resources Information Center

Veletsianos, George; Kimmons, Royce

2012-01-01

We examine the relationship between scholarly practice and participatory technologies and explore how such technologies invite and reflect the emergence of a new form of scholarship that we call "Networked Participatory Scholarship": scholars' participation in online social networks to share, reflect upon, critique, improve, validate, and…

HPNAIDM: The High-Performance Network Anomaly/Intrusion Detection and Mitigation System

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

Chen, Yan

Identifying traffic anomalies and attacks rapidly and accurately is critical for large network operators. With the rapid growth of network bandwidth, such as the next generation DOE UltraScience Network, and fast emergence of new attacks/virus/worms, existing network intrusion detection systems (IDS) are insufficient because they: • Are mostly host-based and not scalable to high-performance networks; • Are mostly signature-based and unable to adaptively recognize flow-level unknown attacks; • Cannot differentiate malicious events from the unintentional anomalies. To address these challenges, we proposed and developed a new paradigm called high-performance network anomaly/intrustion detection and mitigation (HPNAIDM) system. The new paradigm ismore » significantly different from existing IDSes with the following features (research thrusts). • Online traffic recording and analysis on high-speed networks; • Online adaptive flow-level anomaly/intrusion detection and mitigation; • Integrated approach for false positive reduction. Our research prototype and evaluation demonstrate that the HPNAIDM system is highly effective and economically feasible. Beyond satisfying the pre-set goals, we even exceed that significantly (see more details in the next section). Overall, our project harvested 23 publications (2 book chapters, 6 journal papers and 15 peer-reviewed conference/workshop papers). Besides, we built a website for technique dissemination, which hosts two system prototype release to the research community. We also filed a patent application and developed strong international and domestic collaborations which span both academia and industry.« less

A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses

PubMed Central

Qiao, Ning; Mostafa, Hesham; Corradi, Federico; Osswald, Marc; Stefanini, Fabio; Sumislawska, Dora; Indiveri, Giacomo

2015-01-01

Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks, with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm2, and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities. PMID:25972778

Online social networking amongst teens: friend or foe?

PubMed

O'Dea, Bridianne; Campbell, Andrew

2011-01-01

The impact of Internet communication on adolescent social development is of considerable importance to health professionals, parents and teachers. Online social networking and instant messaging programs are popular utilities amongst a generation of techno-savvy youth. Although these utilities provide varied methods of communication, their social benefits are still in question. This study examined the relationship between online social interaction, perceived social support, self-esteem and psychological distress amongst teens. A total of 400 participants (M(age) = 14.31 years) completed an online survey consisting of parametric and non-parametric measures. No significant relationship was found between online interaction and social support. Time spent interacting online was negatively correlated with self-esteem and psychological distress. While previous research has focused on young adults, this study examines the impact of online social networking on emerging teens. It highlights the need for continued caution in the acceptance of these utilities.

Social networking in online support groups for health: how online social networking benefits patients.

PubMed

Chung, Jae Eun

2014-01-01

An increasing number of online support groups (OSGs) have embraced the features of social networking. So far, little is known about how patients use and benefit from these features. By implementing the uses-and-gratifications framework, the author conducted an online survey with current users of OSGs to examine associations among motivation, use of specific features of OSG, and support outcomes. Findings suggest that OSG users make selective use of varied features depending on their needs, and that perceptions of receiving emotional and informational support are associated more with the use of some features than others. For example, those with strong motivation for social interaction use diverse features of OSG and make one-to-one connections with other users by friending. In contrast, those with strong motivation for information seeking limit their use primarily to discussion boards. Results also show that online social networking features, such as friending and sharing of personal stories on blogs, are helpful in satisfying the need for emotional support. The present study sheds light on online social networking features in the context of health-related OSGs and provides practical lessons on how to improve the capacity of OSGs to serve the needs of their users.

Design and Implementation of Online Communities

DTIC Science & Technology

2001-09-01

online community. In reality, the first online community predates even the ARPANET by over 100 years. The first “netizens” communicated on the 19th ...Century’s version of the Internet, which Tom Standage calls “The Victorian Internet” (Standage, 1998). The Victorian Internet was actually the...network of networks extending throughout much of the world. The similarities don’t stop there. The Victorian Internet spawned an extensive online

Teens, Kindness and Cruelty on Social Network Sites: How American Teens Navigate the New World of "Digital Citizenship"

ERIC Educational Resources Information Center

Lenhart, Amanda; Madden, Mary; Smith, Aaron; Purcell, Kristen; Zickuhr, Kathryn; Rainie, Lee

2011-01-01

Social media use has become so pervasive in the lives of American teens that having a presence on a social network site is almost synonymous with being online. Fully 95% of all teens ages 12-17 are now online and 80% of those online teens are users of social media sites. The authors focused their attention in this research on social network sites…

Interaction Patterns of Nurturant Support Exchanged in Online Health Social Networking

PubMed Central

Yang, Christopher C

2012-01-01

Background Expressing emotion in online support communities is an important aspect of enabling e-patients to connect with each other and expand their social resources. Indirectly it increases the amount of support for coping with health issues. Exploring the supportive interaction patterns in online health social networking would help us better understand how technology features impacts user behavior in this context. Objective To build on previous research that identified different types of social support in online support communities by delving into patterns of supportive behavior across multiple computer-mediated communication formats. Each format combines different architectural elements, affecting the resulting social spaces. Our research question compared communication across different formats of text-based computer-mediated communication provided on the MedHelp.org health social networking environment. Methods We identified messages with nurturant support (emotional, esteem, and network) across three different computer-mediated communication formats (forums, journals, and notes) of an online support community for alcoholism using content analysis. Our sample consisted of 493 forum messages, 423 journal messages, and 1180 notes. Results Nurturant support types occurred frequently among messages offering support (forum comments: 276/412 messages, 67.0%; journal posts: 65/88 messages, 74%; journal comments: 275/335 messages, 82.1%; and notes: 1002/1180 messages, 84.92%), but less often among messages requesting support. Of all the nurturing supports, emotional (ie, encouragement) appeared most frequently, with network and esteem support appearing in patterns of varying combinations. Members of the Alcoholism Community appeared to adapt some traditional face-to-face forms of support to their needs in becoming sober, such as provision of encouragement, understanding, and empathy to one another. Conclusions The computer-mediated communication format may have the greatest influence on the supportive interactions because of characteristics such as audience reach and access. Other factors include perception of community versus personal space or purpose of communication. These results lead to a need for further research. PMID:22555303

Interaction patterns of nurturant support exchanged in online health social networking.

PubMed

Chuang, Katherine Y; Yang, Christopher C

2012-05-03

Expressing emotion in online support communities is an important aspect of enabling e-patients to connect with each other and expand their social resources. Indirectly it increases the amount of support for coping with health issues. Exploring the supportive interaction patterns in online health social networking would help us better understand how technology features impacts user behavior in this context. To build on previous research that identified different types of social support in online support communities by delving into patterns of supportive behavior across multiple computer-mediated communication formats. Each format combines different architectural elements, affecting the resulting social spaces. Our research question compared communication across different formats of text-based computer-mediated communication provided on the MedHelp.org health social networking environment. We identified messages with nurturant support (emotional, esteem, and network) across three different computer-mediated communication formats (forums, journals, and notes) of an online support community for alcoholism using content analysis. Our sample consisted of 493 forum messages, 423 journal messages, and 1180 notes. Nurturant support types occurred frequently among messages offering support (forum comments: 276/412 messages, 67.0%; journal posts: 65/88 messages, 74%; journal comments: 275/335 messages, 82.1%; and notes: 1002/1180 messages, 84.92%), but less often among messages requesting support. Of all the nurturing supports, emotional (ie, encouragement) appeared most frequently, with network and esteem support appearing in patterns of varying combinations. Members of the Alcoholism Community appeared to adapt some traditional face-to-face forms of support to their needs in becoming sober, such as provision of encouragement, understanding, and empathy to one another. The computer-mediated communication format may have the greatest influence on the supportive interactions because of characteristics such as audience reach and access. Other factors include perception of community versus personal space or purpose of communication. These results lead to a need for further research.

Self-presentation 2.0: narcissism and self-esteem on Facebook.

PubMed

Mehdizadeh, Soraya

2010-08-01

Online social networking sites have revealed an entirely new method of self-presentation. This cyber social tool provides a new site of analysis to examine personality and identity. The current study examines how narcissism and self-esteem are manifested on the social networking Web site Facebook.com . Self-esteem and narcissistic personality self-reports were collected from 100 Facebook users at York University. Participant Web pages were also coded based on self-promotional content features. Correlation analyses revealed that individuals higher in narcissism and lower in self-esteem were related to greater online activity as well as some self-promotional content. Gender differences were found to influence the type of self-promotional content presented by individual Facebook users. Implications and future research directions of narcissism and self-esteem on social networking Web sites are discussed.

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.

Are Adolescents Engaged in the Problematic Use of Social Networking Sites More Involved in Peer Aggression and Victimization?

PubMed

Martínez-Ferrer, Belén; Moreno, David; Musitu, Gonzalo

2018-01-01

The problematic use of social networking sites is becoming a major public health concern. Previous research has found that adolescents who engage in a problematic use of social networking sites are likely to show maladjustment problems. However, little is known about its links with peer aggression and victimization. The main goal of this study was to analyze the relationship between problematic use of online social networking sites, peer aggression -overt vs. relational and reactive vs. instrumental-, and peer victimization -overt physical and verbal, and relational-, taking into account gender and age (in early and mid-adolescence). Participants were selected using randomized cluster sampling considering school and class as clusters. A battery of instruments was applied to 1,952 adolescents' secondary students from Spain (Andalusia) (50.4% boys), aged 11 to 16 ( M = 14.07, SD = 1.39). Results showed that girls and 14-16 adolescents were more involved in a problematic use of online social networking sites. Furthermore, adolescents with high problematic use of online social networking sites were more involved in overt-reactive and instrumental-and relational-reactive and instrumental-aggressive behaviors, and self-reported higher levels of overt-physical and verbal-and relational victimization. Even though boys indicated higher levels of all types of victimization, girls with high problematic use of online social networking sites scored the highest on relational victimization. Relating to age, early adolescents (aged 11-14) with higher problematic use of online social networking sites reported the highest levels of overt verbal and relational victimization. Overall, results suggested the co-occurrence of problematic use of online social networking sites, peer aggression and victimization. In addition, results showed the influence that gender and age had on peer victimization. This study highlights the continuity between offline and online domains with regard to maladjustment problems in adolescence.

Are Adolescents Engaged in the Problematic Use of Social Networking Sites More Involved in Peer Aggression and Victimization?

PubMed Central

Martínez-Ferrer, Belén; Moreno, David; Musitu, Gonzalo

2018-01-01

The problematic use of social networking sites is becoming a major public health concern. Previous research has found that adolescents who engage in a problematic use of social networking sites are likely to show maladjustment problems. However, little is known about its links with peer aggression and victimization. The main goal of this study was to analyze the relationship between problematic use of online social networking sites, peer aggression –overt vs. relational and reactive vs. instrumental–, and peer victimization –overt physical and verbal, and relational–, taking into account gender and age (in early and mid-adolescence). Participants were selected using randomized cluster sampling considering school and class as clusters. A battery of instruments was applied to 1,952 adolescents' secondary students from Spain (Andalusia) (50.4% boys), aged 11 to 16 (M = 14.07, SD = 1.39). Results showed that girls and 14–16 adolescents were more involved in a problematic use of online social networking sites. Furthermore, adolescents with high problematic use of online social networking sites were more involved in overt—reactive and instrumental—and relational—reactive and instrumental—aggressive behaviors, and self-reported higher levels of overt—physical and verbal—and relational victimization. Even though boys indicated higher levels of all types of victimization, girls with high problematic use of online social networking sites scored the highest on relational victimization. Relating to age, early adolescents (aged 11–14) with higher problematic use of online social networking sites reported the highest levels of overt verbal and relational victimization. Overall, results suggested the co-occurrence of problematic use of online social networking sites, peer aggression and victimization. In addition, results showed the influence that gender and age had on peer victimization. This study highlights the continuity between offline and online domains with regard to maladjustment problems in adolescence. PMID:29896139

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

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

Kumar, Rajeeva; Kumar, Aditya; Dai, Dan

2012-12-31

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developedmore » will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.« less

Social and Virtual Networks: Evaluating Synchronous Online Interviewing Using Instant Messenger

ERIC Educational Resources Information Center

Hinchcliffe, Vanessa; Gavin, Helen

2009-01-01

This paper describes an evaluation of the quality and utility of synchronous online interviewing for data collection in social network research. Synchronous online interviews facilitated by Instant Messenger as the communication medium, were undertaken with ten final year university students. Quantitative and qualitative content analysis of…

Exploring Self-Disclosure in Online Social Networks

ERIC Educational Resources Information Center

Velasco-Martin, Javier

2013-01-01

This project explores how experienced adult users of social media disclose personal information over online social networks (OSN). This work introduces a four-dimensional model to serve as a foundational framework for the study of online self-disclosure (OSD); these four dimensions are personal, social, technological and contextual, and support…

Helping Children Actively Design How They Learn about Health and Wellness: The Institute of Play Tests an Online Social Networking Tool within a Game-Based School Curriculum. Program Results Report

ERIC Educational Resources Information Center

Parker, Susan

2011-01-01

Youth rarely receive opportunities to craft their own strategies around health and wellness within contexts relevant to them. From 2009 to 2010, the Institute of Play, based in New York, developed Being Me, a social networking site, to enable sixth-graders at the Quest to Learn public school to explore, discover and document a range of ideas…

Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention.

PubMed

Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Barman Adhikari, Anamika; Milburn, Norweeta G

2012-04-01

The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth.Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F recruited online youth (OY) to participate in MySpace and Facebook communities where digital media was disseminated and discussed. The resulting social networks were assessed with respect to size, growth, density, relative centrality of positions and homophily of ties. Seven PL, 53 F2F and 103 OY created two large networks. After the first 50 F2F youth participated, online networks entered a rapid growth phase. OY were among the most central youth in these networks. Younger aged persons and females were disproportionately connected to like youth. The program appears highly acceptable to homeless youth. Social network analysis revealed which PL were the most critical to the program and which types of participants (younger youth and females) may require additional outreach efforts in the future.

Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention

PubMed Central

Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Barman Adhikari, Anamika; Milburn, Norweeta G.

2012-01-01

The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth.Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F recruited online youth (OY) to participate in MySpace and Facebook communities where digital media was disseminated and discussed. The resulting social networks were assessed with respect to size, growth, density, relative centrality of positions and homophily of ties. Seven PL, 53 F2F and 103 OY created two large networks. After the first 50 F2F youth participated, online networks entered a rapid growth phase. OY were among the most central youth in these networks. Younger aged persons and females were disproportionately connected to like youth. The program appears highly acceptable to homeless youth. Social network analysis revealed which PL were the most critical to the program and which types of participants (younger youth and females) may require additional outreach efforts in the future. PMID:22247453

Incremental Support Vector Machine Framework for Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Awad, Mariette; Jiang, Xianhua; Motai, Yuichi

2006-12-01

Motivated by the emerging requirements of surveillance networks, we present in this paper an incremental multiclassification support vector machine (SVM) technique as a new framework for action classification based on real-time multivideo collected by homogeneous sites. The technique is based on an adaptation of least square SVM (LS-SVM) formulation but extends beyond the static image-based learning of current SVM methodologies. In applying the technique, an initial supervised offline learning phase is followed by a visual behavior data acquisition and an online learning phase during which the cluster head performs an ensemble of model aggregations based on the sensor nodes inputs. The cluster head then selectively switches on designated sensor nodes for future incremental learning. Combining sensor data offers an improvement over single camera sensing especially when the latter has an occluded view of the target object. The optimization involved alleviates the burdens of power consumption and communication bandwidth requirements. The resulting misclassification error rate, the iterative error reduction rate of the proposed incremental learning, and the decision fusion technique prove its validity when applied to visual sensor networks. Furthermore, the enabled online learning allows an adaptive domain knowledge insertion and offers the advantage of reducing both the model training time and the information storage requirements of the overall system which makes it even more attractive for distributed sensor networks communication.

Research on gender differences in online health communities.

PubMed

Liu, Xuan; Sun, Min; Li, Jia

2018-03-01

With the growing concern about health issues and the emergence of online communities based on user-generated content (UGC), more and more people are participating in online health communities (OHCs) to exchange opinions and health information. This paper aims to examine whether and how male and female users behave differently in OHCs. Using data from a leading diabetes community in China (Tianmijiayuan), we incorporate three different techniques: topic modeling analysis, sentiment analysis and friendship network analysis to investigate gender differences in chronic online health communities. The results indicated that (1) Male users' posting content was usually more professional and included more medical terms. Comparatively speaking, female users were more inclined to seek emotional support in the health communities. (2) Female users expressed more negative emotions than male users did, especially anxiety and sadness. (3) In addition, male users were more centered and influential in the friendship network than were women. Through these analyses, our research revealed the behavioral characteristics and needs for different gender users in online health communities. Gaining a deeper understanding of gender differences in OHCs can serve as guidance to better meet the information needs, emotional needs and relationship needs of male and female patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Investigating Value Creation in a Community of Practice with Social Network Analysis in a Hybrid Online Graduate Education Program

ERIC Educational Resources Information Center

Cowan, John E.; Menchaca, Michael P.

2014-01-01

This study reports an analysis of 10?years in the life of the Internet-based Master in Educational Technology program (iMET) at Sacramento State University. iMET is a hybrid educational technology master's program delivered 20% face to face and 80% online. The program has achieved a high degree of success, with a course completion rate of 93% and…

Emergence, evolution and scaling of online social networks.

PubMed

Wang, Le-Zhi; Huang, Zi-Gang; Rong, Zhi-Hai; Wang, Xiao-Fan; Lai, Ying-Cheng

2014-01-01

Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

Choosing your network: social preferences in an online health community.

PubMed

Centola, Damon; van de Rijt, Arnout

2015-01-01

A growing number of online health communities offer individuals the opportunity to receive information, advice, and support from peers. Recent studies have demonstrated that these new online contacts can be important informational resources, and can even exert significant influence on individuals' behavior in various contexts. However little is known about how people select their health contacts in these virtual domains. This is because selection preferences in peer networks are notoriously difficult to detect. In existing networks, unobserved pressures on tie formation--such as common organizational memberships, introductions to friends of friends, or limitations on accessibility--may mistakenly be interpreted as individual preferences for interacting/not interacting with others. We address these issues by adopting a social media approach to studying network formation. We study social selection using an in vivo study within an online exercise program, in which anonymous participants have equal opportunities for initiating relationships with other program members. This design allows us to identify individuals' preferences for health contacts, and to evaluate what these preferences imply for members' access to new kinds of health information, and for the kinds of social influences to which they are exposed. The study was conducted within a goal-oriented fitness competition, in which participation was greatest among a small core of active individuals. Our results show that the active participants displayed indifference to the fitness and exercise profiles of others, disregarding information about others' fitness levels, exercise preferences, and workout experiences, instead selecting partners almost entirely on the basis of similarities on gender, age, and BMI. Interestingly, the findings suggest that rather than expanding and diversifying their sources of health information, participants' choices limited the value of their online resources by selecting contacts based on characteristics that are common sources of homophily in offline relationships. In light of our findings, we discuss design principles that may be useful for organizations and policy makers trying to improve the value of participants' social capital within online health programs. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.

PubMed

Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao

2017-06-16

This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.

Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method

NASA Astrophysics Data System (ADS)

Al-garadi, Mohammed Ali; Varathan, Kasturi Dewi; Ravana, Sri Devi

2017-02-01

Online social networks (OSNs) have become a vital part of everyday living. OSNs provide researchers and scientists with unique prospects to comprehend individuals on a scale and to analyze human behavioral patterns. Influential spreaders identification is an important subject in understanding the dynamics of information diffusion in OSNs. Targeting these influential spreaders is significant in planning the techniques for accelerating the propagation of information that is useful for various applications, such as viral marketing applications or blocking the diffusion of annoying information (spreading of viruses, rumors, online negative behaviors, and cyberbullying). Existing K-core decomposition methods consider links equally when calculating the influential spreaders for unweighted networks. Alternatively, the proposed link weights are based only on the degree of nodes. Thus, if a node is linked to high-degree nodes, then this node will receive high weight and is treated as an important node. Conversely, the degree of nodes in OSN context does not always provide accurate influence of users. In the present study, we improve the K-core method for OSNs by proposing a novel link-weighting method based on the interaction among users. The proposed method is based on the observation that the interaction of users is a significant factor in quantifying the spreading capability of user in OSNs. The tracking of diffusion links in the real spreading dynamics of information verifies the effectiveness of our proposed method for identifying influential spreaders in OSNs as compared with degree centrality, PageRank, and original K-core.

A VGI data integration framework based on linked data model

NASA Astrophysics Data System (ADS)

Wan, Lin; Ren, Rongrong

2015-12-01

This paper aims at the geographic data integration and sharing method for multiple online VGI data sets. We propose a semantic-enabled framework for online VGI sources cooperative application environment to solve a target class of geospatial problems. Based on linked data technologies - which is one of core components of semantic web, we can construct the relationship link among geographic features distributed in diverse VGI platform by using linked data modeling methods, then deploy these semantic-enabled entities on the web, and eventually form an interconnected geographic data network to support geospatial information cooperative application across multiple VGI data sources. The mapping and transformation from VGI sources to RDF linked data model is presented to guarantee the unique data represent model among different online social geographic data sources. We propose a mixed strategy which combined spatial distance similarity and feature name attribute similarity as the measure standard to compare and match different geographic features in various VGI data sets. And our work focuses on how to apply Markov logic networks to achieve interlinks of the same linked data in different VGI-based linked data sets. In our method, the automatic generating method of co-reference object identification model according to geographic linked data is discussed in more detail. It finally built a huge geographic linked data network across loosely-coupled VGI web sites. The results of the experiment built on our framework and the evaluation of our method shows the framework is reasonable and practicable.

Structural characteristics of the online social networks of maltreated youth and offline sexual risk behavior.

PubMed

Negriff, Sonya; Valente, Thomas W

2018-02-07

Maltreated youth are at risk for exposure to online sexual content and high-risk sexual behavior, yet characteristics of their online social networks have not been examined as a potential source of vulnerability. The aims of the current study were: 1) to test indicators of size (number of friends) and fragmentation (number of connections between friends) of maltreated young adults' online networks as predictors of intentional and unintentional exposure to sexual content and offline high-risk sexual behavior and 2) to test maltreatment as a moderator of these associations. Participants were selected from a longitudinal study on the effects of child maltreatment (n = 152; Mean age 21.84 years). Data downloaded from Facebook were used to calculate network variables of size (number of friends), density (connections between friends), average degree (average number of connections for each friend), and percent isolates (those not connected to others in the network). Self-reports of intentional and unintentional exposure to online sexual content and offline high-risk sexual behavior were the outcome variables. Multiple-group path modeling showed that only for the maltreated group having a higher percent of isolates in the network predicted intentional exposure to online sexual content and offline high-risk sexual behavior. An implication of this finding is that the composition of the Facebook network may be used as a risk indicator for individuals with child-welfare documented maltreatment experiences. Copyright © 2018. Published by Elsevier Ltd.

Study on key technologies of vehicle networking system platform for electric automobiles based on micro-service

NASA Astrophysics Data System (ADS)

Ye, Fei

2018-04-01

With the rapid increase of electric automobiles and charging piles, the elastic expansion and online rapid upgrade were required for the vehicle networking system platform (system platform for short). At present, it is difficult to meet the operation needs due to the traditional huge rock architecture used by the system platform. This paper studied the system platform technology architecture based on "cloud platform +micro-service" to obtain a new generation of vehicle networking system platform with the combination of elastic expansion and application, thus significantly improving the service operation ability of system.

Around the Globe.

ERIC Educational Resources Information Center

Wheeler, Steve

2001-01-01

Provides an overview of current activities in Web-based learning and development in Romania. Discusses promotion of online learning by various societies and institutions; the distance courses based on traditional procedures; problems of the current state of distance education, including shortage of teachers and network administration and poor and…

A network-based dynamical ranking system for competitive sports

NASA Astrophysics Data System (ADS)

Motegi, Shun; Masuda, Naoki

2012-12-01

From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

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

Ondrej Linda; Todd Vollmer; Jason Wright

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrainedmore » computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.« less

Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.

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

Jones, Christian Birk; Robinson, Matt; Yasaei, Yasser

Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often beenmore » perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.« less

The Social Network: Keeping in Touch with Alumni through Online Media

ERIC Educational Resources Information Center

Bunker, Matt

2011-01-01

Not all social-networking tools are created equal. Knowing where alumni are and what they're doing online is key when deciding what social networks to use. Knowing how to address and employ social networking can change the way institutions engage alumni. Social media help institutions connect with alumni; these tools help build, sustain, and even…

Incorporating profile information in community detection for online social networks

NASA Astrophysics Data System (ADS)

Fan, W.; Yeung, K. H.

2014-07-01

Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.

A Study on the Motives of High School and Undergraduate College Students for Using the Social Network Site Facebook

ERIC Educational Resources Information Center

Hart, Michael J.

2010-01-01

An online survey conducted at a mid-Atlantic university and two high schools located in close geographical proximity sought to determine the motives for using the social network site Facebook.com. A redesigned instrument based upon the Interpersonal Communication Motives (ICM) scale used in past uses and gratifications research measured…

Transparency in Cooperative Online Education

ERIC Educational Resources Information Center

Dalsgaard, Christian; Paulsen, Morten Flate

2009-01-01

The purpose of this article is to discuss the following question: What is the potential of social networking within cooperative online education? Social networking does not necessarily involve communication, dialogue, or collaboration. Instead, the authors argue that "transparency" is a unique feature of social networking services.…

Rock Hill Business, Education, and Community Online Network.

ERIC Educational Resources Information Center

Broyles, Alan

The Business, Education & Community On-line Network (BEACON) is designed to support development and implementation of demonstration applications operating in an asynchronous transfer mode (ATM) fiber optic network environment. Initial origination and destination sites include high schools and universities around Rock Hill (South Carolina). The…

A novel information cascade model in online social networks

NASA Astrophysics Data System (ADS)

Tong, Chao; He, Wenbo; Niu, Jianwei; Xie, Zhongyu

2016-02-01

The spread and diffusion of information has become one of the hot issues in today's social network analysis. To analyze the spread of online social network information and the attribute of cascade, in this paper, we discuss the spread of two kinds of users' decisions for city-wide activities, namely the "want to take part in the activity" and "be interested in the activity", based on the users' attention in "DouBan" and the data of the city-wide activities. We analyze the characteristics of the activity-decision's spread in these aspects: the scale and scope of the cascade subgraph, the structure characteristic of the cascade subgraph, the topological attribute of spread tree, and the occurrence frequency of cascade subgraph. On this basis, we propose a new information spread model. Based on the classical independent diffusion model, we introduce three mechanisms, equal probability, similarity of nodes, and popularity of nodes, which can generate and affect the spread of information. Besides, by conducting the experiments in six different kinds of network data set, we compare the effects of three mechanisms above mentioned, totally six specific factors, on the spread of information, and put forward that the node's popularity plays an important role in the information spread.

An experimental study of the Online Information Paradox: Does en-route information improve road network performance?

PubMed Central

2017-01-01

This study investigates the empirical presence of a theoretical transportation paradox, defined as the “Online Information Paradox” (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network. PMID:28902854

Investigating Patterns of Participation in an Online Support Group for Problem Drinking: a Social Network Analysis.

PubMed

Urbanoski, Karen; van Mierlo, Trevor; Cunningham, John

2017-10-01

This study contributes to emerging literature on online health networks by modeling communication patterns between members of a moderated online support group for problem drinking. Using social network analysis, we described members' patterns of joint participation in threads, parsing out the role of site moderators, and explored differences in member characteristics by network position. Posts made to the online support group of Alcohol Help Centre during 2013 were structured as a two-mode network of members (n = 205) connected via threads (n = 506). Metrics included degree centrality, clique membership, and tie strength. The network consisted of one component and no cliques of members, although most made few posts and a small number communicated only with the site's moderators. Highly active members were older and tended to have started posting prior to 2013. The distribution of members across threads varied from threads containing posts by one member to others that connected multiple members. Moderators accounted for sizable proportions of the connectivity between both members and threads. After 5 years of operation, the AHC online support group appears to be fairly cohesive and stable, in the sense that there were no isolated subnetworks comprised of specific types of members or devoted to specific topics. Participation and connectedness at the member-level was varied, however, and tended to be low on average. The moderators were among the most central in the network, although there were also members who emerged as central and dedicated contributors to the online discussions across topics. Study findings highlight a number of areas for consideration by online support group developers and managers.

Advocacy, Efficacy, and Engagement in an Online Network for Latino Childhood Obesity Prevention.

PubMed

Ramirez, Amelie G; Gallion, Kipling J; Despres, Cliff; Aguilar, Rosalie P; Adeigbe, Rebecca T; Seidel, Sarah E; McAlister, Alfred L

2015-11-01

Salud America! is a national network created to engage Latino researchers, health professionals and community leaders in actions to reduce Latino childhood obesity. An online survey of 148 Salud America! network members investigated relationships between (1) their levels of engagement with the network, (2) self- and collective-efficacy, and (3) behavioral intentions to engage in advocacy for policies that can help reduce Latino childhood obesity. Analyses of these data found that higher levels of Salud America! engagement was associated with collective-advocacy efficacy-greater confidence in organized group advocacy as a way of advancing policies to reduce Latino childhood obesity. A multiple regression analysis found that this sense of collective-efficacy moderately predicted intentions to engage in advocacy behaviors. Salud America! engagement levels were less strongly associated with members' confidence in their personal ability to be an effective advocate, yet this sense of self-efficacy was a very strong predictor of a behavioral intention to advocate. Based on these findings, new online applications aimed at increasing self- and collective-efficacy through peer modeling are being developed for Salud America! in order to help individuals interested in Latino childhood obesity prevention to connect with each other and with opportunities for concerted local actions in their communities. © 2015 Society for Public Health Education.

Developing Health Promotion Interventions on Social Networking Sites: Recommendations from The FaceSpace Project

PubMed Central

Pedrana, Alisa E; Stoove, Mark A; Chang, Shanton; Howard, Steve; Asselin, Jason; Ilic, Olivia; Batrouney, Colin; Hellard, Margaret E

2012-01-01

Online social networking sites offer a novel setting for the delivery of health promotion interventions due to their potential to reach a large population and the possibility for two-way engagement. However, few have attempted to host interventions on these sites, or to use the range of interactive functions available to enhance the delivery of health-related messages. This paper presents lessons learnt from “The FaceSpace Project”, a sexual health promotion intervention using social networking sites targeting two key at-risk groups. Based on our experience, we make recommendations for developing and implementing health promotion interventions on these sites. Elements crucial for developing interventions include establishing a multidisciplinary team, allowing adequate time for obtaining approvals, securing sufficient resources for building and maintaining an online presence, and developing an integrated process and impact evaluation framework. With two-way interaction an important and novel feature of health promotion interventions in this medium, we also present strategies trialled to generate interest and engagement in our intervention. Social networking sites are now an established part of the online environment; our experience in developing and implementing a health promotion intervention using this medium are of direct relevance and utility for all health organizations creating a presence in this new environment. PMID:22374589

The Preventing Suicide Network: Delivering online tailored resources to those who help others.

PubMed

Elfrink, Victoria; Schlachta-Fairchild, Loretta; Szczur, Martha; Chang, Hua Florence; Young-Weeden, Elizabeth; Rocca, Mitra

2006-01-01

Concerned over the growing epidemic of death by suicide in the United States, the National Institute of Mental Health of the U.S. National Institutes of Health funded Small Business Innovation Research (SBIR) projects using innovative web-based approaches to provide resources to professionals and the general public about suicide prevention. The Preventing Suicide Network (PSN) was funded (SBIR Contract #N44MH22044) and developed over a three and a half year period (2001-2005) as part of this initiative. The PSN provides intermediaries (those who participate in activities to prevent suicide) with an online community dedicated to timely access to authoritative and problem-specific tailored information.

Building trusting relationships in online health communities.

PubMed

Zhao, Jing; Ha, Sejin; Widdows, Richard

2013-09-01

This study investigates consumers' use of online health communities (OHCs) for healthcare from a relationship building perspective based on the commitment-trust theory of relationships. The study proposes that perspective taking, empathic concern, self-efficacy, and network density affect the development of both cognitive and affective trust, which together determine OHC members' membership continuance intention (MCI) and knowledge contribution. Data collected from eight existing OHCs (N=255) were utilized to test the hypothesized model. Results show that perspective taking and self-efficacy can increase cognitive trust and affective trust, respectively. Network density contributes to cognitive and affective trust. Both cognitive trust and affective trust influence MCI, while only affective trust impacts members' knowledge contribution behaviors.

The application of neural network PID controller to control the light gasoline etherification

NASA Astrophysics Data System (ADS)

Cheng, Huanxin; Zhang, Yimin; Kong, Lingling; Meng, Xiangyong

2017-06-01

Light gasoline etherification technology can effectively improve the quality of gasoline, which is environmental- friendly and economical. By combining BP neural network and PID control and using BP neural network self-learning ability for online parameter tuning, this method optimizes the parameters of PID controller and applies this to the Fcc gas flow control to achieve the control of the final product- heavy oil concentration. Finally, through MATLAB simulation, it is found that the PID control based on BP neural network has better controlling effect than traditional PID control.

Online Learning of Genetic Network Programming and its Application to Prisoner’s Dilemma Game

NASA Astrophysics Data System (ADS)

Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

A new evolutionary model with the network structure named Genetic Network Programming (GNP) has been proposed recently. GNP, that is, an expansion of GA and GP, represents solutions as a network structure and evolves it by using “offline learning (selection, mutation, crossover)”. GNP can memorize the past action sequences in the network flow, so it can deal with Partially Observable Markov Decision Process (POMDP) well. In this paper, in order to improve the ability of GNP, Q learning (an off-policy TD control algorithm) that is one of the famous online methods is introduced for online learning of GNP. Q learning is suitable for GNP because (1) in reinforcement learning, the rewards an agent will get in the future can be estimated, (2) TD control doesn’t need much memory and can learn quickly, and (3) off-policy is suitable in order to search for an optimal solution independently of the policy. Finally, in the simulations, online learning of GNP is applied to a player for “Prisoner’s dilemma game” and its ability for online adaptation is confirmed.

Pharmacists on Facebook: online social networking and the profession.

PubMed

Mattingly, T Joseph; Cain, Jeff; Fink, Joseph L

2010-01-01

To provide a brief history of Facebook and online social networking and discuss how it has contributed and can contribute in the future to a paradigm change in social communications. When student pharmacists complete school and enter practice, they encounter enhanced expectations to act appropriately and professionally. Facebook expands the dilemma of separating private and public life--a challenge for individuals in all professions. From the standpoint of a professional association, Facebook provides a tremendous opportunity to reach out to members in an unprecedented way. Pharmacy organizations are beginning to use these new tools to increase communication and dissemination of information. The popularity of Facebook has brought the issue of online social networking to the forefront of professional and organizational discussions. The issues of privacy, identity protection, and e-professionalism are likely to reappear as pharmacists and student pharmacists continue to communicate via online networks. The potential exists for organizations to harness this organizational and communication power for their own interests. Further study is needed regarding the interaction between online social networking applications and the profession of pharmacy.

Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building.

PubMed

Namkoong, Kang; Shah, Dhavan V; Gustafson, David H

2017-11-01

This study investigates how social support and family relationship perceptions influence breast cancer patients' online communication networks in a computer-mediated social support (CMSS) group. To examine social interactions in the CMSS group, we identified two types of online social networks: open and targeted communication networks. The open communication network reflects group communication behaviors (i.e., one-to-many or "broadcast" communication) in which the intended audience is not specified; in contrast, the targeted communication network reflects interpersonal discourses (i.e., one-to-one or directed communication) in which the audience for the message is specified. The communication networks were constructed by tracking CMSS group usage data of 237 breast cancer patients who participated in one of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of a diagnosis of primary breast cancer or recurrence at the time of recruitment. Findings reveal that breast cancer patients who perceived less availability of offline social support had a larger social network size in the open communication network. In contrast, those who perceived less family cohesion had a larger targeted communication network in the CMSS group, meaning they were inclined to use the CMSS group for developing interpersonal relationships.

A Multirelational Social Network Analysis of an Online Health Community for Smoking Cessation.

PubMed

Zhao, Kang; Wang, Xi; Cha, Sarah; Cohn, Amy M; Papandonatos, George D; Amato, Michael S; Pearson, Jennifer L; Graham, Amanda L

2016-08-25

Online health communities (OHCs) provide a convenient and commonly used way for people to connect around shared health experiences, exchange information, and receive social support. Users often interact with peers via multiple communication methods, forming a multirelational social network. Use of OHCs is common among smokers, but to date, there have been no studies on users' online interactions via different means of online communications and how such interactions are related to smoking cessation. Such information can be retrieved in multirelational social networks and could be useful in the design and management of OHCs. To examine the social network structure of an OHC for smoking cessation using a multirelational approach, and to explore links between subnetwork position (ie, centrality) and smoking abstinence. We used NetworkX to construct 4 subnetworks based on users' interactions via blogs, group discussions, message boards, and private messages. We illustrated topological properties of each subnetwork, including its degree distribution, density, and connectedness, and compared similarities among these subnetworks by correlating node centrality and measuring edge overlap. We also investigated coevolution dynamics of this multirelational network by analyzing tie formation sequences across subnetworks. In a subset of users who participated in a randomized, smoking cessation treatment trial, we conducted user profiling based on users' centralities in the 4 subnetworks and identified user groups using clustering techniques. We further examined 30-day smoking abstinence at 3 months postenrollment in relation to users' centralities in the 4 subnetworks. The 4 subnetworks have different topological characteristics, with message board having the most nodes (36,536) and group discussion having the highest network density (4.35×10(-3)). Blog and message board subnetworks had the most similar structures with an in-degree correlation of .45, out-degree correlation of .55, and Jaccard coefficient of .23 for edge overlap. A new tie in the group discussion subnetwork had the lowest probability of triggering subsequent ties among the same two users in other subnetworks: 6.33% (54,142/855,893) for 2-tie sequences and 2.13% (18,207/855,893) for 3-tie sequences. Users' centralities varied across the 4 subnetworks. Among a subset of users enrolled in a randomized trial, those with higher centralities across subnetworks generally had higher abstinence rates, although high centrality in the group discussion subnetwork was not associated with higher abstinence rates. A multirelational approach revealed insights that could not be obtained by analyzing the aggregated network alone, such as the ineffectiveness of group discussions in triggering social ties of other types, the advantage of blogs, message boards, and private messages in leading to subsequent social ties of other types, and the weak connection between one's centrality in the group discussion subnetwork and smoking abstinence. These insights have implications for the design and management of online social networks for smoking cessation.

A Multirelational Social Network Analysis of an Online Health Community for Smoking Cessation

PubMed Central

Wang, Xi; Cha, Sarah; Cohn, Amy M; Papandonatos, George D; Amato, Michael S; Pearson, Jennifer L; Graham, Amanda L

2016-01-01

Background Online health communities (OHCs) provide a convenient and commonly used way for people to connect around shared health experiences, exchange information, and receive social support. Users often interact with peers via multiple communication methods, forming a multirelational social network. Use of OHCs is common among smokers, but to date, there have been no studies on users’ online interactions via different means of online communications and how such interactions are related to smoking cessation. Such information can be retrieved in multirelational social networks and could be useful in the design and management of OHCs. Objective To examine the social network structure of an OHC for smoking cessation using a multirelational approach, and to explore links between subnetwork position (ie, centrality) and smoking abstinence. Methods We used NetworkX to construct 4 subnetworks based on users’ interactions via blogs, group discussions, message boards, and private messages. We illustrated topological properties of each subnetwork, including its degree distribution, density, and connectedness, and compared similarities among these subnetworks by correlating node centrality and measuring edge overlap. We also investigated coevolution dynamics of this multirelational network by analyzing tie formation sequences across subnetworks. In a subset of users who participated in a randomized, smoking cessation treatment trial, we conducted user profiling based on users’ centralities in the 4 subnetworks and identified user groups using clustering techniques. We further examined 30-day smoking abstinence at 3 months postenrollment in relation to users’ centralities in the 4 subnetworks. Results The 4 subnetworks have different topological characteristics, with message board having the most nodes (36,536) and group discussion having the highest network density (4.35×10−3). Blog and message board subnetworks had the most similar structures with an in-degree correlation of .45, out-degree correlation of .55, and Jaccard coefficient of .23 for edge overlap. A new tie in the group discussion subnetwork had the lowest probability of triggering subsequent ties among the same two users in other subnetworks: 6.33% (54,142/855,893) for 2-tie sequences and 2.13% (18,207/855,893) for 3-tie sequences. Users’ centralities varied across the 4 subnetworks. Among a subset of users enrolled in a randomized trial, those with higher centralities across subnetworks generally had higher abstinence rates, although high centrality in the group discussion subnetwork was not associated with higher abstinence rates. Conclusions A multirelational approach revealed insights that could not be obtained by analyzing the aggregated network alone, such as the ineffectiveness of group discussions in triggering social ties of other types, the advantage of blogs, message boards, and private messages in leading to subsequent social ties of other types, and the weak connection between one’s centrality in the group discussion subnetwork and smoking abstinence. These insights have implications for the design and management of online social networks for smoking cessation. PMID:27562640

Experimental demonstration of OpenFlow-enabled media ecosystem architecture for high-end applications over metro and core networks.

PubMed

Ntofon, Okung-Dike; Channegowda, Mayur P; Efstathiou, Nikolaos; Rashidi Fard, Mehdi; Nejabati, Reza; Hunter, David K; Simeonidou, Dimitra

2013-02-25

In this paper, a novel Software-Defined Networking (SDN) architecture is proposed for high-end Ultra High Definition (UHD) media applications. UHD media applications require huge amounts of bandwidth that can only be met with high-capacity optical networks. In addition, there are requirements for control frameworks capable of delivering effective application performance with efficient network utilization. A novel SDN-based Controller that tightly integrates application-awareness with network control and management is proposed for such applications. An OpenFlow-enabled test-bed demonstrator is reported with performance evaluations of advanced online and offline media- and network-aware schedulers.

Higher Education Scholars' Participation and Practices on Twitter

ERIC Educational Resources Information Center

Veletsianos, G.

2012-01-01

Scholars participate in online social networks for professional purposes. In such networks, learning takes the form of participation and identity formation through engagement in and contribution to networked practices. While current literature describes the possible benefits of online participation, empirical research on scholars' use of online…

Synchronised integrated online e-health profiles.

PubMed

Liang, Jian; Iannella, Renato; Sahama, Tony

2011-01-01

Web-based social networking applications have become increasingly important in recent years. The current applications in the healthcare sphere can support the health management, but to date there is no patient-controlled integrator. This paper proposes a platform called Multiple Profile Manager (MPM) that enables a user to create and manage an integrated profile that can be shared across numerous social network sites. Moreover, it is able to facilitate the collection of personal healthcare data, which makes a contribution to the development of public health informatics. Here we want to illustrate how patients and physicians can be benefited from enabling the platform for online social network sites. The MPM simplifies the management of patients' profiles and allows health professionals to obtain a more complete picture of the patients' background so that they can provide better health care. To do so, we demonstrate a prototype of the platform and describe its protocol specification, which is an XMPP (Extensible Messaging and Presence Protocol) [1] extension, for sharing and synchronising profile data (vCard²) between different social networks.

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

Moving health promotion communities online: a review of the literature.

PubMed

Sunderland, Naomi; Beekhuyzen, Jenine; Kendall, Elizabeth; Wolski, Malcom

There is a need to enhance the effectiveness and reach of complex health promotion initiatives by providing opportunities for diverse health promotion practitioners and others to interact in online settings. This paper reviews the existing literature on how to take health promotion communities and networks into online settings. A scoping review of relevant bodies of literature and empirical evidence was undertaken to provide an interpretive synthesis of existing knowledge on the topic. Sixteen studies were identified between 1986 and 2007. Relatively little research has been conducted on the process of taking existing offline communities and networks into online settings. However, more research has focused on offline (i.e. not mediated via computer networks); 'virtual' (purely online with no offline interpersonal contact); and 'multiplex' communities (i.e. those that interact across both online and offline settings). Results are summarised under three themes: characteristics of communities in online and offline settings; issues in moving offline communities online, and designing online communities to match community needs. Existing health promotion initiatives can benefit from online platforms that promote community building and knowledge sharing. Online e-health promotion settings and communities can successfully integrate with existing offline settings and communities to form 'multiplex' communities (i.e. communities that operate fluently across both online and offline settings).

Community (in) Colleges: The Relationship Between Online Network Involvement and Academic Outcomes at a Community College

ERIC Educational Resources Information Center

Evans, Eliza D.; McFarland, Daniel A.; Rios-Aguilar, Cecilia; Deil-Amen, Regina

2016-01-01

Objective: This study explores the relationship between online social network involvement and academic outcomes among community college students. Prior theory hypothesizes that socio-academic moments are especially important for the integration of students into community colleges and that integration is related to academic outcomes. Online social…

On-Line Assessment: What, Why, How.

ERIC Educational Resources Information Center

Natal, Dottie

Recent increases in the speed and accessibility of computers and networks have made it possible to administer tests on-line. On-line assessment can be conducted in a controlled setting, such as a testing center, or distributed over local area networks or the Internet to libraries and student homes, allowing students the flexibility to complete…

The Impact of Cognitive Style on Social Networks in On-Line Discussions

ERIC Educational Resources Information Center

Jablokow, Kathryn; Vercellone-Smith, Pamela

2011-01-01

With the rise of e-Learning in engineering education, understanding the impact of individual differences on the ways students communicate and collaborate on-line has become increasingly important. The research described here investigates the influence of cognitive style on the interactions within student social networks in an on-line learning…

Online Social Networking: Usage in Adolescents

ERIC Educational Resources Information Center

Raju, Nevil Johnson; Valsaraj, Blessy Prabha; Noronha, Judith

2015-01-01

Online social networking (OSN) has played a significant role on the relationship among college students. It is becoming a popular medium for socializing online and tools to facilitate friendship. Young adults and adolescents are the most prolific users of OSN sites. The frequent use of OSN sites results in addiction toward these sites and…

Culture, Role and Group Work: A Social Network Analysis Perspective on an Online Collaborative Course

ERIC Educational Resources Information Center

Stepanyan, Karen; Mather, Richard; Dalrymple, Roger

2014-01-01

This paper discusses the patterns of network dynamics within a multicultural online collaborative learning environment. It analyses the interaction of participants (both students and facilitators) within a discussion board that was established as part of a 3-month online collaborative course. The study employs longitudinal probabilistic social…

Student Interaction and Community Building: An Evaluation of Social Networking in Online Learning Environments

ERIC Educational Resources Information Center

Cardona-Divale, Maria Victoria

2012-01-01

Learners often report difficulty maintaining social connectivity in online courses. Technology is quickly changing how people communicate, collaborate and learn using online social networking sites (SNSs). These sites have transformed education in a way that provides new learning opportunities when integrated with web 2.0 tools. Little research is…

Blessed Oblivion? Knowledge and Metacognitive Accuracy in Online Social Networks

ERIC Educational Resources Information Center

Moll, Ricarda; Pieschl, Stephanie; Bromme, Rainer

2015-01-01

In order to reap the social gratifications of Online Social Networks (OSNs), users often disclose self-related information, making them potentially vulnerable to their online audiences. We give a brief overview of our theoretical ideas and empirical research about additional cognitive and metacognitive factors relevant for the perception of risk…

Learning Tools for Knowledge Nomads: Using Personal Digital Assistants (PDAs) in Web-based Learning Environments.

ERIC Educational Resources Information Center

Loh, Christian Sebastian

2001-01-01

Examines how mobile computers, or personal digital assistants (PDAs), can be used in a Web-based learning environment. Topics include wireless networks on college campuses; online learning; Web-based learning technologies; synchronous and asynchronous communication via the Web; content resources; Web connections; and collaborative learning. (LRW)

The adoption of Firm-Hosted Online Communities: an empirical investigation into the role of service quality and social interactions

NASA Astrophysics Data System (ADS)

Corkindale, David; Ram, Jiwat; Chen, Howard

2018-02-01

Online communities are a powerful device for collaborative creativity and innovation. Developments in Web 2.0 technologies have given rise to such interactions through firm-hosted online communities (FHOCs) - firm-run online information services that also provide self-help to a community. We devise a model that seeks to explain the factors that encourage people to become members of a FHOC and test the model using structural equation modelling based on data collected from 511 users of a FHOC. The study finds that: (a) an understanding of Perceived Usefulness (PU) plays a mediating role between Behavioural Intention (BI) to adopt FHOC and Trust, as well as Interface design; b) Networking among users has an indirect effect on BI; and c) design of the Interface has a direct influence on BI. A managerial implication is that Networking plays a role in the way supplementary services, including blogs and discussion forums, are perceived. Theoretically, when service quality is decomposed into components such as core services and supplementary services, it also positively influences PU.

The Detection of Emerging Trends Using Wikipedia Traffic Data and Context Networks.

PubMed

Kämpf, Mirko; Tessenow, Eric; Kenett, Dror Y; Kantelhardt, Jan W

2015-01-01

Can online media predict new and emerging trends, since there is a relationship between trends in society and their representation in online systems? While several recent studies have used Google Trends as the leading online information source to answer corresponding research questions, we focus on the online encyclopedia Wikipedia often used for deeper topical reading. Wikipedia grants open access to all traffic data and provides lots of additional (semantic) information in a context network besides single keywords. Specifically, we suggest and study context-normalized and time-dependent measures for a topic's importance based on page-view time series of Wikipedia articles in different languages and articles related to them by internal links. As an example, we present a study of the recently emerging Big Data market with a focus on the Hadoop ecosystem, and compare the capabilities of Wikipedia versus Google in predicting its popularity and life cycles. To support further applications, we have developed an open web platform to share results of Wikipedia analytics, providing context-rich and language-independent relevance measures for emerging trends.

The Detection of Emerging Trends Using Wikipedia Traffic Data and Context Networks

PubMed Central

Kämpf, Mirko; Tessenow, Eric; Kenett, Dror Y.; Kantelhardt, Jan W.

2015-01-01

Can online media predict new and emerging trends, since there is a relationship between trends in society and their representation in online systems? While several recent studies have used Google Trends as the leading online information source to answer corresponding research questions, we focus on the online encyclopedia Wikipedia often used for deeper topical reading. Wikipedia grants open access to all traffic data and provides lots of additional (semantic) information in a context network besides single keywords. Specifically, we suggest and study context-normalized and time-dependent measures for a topic’s importance based on page-view time series of Wikipedia articles in different languages and articles related to them by internal links. As an example, we present a study of the recently emerging Big Data market with a focus on the Hadoop ecosystem, and compare the capabilities of Wikipedia versus Google in predicting its popularity and life cycles. To support further applications, we have developed an open web platform to share results of Wikipedia analytics, providing context-rich and language-independent relevance measures for emerging trends. PMID:26720074

Discovering the influential users oriented to viral marketing based on online social networks

NASA Astrophysics Data System (ADS)

Zhu, Zhiguo

2013-08-01

The target of viral marketing on the platform of popular online social networks is to rapidly propagate marketing information at lower cost and increase sales, in which a key problem is how to precisely discover the most influential users in the process of information diffusion. A novel method is proposed in this paper for helping companies to identify such users as seeds to maximize information diffusion in the viral marketing. Firstly, the user trust network oriented to viral marketing and users’ combined interest degree in the network including isolated users are extensively defined. Next, we construct a model considering the time factor to simulate the process of information diffusion in viral marketing and propose a dynamic algorithm description. Finally, experiments are conducted with a real dataset extracted from the famous SNS website Epinions. The experimental results indicate that the proposed algorithm has better scalability and is less time-consuming. Compared with the classical model, the proposed algorithm achieved a better performance than does the classical method on the two aspects of network coverage rate and time-consumption in our four sub-datasets.

From Telecommunications to Networking: The MELVYL Online Union Catalog and the Development of Intercampus Networks at the University of California.

ERIC Educational Resources Information Center

Lynch, Clifford A.

1989-01-01

Reviews the history of the network that supports the MELVYL online union catalog, describes current technological and policy issues, and discusses the role the network plays in integrating local automation, the union catalog, access to resource databases, and other initiatives. Sidebars by Mark Needleman discuss the TCP/IP protocol suite, internet…

Limitation of degree information for analyzing the interaction evolution in online social networks

NASA Astrophysics Data System (ADS)

Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

2014-04-01

Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

An Introduction to Social Network Data Analytics

NASA Astrophysics Data System (ADS)

Aggarwal, Charu C.

The advent of online social networks has been one of the most exciting events in this decade. Many popular online social networks such as Twitter, LinkedIn, and Facebook have become increasingly popular. In addition, a number of multimedia networks such as Flickr have also seen an increasing level of popularity in recent years. Many such social networks are extremely rich in content, and they typically contain a tremendous amount of content and linkage data which can be leveraged for analysis. The linkage data is essentially the graph structure of the social network and the communications between entities; whereas the content data contains the text, images and other multimedia data in the network. The richness of this network provides unprecedented opportunities for data analytics in the context of social networks. This book provides a data-centric view of online social networks; a topic which has been missing from much of the literature. This chapter provides an overview of the key topics in this field, and their coverage in this book.

Intercultural Communication in Online Social Networking Discourse

ERIC Educational Resources Information Center

Chen, Hsin-I

2017-01-01

This article presents a case study that examines how an online social networking community is constituted through intercultural discourse on the part of one learner sojourning in the US. Using Byram's model of intercultural communicative competence, this study examines the learner's naturalistic communication in a social networking site (SNS). The…

Environmental Learning in Online Social Networks: Adopting Environmentally Responsible Behaviors

ERIC Educational Resources Information Center

Robelia, Beth A.; Greenhow, Christine; Burton, Lisa

2011-01-01

Online social networks are increasingly important information and communication tools for young people and for the environmental movement. Networks may provide the motivation for young adults to increase environmental behaviors by increasing their knowledge of environmental issues and of the specific actions they can take to reduce greenhouse gas…

Measurement of Online Social Networks

ERIC Educational Resources Information Center

Gjoka, Mina

2010-01-01

In recent years, the popularity of online social networks (OSN) has risen to unprecedented levels, with the most popular ones having hundreds of millions of users. This success has generated interest within the networking community and has given rise to a number of measurement and characterization studies, which provide a first step towards their…

A Study of the Predictive Relationship between Online Social Presence and ONLE Interaction

ERIC Educational Resources Information Center

Tu, Chih-Hsiung; Yen, Cherng-Jyh; Blocher, J. Michael; Chan, Junn-Yih

2012-01-01

Open Network Learning Environments (ONLE) are online networks that afford learners the opportunity to participate in creative content endeavors, personalized identity projections, networked mechanism management, and effective collaborative community integration by applying Web 2.0 tools in open environments. It supports social interaction by…

Linking Online and Offline Social Worlds: Opportunities and Threats

ERIC Educational Resources Information Center

Dong, Cailing

2017-01-01

Social networks bring both opportunities and threats to the users. On one hand, social networks provide a platform for users to build online profiles, make connections with others beyond geographical boundaries, enjoy the "openness" of social networks to meet their intrinsic need of "self-presentation", explore and strengthen…

Online network of subspecialty aortic disease experts: Impact of "cloud" technology on management of acute aortic emergencies.

PubMed

Schoenhagen, Paul; Roselli, Eric E; Harris, C Martin; Eagleton, Matthew; Menon, Venu

2016-07-01

For the management of acute aortic syndromes, regional treatment networks have been established to coordinate diagnosis and treatment between local emergency rooms and central specialized centers. Triage of acute aortic syndromes requires definitive imaging, resulting in complex data files. Modern information technology network structures, specifically "cloud" technology, coupled with mobile communication, increasingly support sharing of these data in a network of experts using mobile, online access and communication. Although this network is technically complex, the potential benefit of online sharing of data files between professionals at multiple locations within a treatment network appear obvious; however, clinical experience is limited, and further evaluation is needed. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Use of behavioral biometrics in intrusion detection and online gaming

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2006-04-01

Behavior based intrusion detection is a frequently used approach for insuring network security. We expend behavior based intrusion detection approach to a new domain of game networks. Specifically, our research shows that a unique behavioral biometric can be generated based on the strategy used by an individual to play a game. We wrote software capable of automatically extracting behavioral profiles for each player in a game of Poker. Once a behavioral signature is generated for a player, it is continuously compared against player's current actions. Any significant deviations in behavior are reported to the game server administrator as potential security breaches. Our algorithm addresses a well-known problem of user verification and can be re-applied to the fields beyond game networks, such as operating systems and non-game networks security.

Online support and education for dementia caregivers: overview, utilization, and initial program evaluation.

PubMed

Glueckauf, Robert L; Ketterson, Timothy U; Loomis, Jeffrey S; Dages, Pat

2004-01-01

Family caregivers of older adults with progressive dementia (e.g., Alzheimer's disease) are confronted with a variety of challenges in providing assistance to their loved ones, such as dealing with persistent, repetitive questions, managing episodes of agitation and aggressive responding, as well as monitoring hygiene and self-care activities. Although professional and governmental organizations have called for the creation of community-based education and support programs, a significant proportion of dementia caregivers in the United States continue to receive little or no formal instruction in responding effectively to these anxiety-provoking situations. This paper describes the development and implementation of Alzheimer's Caregiver Support Online (also known as AlzOnline), an Internet- and telephone-based education and support network for caregivers of individuals with progressive dementia. An outcome analysis of a Robert Wood Johnson Foundation-funded strategic marketing initiative to promote the use of AlzOnline is reviewed, followed by a presentation of the findings of an initial program evaluation. Finally, future directions for online caregiver evaluation research are proposed.

Comparing the use of an online expert health network against common information sources to answer health questions.

PubMed

Rhebergen, Martijn D F; Lenderink, Annet F; van Dijk, Frank J H; Hulshof, Carel T J

2012-02-02

Many workers have questions about occupational safety and health (OSH). It is unknown whether workers are able to find correct, evidence-based answers to OSH questions when they use common information sources, such as websites, or whether they would benefit from using an easily accessible, free-of-charge online network of OSH experts providing advice. To assess the rate of correct, evidence-based answers to OSH questions in a group of workers who used an online network of OSH experts (intervention group) compared with a group of workers who used common information sources (control group). In a quasi-experimental study, workers in the intervention and control groups were randomly offered 2 questions from a pool of 16 standardized OSH questions. Both questions were sent by mail to all participants, who had 3 weeks to answer them. The intervention group was instructed to use only the online network ArboAntwoord, a network of about 80 OSH experts, to solve the questions. The control group was instructed that they could use all information sources available to them. To assess answer correctness as the main study outcome, 16 standardized correct model answers were constructed with the help of reviewers who performed literature searches. Subsequently, the answers provided by all participants in the intervention (n = 94 answers) and control groups (n = 124 answers) were blinded and compared with the correct model answers on the degree of correctness. Of the 94 answers given by participants in the intervention group, 58 were correct (62%), compared with 24 of the 124 answers (19%) in the control group, who mainly used informational websites found via Google. The difference between the 2 groups was significant (rate difference = 43%, 95% confidence interval [CI] 30%-54%). Additional analysis showed that the rate of correct main conclusions of the answers was 85 of 94 answers (90%) in the intervention group and 75 of 124 answers (61%) in the control group (rate difference = 29%, 95% CI 19%-40%). Remarkably, we could not identify differences between workers who provided correct answers and workers who did not on how they experienced the credibility, completeness, and applicability of the information found (P > .05). Workers are often unable to find correct answers to OSH questions when using common information sources, generally informational websites. Because workers frequently misjudge the quality of the information they find, other strategies are required to assist workers in finding correct answers. Expert advice provided through an online expert network can be effective for this purpose. As many people experience difficulties in finding correct answers to their health questions, expert networks may be an attractive new source of information for health fields in general.

Comparing the Use of an Online Expert Health Network against Common Information Sources to Answer Health Questions

PubMed Central

Lenderink, Annet F; van Dijk, Frank JH; Hulshof, Carel TJ

2012-01-01

Background Many workers have questions about occupational safety and health (OSH). It is unknown whether workers are able to find correct, evidence-based answers to OSH questions when they use common information sources, such as websites, or whether they would benefit from using an easily accessible, free-of-charge online network of OSH experts providing advice. Objective To assess the rate of correct, evidence-based answers to OSH questions in a group of workers who used an online network of OSH experts (intervention group) compared with a group of workers who used common information sources (control group). Methods In a quasi-experimental study, workers in the intervention and control groups were randomly offered 2 questions from a pool of 16 standardized OSH questions. Both questions were sent by mail to all participants, who had 3 weeks to answer them. The intervention group was instructed to use only the online network ArboAntwoord, a network of about 80 OSH experts, to solve the questions. The control group was instructed that they could use all information sources available to them. To assess answer correctness as the main study outcome, 16 standardized correct model answers were constructed with the help of reviewers who performed literature searches. Subsequently, the answers provided by all participants in the intervention (n = 94 answers) and control groups (n = 124 answers) were blinded and compared with the correct model answers on the degree of correctness. Results Of the 94 answers given by participants in the intervention group, 58 were correct (62%), compared with 24 of the 124 answers (19%) in the control group, who mainly used informational websites found via Google. The difference between the 2 groups was significant (rate difference = 43%, 95% confidence interval [CI] 30%–54%). Additional analysis showed that the rate of correct main conclusions of the answers was 85 of 94 answers (90%) in the intervention group and 75 of 124 answers (61%) in the control group (rate difference = 29%, 95% CI 19%–40%). Remarkably, we could not identify differences between workers who provided correct answers and workers who did not on how they experienced the credibility, completeness, and applicability of the information found (P > .05). Conclusions Workers are often unable to find correct answers to OSH questions when using common information sources, generally informational websites. Because workers frequently misjudge the quality of the information they find, other strategies are required to assist workers in finding correct answers. Expert advice provided through an online expert network can be effective for this purpose. As many people experience difficulties in finding correct answers to their health questions, expert networks may be an attractive new source of information for health fields in general. PMID:22356848

Rumor spreading in online social networks by considering the bipolar social reinforcement

NASA Astrophysics Data System (ADS)

Ma, Jing; Li, Dandan; Tian, Zihao

2016-04-01

Considering the bipolar social reinforcement which includes positive and negative effects, in this paper we explore the rumor spreading dynamics in online social networks. By means of the generation function and cavity method developed from statistical physics of disordered system, the rumor spreading threshold can be theoretically drawn. Simulation results indicate that decreasing the positive reinforcement factor or increasing the negative reinforcement factor can suppress the rumor spreading effectively. By analyzing the topological properties of the real world social network, we find that the nodes with lower degree usually have smaller weight. However, the nodes with lower degree may have larger k-shell. In order to curb rumor spreading, some control strategies that are based on the nodes' degree, k-shell and weight are presented. By comparison, we show that controlling those nodes that have larger degree or weight are two effective strategies to prevent the rumor spreading.

A secure file manager for UNIX

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

DeVries, R.G.

1990-12-31

The development of a secure file management system for a UNIX-based computer facility with supercomputers and workstations is described. Specifically, UNIX in its usual form does not address: (1) Operation which would satisfy rigorous security requirements. (2) Online space management in an environment where total data demands would be many times the actual online capacity. (3) Making the file management system part of a computer network in which users of any computer in the local network could retrieve data generated on any other computer in the network. The characteristics of UNIX can be exploited to develop a portable, secure filemore » manager which would operate on computer systems ranging from workstations to supercomputers. Implementation considerations making unusual use of UNIX features, rather than requiring extensive internal system changes, are described, and implementation using the Cray Research Inc. UNICOS operating system is outlined.« less

Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network

PubMed Central

Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui

2012-01-01

This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. PMID:22778587

Tracking cohesive subgroups over time in inferred social networks

NASA Astrophysics Data System (ADS)

Chin, Alvin; Chignell, Mark; Wang, Hao

2010-04-01

As a first step in the development of community trackers for large-scale online interaction, this paper shows how cohesive subgroup analysis using the Social Cohesion Analysis of Networks (SCAN; Chin and Chignell 2008) and Data-Intensive Socially Similar Evolving Community Tracker (DISSECT; Chin and Chignell 2010) methods can be applied to the problem of identifying cohesive subgroups and tracking them over time. Three case studies are reported, and the findings are used to evaluate how well the SCAN and DISSECT methods work for different types of data. In the largest of the case studies, variations in temporal cohesiveness are identified across a set of subgroups extracted from the inferred social network. Further modifications to the DISSECT methodology are suggested based on the results obtained. The paper concludes with recommendations concerning further research that would be beneficial in addressing the community tracking problem for online data.

Do online social media cut through the constraints that limit the size of offline social networks?

PubMed Central

Dunbar, R. I. M.

2016-01-01

The social brain hypothesis has suggested that natural social network sizes may have a characteristic size in humans. This is determined in part by cognitive constraints and in part by the time costs of servicing relationships. Online social networking offers the potential to break through the glass ceiling imposed by at least the second of these, potentially enabling us to maintain much larger social networks. This is tested using two separate UK surveys, each randomly stratified by age, gender and regional population size. The data show that the size and range of online egocentric social networks, indexed as the number of Facebook friends, is similar to that of offline face-to-face networks. For one sample, respondents also specified the number of individuals in the inner layers of their network (formally identified as support clique and sympathy group), and these were also similar in size to those observed in offline networks. This suggests that, as originally proposed by the social brain hypothesis, there is a cognitive constraint on the size of social networks that even the communication advantages of online media are unable to overcome. In practical terms, it may reflect the fact that real (as opposed to casual) relationships require at least occasional face-to-face interaction to maintain them. PMID:26909163

Do online social media cut through the constraints that limit the size of offline social networks?

PubMed

Dunbar, R I M

2016-01-01

The social brain hypothesis has suggested that natural social network sizes may have a characteristic size in humans. This is determined in part by cognitive constraints and in part by the time costs of servicing relationships. Online social networking offers the potential to break through the glass ceiling imposed by at least the second of these, potentially enabling us to maintain much larger social networks. This is tested using two separate UK surveys, each randomly stratified by age, gender and regional population size. The data show that the size and range of online egocentric social networks, indexed as the number of Facebook friends, is similar to that of offline face-to-face networks. For one sample, respondents also specified the number of individuals in the inner layers of their network (formally identified as support clique and sympathy group), and these were also similar in size to those observed in offline networks. This suggests that, as originally proposed by the social brain hypothesis, there is a cognitive constraint on the size of social networks that even the communication advantages of online media are unable to overcome. In practical terms, it may reflect the fact that real (as opposed to casual) relationships require at least occasional face-to-face interaction to maintain them.

Technology use and reasons to participate in social networking health websites among people living with HIV in the US.

PubMed

Horvath, Keith J; Danilenko, Gene P; Williams, Mark L; Simoni, Jane; Amico, K Rivet; Oakes, J Michael; Simon Rosser, B R

2012-05-01

Online social media and mobile technologies hold potential to enhance adherence to antiretroviral therapy (ART), although little is known about the current use of these technologies among people living with HIV (PLWH). To address this gap in understanding, 312 PLWH (84% male, 69% White) US adults completed an online survey in 2009, from which 22 persons accepted an invitation to participate in one of two online focus groups. Results showed that 76% of participants with lower ART adherence used social networking websites/features at least once a week. Their ideal online social networking health websites included one that facilitated socializing with others (45% of participants) and ones with relevant HIV informational content (22%), although privacy was a barrier to use (26%). Texting (81%), and to a lesser extent mobile web-access (51%), was widely used among participants. Results support the potential reach of online social networking and text messaging intervention approaches.

Cascaded deep decision networks for classification of endoscopic images

NASA Astrophysics Data System (ADS)

Murthy, Venkatesh N.; Singh, Vivek; Sun, Shanhui; Bhattacharya, Subhabrata; Chen, Terrence; Comaniciu, Dorin

2017-02-01

Both traditional and wireless capsule endoscopes can generate tens of thousands of images for each patient. It is desirable to have the majority of irrelevant images filtered out by automatic algorithms during an offline review process or to have automatic indication for highly suspicious areas during an online guidance. This also applies to the newly invented endomicroscopy, where online indication of tumor classification plays a significant role. Image classification is a standard pattern recognition problem and is well studied in the literature. However, performance on the challenging endoscopic images still has room for improvement. In this paper, we present a novel Cascaded Deep Decision Network (CDDN) to improve image classification performance over standard Deep neural network based methods. During the learning phase, CDDN automatically builds a network which discards samples that are classified with high confidence scores by a previously trained network and concentrates only on the challenging samples which would be handled by the subsequent expert shallow networks. We validate CDDN using two different types of endoscopic imaging, which includes a polyp classification dataset and a tumor classification dataset. From both datasets we show that CDDN can outperform other methods by about 10%. In addition, CDDN can also be applied to other image classification problems.

Developing an online professional network for veterinary education: the NOVICE project.

PubMed

Baillie, Sarah; Kinnison, Tierney; Forrest, Neil; Dale, Vicki H M; Ehlers, Jan P; Koch, Michael; Mándoki, Mira; Ciobotaru, Emilia; de Groot, Esther; Boerboom, Tobias B B; van Beukelen, Peter

2011-01-01

An online professional network for veterinarians, veterinary students, veterinary educationalists, and ICT (Information and Communication Technology) educationalists is being developed under the EU (European Union) Lifelong Learning Programme. The network uses Web 2.0, a term used to describe the new, more interactive version of the Internet, and includes tools such as wikis, blogs, and discussion boards. Focus groups conducted with qualified and student veterinarians within the project's five founding countries (The Netherlands, Germany, United Kingdom, Hungary, Romania) demonstrated that online professional communities can be valuable for accessing information and establishing contacts. Online networks have the potential to overcome common challenges to face-to-face communities-such as distance, cost, and timing-but they have their own drawbacks, such as security and professionalism issues. The Network Of Veterinary ICt in Education (NOVICE) was developed using Elgg, an open-source, free social networking platform, after several software options had been considered. NOVICE aims to promote the understanding of Web 2.0, confidence to use social software tools, and participation in an online community. Therefore, the Web site contains help sections, Frequently Asked Questions, and access to support from ICT experts. Five months after the network's launch (and just over one year into the project) 515 members from 28 countries had registered. Further research will include analysis of a core group's activities, which will inform ongoing support for and development of informal, lifelong learning in a veterinary context.

Exploring the presentation of HPV information online: A semantic network analysis of websites.

PubMed

Ruiz, Jeanette B; Barnett, George A

2015-06-26

Negative vaccination-related information online leads some to opt out of recommended vaccinations. To determine how HPV vaccine information is presented online and what concepts co-occur. A semantic network analysis of the words in first-page Google search results was conducted using three negative, three neutral, and three positive search terms for 10 base concepts such as HPV vaccine, and HPV immunizations. In total, 223 of the 300 websites retrieved met inclusion requirements. Website information was analyzed using network statistics to determine what words most frequently appear, which words co-occur, and the sentiment of the words. High levels of word interconnectivity were found suggesting a rich set of semantic links and a very integrated set of concepts. Limited number of words held centrality indicating limited concept prominence. This dense network signifies concepts that are well connected. Negative words were most prevalent and were associated with describing the HPV vaccine's side-effects as well as the negative effects of HPV and cervical cancer. A smaller cluster focuses on reporting negative vaccine side-effects. Clustering shows the words women and girls closely located to the words sexually, virus, and infection. Information about the HPV vaccine online centered on a limited number of concepts. HPV vaccine benefits as well as the risks of HPV, including severity and susceptibility, were centrally presented. Word cluster results imply that HPV vaccine information for women and girls is discussed in more sexual terms than for men and boys. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Online Life Like Any Other: Identity, Self-Determination, and Social Networking Among Adults with Intellectual Disabilities.

PubMed

Chadwick, Darren D; Fullwood, Chris

2018-01-01

Research focusing on online identity and the personal experiences of adults with intellectual disabilities (ID) is currently limited. Eleven adults with ID were interviewed regarding personal experiences of being online and using social media. Data were analyzed qualitatively using thematic network analysis. Two global themes, online relatedness and sharing and online agency and support, highlighted the positive potential of social media in enabling the development and maintenance of social bonds, valued social roles, and feelings of enjoyment, competence, autonomy, and self-worth. Participants reported sharing various expressed online identities that did not focus on or hide impairment, challenging notions of dependency, with participants both providing support and being supported online.

Study on feed forward neural network convex optimization for LiFePO4 battery parameters

NASA Astrophysics Data System (ADS)

Liu, Xuepeng; Zhao, Dongmei

2017-08-01

Based on the modern facility agriculture automatic walking equipment LiFePO4 Battery, the parameter identification of LiFePO4 Battery is analyzed. An improved method for the process model of li battery is proposed, and the on-line estimation algorithm is presented. The parameters of the battery are identified using feed forward network neural convex optimization algorithm.

Host-Based Systemic Network Obfuscation System for Windows

DTIC Science & Technology

2011-06-01

speed, CPU speed, and memory size. These additional parameters are control variables and do not change throughout the experiment. The applications...physical median that passes the network traffic, such as a wireless signal or Ethernet cable and does not need obfuscation. The colored layers in Figure...Gul09] Ron Gula, “ Enchanced Operating System Identification with Nessus.” [Online]. Available: http://blog.tenablesecurity.com/2009/02

Neural-network-based online HJB solution for optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems.

PubMed

Liu, Derong; Wang, Ding; Wang, Fei-Yue; Li, Hongliang; Yang, Xiong

2014-12-01

In this paper, the infinite horizon optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems is investigated using neural-network-based online solution of Hamilton-Jacobi-Bellman (HJB) equation. By establishing an appropriate bounded function and defining a modified cost function, the optimal robust guaranteed cost control problem is transformed into an optimal control problem. It can be observed that the optimal cost function of the nominal system is nothing but the optimal guaranteed cost of the original uncertain system. A critic neural network is constructed to facilitate the solution of the modified HJB equation corresponding to the nominal system. More importantly, an additional stabilizing term is introduced for helping to verify the stability, which reinforces the updating process of the weight vector and reduces the requirement of an initial stabilizing control. The uniform ultimate boundedness of the closed-loop system is analyzed by using the Lyapunov approach as well. Two simulation examples are provided to verify the effectiveness of the present control approach.

Banking on the Internet.

ERIC Educational Resources Information Center

Internet Research, 1996

1996-01-01

Electronic ground was broken in 1995 with the development of the completely Internet-based bank Security First Network Bank. This article discusses the need for developing online services, outlines the reasons for the formation of an Internet-based bank and argues that to remain competitive financial services providers must provide easier customer…

User recommendation in healthcare social media by assessing user similarity in heterogeneous network.

PubMed

Jiang, Ling; Yang, Christopher C

2017-09-01

The rapid growth of online health social websites has captured a vast amount of healthcare information and made the information easy to access for health consumers. E-patients often use these social websites for informational and emotional support. However, health consumers could be easily overwhelmed by the overloaded information. Healthcare information searching can be very difficult for consumers, not to mention most of them are not skilled information searcher. In this work, we investigate the approaches for measuring user similarity in online health social websites. By recommending similar users to consumers, we can help them to seek informational and emotional support in a more efficient way. We propose to represent the healthcare social media data as a heterogeneous healthcare information network and introduce the local and global structural approaches for measuring user similarity in a heterogeneous network. We compare the proposed structural approaches with the content-based approach. Experiments were conducted on a dataset collected from a popular online health social website, and the results showed that content-based approach performed better for inactive users, while structural approaches performed better for active users. Moreover, global structural approach outperformed local structural approach for all user groups. In addition, we conducted experiments on local and global structural approaches using different weight schemas for the edges in the network. Leverage performed the best for both local and global approaches. Finally, we integrated different approaches and demonstrated that hybrid method yielded better performance than the individual approach. The results indicate that content-based methods can effectively capture the similarity of inactive users who usually have focused interests, while structural methods can achieve better performance when rich structural information is available. Local structural approach only considers direct connections between nodes in the network, while global structural approach takes the indirect connections into account. Therefore, the global similarity approach can deal with sparse networks and capture the implicit similarity between two users. Different approaches may capture different aspects of the similarity relationship between two users. When we combine different methods together, we could achieve a better performance than using each individual method. Copyright © 2017 Elsevier B.V. All rights reserved.

Adolescents' and Emerging Adults' Social Networking Online: Homophily or Diversity?

ERIC Educational Resources Information Center

Mazur, Elizabeth; Richards, Lacey

2011-01-01

More than half of all online American adolescents and emerging adults have created personal profiles for social networking on the Internet. Does homophily in their offline friendships extend online? Drawing mainly on research of face-to-face friendship, we collected data from the public spaces, called "walls," of 129 young Americans ages 16 to 19…

Online Social Networks as Formal Learning Environments: Learner Experiences and Activities

ERIC Educational Resources Information Center

Veletsianos, George; Navarrete, Cesar C.

2012-01-01

While the potential of social networking sites to contribute to educational endeavors is highlighted by researchers and practitioners alike, empirical evidence on the use of such sites for formal online learning is scant. To fill this gap in the literature, we present a case study of learners' perspectives and experiences in an online course…

Social Networking Sites and Contact Risks among Flemish Youth

ERIC Educational Resources Information Center

Vandoninck, Sofie; d'Haenens, Leen; De Cock, Rozane; Donoso, Veronica

2012-01-01

This study investigates how teenagers use social networking sites (SNS) and other online communication applications, to what extent they are exposed to online contact risks related to the use of these online tools and how they cope with these risks. A written survey was administered among 815 Flemish adolescents aged 14-19. The study controls for…

The Structure and Characteristics of #PhDChat, an Emergent Online Social Network

ERIC Educational Resources Information Center

Ford, Kasey C.; Veletsianos, George; Resta, Paul

2014-01-01

#PhDChat is an online network of individuals that has its roots to a group of UK doctoral students who began using Twitter in 2010 to hold discussions. Since then, the network around #PhDchat has evolved and grown. In this study, we examine this network using a mixed methods analysis of the tweets that were labeled with the hashtag over a…

Information jet: Handling noisy big data from weakly disconnected network

NASA Astrophysics Data System (ADS)

Aurongzeb, Deeder

Sudden aggregation (information jet) of large amount of data is ubiquitous around connected social networks, driven by sudden interacting and non-interacting events, network security threat attacks, online sales channel etc. Clustering of information jet based on time series analysis and graph theory is not new but little work is done to connect them with particle jet statistics. We show pre-clustering based on context can element soft network or network of information which is critical to minimize time to calculate results from noisy big data. We show difference between, stochastic gradient boosting and time series-graph clustering. For disconnected higher dimensional information jet, we use Kallenberg representation theorem (Kallenberg, 2005, arXiv:1401.1137) to identify and eliminate jet similarities from dense or sparse graph.

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

PubMed Central

Gutierrez-Villalobos, Jose M.; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A.; Martínez-Hernández, Moisés A.

2015-01-01

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor. PMID:26131677

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

PubMed

Gutierrez-Villalobos, Jose M; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A; Martínez-Hernández, Moisés A

2015-06-29

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

Estimation of tool wear during CNC milling using neural network-based sensor fusion

NASA Astrophysics Data System (ADS)

Ghosh, N.; Ravi, Y. B.; Patra, A.; Mukhopadhyay, S.; Paul, S.; Mohanty, A. R.; Chattopadhyay, A. B.

2007-01-01

Cutting tool wear degrades the product quality in manufacturing processes. Monitoring tool wear value online is therefore needed to prevent degradation in machining quality. Unfortunately there is no direct way of measuring the tool wear online. Therefore one has to adopt an indirect method wherein the tool wear is estimated from several sensors measuring related process variables. In this work, a neural network-based sensor fusion model has been developed for tool condition monitoring (TCM). Features extracted from a number of machining zone signals, namely cutting forces, spindle vibration, spindle current, and sound pressure level have been fused to estimate the average flank wear of the main cutting edge. Novel strategies such as, signal level segmentation for temporal registration, feature space filtering, outlier removal, and estimation space filtering have been proposed. The proposed approach has been validated by both laboratory and industrial implementations.

A mixing evolution model for bidirectional microblog user networks

NASA Astrophysics Data System (ADS)

Yuan, Wei-Guo; Liu, Yun

2015-08-01

Microblogs have been widely used as a new form of online social networking. Based on the user profile data collected from Sina Weibo, we find that the number of microblog user bidirectional friends approximately corresponds with the lognormal distribution. We then build two microblog user networks with real bidirectional relationships, both of which have not only small-world and scale-free but also some special properties, such as double power-law degree distribution, disassortative network, hierarchical and rich-club structure. Moreover, by detecting the community structures of the two real networks, we find both of their community scales follow an exponential distribution. Based on the empirical analysis, we present a novel evolution network model with mixed connection rules, including lognormal fitness preferential and random attachment, nearest neighbor interconnected in the same community, and global random associations in different communities. The simulation results show that our model is consistent with real network in many topology features.

Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants

PubMed Central

Hogan, Bernie; Melville, Joshua R.; Philips, Gregory Lee; Janulis, Patrick; Contractor, Noshir; Mustanski, Brian S.; Birkett, Michelle

2016-01-01

While much social network data exists online, key network metrics for high-risk populations must still be captured through self-report. This practice has suffered from numerous limitations in workflow and response burden. However, advances in technology, network drawing libraries and databases are making interactive network drawing increasingly feasible. We describe the translation of an analog-based technique for capturing personal networks into a digital framework termed netCanvas that addresses many existing shortcomings such as: 1) complex data entry; 2) extensive interviewer intervention and field setup; 3) difficulties in data reuse; and 4) a lack of dynamic visualizations. We test this implementation within a health behavior study of a high-risk and difficult-to-reach population. We provide a within–subjects comparison between paper and touchscreens. We assert that touchscreen-based social network capture is now a viable alternative for highly sensitive data and social network data entry tasks. PMID:28018995

Are the users of social networking sites homogeneous? A cross-cultural study.

PubMed

Alarcón-Del-Amo, María-Del-Carmen; Gómez-Borja, Miguel-Ángel; Lorenzo-Romero, Carlota

2015-01-01

The growing use of Social Networking Sites (SNS) around the world has made it necessary to understand individuals' behaviors within these sites according to different cultures. Based on a comparative study between two different European countries (The Netherlands versus Spain), a comparison of typologies of networked Internet users has been obtained through a latent segmentation approach. These typologies are based on the frequency with which users perform different activities, their socio-demographic variables, and experience in social networking and interaction patterns. The findings show new insights regarding international segmentation in order to analyse SNS user behaviors in both countries. These results are relevant for marketing strategists eager to use the communication potential of networked individuals and for marketers willing to explore the potential of online networking as a low cost and a highly efficient alternative to traditional networking approaches. For most businesses, expert users could be valuable opinion leaders and potential brand influencers.

Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants.

PubMed

Hogan, Bernie; Melville, Joshua R; Philips, Gregory Lee; Janulis, Patrick; Contractor, Noshir; Mustanski, Brian S; Birkett, Michelle

2016-05-01

While much social network data exists online, key network metrics for high-risk populations must still be captured through self-report. This practice has suffered from numerous limitations in workflow and response burden. However, advances in technology, network drawing libraries and databases are making interactive network drawing increasingly feasible. We describe the translation of an analog-based technique for capturing personal networks into a digital framework termed netCanvas that addresses many existing shortcomings such as: 1) complex data entry; 2) extensive interviewer intervention and field setup; 3) difficulties in data reuse; and 4) a lack of dynamic visualizations. We test this implementation within a health behavior study of a high-risk and difficult-to-reach population. We provide a within-subjects comparison between paper and touchscreens. We assert that touchscreen-based social network capture is now a viable alternative for highly sensitive data and social network data entry tasks.

Are the users of social networking sites homogeneous? A cross-cultural study

PubMed Central

Alarcón-del-Amo, María-del-Carmen; Gómez-Borja, Miguel-Ángel; Lorenzo-Romero, Carlota

2015-01-01

The growing use of Social Networking Sites (SNS) around the world has made it necessary to understand individuals' behaviors within these sites according to different cultures. Based on a comparative study between two different European countries (The Netherlands versus Spain), a comparison of typologies of networked Internet users has been obtained through a latent segmentation approach. These typologies are based on the frequency with which users perform different activities, their socio-demographic variables, and experience in social networking and interaction patterns. The findings show new insights regarding international segmentation in order to analyse SNS user behaviors in both countries. These results are relevant for marketing strategists eager to use the communication potential of networked individuals and for marketers willing to explore the potential of online networking as a low cost and a highly efficient alternative to traditional networking approaches. For most businesses, expert users could be valuable opinion leaders and potential brand influencers. PMID:26321971

Community water fluoridation online: an analysis of the digital media ecosystem.

PubMed

Helmi, Mohammad; Spinella, Mary Kate; Seymour, Brittany

2018-03-30

Research demonstrates the safety and efficacy of community water fluoridation (CWF). Yet, the digitization of communication has triggered the spread of inaccurate information online. The purpose of this study was to analyze patterns of CWF information dissemination by a network of sources on the web. We used Media Cloud, a searchable big data platform of over 550 million stories from 50 thousand sources, along with tools to analyze that archive. We generated a network of fluoridation publishers using Media Cloud's keyword identification from August 1, 2015 to July 31, 2016. We defined the media type and sentiment toward CWF for each source and generated a network map of the most influential sources during our study period based on hyperlinking activity. Media Cloud detected a total of 980 stories from 325 different sources related to water fluoridation. We identified nine different media types participating in the dissemination of information: academic, government, scientific group, natural medicine, blogs, mainstream media, advocacy groups, user-generated (e.g., YouTube), and "other." We detected five sub-networks within the overall fluoridation network map, each with its own characteristics. Twenty-one percent of sources were pro-fluoridation, receiving 57 percent of all inlinks, 22 percent of sources were anti-fluoridation, and the rest were neutral (54 percent). The dominant neutral sentiment of the network may signify that anti- and pro-sides of the debate are viewed as balanced, not just in number but also in quality of information. Despite high inlinks to pro-sources, anti-fluoridation sentiment maintains influence online. © 2018 American Association of Public Health Dentistry.

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

Abercrombie, Robert K; Udoeyop, Akaninyene W; Schlicher, Bob G

This work examines a scientometric model that tracks the emergence of an identified technology from initial discovery (via original scientific and conference literature), through critical discoveries (via original scientific, conference literature and patents), transitioning through Technology Readiness Levels (TRLs) and ultimately on to commercial application. During the period of innovation and technology transfer, the impact of scholarly works, patents and on-line web news sources are identified. As trends develop, currency of citations, collaboration indicators, and on-line news patterns are identified. The combinations of four distinct and separate searchable on-line networked sources (i.e., scholarly publications and citation, patents, news archives, andmore » online mapping networks) are assembled to become one collective network (a dataset for analysis of relations). This established network becomes the basis from which to quickly analyze the temporal flow of activity (searchable events) for the example subject domain we investigated.« less

Community Structure in Online Collegiate Social Networks

NASA Astrophysics Data System (ADS)

Traud, Amanda; Kelsic, Eric; Mucha, Peter; Porter, Mason

2009-03-01

Online social networking sites have become increasingly popular with college students. The networks we studied are defined through ``friendships'' indicated by Facebook users from UNC, Oklahoma, Caltech, Georgetown, and Princeton. We apply the tools of network science to study the Facebook networks from these five different universities at a single point in time. We investigate each single-institution network's community structure, which we obtain through partitioning the graph using an eigenvector method. We use both graphical and quantitative tools, including pair-counting methods, which we interpret through statistical analysis and permutation tests to measure the correlations between the network communities and a set of characteristics given by each user (residence, class year, major, and high school). We also analyze the single gender subsets of these networks, and the impact of missing demographical data. Our study allows us to compare the online social networks for the five schools as well as infer differences in offline social interactions. At the schools studied, we were able to define which characteristics of the Facebook users correlate best with friendships.

Do online gossipers promote brands?

PubMed

Okazaki, Shintaro; Rubio, Natalia; Campo, Sara

2013-02-01

Online gossip has been recognized as small talk on social networking sites (SNSs) that influences consumer behavior, but little attention has been paid to its role. This study makes three theoretical predictions: (a) propensity to gossip online leads to greater information value, entertainment value, and friendship value; (b) upon exposure to a high-involvement product, online gossipers are more willing to spread such information through electronic word-of-mouth (eWOM) in search of prestige or fame as a knowledge expert; and (c) this tendency will be more pronounced when they are connected with strong ties (rather than weak ties) and belong to a large network (rather than a small network). An experimental survey was conducted with a scenario method. In total, 818 general consumers participated in the survey. A multivariate analysis of variance (ANOVA) provides empirical support for prediction (1). With regard to predictions (2) and (3), a series of three-way and two-way between-subjective ANOVAs were performed. When a high-involvement product is promoted, gossipers, rather than nongossipers, are more willing to participate in eWOM on an SNS. Furthermore, a significant interaction effect indicates that online gossipers' willingness to particiapte in eWOM would be more pronounced if they belonged to a large network rather than a small network. However, when a low-involvement product is promoted, no interaction effect is found between online gossip and network size. In closing, theoretical and managerial implications are discussed, while important limitations are recognized.

Do Online Gossipers Promote Brands?

PubMed Central

Rubio, Natalia; Campo, Sara

2013-01-01

Abstract Online gossip has been recognized as small talk on social networking sites (SNSs) that influences consumer behavior, but little attention has been paid to its role. This study makes three theoretical predictions: (a) propensity to gossip online leads to greater information value, entertainment value, and friendship value; (b) upon exposure to a high-involvement product, online gossipers are more willing to spread such information through electronic word-of-mouth (eWOM) in search of prestige or fame as a knowledge expert; and (c) this tendency will be more pronounced when they are connected with strong ties (rather than weak ties) and belong to a large network (rather than a small network). An experimental survey was conducted with a scenario method. In total, 818 general consumers participated in the survey. A multivariate analysis of variance (ANOVA) provides empirical support for prediction (1). With regard to predictions (2) and (3), a series of three-way and two-way between-subjective ANOVAs were performed. When a high-involvement product is promoted, gossipers, rather than nongossipers, are more willing to participate in eWOM on an SNS. Furthermore, a significant interaction effect indicates that online gossipers' willingness to particiapte in eWOM would be more pronounced if they belonged to a large network rather than a small network. However, when a low-involvement product is promoted, no interaction effect is found between online gossip and network size. In closing, theoretical and managerial implications are discussed, while important limitations are recognized. PMID:23276259

Friending, IMing, and hanging out face-to-face: overlap in adolescents' online and offline social networks.

PubMed

Reich, Stephanie M; Subrahmanyam, Kaveri; Espinoza, Guadalupe

2012-03-01

Many new and important developmental issues are encountered during adolescence, which is also a time when Internet use becomes increasingly popular. Studies have shown that adolescents are using these online spaces to address developmental issues, especially needs for intimacy and connection to others. Online communication with its potential for interacting with unknown others, may put teens at increased risk. Two hundred and fifty-one high school students completed an in-person survey, and 126 of these completed an additional online questionnaire about how and why they use the Internet, their activities on social networking sites (e.g., Facebook, MySpace) and their reasons for participation, and how they perceive these online spaces to impact their friendships. To examine the extent of overlap between online and offline friends, participants were asked to list the names of their top interaction partners offline and online (Facebook and instant messaging). Results reveal that adolescents mainly use social networking sites to connect with others, in particular with people known from offline contexts. While adolescents report little monitoring by their parents, there was no evidence that teens are putting themselves at risk by interacting with unknown others. Instead, adolescents seem to use the Internet, especially social networking sites, to connect with known others. While the study found moderate overlap between teens' closest online and offline friends, the patterns suggest that adolescents use online contexts to strengthen offline relationships. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Semantic Social Network Portal for Collaborative Online Communities

ERIC Educational Resources Information Center

Neumann, Marco; O'Murchu, Ina; Breslin, John; Decker, Stefan; Hogan, Deirdre; MacDonaill, Ciaran

2005-01-01

Purpose: The motivation for this investigation is to apply social networking features to a semantic network portal, which supports the efforts in enterprise training units to up-skill the employee in the company, and facilitates the creation and reuse of knowledge in online communities. Design/methodology/approach: The paper provides an overview…

Spreading in online social networks: the role of social reinforcement.

PubMed

Zheng, Muhua; Lü, Linyuan; Zhao, Ming

2013-07-01

Some epidemic spreading models are usually applied to analyze the propagation of opinions or news. However, the dynamics of epidemic spreading and information or behavior spreading are essentially different in many aspects. Centola's experiments [Science 329, 1194 (2010)] on behavior spreading in online social networks showed that the spreading is faster and broader in regular networks than in random networks. This result contradicts with the former understanding that random networks are preferable for spreading than regular networks. To describe the spreading in online social networks, a unknown-known-approved-exhausted four-status model was proposed, which emphasizes the effect of social reinforcement and assumes that the redundant signals can improve the probability of approval (i.e., the spreading rate). Performing the model on regular and random networks, it is found that our model can well explain the results of Centola's experiments on behavior spreading and some former studies on information spreading in different parameter space. The effects of average degree and network size on behavior spreading process are further analyzed. The results again show the importance of social reinforcement and are accordant with Centola's anticipation that increasing the network size or decreasing the average degree will enlarge the difference of the density of final approved nodes between regular and random networks. Our work complements the former studies on spreading dynamics, especially the spreading in online social networks where the information usually requires individuals' confirmations before being transmitted to others.

Estimating User Influence in Online Social Networks Subject to Information Overload

NASA Astrophysics Data System (ADS)

Li, Pei; Sun, Yunchuan; Chen, Yingwen; Tian, Zhi

2014-11-01

Online social networks have attracted remarkable attention since they provide various approaches for hundreds of millions of people to stay connected with their friends. Due to the existence of information overload, the research on diffusion dynamics in epidemiology cannot be adopted directly to that in online social networks. In this paper, we consider diffusion dynamics in online social networks subject to information overload, and model the information-processing process of a user by a queue with a batch arrival and a finite buffer. We use the average number of times a message is processed after it is generated by a given user to characterize the user influence, which is then estimated through theoretical analysis for a given network. We validate the accuracy of our estimation by simulations, and apply the results to study the impacts of different factors on the user influence. Among the observations, we find that the impact of network size on the user influence is marginal while the user influence decreases with assortativity due to information overload, which is particularly interesting.

Medical students' online learning technology needs.

PubMed

Han, Heeyoung; Nelson, Erica; Wetter, Nathan

2014-02-01

This study investigated medical students' online learning technology needs at a medical school. The study aimed to provide evidence-based guidance for technology selection and online learning design in medical education. The authors developed a 120-item survey in collaboration with the New Technology in Medical Education (NTIME) committee at the Southern Illinois University School of Medicine (SIUSOM). Overall, 123 of 290 medical students (42%) at the medical school participated in the survey. The survey focused on five major areas: students' hardware and software use; perception of educational technology (ET) in general; online behaviours; perception of ET use at the school; and demographic information. Students perceived multimedia tools, scheduling tools, communication tools, collaborative authoring tools, learning management systems and electronic health records useful educational technologies for their learning. They did not consider social networking tools useful for their learning, despite their frequent use. Third-year students were less satisfied with current technology integration in the curriculum, information sharing and collaborative learning than other years. Students in clerkships perceived mobile devices as useful for their learning. Students using a mobile device (i.e. a smartphone) go online, text message, visit social networking sites and are online during classes more frequently than non-users. Medical students' ET needs differ between preclinical and clinical years. Technology supporting ubiquitous mobile learning and health information technology (HIT) systems at hospitals and out-patient clinics can be integrated into clerkship curricula. © 2014 John Wiley & Sons Ltd.

The Healthnet project: extending online information resources to end users in rural hospitals.

PubMed

Holtum, E; Zollo, S A

1998-10-01

The importance of easily available, high quality, and current biomedical literature within the clinical enterprise is now widely documented and accepted. Access to this information has been shown to have a direct bearing on diagnosis, choices of tests, choices of drugs, and length of hospital stay. However, many health professionals do not have adequate access to current health information, particularly those practicing in rural, isolated, or underserved hospitals. Thanks to a three-year telemedicine award from the National Library of Medicine, The University of Iowa (UI) has developed a high-speed, point-to-point telecommunications network to deliver clinical and educational applications to ten community-based Iowa hospitals. One of the services offered over the network allows health professionals from the site hospitals to access online health databases and order articles via an online document delivery service. Installation, training, and troubleshooting support are provided to the remote sites by UI project staff. To date, 1,339 health professionals from the ten networked hospitals have registered to use the Healthnet program. Despite the friendly interface on the computer workstations installed at the sites, training emerged as the key issue in maximizing health professional utilization of these programs.

The Healthnet project: extending online information resources to end users in rural hospitals.

PubMed Central

Holtum, E; Zollo, S A

1998-01-01

The importance of easily available, high quality, and current biomedical literature within the clinical enterprise is now widely documented and accepted. Access to this information has been shown to have a direct bearing on diagnosis, choices of tests, choices of drugs, and length of hospital stay. However, many health professionals do not have adequate access to current health information, particularly those practicing in rural, isolated, or underserved hospitals. Thanks to a three-year telemedicine award from the National Library of Medicine, The University of Iowa (UI) has developed a high-speed, point-to-point telecommunications network to deliver clinical and educational applications to ten community-based Iowa hospitals. One of the services offered over the network allows health professionals from the site hospitals to access online health databases and order articles via an online document delivery service. Installation, training, and troubleshooting support are provided to the remote sites by UI project staff. To date, 1,339 health professionals from the ten networked hospitals have registered to use the Healthnet program. Despite the friendly interface on the computer workstations installed at the sites, training emerged as the key issue in maximizing health professional utilization of these programs. PMID:9803302

Social Networking Technology Use and Engagement in HIV-Related Risk and Protective Behaviors Among Homeless Youth.

PubMed

Barman-Adhikari, Anamika; Rice, Eric; Bender, Kimberly; Lengnick-Hall, Rebecca; Yoshioka-Maxwell, Amanda; Rhoades, Harmony

2016-07-01

Preliminary studies with homeless youth have found surprisingly pervasive social media use and suggest that youth's online interactions may be associated with their HIV-related risk and protective behaviors. As homeless youth are transient and difficult to engage in place-based services, social media may represent a novel venue for intervention. A critical 1st step in intervention development is gaining greater understanding of how homeless youth use social media, especially as it relates to who they connect to and around what topics. Given the salience of social networking sites in the lives of these otherwise difficult-to-reach adolescents, and their potential to disseminate prevention interventions, this study assessed associations between online social networking technology use and HIV risk behaviors among homeless youth in Los Angeles, California. Homeless youth ages 13 through 24 (N = 1,046) were recruited through 3 drop-in centers and surveyed about their social media use and self-reported HIV-related risk behaviors. Results suggest that social media use is widely prevalent among this population, and the content of these online interactions is associated with whether youth engage in risk or protective behaviors. Implications for interventions and further research are discussed.

Social Networking Technology Use and Engagement in HIV Related Risk and Protective Behaviors among Homeless Youth

PubMed Central

Barman-Adhikari, Anamika; Rice, Eric; Bender, Kimberly; Lengnick-Hall, Rebecca; Yoshioka-Maxwell, Amanda; Rhoades, Harmony

2016-01-01

Preliminary studies with homeless youth find surprisingly pervasive social media use and suggest youths’ online interactions may be associated with their HIV-related risk and protective behaviors. As homeless youth are transient and difficult to engage in place-based services, social media may represent a novel venue for intervention. A critical first step in intervention development is gaining greater understanding of how homeless youth use social media especially as it relates to whom they connect to and around what topics. Given the salience of Social Networking Sites in the lives of these otherwise difficult to reach adolescents, and their potential to disseminate prevention interventions, this study assessed associations between online social networking technology use and HIV risk behaviors among homeless youth in Los Angeles, California. Homeless youth ages 13 through 24 (N=1046) were recruited through three drop-in centers and surveyed about their social media use and self-reported HIV-related risk behaviors. Results suggest that social media use is widely prevalent among this population, and the content of these online interactions is associated with whether or not they engage in risk or protective behaviors. Implications for interventions and further research are discussed. PMID:27337044

Connecting to young adults: an online social network survey of beliefs and attitudes associated with prescription opioid misuse among college students.

PubMed

Lord, Sarah; Brevard, Julie; Budman, Simon

2011-01-01

A survey of motives and attitudes associated with patterns of nonmedical prescription opioid medication use among college students was conducted on Facebook, a popular online social networking Web site. Response metrics for a 2-week random advertisement post, targeting students who had misused prescription medications, surpassed typical benchmarks for online marketing campaigns and yielded 527 valid surveys. Respondent characteristics, substance use patterns, and use motives were consistent with other surveys of prescription opioid use among college populations. Results support the potential of online social networks to serve as powerful vehicles to connect with college-aged populations about their drug use. Limitations of the study are noted.

An Approach to V&V of Embedded Adaptive Systems

NASA Technical Reports Server (NTRS)

Liu, Yan; Yerramalla, Sampath; Fuller, Edgar; Cukic, Bojan; Gururajan, Srikaruth

2004-01-01

Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

Competitive diffusion in online social networks with heterogeneous users

NASA Astrophysics Data System (ADS)

Li, Pei; He, Su; Wang, Hui; Zhang, Xin

2014-06-01

Online social networks have attracted increasing attention since they provide various approaches for hundreds of millions of people to stay connected with their friends. However, most research on diffusion dynamics in epidemiology cannot be applied directly to characterize online social networks, where users are heterogeneous and may act differently according to their standpoints. In this paper, we propose models to characterize the competitive diffusion in online social networks with heterogeneous users. We classify messages into two types (i.e., positive and negative) and users into three types (i.e., positive, negative and neutral). We estimate the positive (negative) influence for a user generating a given type message, which is the number of times that positive (negative) messages are processed (i.e., read) incurred by this action. We then consider the diffusion threshold, above which the corresponding influence will approach infinity, and the effect threshold, above which the unexpected influence of generating a message will exceed the expected one. We verify all these results by simulations, which show the analysis results are perfectly consistent with the simulation results. These results are of importance in understanding the diffusion dynamics in online social networks, and also critical for advertisers in viral marketing where there are fans, haters and neutrals.

Towards Meaningful Learning through Digital Video Supported, Case Based Teaching

ERIC Educational Resources Information Center

Hakkarainen, Paivi; Saarelainen, Tarja; Ruokamo, Heli

2007-01-01

This paper reports an action research case study in which a traditional lecture based, face to face "Network Management" course at the University of Lapland's Faculty of Social Sciences was developed into two different course versions resorting to case based teaching: a face to face version and an online version. In the face to face…

Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

ERIC Educational Resources Information Center

Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

2012-01-01

This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

Prediction of Student's Mood during an Online Test Using Formula-based and Neural Network-based Method

ERIC Educational Resources Information Center

Moridis, Christos N.; Economides, Anastasios A.

2009-01-01

Building computerized mechanisms that will accurately, immediately and continually recognize a learner's affective state and activate an appropriate response based on integrated pedagogical models is becoming one of the main aims of artificial intelligence in education. The goal of this paper is to demonstrate how the various kinds of evidence…

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys.

PubMed

Mastrandrea, Rossana; Fournet, Julie; Barrat, Alain

2015-01-01

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations.

Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys

PubMed Central

Mastrandrea, Rossana; Fournet, Julie; Barrat, Alain

2015-01-01

Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations. PMID:26325289

Dynamic Online Bandwidth Adjustment Scheme Based on Kalai-Smorodinsky Bargaining Solution

NASA Astrophysics Data System (ADS)

Kim, Sungwook

Virtual Private Network (VPN) is a cost effective method to provide integrated multimedia services. Usually heterogeneous multimedia data can be categorized into different types according to the required Quality of Service (QoS). Therefore, VPN should support the prioritization among different services. In order to support multiple types of services with different QoS requirements, efficient bandwidth management algorithms are important issues. In this paper, I employ the Kalai-Smorodinsky Bargaining Solution (KSBS) for the development of an adaptive bandwidth adjustment algorithm. In addition, to effectively manage the bandwidth in VPNs, the proposed control paradigm is realized in a dynamic online approach, which is practical for real network operations. The simulations show that the proposed scheme can significantly improve the system performances.

How people make friends in social networking sites—A microscopic perspective

NASA Astrophysics Data System (ADS)

Hu, Haibo; Wang, Xiaofan

2012-02-01

We study the detailed growth of a social networking site with full temporal information by examining the creation process of each friendship relation that can collectively lead to the macroscopic properties of the network. We first study the reciprocal behavior of users, and find that link requests are quickly responded to and that the distribution of reciprocation intervals decays in an exponential form. The degrees of inviters/accepters are slightly negatively correlative with reciprocation time. In addition, the temporal feature of the online community shows that the distributions of intervals of user behaviors, such as sending or accepting link requests, follow a power law with a universal exponent, and peaks emerge for intervals of an integral day. We finally study the preferential selection and linking phenomena of the social networking site and find that, for the former, a linear preference holds for preferential sending and reception, and for the latter, a linear preference also holds for preferential acceptance, creation, and attachment. Based on the linearly preferential linking, we put forward an analyzable network model which can reproduce the degree distribution of the network. The research framework presented in the paper could provide a potential insight into how the micro-motives of users lead to the global structure of online social networks.

On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

NASA Astrophysics Data System (ADS)

Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

2017-10-01

Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

A Study of Malware Propagation via Online Social Networking

NASA Astrophysics Data System (ADS)

Faghani, Mohammad Reza; Nguyen, Uyen Trang

The popularity of online social networks (OSNs) have attracted malware creators who would use OSNs as a platform to propagate automated worms from one user's computer to another's. On the other hand, the topic of malware propagation in OSNs has only been investigated recently. In this chapter, we discuss recent advances on the topic of malware propagation by way of online social networking. In particular, we present three malware propagation techniques in OSNs, namely cross site scripting (XSS), Trojan and clickjacking types, and their characteristics via analytical models and simulations.

Thermoelastic steam turbine rotor control based on neural network

NASA Astrophysics Data System (ADS)

Rzadkowski, Romuald; Dominiczak, Krzysztof; Radulski, Wojciech; Szczepanik, R.

2015-12-01

Considered here are Nonlinear Auto-Regressive neural networks with eXogenous inputs (NARX) as a mathematical model of a steam turbine rotor for controlling steam turbine stress on-line. In order to obtain neural networks that locate critical stress and temperature points in the steam turbine during transient states, an FE rotor model was built. This model was used to train the neural networks on the basis of steam turbine transient operating data. The training included nonlinearity related to steam turbine expansion, heat exchange and rotor material properties during transients. Simultaneous neural networks are algorithms which can be implemented on PLC controllers. This allows for the application neural networks to control steam turbine stress in industrial power plants.

How Memorial Hermann’s Online Payments Are Boosting Patient Loyalty and Revenue.

PubMed

Ramos Hegwer, Laura

2016-01-01

The Houston-based health system has implemented new workflows and technology in 14 of its hospitals and across its care delivery network to make the payment process more patient-friendly and build consumer loyalty.

How risky are social networking sites? A comparison of places online where youth sexual solicitation and harassment occurs.

PubMed

Ybarra, Michele L; Mitchell, Kimberly J

2008-02-01

Recently, public attention has focused on the possibility that social networking sites such as MySpace and Facebook are being widely used to sexually solicit underage youth, consequently increasing their vulnerability to sexual victimization. Beyond anecdotal accounts, however, whether victimization is more commonly reported in social networking sites is unknown. The Growing up With Media Survey is a national cross-sectional online survey of 1588 youth. Participants were 10- to 15-year-old youth who have used the Internet at least once in the last 6 months. The main outcome measures were unwanted sexual solicitation on the Internet, defined as unwanted requests to talk about sex, provide personal sexual information, and do something sexual, and Internet harassment, defined as rude or mean comments, or spreading of rumors. Fifteen percent of all of the youth reported an unwanted sexual solicitation online in the last year; 4% reported an incident on a social networking site specifically. Thirty-three percent reported an online harassment in the last year; 9% reported an incident on a social networking site specifically. Among targeted youth, solicitations were more commonly reported via instant messaging (43%) and in chat rooms (32%), and harassment was more commonly reported in instant messaging (55%) than through social networking sites (27% and 28%, respectively). Broad claims of victimization risk, at least defined as unwanted sexual solicitation or harassment, associated with social networking sites do not seem justified. Prevention efforts may have a greater impact if they focus on the psychosocial problems of youth instead of a specific Internet application, including funding for online youth outreach programs, school antibullying programs, and online mental health services.

Sentiment Diffusion of Public Opinions about Hot Events: Based on Complex Network

PubMed Central

Hao, Xiaoqing; An, Haizhong; Zhang, Lijia; Li, Huajiao; Wei, Guannan

2015-01-01

To study the sentiment diffusion of online public opinions about hot events, we collected people’s posts through web data mining techniques. We calculated the sentiment value of each post based on a sentiment dictionary. Next, we divided those posts into five different orientations of sentiments: strongly positive (P), weakly positive (p), neutral (o), weakly negative (n), and strongly negative (N). These sentiments are combined into modes through coarse graining. We constructed sentiment mode complex network of online public opinions (SMCOP) with modes as nodes and the conversion relation in chronological order between different types of modes as edges. We calculated the strength, k-plex clique, clustering coefficient and betweenness centrality of the SMCOP. The results show that the strength distribution obeys power law. Most posts’ sentiments are weakly positive and neutral, whereas few are strongly negative. There are weakly positive subgroups and neutral subgroups with ppppp and ooooo as the core mode, respectively. Few modes have larger betweenness centrality values and most modes convert to each other with these higher betweenness centrality modes as mediums. Therefore, the relevant person or institutes can take measures to lead people’s sentiments regarding online hot events according to the sentiment diffusion mechanism. PMID:26462230

#Stupidcancer: Exploring a Typology of Social Support and the Role of Emotional Expression in a Social Media Community.

PubMed

Myrick, Jessica Gall; Holton, Avery E; Himelboim, Itai; Love, Brad

2016-01-01

Social network sites (SNSs) like Twitter continue to attract users, many of whom turn to these spaces for social support for serious illnesses like cancer. Building on literature that explored the functionality of online spaces for health-related social support, we propose a typology that situates this type of support in an SNS-based open cancer community based on the type (informational or emotional) and the direction (expression or reception) of support. A content analysis applied the typology to a 2-year span of Twitter messages using the popular hashtag "#stupidcancer." Given that emotions form the basis for much of human communication and behavior, including aspects of social support, this content analysis also examined the relationship between emotional expression and online social support in tweets about cancer. Furthermore, this study looked at the various ways in which Twitter allows for message sharing across a user's entire network (not just among the cancer community). This work thus begins to lay the conceptual and empirical groundwork for future research testing the effects of various types of social support in open, interactive online cancer communities.

Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange

NASA Astrophysics Data System (ADS)

Jahangoshai Rezaee, Mustafa; Jozmaleki, Mehrdad; Valipour, Mahsa

2018-01-01

One of the main features to invest in stock exchange companies is their financial performance. On the other hand, conventional evaluation methods such as data envelopment analysis are not only a retrospective process, but are also a process, which are incomplete and ineffective approaches to evaluate the companies in the future. To remove this problem, it is required to plan an expert system for evaluating organizations when the online data are received from stock exchange market. This paper deals with an approach for predicting the online financial performance of companies when data are received in different time's intervals. The proposed approach is based on integrating fuzzy C-means (FCM), data envelopment analysis (DEA) and artificial neural network (ANN). The classical FCM method is unable to update the number of clusters and their members when the data are changed or the new data are received. Hence, this method is developed in order to make dynamic features for the number of clusters and clusters members in classical FCM. Then, DEA is used to evaluate DMUs by using financial ratios to provide targets in neural network. Finally, the designed network is trained and prepared for predicting companies' future performance. The data on Tehran Stock Market companies for six consecutive years (2007-2012) are used to show the abilities of the proposed approach.

Social networking versus facebook advertising to recruit survey respondents: a quasi-experimental study.

PubMed

Gilligan, Conor; Kypri, Kypros; Bourke, Jesse

2014-09-17

Increasingly, social contact and knowledge of other people's attitudes and behavior are mediated by online social media such as Facebook. The main research to which this recruitment study pertains investigates the influence of parents on adolescent alcohol consumption. Given the pervasiveness of online social media use, Facebook may be an effective means of recruitment and intervention delivery. The objective of the study was to determine the efficacy of study recruitment via social networks versus paid advertising on Facebook. We conducted a quasi-experimental sequential trial with response rate as the outcome, and estimates of cost-effectiveness. The target population was parents of 13-17 year old children attending high schools in the Hunter region of New South Wales, Australia. Recruitment occurred via: method (1) social recruitment using Facebook, email-based, social networks, and media coverage followed by method (2) Facebook advertising. Using a range of online and other social network approaches only: method (1) 74 parents were recruited to complete a survey over eight months, costing AUD58.70 per completed survey. After Facebook advertising: method (2) 204 parents completed the survey over four weeks, costing AUD5.94 per completed survey. Participants were representative of the parents recruited from the region's schools using standard mail and email. Facebook advertising is a cost-effective means of recruiting parents, a group difficult to reach by other methods.

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

Abercrombie, Robert K; Udoeyop, Akaninyene W

This work examines a scientometric model that tracks the emergence of an identified technology from initial discovery (via original scientific and conference literature), through critical discoveries (via original scientific, conference literature and patents), transitioning through Technology Readiness Levels (TRLs) and ultimately on to commercial application. During the period of innovation and technology transfer, the impact of scholarly works, patents and on-line web news sources are identified. As trends develop, currency of citations, collaboration indicators, and on-line news patterns are identified. The combinations of four distinct and separate searchable on-line networked sources (i.e., scholarly publications and citation, worldwide patents, news archives,more » and on-line mapping networks) are assembled to become one collective network (a dataset for analysis of relations). This established network becomes the basis from which to quickly analyze the temporal flow of activity (searchable events) for the example subject domain we investigated.« less

Scientometric methods for identifying emerging technologies

DOEpatents

Abercrombie, Robert K; Schlicher, Bob G; Sheldon, Frederick T

2015-11-03

Provided is a method of generating a scientometric model that tracks the emergence of an identified technology from initial discovery (via original scientific and conference literature), through critical discoveries (via original scientific, conference literature and patents), transitioning through Technology Readiness Levels (TRLs) and ultimately on to commercial application. During the period of innovation and technology transfer, the impact of scholarly works, patents and on-line web news sources are identified. As trends develop, currency of citations, collaboration indicators, and on-line news patterns are identified. The combinations of four distinct and separate searchable on-line networked sources (i.e., scholarly publications and citation, worldwide patents, news archives, and on-line mapping networks) are assembled to become one collective network (a dataset for analysis of relations). This established network becomes the basis from which to quickly analyze the temporal flow of activity (searchable events) for the example subject domain.

Connecting the Invisible Dots: Network-Based Methods to Reach a Hidden Population at Risk for Suicide

PubMed Central

Duberstein, Paul R; Tu, Xin; Tang, Wan; Lu, Naiji; Homan, Christopher M

2009-01-01

Young lesbian, gay, and bisexual (young LGB) individuals report higher rates of suicide ideation and attempts from their late teens through early twenties. Their high rate of Internet use suggests that online social networks offer a novel opportunity to reach them. This study explores online social networks as a venue for prevention research targeting young LGB. An automated data collection program was used to map the social connections between LGB self-identified individuals between 16 and 24 years old participating in an online social network. We then completed a descriptive analysis of the structural characteristics known to affect diffusion within such networks. Finally, we conducted Monte Carlo simulations of peer-driven diffusion of a hypothetical preventive intervention within the observed network under varying starting conditions. We mapped a network of 100,014 young LGB. The mean age was 20.4 years. The mean nodal degree was 137.5, representing an exponential degree distribution ranging from 1 through 4,309. Monte Carlo simulations revealed that a peer-driven preventive intervention ultimately reached final sample sizes of up to 18,409 individuals. The network’s structure is consistent with other social networks in terms of the underlying degree distribution. Such networks are typically formed dynamically through a process of preferential attachment. This implies that some individuals could be more important to target to facilitate the diffusion of interventions. However, in terms of determining the success of an intervention targeting this population, our simulation results suggest that varying the number of peers that can be recruited is more important than increasing the number of randomly-selected starting individuals. This has implications for intervention design. Given the potential to access this previously isolated population, this novel approach represents a promising new frontier in suicide prevention and other research areas. PMID:19540641

Practices and Strategies of Self-Initiated Language Learning in an Online Social Network Discussion Forum: A Descriptive Case Study

ERIC Educational Resources Information Center

Hsieh, Hsiu-Wei

2012-01-01

The proliferation of information and communication technologies and the prevalence of online social networks have facilitated the opportunities for informal learning of foreign languages. However, little educational research has been conducted on how individuals utilize those social networks to take part in self-initiated language learning without…

Usefulness of Social Network Sites for Adolescents' Development of Online Career Skills

ERIC Educational Resources Information Center

Rutten, Mariëlle; Ros, Anje; Kuijpers, Marinka; Kreijns, Karel

2016-01-01

Schools have an important role in teaching students how to use Social Network Site (SNS) for career purposes. This involves the opportunity for students to practice online career skills. Different types of digital environments are available for schools. There are SNS designed to enable users to interact and network. In addition there are digital…

The Program Management Challenges of Web 2.0

DTIC Science & Technology

2010-06-01

identifying and keeping abreast of the newly emerging technologies; their fast pace of evolution or modification, changing domain focus areas, their varied...definitive experts. No one knows what the future holds for network-centric materiel development . We are in the early stages of the Information Age and...led to the development and evolution of online Web-based communities and services such as auction houses, knowledge portals, social networking sites

The persuasion context and results in online opinion seeking: effects of message and source-the moderating role of network managers.

PubMed

Cabezudo, Rebeca San José; Izquierdo, Carmen Camarero; Pinto, Javier Rodríguez

2013-11-01

Online opinion networks are areas for social exchange, or conversational networks, made up of individuals actively involved in sharing experiences and opinions concerning matters of mutual interest between consumers or concerning their experience with a given product or service. We pinpoint a gap in the literature regarding how the persuasion process occurs when individuals seek opinions online, including the results process. In an attempt to find an answer, we draw on traditional theories related to information processing. These are mostly taken from the field of psychology and enable us to identify which signals or aspects of communication or opinions the individuals focus their attention on (message and source) and the value attached to such communications as well as how much they impact individuals' purchase decisions, bearing in mind the medium (or online opinion network) in which the opinions are located. Findings from those interviewed support the idea that the quality of information on the Internet, as well as trust in the source of said information, or in the opinion of network users, have an impact on the informational value obtained from involvement in this online opinion seeking and on purchasing decisions. Moreover, depending on the kind of network (firm or brand controlled, review Web sites, and user-controlled nonofficial opinion networks), the quality of the information or trust in the users will have a different bearing in the persuasion process.

A Web-Based, Social Networking Physical Activity Intervention for Insufficiently Active Adults Delivered via Facebook App: Randomized Controlled Trial

PubMed Central

Ferguson, Monika; Vandelanotte, Corneel; Plotnikoff, Ron; De Bourdeaudhuij, Ilse; Thomas, Samantha; Nelson-Field, Karen; Olds, Tim

2015-01-01

Background Online social networks offer considerable potential for delivery of socially influential health behavior change interventions. Objective To determine the efficacy, engagement, and feasibility of an online social networking physical activity intervention with pedometers delivered via Facebook app. Methods A total of 110 adults with a mean age of 35.6 years (SD 12.4) were recruited online in teams of 3 to 8 friends. Teams were randomly allocated to receive access to a 50-day online social networking physical activity intervention which included self-monitoring, social elements, and pedometers (“Active Team” Facebook app; n=51 individuals, 12 teams) or a wait-listed control condition (n=59 individuals, 13 teams). Assessments were undertaken online at baseline, 8 weeks, and 20 weeks. The primary outcome measure was self-reported weekly moderate-to-vigorous physical activity (MVPA). Secondary outcomes were weekly walking, vigorous physical activity time, moderate physical activity time, overall quality of life, and mental health quality of life. Analyses were undertaken using random-effects mixed modeling, accounting for potential clustering at the team level. Usage statistics were reported descriptively to determine engagement and feasibility. Results At the 8-week follow-up, the intervention participants had significantly increased their total weekly MVPA by 135 minutes relative to the control group (P=.03), due primarily to increases in walking time (155 min/week increase relative to controls, P<.001). However, statistical differences between groups for total weekly MVPA and walking time were lost at the 20-week follow-up. There were no significant changes in vigorous physical activity, nor overall quality of life or mental health quality of life at either time point. High levels of engagement with the intervention, and particularly the self-monitoring features, were observed. Conclusions An online, social networking physical activity intervention with pedometers can produce sizable short-term physical activity changes. Future work is needed to determine how to maintain behavior change in the longer term, how to reach at-need populations, and how to disseminate such interventions on a mass scale. Trial Registration Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12614000488606; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366239 (Archived by WebCite at http://www.webcitation.org/6ZVtu6TMz). PMID:26169067

A Web-Based, Social Networking Physical Activity Intervention for Insufficiently Active Adults Delivered via Facebook App: Randomized Controlled Trial.

PubMed

Maher, Carol; Ferguson, Monika; Vandelanotte, Corneel; Plotnikoff, Ron; De Bourdeaudhuij, Ilse; Thomas, Samantha; Nelson-Field, Karen; Olds, Tim

2015-07-13

Online social networks offer considerable potential for delivery of socially influential health behavior change interventions. To determine the efficacy, engagement, and feasibility of an online social networking physical activity intervention with pedometers delivered via Facebook app. A total of 110 adults with a mean age of 35.6 years (SD 12.4) were recruited online in teams of 3 to 8 friends. Teams were randomly allocated to receive access to a 50-day online social networking physical activity intervention which included self-monitoring, social elements, and pedometers ("Active Team" Facebook app; n=51 individuals, 12 teams) or a wait-listed control condition (n=59 individuals, 13 teams). Assessments were undertaken online at baseline, 8 weeks, and 20 weeks. The primary outcome measure was self-reported weekly moderate-to-vigorous physical activity (MVPA). Secondary outcomes were weekly walking, vigorous physical activity time, moderate physical activity time, overall quality of life, and mental health quality of life. Analyses were undertaken using random-effects mixed modeling, accounting for potential clustering at the team level. Usage statistics were reported descriptively to determine engagement and feasibility. At the 8-week follow-up, the intervention participants had significantly increased their total weekly MVPA by 135 minutes relative to the control group (P=.03), due primarily to increases in walking time (155 min/week increase relative to controls, P<.001). However, statistical differences between groups for total weekly MVPA and walking time were lost at the 20-week follow-up. There were no significant changes in vigorous physical activity, nor overall quality of life or mental health quality of life at either time point. High levels of engagement with the intervention, and particularly the self-monitoring features, were observed. An online, social networking physical activity intervention with pedometers can produce sizable short-term physical activity changes. Future work is needed to determine how to maintain behavior change in the longer term, how to reach at-need populations, and how to disseminate such interventions on a mass scale. Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12614000488606; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366239 (Archived by WebCite at http://www.webcitation.org/6ZVtu6TMz).

Safety and privacy outcomes from a moderated online social therapy for young people with first-episode psychosis.

PubMed

Gleeson, John F; Lederman, Reeva; Wadley, Greg; Bendall, Sarah; McGorry, Patrick D; Alvarez-Jimenez, Mario

2014-04-01

Internet-based treatments for early psychosis offer considerable promise, but safety and security need to be established. This study pilot tested Horyzons, a novel online treatment application that integrates purpose-built moderated social networking with psychoeducation for recovery from early psychosis. Safety, privacy, and security were evaluated during a one-month single-group trial with 20 young consumers recovering from early psychosis who were recruited in Melbourne, Australia. Known clinical risk factors informed the safety protocol. Safety, privacy, and security were evaluated with respect to relapse and self-harm, users' perceptions of safety and privacy, and activity using Horyzons. No clinical or security problems with use of Horyzons were noted. Participants described feeling safe and trusting Horyzons. Private moderated online social networking combined with psychoeducation was a safe and secure therapeutic environment for consumers recovering from a first episode of psychosis. Testing the intervention in a randomized controlled trial is warranted.

Is it meaningful to distinguish between generalized and specific Internet addiction? Evidence from a cross-cultural study from Germany, Sweden, Taiwan and China.

PubMed

Montag, Christian; Bey, Katharina; Sha, Peng; Li, Mei; Chen, Ya-Fei; Liu, Wei-Yin; Zhu, Yi-Kang; Li, Chun-Bo; Markett, Sebastian; Keiper, Julia; Reuter, Martin

2015-03-01

It has been hypothesized that two distinctive forms of Internet addiction exist. Here, generalized Internet addiction refers to the problematic use of the Internet covering a broad range of Internet-related activities. In contrast, specific forms of Internet addiction target the problematic use of distinct online activities such as excessive online video gaming or activities in social networks. The present study investigates the relationship between generalized and specific Internet addiction in a cross-cultural study encompassing data from China, Taiwan, Sweden and Germany in n = 636 participants. In this study, we assessed - besides generalized Internet addiction - addictive behavior in the domains of online video gaming, online shopping, online social networks and online pornography. The results confirm the existence of distinct forms of specific Internet addiction. One exception, however, was established in five of the six samples under investigation: online social network addiction correlates in large amounts with generalized Internet addiction. In general, it is of importance to distinguish between generalized and specific Internet addiction. Copyright © 2014 Wiley Publishing Asia Pty Ltd.

An Indoor Positioning Technique Based on a Feed-Forward Artificial Neural Network Using Levenberg-Marquardt Learning Method

NASA Astrophysics Data System (ADS)

Pahlavani, P.; Gholami, A.; Azimi, S.

2017-09-01

This paper presents an indoor positioning technique based on a multi-layer feed-forward (MLFF) artificial neural networks (ANN). Most of the indoor received signal strength (RSS)-based WLAN positioning systems use the fingerprinting technique that can be divided into two phases: the offline (calibration) phase and the online (estimation) phase. In this paper, RSSs were collected for all references points in four directions and two periods of time (Morning and Evening). Hence, RSS readings were sampled at a regular time interval and specific orientation at each reference point. The proposed ANN based model used Levenberg-Marquardt algorithm for learning and fitting the network to the training data. This RSS readings in all references points and the known position of these references points was prepared for training phase of the proposed MLFF neural network. Eventually, the average positioning error for this network using 30% check and validation data was computed approximately 2.20 meter.

Animating Inquiry-Based Teaching in Grade-School Classrooms

ERIC Educational Resources Information Center

Kinash, Shelley

2007-01-01

This paper describes interpretive empirical research with five teachers who: a) articulate their pedagogy as defined by an inquiry-based stance, b) use digital technologies within their teaching, and c) engaged in online and/or face-to-face professional development with the Galileo Educational Network (GENA). Four questions guided the inquiry:…

Surveillance at the molecular level: Developing an integrated network for detecting variation in avian influenza viruses in Indonesia.

PubMed

Hartaningsih, Nining; Wibawa, Hendra; Pudjiatmoko; Rasa, Fadjar Sumping Tjatur; Irianingsih, Sri Handayani; Dharmawan, Rama; Azhar, Muhammad; Siregar, Elly Sawitri; McGrane, James; Wong, Frank; Selleck, Paul; Allen, John; Broz, Ivano; Torchetti, Mia Kim; Dauphin, Gwenaelle; Claes, Filip; Sastraningrat, Wiryadi; Durr, Peter A

2015-06-01

Since 2006, Indonesia has used vaccination as the principal means of control of H5N1-HPAI. During this time, the virus has undergone gradual antigenic drift, which has necessitated changes in seed strains for vaccine production and associated modifications to diagnostic antigens. In order to improve the system of monitoring such viral evolution, the Government of Indonesia, with the assistance of FAO/OFFLU, has developed an innovative network whereby H5N1 isolates are antigenically and genetically characterised. This molecular surveillance network ("Influenza Virus Monitoring" or "IVM") is based on the regional network of veterinary diagnostic laboratories, and is supported by a web-based data management system ("IVM Online"). The example of the Indonesian IVM network has relevance for other countries seeking to establish laboratory networks for the molecular surveillance of avian influenza and other pathogens. Copyright © 2015 Elsevier B.V. All rights reserved.

Implementation of the Enhanced Moderated Online Social Therapy (MOST+) Model Within a National Youth E-Mental Health Service (eheadspace): Protocol for a Single Group Pilot Study for Help-Seeking Young People

PubMed Central

Gleeson, John; Leicester, Steven; Bendall, Sarah; D'Alfonso, Simon; Gilbertson, Tamsyn; Killackey, Eoin; Parker, Alexandra; Lederman, Reeva; Wadley, Greg; Santesteban-Echarri, Olga; Pryor, Ingrid; Mawren, Daveena; Ratheesh, Aswin; Alvarez-Jimenez, Mario

2018-01-01

Background There is a substantial need for youth electronic mental health (e-mental health) services. In addressing this need, our team has developed a novel moderated online social therapy intervention called enhanced moderated online social therapy (MOST+). MOST+ integrates real-time, clinician-delivered Web chat counseling, interactive user-directed online therapy, expert and peer moderation, and private and secure peer-to-peer social networking. MOST+ has been designed to give young people immediate, 24-hour access to anonymous, evidence-based, and short-term mental health care. Objective The primary aims of this pilot study were to determine the feasibility, acceptability, and safety of the intervention. Secondary aims were to assess prepost changes in key psychosocial outcomes and collect qualitative data for future intervention refinement. Methods MOST+ will be embedded within eheadspace, an Australian youth e-mental health service, and will be evaluated via an uncontrolled single-group study. Approximately 250 help-seeking young people (16-25 years) will be progressively recruited to the intervention from the eheadspace home page over the first 4 weeks of an 8-week intervention period. All participants will have access to evidence-based therapeutic content and integrated Web chat counseling. Additional access to moderated peer-to-peer social networking will be granted to individuals for whom it is deemed safe and appropriate, through a three-tiered screening process. Participants will be enrolled in the MOST+ intervention for 1 week, with the option to renew their enrollment across the duration of the pilot. Participants will complete a survey at enrollment to assess psychological well-being and other mental health outcomes. Additional assessment will occur following account deactivation (ie, after participant has opted not to renew their enrollment, or at trial conclusion) and will include an online survey and telephone interview assessing psychological well-being and experience of using MOST+. Results Recruitment for the study commenced in October 2017. We expect to have initial results in March 2018, with more detailed qualitative and quantitative analyses to follow. Conclusions This is the first Australia-wide research trial to pilot an online social media platform merging real-time clinical support, expert and peer moderation, interactive online therapy, and peer-to-peer social networking. The importance of the project stems from the need to develop innovative new models for the efficient delivery of responsive evidence-based online support to help-seeking young people. If successful, this research stands to complement and enhance e-mental health services in Australia. PMID:29472177

Diffusion Dynamics of Energy Saving Practices in Large Heterogeneous Online Networks

PubMed Central

Mohammadi, Neda; Wang, Qi; Taylor, John E.

2016-01-01

Online social networks are today’s fastest growing communications channel and a popular source of information for many, so understanding their contribution to building awareness and shaping public perceptions of climate change is of utmost importance. Today’s online social networks are composed of complex combinations of entities and communication channels and it is not clear which communicators are the most influential, what the patterns of communication flow are, or even whether the widely accepted two-step flow of communication model applies in this new arena. This study examines the diffusion of energy saving practices in a large online social network across organizations, opinion leaders, and the public by tracking 108,771 communications on energy saving practices among 1,084 communicators, then analyzing the flow of information and influence over a 28 day period. Our findings suggest that diffusion networks of messages advocating energy saving practices are predominantly led by the activities of dedicated organizations but their attempts do not result in substantial public awareness, as most of these communications are effectively trapped in organizational loops in which messages are simply shared between organizations. Despite their comparably significant influential values, opinion leaders played a weak role in diffusing energy saving practices to a wider audience. Thus, the two-step flow of communication model does not appear to describe the sharing of energy conservation practices in large online heterogeneous networks. These results shed new light on the underlying mechanisms driving the diffusion of important societal issues such as energy efficiency, particularly in the context of large online social media outlets. PMID:27736912

Diffusion Dynamics of Energy Saving Practices in Large Heterogeneous Online Networks.

PubMed

Mohammadi, Neda; Wang, Qi; Taylor, John E

2016-01-01

Online social networks are today's fastest growing communications channel and a popular source of information for many, so understanding their contribution to building awareness and shaping public perceptions of climate change is of utmost importance. Today's online social networks are composed of complex combinations of entities and communication channels and it is not clear which communicators are the most influential, what the patterns of communication flow are, or even whether the widely accepted two-step flow of communication model applies in this new arena. This study examines the diffusion of energy saving practices in a large online social network across organizations, opinion leaders, and the public by tracking 108,771 communications on energy saving practices among 1,084 communicators, then analyzing the flow of information and influence over a 28 day period. Our findings suggest that diffusion networks of messages advocating energy saving practices are predominantly led by the activities of dedicated organizations but their attempts do not result in substantial public awareness, as most of these communications are effectively trapped in organizational loops in which messages are simply shared between organizations. Despite their comparably significant influential values, opinion leaders played a weak role in diffusing energy saving practices to a wider audience. Thus, the two-step flow of communication model does not appear to describe the sharing of energy conservation practices in large online heterogeneous networks. These results shed new light on the underlying mechanisms driving the diffusion of important societal issues such as energy efficiency, particularly in the context of large online social media outlets.

Competition between global and local online social networks

NASA Astrophysics Data System (ADS)

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-01

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Competition between global and local online social networks.

PubMed

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-27

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Structural and Dynamical Patterns on Online Social Networks: The Spanish May 15th Movement as a Case Study

PubMed Central

Borge-Holthoefer, Javier; Rivero, Alejandro; García, Iñigo; Cauhé, Elisa; Ferrer, Alfredo; Ferrer, Darío; Francos, David; Iñiguez, David; Pérez, María Pilar; Ruiz, Gonzalo; Sanz, Francisco; Serrano, Fermín; Viñas, Cristina; Tarancón, Alfonso; Moreno, Yamir

2011-01-01

The number of people using online social networks in their everyday life is continuously growing at a pace never saw before. This new kind of communication has an enormous impact on opinions, cultural trends, information spreading and even in the commercial success of new products. More importantly, social online networks have revealed as a fundamental organizing mechanism in recent country-wide social movements. In this paper, we provide a quantitative analysis of the structural and dynamical patterns emerging from the activity of an online social network around the ongoing May 15th (15M) movement in Spain. Our network is made up by users that exchanged tweets in a time period of one month, which includes the birth and stabilization of the 15M movement. We characterize in depth the growth of such dynamical network and find that it is scale-free with communities at the mesoscale. We also find that its dynamics exhibits typical features of critical systems such as robustness and power-law distributions for several quantities. Remarkably, we report that the patterns characterizing the spreading dynamics are asymmetric, giving rise to a clear distinction between information sources and sinks. Our study represents a first step towards the use of data from online social media to comprehend modern societal dynamics. PMID:21886834

Connecting to Young Adults: An Online Social Network Survey of Beliefs and Attitudes Associated With Prescription Opioid Misuse Among College Students

PubMed Central

Lord, Sarah; Brevard, Julie; Budman, Simon

2011-01-01

A survey of motives and attitudes associated with patterns of nonmedical prescription opioid medication use among college students was conducted on Facebook, a popular online social networking Web site. Response metrics for a 2-week random advertisement post, targeting students who had misused prescription medications, surpassed typical benchmarks for online marketing campaigns and yielded 527 valid surveys. Respondent characteristics, substance use patterns, and use motives were consistent with other surveys of prescription opioid use among college populations. Results support the potential of online social networks to serve as powerful vehicles to connect with college-aged populations about their drug use. Limitations of the study are noted. PMID:21190407

Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation.

PubMed

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

2016-01-01

Analysis of user interactions in online communities could improve our understanding of health-related behaviors and inform the design of technological solutions that support behavior change. However, to achieve this we would need methods that provide granular perspective, yet are scalable. In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. We apply this method to derive content-specific network visualizations of 16,492 user interactions in an online community for smoking cessation. Performance of the categorization system was reasonable (average F-measure of 0.74, with system-rater reliability approaching rater-rater reliability). The resulting semantically specific network analysis of user interactions reveals content- and behavior-specific network topologies. Implications for socio-behavioral health and wellness platforms are also discussed.

Harnessing Online Peer Education (HOPE): integrating C-POL and social media to train peer leaders in HIV prevention.

PubMed

Jaganath, Devan; Gill, Harkiran K; Cohen, Adam Carl; Young, Sean D

2012-01-01

Novel methods, such as Internet-based interventions, are needed to combat the spread of HIV. While past initiatives have used the Internet to promote HIV prevention, the growing popularity, decreasing digital divide, and multi-functionality of social networking sites, such as Facebook, make this an ideal time to develop innovative ways to use online social networking sites to scale HIV prevention interventions among high-risk groups. The UCLA Harnessing Online Peer Education study is a longitudinal experimental study to evaluate the feasibility, acceptability, and preliminary effectiveness of using social media for peer-led HIV prevention, specifically among African American and Latino Men who have Sex with Men (MSM). No curriculum currently exists to train peer leaders in delivering culturally aware HIV prevention messages using social media. Training was created that adapted the Community Popular Opinion Leader (C-POL) model, for use on social networking sites. Peer leaders are recruited who represent the target population and have experience with both social media and community outreach. The curriculum contains the following elements: discussion and role playing exercises to integrate basic knowledge of HIV/AIDS, awareness of sociocultural HIV/AIDS issues in the age of technology, and communication methods for training peer leaders in effective, interactive social media-based HIV prevention. Ethical issues related to Facebook and health interventions are integrated throughout the sessions. Training outcomes have been developed for long-term assessment of retention and efficacy. This is the first C-POL curriculum that has been adapted for use on social networking websites. Although this curriculum has been used to target African-American and Latino MSM, it has been created to allow generalization to other high-risk groups.

Harnessing Online Peer Education (HOPE): Integrating C-POL and Social Media to Train Peer Leaders in HIV Prevention

PubMed Central

Jaganath, Devan; Gill, Harkiran K.; Cohen, Adam Carl; Young, Sean D.

2011-01-01

Novel methods, such as Internet-based interventions, are needed to combat the spread of HIV. While past initiatives have used the Internet to promote HIV prevention, the growing popularity, decreasing digital divide, and multi-functionality of social networking sites, such as Facebook, make this an ideal time to develop innovative ways to use online social networking sites to scale HIV prevention interventions among high-risk groups. The UCLA HOPE [Harnessing Online Peer Education] study is a longitudinal experimental study to evaluate the feasibility, acceptability, and preliminary effectiveness of using social media for peer-led HIV prevention, specifically among African American and Latino Men who have Sex with Men (MSM). No curriculum currently exists to train peer leaders in delivering culturally aware HIV prevention messages using social media. Training was created that adapted the Community Popular Opinion Leader (C-POL) model, for use on social networking sites. Peer leaders are recruited who represent the target population and have experience with both social media and community outreach. The curriculum contains the following elements: discussion and role playing exercises to integrate basic knowledge of HIV/AIDS, awareness of sociocultural HIV/AIDS issues in the age of technology, and communication methods for training peer leaders in effective, interactive social media-based HIV prevention. Ethical issues related to Facebook and health interventions are integrated throughout the sessions. Training outcomes have been developed for long-term assessment of retention and efficacy. This is the first C-POL curriculum that has been adapted for use on social networking websites. Although this curriculum has been used to target African American and Latino MSM, it has been created to allow generalization to other high-risk groups. PMID:22149081

Advanced Networks in Dental Rich Online MEDiA (ANDROMEDA)

NASA Astrophysics Data System (ADS)

Elson, Bruce; Reynolds, Patricia; Amini, Ardavan; Burke, Ezra; Chapman, Craig

There is growing demand for dental education and training not only in terms of knowledge but also skills. This demand is driven by continuing professional development requirements in the more developed economies, personnel shortages and skills differences across the European Union (EU) accession states and more generally in the developing world. There is an excellent opportunity for the EU to meet this demand by developing an innovative online flexible learning platform (FLP). Current clinical online systems are restricted to the delivery of general, knowledge-based training with no easy method of personalization or delivery of skill-based training. The PHANTOM project, headed by Kings College London is developing haptic-based virtual reality training systems for clinical dental training. ANDROMEDA seeks to build on this and establish a Flexible Learning Platform that can integrate the haptic and sensor based training with rich media knowledge transfer, whilst using sophisticated technologies such as including service-orientated architecture (SOA), Semantic Web technologies, knowledge-based engineering, business intelligence (BI) and virtual worlds for personalization.

Online social networking for HIV education and prevention: a mixed-methods analysis.

PubMed

Young, Sean D; Jaganath, Devan

2013-02-01

The purpose of this study is to use mixed (qualitative/quantitative) methods to determine (1) the feasibility and acceptability of using online social networking to facilitate HIV-related discussions and (2) the relationship between HIV-related online discussions and requests for a home-based HIV testing kit among men who have sex with men. Participants, primarily African American and Latino, were invited to join a "secret" group on the social networking Web site, Facebook. Peer leaders, trained in HIV prevention, posted HIV-related content. Participants were not obligated to respond to discussions or remain within the group. Participant public group conversations were qualitatively and thematically analyzed. Quantitative methods tested associations between qualitative data, participants' demographic information, and likelihood of requesting a home-based HIV testing kit. Latino and African American participants (n = 57) voluntarily used Facebook to discuss the following HIV-related topics (n = 485 conversations): prevention and testing, knowledge, stigma, and advocacy. Older participants more frequently discussed prevention and testing, stigma, and advocacy, although younger participants more frequently discussed HIV knowledge-related conversations. As the study progressed, the proportion of messages related to prevention and testing and HIV stigma increased. Multivariate analysis showed that participants posting about HIV prevention and testing (compared with those who did not) were significantly more likely to request an HIV testing kit (odds ratio, 11.14; P = 0.001). Facebook can serve as an innovative forum to increase both HIV prevention discussions and HIV testing requests among at-risk groups.

Surface inspection of flat products by means of texture analysis: on-line implementation using neural networks

NASA Astrophysics Data System (ADS)

Fernandez, Carlos; Platero, Carlos; Campoy, Pascual; Aracil, Rafael

1994-11-01

This paper describes some texture-based techniques that can be applied to quality assessment of flat products continuously produced (metal strips, wooden surfaces, cork, textile products, ...). Since the most difficult task is that of inspecting for product appearance, human-like inspection ability is required. A common feature to all these products is the presence of non- deterministic texture on their surfaces. Two main subjects are discussed: statistical techniques for both surface finishing determination and surface defect analysis as well as real-time implementation for on-line inspection in high-speed applications. For surface finishing determination a Gray Level Difference technique is presented to perform over low resolution images, that is, no-zoomed images. Defect analysis is performed by means of statistical texture analysis over defective portions of the surface. On-line implementation is accomplished by means of neural networks. When a defect arises, textural analysis is applied which result in a data-vector, acting as input of a neural net, previously trained in a supervised way. This approach tries to reach on-line performance in automated visual inspection applications when texture is presented in flat product surfaces.

European health telematics networks for positron emission tomography

NASA Astrophysics Data System (ADS)

Kontaxakis, George; Pozo, Miguel Angel; Ohl, Roland; Visvikis, Dimitris; Sachpazidis, Ilias; Ortega, Fernando; Guerra, Pedro; Cheze-Le Rest, Catherine; Selby, Peter; Pan, Leyun; Diaz, Javier; Dimitrakopoulou-Strauss, Antonia; Santos, Andres; Strauss, Ludwig; Sakas, Georgios

2006-12-01

A pilot network of positron emission tomography centers across Europe has been setup employing telemedicine services. The primary aim is to bring all PET centers in Europe (and beyond) closer, by integrating advanced medical imaging technology and health telematics networks applications into a single, easy to operate health telematics platform, which allows secure transmission of medical data via a variety of telecommunications channels and fosters the cooperation between professionals in the field. The platform runs on PCs with Windows 2000/XP and incorporates advanced techniques for image visualization, analysis and fusion. The communication between two connected workstations is based on a TCP/IP connection secured by secure socket layers and virtual private network or jabber protocols. A teleconsultation can be online (with both physicians physically present) or offline (via transmission of messages which contain image data and other information). An interface sharing protocol enables online teleconsultations even over low bandwidth connections. This initiative promotes the cooperation and improved communication between nuclear medicine professionals, offering options for second opinion and training. It permits physicians to remotely consult patient data, even if they are away from the physical examination site.

Dairy Herd On-line Information System

NASA Astrophysics Data System (ADS)

Takahashi, Satoshi

As the business circumstances have become worse, computational breeding management based on the scientific matters has been needed for dairy farming in our country. In this connection it was urgent to construct the system which provided data effectively used in the fields for dairy farmers. The Federation has executed to provide dairy farming technical data promptly through its own on-line network being composed of middle sized general-purpose computer (main memory : 5MB, and fixed disk : 1100MB) and 22 terminals.

Use of on-line bibliographic retrieval services in health sciences libraries in the United States and Canada.

PubMed Central

Werner, G

1979-01-01

This paper reports the major findings of a questionnaire sent to the 708 U. S. and Canadian institutions which were using the National Library of Medicine's search services as of November 1977. Development of the National Library of Medicine (NLM) on-line network is traced characterizes type of institution, use of NLM and non-NLM data bases, operational service patterns, staffing levels, fee-for-service policies, and perceived impact. PMID:371720

An Analysis of Density and Degree-Centrality According to the Social Networking Structure Formed in an Online Learning Environment

ERIC Educational Resources Information Center

Ergün, Esin; Usluel, Yasemin Koçak

2016-01-01

In this study, we assessed the communication structure in an educational online learning environment using social network analysis (SNA). The communication structure was examined with respect to time, and instructor's participation. The course was implemented using ELGG, a network learning environment, blended with face-to-face sessions over a…

Integrating Emerging Topics through Online Team Design in a Hybrid Communication Networks Course: Interaction Patterns and Impact of Prior Knowledge

ERIC Educational Resources Information Center

Reisslein, Jana; Seeling, Patrick; Reisslein, Martin

2005-01-01

An important challenge in the introductory communication networks course in electrical and computer engineering curricula is to integrate emerging topics, such as wireless Internet access and network security, into the already content-intensive course. At the same time it is essential to provide students with experiences in online collaboration,…

Networked Reading: Using AustLit to Assist Reading and Understanding of Texts from the Past

ERIC Educational Resources Information Center

Osborne, Roger; Allan, Cherie

2012-01-01

In response to a focus on reading, this paper examines the notion of reading online; as such it uses the term "networked reading" to describe any act of reading in an online or digital environment. In accordance with this notion of "networked" reading, the paper provides a broad introduction to AustLit: the Australian…

An Examination of Organizational Information Protection in the Era of Social Media: A Study of Social Network Security and Privacy Protection

ERIC Educational Resources Information Center

Maar, Michael C.

2013-01-01

This study investigates information protection for professional users of online social networks. It addresses management's desire to motivate their employees to adopt protective measures while accessing online social networks and to help their employees improve their proficiency in information security and ability to detect deceptive…

Walk-based measure of balance in signed networks: Detecting lack of balance in social networks

NASA Astrophysics Data System (ADS)

Estrada, Ernesto; Benzi, Michele

2014-10-01

There is a longstanding belief that in social networks with simultaneous friendly and hostile interactions (signed networks) there is a general tendency to a global balance. Balance represents a state of the network with a lack of contentious situations. Here we introduce a method to quantify the degree of balance of any signed (social) network. It accounts for the contribution of all signed cycles in the network and gives, in agreement with empirical evidence, more weight to the shorter cycles than to the longer ones. We found that, contrary to what is generally believed, many signed social networks, in particular very large directed online social networks, are in general very poorly balanced. We also show that unbalanced states can be changed by tuning the weights of the social interactions among the agents in the network.

First field trial of Virtual Network Operator oriented network on demand (NoD) service provisioning over software defined multi-vendor OTN networks

NASA Astrophysics Data System (ADS)

Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Chen, Haoran; Zhu, Ruijie; Zhou, Quanwei; Yu, Chenbei; Cui, Rui

2017-01-01

A Virtual Network Operator (VNO) is a provider and reseller of network services from other telecommunications suppliers. These network providers are categorized as virtual because they do not own the underlying telecommunication infrastructure. In terms of business operation, VNO can provide customers with personalized services by leasing network infrastructure from traditional network providers. The unique business modes of VNO lead to the emergence of network on demand (NoD) services. The conventional network provisioning involves a series of manual operation and configuration, which leads to high cost in time. Considering the advantages of Software Defined Networking (SDN), this paper proposes a novel NoD service provisioning solution to satisfy the private network need of VNOs. The solution is first verified in the real software defined multi-domain optical networks with multi-vendor OTN equipment. With the proposed solution, NoD service can be deployed via online web portals in near-real time. It reinvents the customer experience and redefines how network services are delivered to customers via an online self-service portal. Ultimately, this means a customer will be able to simply go online, click a few buttons and have new services almost instantaneously.

Las Cumbres Observatory Global Telescope Network: Keeping Education in the Dark

NASA Astrophysics Data System (ADS)

Ross, Rachel J.

2007-12-01

Las Cumbres Observatory Global Telescope Network is a non-profit organization that is building a completely robotic network of telescopes for education (24 x 0.4m, clusters of 4) and science (18 x 1.0m, clusters of 3 and 2 x 2.0 meters) which will be longitudinally spaced so there will always be at least one cluster in the dark. The network will be completely accessible online with observations being completed in either real-time or queued-based modes. The network will also have the ability to complete very long observations of all kinds of variable objects and include a rapid response system will allow the telescopes to quickly slew to unexpected phenomena and provide around-the-clock monitoring. Students will be able to do research projects using and collecting data from both the long observations (e.g. extrasolar planet follow-up, variable star light curves, etc.) and the quick response (e.g. supernovae, GRBs, etc.), as well as use their own ideas to create personalized projects. Also available online will be a huge archive of data and the ability to use online software to process it. A large library of activities and resources will be available for all age groups and levels of science. LCOGTN will work cooperatively with international organizations to bring a vast amount of knowledge and experience together to create a world class program. Through these collaborations, pilots have already been started in a few European countries, as well as trial programs involving schools partnered between the USA and UK. LCOGTN's education network will provide an avenue for educators and learners to use cutting edge technology to do real science. All you need is a broadband internet connection, computer, and lots of enthusiasm and imagination.

Online social network response to studies on antidepressant use in pregnancy.

PubMed

Vigod, Simone N; Bagheri, Ebrahim; Zarrinkalam, Fattane; Brown, Hilary K; Mamdani, Muhammad; Ray, Joel G

2018-03-01

About 8% of U.S women are prescribed antidepressant medications around the time of pregnancy. Decisions about medication use in pregnancy can be swayed by the opinion of family, friends and online media, sometimes beyond the advice offered by healthcare providers. Exploration of the online social network response to research on antidepressant use in pregnancy could provide insight about how to optimize decision-making in this complex area. For all 17 research articles published on the safety of antidepressant use in pregnancy in 2012, we sought to explore online social network activity regarding antidepressant use in pregnancy, via Twitter, in the 48h after a study was published, compared to the social network activity in the same period 1week prior to each article's publication. Online social network activity about antidepressants in pregnancy quickly doubled upon study publication. The increased activity was driven by studies demonstrating harm associated with antidepressants, lower-quality studies, and studies where abstracts presented relative versus absolute risks. These findings support a call for leadership from medical journals to consider how to best incentivize and support a balanced and clear translation of knowledge around antidepressant safety in pregnancy to their readership and the public. Copyright © 2018 Elsevier Inc. All rights reserved.

Intelligent complementary sliding-mode control for LUSMS-based X-Y-theta motion control stage.

PubMed

Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai; Liu, Yen-Hung

2010-07-01

An intelligent complementary sliding-mode control (ICSMC) system using a recurrent wavelet-based Elman neural network (RWENN) estimator is proposed in this study to control the mover position of a linear ultrasonic motors (LUSMs)-based X-Y-theta motion control stage for the tracking of various contours. By the addition of a complementary generalized error transformation, the complementary sliding-mode control (CSMC) can efficiently reduce the guaranteed ultimate bound of the tracking error by half compared with the slidingmode control (SMC) while using the saturation function. To estimate a lumped uncertainty on-line and replace the hitting control of the CSMC directly, the RWENN estimator is adopted in the proposed ICSMC system. In the RWENN, each hidden neuron employs a different wavelet function as an activation function to improve both the convergent precision and the convergent time compared with the conventional Elman neural network (ENN). The estimation laws of the RWENN are derived using the Lyapunov stability theorem to train the network parameters on-line. A robust compensator is also proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher-order terms in Taylor series. Finally, some experimental results of various contours tracking show that the tracking performance of the ICSMC system is significantly improved compared with the SMC and CSMC systems.