A Two-Stage Composition Method for Danger-Aware Services Based on Context Similarity

NASA Astrophysics Data System (ADS)

Wang, Junbo; Cheng, Zixue; Jing, Lei; Ota, Kaoru; Kansen, Mizuo

Context-aware systems detect user's physical and social contexts based on sensor networks, and provide services that adapt to the user accordingly. Representing, detecting, and managing the contexts are important issues in context-aware systems. Composition of contexts is a useful method for these works, since it can detect a context by automatically composing small pieces of information to discover service. Danger-aware services are a kind of context-aware services which need description of relations between a user and his/her surrounding objects and between users. However when applying the existing composition methods to danger-aware services, they show the following shortcomings that (1) they have not provided an explicit method for representing composition of multi-user' contexts, (2) there is no flexible reasoning mechanism based on similarity of contexts, so that they can just provide services exactly following the predefined context reasoning rules. Therefore, in this paper, we propose a two-stage composition method based on context similarity to solve the above problems. The first stage is composition of the useful information to represent the context for a single user. The second stage is composition of multi-users' contexts to provide services by considering the relation of users. Finally the danger degree of the detected context is computed by using context similarity between the detected context and the predefined context. Context is dynamically represented based on two-stage composition rules and a Situation theory based Ontology, which combines the advantages of Ontology and Situation theory. We implement the system in an indoor ubiquitous environment, and evaluate the system through two experiments with the support of subjects. The experiment results show the method is effective, and the accuracy of danger detection is acceptable to a danger-aware system.

Investigating accident causation through information network modelling.

PubMed

Griffin, T G C; Young, M S; Stanton, N A

2010-02-01

Management of risk in complex domains such as aviation relies heavily on post-event investigations, requiring complex approaches to fully understand the integration of multi-causal, multi-agent and multi-linear accident sequences. The Event Analysis of Systemic Teamwork methodology (EAST; Stanton et al. 2008) offers such an approach based on network models. In this paper, we apply EAST to a well-known aviation accident case study, highlighting communication between agents as a central theme and investigating the potential for finding agents who were key to the accident. Ultimately, this work aims to develop a new model based on distributed situation awareness (DSA) to demonstrate that the risk inherent in a complex system is dependent on the information flowing within it. By identifying key agents and information elements, we can propose proactive design strategies to optimize the flow of information and help work towards avoiding aviation accidents. Statement of Relevance: This paper introduces a novel application of an holistic methodology for understanding aviation accidents. Furthermore, it introduces an ongoing project developing a nonlinear and prospective method that centralises distributed situation awareness and communication as themes. The relevance of findings are discussed in the context of current ergonomic and aviation issues of design, training and human-system interaction.

Context-aware distributed cloud computing using CloudScheduler

NASA Astrophysics Data System (ADS)

Seuster, R.; Leavett-Brown, CR; Casteels, K.; Driemel, C.; Paterson, M.; Ring, D.; Sobie, RJ; Taylor, RP; Weldon, J.

2017-10-01

The distributed cloud using the CloudScheduler VM provisioning service is one of the longest running systems for HEP workloads. It has run millions of jobs for ATLAS and Belle II over the past few years using private and commercial clouds around the world. Our goal is to scale the distributed cloud to the 10,000-core level, with the ability to run any type of application (low I/O, high I/O and high memory) on any cloud. To achieve this goal, we have been implementing changes that utilize context-aware computing designs that are currently employed in the mobile communication industry. Context-awareness makes use of real-time and archived data to respond to user or system requirements. In our distributed cloud, we have many opportunistic clouds with no local HEP services, software or storage repositories. A context-aware design significantly improves the reliability and performance of our system by locating the nearest location of the required services. We describe how we are collecting and managing contextual information from our workload management systems, the clouds, the virtual machines and our services. This information is used not only to monitor the system but also to carry out automated corrective actions. We are incrementally adding new alerting and response services to our distributed cloud. This will enable us to scale the number of clouds and virtual machines. Further, a context-aware design will enable us to run analysis or high I/O application on opportunistic clouds. We envisage an open-source HTTP data federation (for example, the DynaFed system at CERN) as a service that would provide us access to existing storage elements used by the HEP experiments.

Susceptible-infected-recovered epidemics in random networks with population awareness

NASA Astrophysics Data System (ADS)

Wu, Qingchu; Chen, Shufang

2017-10-01

The influence of epidemic information-based awareness on the spread of infectious diseases on networks cannot be ignored. Within the effective degree modeling framework, we discuss the susceptible-infected-recovered model in complex networks with general awareness and general degree distribution. By performing the linear stability analysis, the conditions of epidemic outbreak can be deduced and the results of the previous research can be further expanded. Results show that the local awareness can suppress significantly the epidemic spreading on complex networks via raising the epidemic threshold and such effects are closely related to the formulation of awareness functions. In addition, our results suggest that the recovered information-based awareness has no effect on the critical condition of epidemic outbreak.

Context-aware workflow management of mobile health applications.

PubMed

Salden, Alfons; Poortinga, Remco

2006-01-01

We propose a medical application management architecture that allows medical (IT) experts readily designing, developing and deploying context-aware mobile health (m-health) applications or services. In particular, we elaborate on how our application workflow management architecture enables chaining, coordinating, composing, and adapting context-sensitive medical application components such that critical Quality of Service (QoS) and Quality of Context (QoC) requirements typical for m-health applications or services can be met. This functional architectural support requires learning modules for distilling application-critical selection of attention and anticipation models. These models will help medical experts constructing and adjusting on-the-fly m-health application workflows and workflow strategies. We illustrate our context-aware workflow management paradigm for a m-health data delivery problem, in which optimal communication network configurations have to be determined.

Mobile Context Provider for Social Networking

NASA Astrophysics Data System (ADS)

Santos, André C.; Cardoso, João M. P.; Ferreira, Diogo R.; Diniz, Pedro C.

The ability to infer user context based on a mobile device together with a set of external sensors opens up the way to new context-aware services and applications. In this paper, we describe a mobile context provider that makes use of sensors available in a smartphone as well as sensors externally connected via bluetooth. We describe the system architecture from sensor data acquisition to feature extraction, context inference and the publication of context information to well-known social networking services such as Twitter and Hi5. In the current prototype, context inference is based on decision trees, but the middleware allows the integration of other inference engines. Experimental results suggest that the proposed solution is a promising approach to provide user context to both local and network-level services.

Challenges in Wireless System Integration as Enablers for Indoor Context Aware Environments

PubMed Central

Aguirre, Erik

2017-01-01

The advent of fully interactive environments within Smart Cities and Smart Regions requires the use of multiple wireless systems. In the case of user-device interaction, which finds multiple applications such as Ambient Assisted Living, Intelligent Transportation Systems or Smart Grids, among others, large amount of transceivers are employed in order to achieve anytime, anyplace and any device connectivity. The resulting combination of heterogeneous wireless network exhibits fundamental limitations derived from Coverage/Capacity relations, as a function of required Quality of Service parameters, required bit rate, energy restrictions and adaptive modulation and coding schemes. In this context, inherent transceiver density poses challenges in overall system operation, given by multiple node operation which increases overall interference levels. In this work, a deterministic based analysis applied to variable density wireless sensor network operation within complex indoor scenarios is presented, as a function of topological node distribution. The extensive analysis derives interference characterizations, both for conventional transceivers as well as wearables, which provide relevant information in terms of individual node configuration as well as complete network layout. PMID:28704963

IoT Contextual Factors on Healthcare.

PubMed

Michalakis, Konstantinos; Caridakis, George

2017-01-01

With the emergence of the Internet of Things, new services in healthcare will be available and existing systems will be integrated in the IoT framework, providing automated medical supervision and efficient medical treatment. Context awareness plays a critical role in realizing the vision of the IoT, providing rich contextual information that can help the system act more efficiently. Since context in healthcare has its unique characteristics, it is necessary to define an appropriate context aware framework for healthcare IoT applications. We identify this context as perceived in healthcare applications and describe the context aware procedures. We also present an architecture that connects the sensors that measure biometric data with the sensory networks of the environment and the various IoT middleware that reside in the geographical area. Finally, we discuss the challenges for the realization of this vision.

Intrusion-aware alert validation algorithm for cooperative distributed intrusion detection schemes of wireless sensor networks.

PubMed

Shaikh, Riaz Ahmed; Jameel, Hassan; d'Auriol, Brian J; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

PubMed Central

Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm. PMID:22454568

Analysis of wireless sensor network topology and estimation of optimal network deployment by deterministic radio channel characterization.

PubMed

Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leire; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2015-02-05

One of the main challenges in the implementation and design of context-aware scenarios is the adequate deployment strategy for Wireless Sensor Networks (WSNs), mainly due to the strong dependence of the radiofrequency physical layer with the surrounding media, which can lead to non-optimal network designs. In this work, radioplanning analysis for WSN deployment is proposed by employing a deterministic 3D ray launching technique in order to provide insight into complex wireless channel behavior in context-aware indoor scenarios. The proposed radioplanning procedure is validated with a testbed implemented with a Mobile Ad Hoc Network WSN following a chain configuration, enabling the analysis and assessment of a rich variety of parameters, such as received signal level, signal quality and estimation of power consumption. The adoption of deterministic radio channel techniques allows the design and further deployment of WSNs in heterogeneous wireless scenarios with optimized behavior in terms of coverage, capacity, quality of service and energy consumption.

Packet-aware transport for video distribution [Invited

NASA Astrophysics Data System (ADS)

Aguirre-Torres, Luis; Rosenfeld, Gady; Bruckman, Leon; O'Connor, Mannix

2006-05-01

We describe a solution based on resilient packet rings (RPR) for the distribution of broadcast video and video-on-demand (VoD) content over a packet-aware transport network. The proposed solution is based on our experience in the design and deployment of nationwide Triple Play networks and relies on technologies such as RPR, multiprotocol label switching (MPLS), and virtual private LAN service (VPLS) to provide the most efficient solution in terms of utilization, scalability, and availability.

Context-awareness in ubiquitous computing and the mobile devices

NASA Astrophysics Data System (ADS)

Akçit, Nuhcan; Tomur, Emrah; Karslıoǧlu, Mahmut Onur

2015-06-01

Mobile device use has vastly increased in the last few years. Many people use many mobile devices in their daily lives. Context-aware computing is the main feature of pervasive and ubiquitous computing. Context awareness is also an important topic that becomes more available with ubiquitous computing. As the sensors increase, the data collected via mobile device sensors and sensor networks do not have much value because of the difficulty in analysis and understanding the data. Context-aware computing helps us store contextual information and use or search it by mobile devices when we want to see or analyze it. Contextual data can be made more meaningful by context-aware processing. There are different types of data and context information that must be considered. By combining spatial and contextual data, we obtain more meaningful data based on the entities. Contextual data is any information that can be used to characterize the situation of the entity. The entity is a person, place, or object considered relevant to the interaction between the user and an application, including the users and the applications. Using contextual data and good integration to mobile devices adds great value to this data, and combining these with our other data sets will allow us to obtain more useful information and analysis.

Flexible Macroblock Ordering for Context-Aware Ultrasound Video Transmission over Mobile WiMAX

PubMed Central

Martini, Maria G.; Hewage, Chaminda T. E. R.

2010-01-01

The most recent network technologies are enabling a variety of new applications, thanks to the provision of increased bandwidth and better management of Quality of Service. Nevertheless, telemedical services involving multimedia data are still lagging behind, due to the concern of the end users, that is, clinicians and also patients, about the low quality provided. Indeed, emerging network technologies should be appropriately exploited by designing the transmission strategy focusing on quality provision for end users. Stemming from this principle, we propose here a context-aware transmission strategy for medical video transmission over WiMAX systems. Context, in terms of regions of interest (ROI) in a specific session, is taken into account for the identification of multiple regions of interest, and compression/transmission strategies are tailored to such context information. We present a methodology based on H.264 medical video compression and Flexible Macroblock Ordering (FMO) for ROI identification. Two different unequal error protection methodologies, providing higher protection to the most diagnostically relevant data, are presented. PMID:20827292

A Scalable QoS-Aware VoD Resource Sharing Scheme for Next Generation Networks

NASA Astrophysics Data System (ADS)

Huang, Chenn-Jung; Luo, Yun-Cheng; Chen, Chun-Hua; Hu, Kai-Wen

In network-aware concept, applications are aware of network conditions and are adaptable to the varying environment to achieve acceptable and predictable performance. In this work, a solution for video on demand service that integrates wireless and wired networks by using the network aware concepts is proposed to reduce the blocking probability and dropping probability of mobile requests. Fuzzy logic inference system is employed to select appropriate cache relay nodes to cache published video streams and distribute them to different peers through service oriented architecture (SOA). SIP-based control protocol and IMS standard are adopted to ensure the possibility of heterogeneous communication and provide a framework for delivering real-time multimedia services over an IP-based network to ensure interoperability, roaming, and end-to-end session management. The experimental results demonstrate that effectiveness and practicability of the proposed work.

Energy Efficiency in Public Buildings through Context-Aware Social Computing.

PubMed

García, Óscar; Alonso, Ricardo S; Prieto, Javier; Corchado, Juan M

2017-04-11

The challenge of promoting behavioral changes in users that leads to energy savings in public buildings has become a complex task requiring the involvement of multiple technologies. Wireless sensor networks have a great potential for the development of tools, such as serious games, that encourage acquiring good energy and healthy habits among users in the workplace. This paper presents the development of a serious game using CAFCLA, a framework that allows for integrating multiple technologies, which provide both context-awareness and social computing. Game development has shown that the data provided by sensor networks encourage users to reduce energy consumption in their workplace and that social interactions and competitiveness allow for accelerating the achievement of good results and behavioral changes that favor energy savings.

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System.

PubMed

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-08-18

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems.

Context Aware Programmable Trackers for the Next Generation Internet

NASA Astrophysics Data System (ADS)

Sousa, Pedro

This work introduces and proposes the concept of context aware programmable trackers for the next generation Internet. The proposed solution gives ground for the development of advanced applications based on the P2P paradigm and will foster collaborative efforts among several network entities (e.g. P2P applications and ISPs). The proposed concept of context aware programmable trackers allows that several peer selection strategies might be supported by a P2P tracker entity able to improve the peer selection decisions according with pre-defined objectives and external inputs provided by specific services. The flexible, adaptive and enhanced peer selection semantics that might be achieved by the proposed solution will contribute for devising novel P2P based services and business models for the future Internet.

Talking about Climate Change and Global Warming

PubMed Central

Kim, Ji Yoon; Joo, Gea-Jae

2015-01-01

The increasing prevalence of social networks provides researchers greater opportunities to evaluate and assess changes in public opinion and public sentiment towards issues of social consequence. Using trend and sentiment analysis is one method whereby researchers can identify changes in public perception that can be used to enhance the development of a social consciousness towards a specific public interest. The following study assessed Relative search volume (RSV) patterns for global warming (GW) and Climate change (CC) to determine public knowledge and awareness of these terms. In conjunction with this, the researchers looked at the sentiment connected to these terms in social media networks. It was found that there was a relationship between the awareness of the information and the amount of publicity generated around the terminology. Furthermore, the primary driver for the increase in awareness was an increase in publicity in either a positive or a negative light. Sentiment analysis further confirmed that the primary emotive connections to the words were derived from the original context in which the word was framed. Thus having awareness or knowledge of a topic is strongly related to its public exposure in the media, and the emotional context of this relationship is dependent on the context in which the relationship was originally established. This has value in fields like conservation, law enforcement, or other fields where the practice can and often does have two very strong emotive responses based on the context of the problems being examined. PMID:26418127

Talking about Climate Change and Global Warming.

PubMed

Lineman, Maurice; Do, Yuno; Kim, Ji Yoon; Joo, Gea-Jae

2015-01-01

The increasing prevalence of social networks provides researchers greater opportunities to evaluate and assess changes in public opinion and public sentiment towards issues of social consequence. Using trend and sentiment analysis is one method whereby researchers can identify changes in public perception that can be used to enhance the development of a social consciousness towards a specific public interest. The following study assessed Relative search volume (RSV) patterns for global warming (GW) and Climate change (CC) to determine public knowledge and awareness of these terms. In conjunction with this, the researchers looked at the sentiment connected to these terms in social media networks. It was found that there was a relationship between the awareness of the information and the amount of publicity generated around the terminology. Furthermore, the primary driver for the increase in awareness was an increase in publicity in either a positive or a negative light. Sentiment analysis further confirmed that the primary emotive connections to the words were derived from the original context in which the word was framed. Thus having awareness or knowledge of a topic is strongly related to its public exposure in the media, and the emotional context of this relationship is dependent on the context in which the relationship was originally established. This has value in fields like conservation, law enforcement, or other fields where the practice can and often does have two very strong emotive responses based on the context of the problems being examined.

Energy Aware Clustering Algorithms for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Rakhshan, Noushin; Rafsanjani, Marjan Kuchaki; Liu, Chenglian

2011-09-01

The sensor nodes deployed in wireless sensor networks (WSNs) are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. In wireless sensor networks, hierarchical network structures have the advantage of providing scalable and energy efficient solutions. In this paper, we investigate different clustering algorithms for WSNs and also compare these clustering algorithms based on metrics such as clustering distribution, cluster's load balancing, Cluster Head's (CH) selection strategy, CH's role rotation, node mobility, clusters overlapping, intra-cluster communications, reliability, security and location awareness.

Energy Efficiency in Public Buildings through Context-Aware Social Computing

PubMed Central

García, Óscar; Alonso, Ricardo S.; Prieto, Javier; Corchado, Juan M.

2017-01-01

The challenge of promoting behavioral changes in users that leads to energy savings in public buildings has become a complex task requiring the involvement of multiple technologies. Wireless sensor networks have a great potential for the development of tools, such as serious games, that encourage acquiring good energy and healthy habits among users in the workplace. This paper presents the development of a serious game using CAFCLA, a framework that allows for integrating multiple technologies, which provide both context-awareness and social computing. Game development has shown that the data provided by sensor networks encourage users to reduce energy consumption in their workplace and that social interactions and competitiveness allow for accelerating the achievement of good results and behavioral changes that favor energy savings. PMID:28398237

Appropriating Video Surveillance for Art and Environmental Awareness: Experiences from ARTiVIS.

PubMed

Mendes, Mónica; Ângelo, Pedro; Correia, Nuno; Nisi, Valentina

2018-06-01

Arts, Real-Time Video and Interactivity for Sustainability (ARTiVIS) is an ongoing collaborative research project investigating how real-time video, DIY surveillance technologies and sensor data can be used as a tool for environmental awareness, activism and artistic explorations. The project consists of a series of digital contexts for aesthetic contemplation of nature and civic engagement, aiming to foster awareness and empowerment of local populations through DIY surveillance. At the core of the ARTIVIS efforts are a series of interactive installations (namely B-Wind!, Hug@tree and Play with Fire), that make use of surveillance technologies and real-time video as raw material to promote environmental awareness through the emotion generated by real-time connections with nature. Throughout the project development, the surveillance concept has been shifting from the use of surveillance technology in a centralized platform, to the idea of veillance with distributed peer-to-peer networks that can be used for science and environmental monitoring. In this paper we present the history of the ARTiVIS project, related and inspiring work, describe ongoing research work and explore the present and future challenges of appropriating surveillance technology for artistic, educational and civic engagement purposes.

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System

PubMed Central

Liu, Youda; Wang, Xue; Liu, Yanchi; Cui, Sujin

2016-01-01

Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems. PMID:27548171

Context-based user grouping for multi-casting in heterogeneous radio networks

NASA Astrophysics Data System (ADS)

Mannweiler, C.; Klein, A.; Schneider, J.; Schotten, H. D.

2011-08-01

Along with the rise of sophisticated smartphones and smart spaces, the availability of both static and dynamic context information has steadily been increasing in recent years. Due to the popularity of social networks, these data are complemented by profile information about individual users. Making use of this information by classifying users in wireless networks enables targeted content and advertisement delivery as well as optimizing network resources, in particular bandwidth utilization, by facilitating group-based multi-casting. In this paper, we present the design and implementation of a web service for advanced user classification based on user, network, and environmental context information. The service employs simple and advanced clustering algorithms for forming classes of users. Available service functionalities include group formation, context-aware adaptation, and deletion as well as the exposure of group characteristics. Moreover, the results of a performance evaluation, where the service has been integrated in a simulator modeling user behavior in heterogeneous wireless systems, are presented.

Virtual Social Network Communities: An Investigation of Language Learners' Development of Sociopragmatic Awareness and Multiliteracy Skills

ERIC Educational Resources Information Center

Blattner, Geraldine; Fiori, Melissa

2011-01-01

Although often neglected in language textbooks and classrooms, sociopragmatic and multiliteracy skills are crucial elements in language learning that language educators should not disregard. This article investigates whether a social networking community (SNC) website such as Facebook can be exploited in the context of an intermediate foreign…

Context Aware Routing Management Architecture for Airborne Networks

DTIC Science & Technology

2012-03-22

awareness, increased survivability, 2 higher operation tempo , greater lethality, improve speed of command and certain degree of self-synchronization [35...first two sets of experiments. This error model simulates deviations from predetermined routes as well as variations on signal strength for radio...routes computed using Maximum Concurrent Multi-Commodity flow algorithm are not susceptible to rapid topology variations induced by noise. 57 5

Internet of Things: A Review of Surveys Based on Context Aware Intelligent Services.

PubMed

Gil, David; Ferrández, Antonio; Mora-Mora, Higinio; Peral, Jesús

2016-07-11

The Internet of Things (IoT) has made it possible for devices around the world to acquire information and store it, in order to be able to use it at a later stage. However, this potential opportunity is often not exploited because of the excessively big interval between the data collection and the capability to process and analyse it. In this paper, we review the current IoT technologies, approaches and models in order to discover what challenges need to be met to make more sense of data. The main goal of this paper is to review the surveys related to IoT in order to provide well integrated and context aware intelligent services for IoT. Moreover, we present a state-of-the-art of IoT from the context aware perspective that allows the integration of IoT and social networks in the emerging Social Internet of Things (SIoT) term.

A Context-Aware Paradigm for Information Discovery and Dissemination in Mobile Environments

ERIC Educational Resources Information Center

Lundquist, Doug

2011-01-01

The increasing power and ubiquity of mobile wireless devices is enabling real-time information delivery for many diverse applications. A crucial question is how to allocate finite network resources efficiently and fairly despite the uncertainty common in highly dynamic mobile ad hoc networks. We propose a set of routing protocols, Self-Balancing…

Network-Based Learning and Assessment Applications on the Semantic Web

ERIC Educational Resources Information Center

Gibson, David

2005-01-01

Today's Web applications are already "aware" of the network of computers and data on the Internet, in the sense that they perceive, remember, and represent knowledge external to themselves. However, Web applications are generally not able to respond to the meaning and context of the information in their memories. As a result, most applications are…

A Methodology and a Web Platform for the Collaborative Development of Context-Aware Systems

PubMed Central

Martín, David; López-de-Ipiña, Diego; Alzua-Sorzabal, Aurkene; Lamsfus, Carlos; Torres-Manzanera, Emilio

2013-01-01

Information and services personalization is essential for an optimal user experience. Systems have to be able to acquire data about the user's context, process them in order to identify the user's situation and finally, adapt the functionality of the system to that situation, but the development of context-aware systems is complex. Data coming from distributed and heterogeneous sources have to be acquired, processed and managed. Several programming frameworks have been proposed in order to simplify the development of context-aware systems. These frameworks offer high-level application programming interfaces for programmers that complicate the involvement of domain experts in the development life-cycle. The participation of users that do not have programming skills but are experts in the application domain can speed up and improve the development process of these kinds of systems. Apart from that, there is a lack of methodologies to guide the development process. This article presents as main contributions, the implementation and evaluation of a web platform and a methodology to collaboratively develop context-aware systems by programmers and domain experts. PMID:23666131

Distributed Pervasive Worlds: The Case of Exergames

ERIC Educational Resources Information Center

Laine, Teemu H.; Sedano, Carolina Islas

2015-01-01

Pervasive worlds are computing environments where a virtual world converges with the physical world through context-aware technologies such as sensors. In pervasive worlds, technology is distributed among entities that may be distributed geographically. We explore the concept, possibilities, and challenges of distributed pervasive worlds in a case…

Mobile Tracking and Location Awareness in Disaster Relief and Humanitarian Assistance Situations

DTIC Science & Technology

2012-09-01

establishing mobile ad - hoc networks. Smartphones also have accelerometers that are used to detect any motion by the device. Furthermore, almost every...AVAILABILITY STATEMENT Approved for public release; distribution is unlimited 12b. DISTRIBUTION CODE A 13. ABSTRACT (maximum 200 words...Picture, Situational Awareness 15. NUMBER OF PAGES 55 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY

A Distributed Energy-Aware Trust Management System for Secure Routing in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Stelios, Yannis; Papayanoulas, Nikos; Trakadas, Panagiotis; Maniatis, Sotiris; Leligou, Helen C.; Zahariadis, Theodore

Wireless sensor networks are inherently vulnerable to security attacks, due to their wireless operation. The situation is further aggravated because they operate in an infrastructure-less environment, which mandates the cooperation among nodes for all networking tasks, including routing, i.e. all nodes act as “routers”, forwarding the packets generated by their neighbours in their way to the sink node. This implies that malicious nodes (denying their cooperation) can significantly affect the network operation. Trust management schemes provide a powerful tool for the detection of unexpected node behaviours (either faulty or malicious). Once misbehaving nodes are detected, their neighbours can use this information to avoid cooperating with them either for data forwarding, data aggregation or any other cooperative function. We propose a secure routing solution based on a novel distributed trust management system, which allows for fast detection of a wide set of attacks and also incorporates energy awareness.

QoS and energy aware cooperative routing protocol for wildfire monitoring wireless sensor networks.

PubMed

Maalej, Mohamed; Cherif, Sofiane; Besbes, Hichem

2013-01-01

Wireless sensor networks (WSN) are presented as proper solution for wildfire monitoring. However, this application requires a design of WSN taking into account the network lifetime and the shadowing effect generated by the trees in the forest environment. Cooperative communication is a promising solution for WSN which uses, at each hop, the resources of multiple nodes to transmit its data. Thus, by sharing resources between nodes, the transmission quality is enhanced. In this paper, we use the technique of reinforcement learning by opponent modeling, optimizing a cooperative communication protocol based on RSSI and node energy consumption in a competitive context (RSSI/energy-CC), that is, an energy and quality-of-service aware-based cooperative communication routing protocol. Simulation results show that the proposed algorithm performs well in terms of network lifetime, packet delay, and energy consumption.

Cost-aware request routing in multi-geography cloud data centres using software-defined networking

NASA Astrophysics Data System (ADS)

Yuan, Haitao; Bi, Jing; Li, Bo Hu; Tan, Wei

2017-03-01

Current geographically distributed cloud data centres (CDCs) require gigantic energy and bandwidth costs to provide multiple cloud applications to users around the world. Previous studies only focus on energy cost minimisation in distributed CDCs. However, a CDC provider needs to deliver gigantic data between users and distributed CDCs through internet service providers (ISPs). Geographical diversity of bandwidth and energy costs brings a highly challenging problem of how to minimise the total cost of a CDC provider. With the recently emerging software-defined networking, we study the total cost minimisation problem for a CDC provider by exploiting geographical diversity of energy and bandwidth costs. We formulate the total cost minimisation problem as a mixed integer non-linear programming (MINLP). Then, we develop heuristic algorithms to solve the problem and to provide a cost-aware request routing for joint optimisation of the selection of ISPs and the number of servers in distributed CDCs. Besides, to tackle the dynamic workload in distributed CDCs, this article proposes a regression-based workload prediction method to obtain future incoming workload. Finally, this work evaluates the cost-aware request routing by trace-driven simulation and compares it with the existing approaches to demonstrate its effectiveness.

An energy-aware routing protocol for query-based applications in wireless sensor networks.

PubMed

Ahvar, Ehsan; Ahvar, Shohreh; Lee, Gyu Myoung; Crespi, Noel

2014-01-01

Wireless sensor network (WSN) typically has energy consumption restriction. Designing energy-aware routing protocol can significantly reduce energy consumption in WSNs. Energy-aware routing protocols can be classified into two categories, energy savers and energy balancers. Energy saving protocols are used to minimize the overall energy consumed by a WSN, while energy balancing protocols attempt to efficiently distribute the consumption of energy throughout the network. In general terms, energy saving protocols are not necessarily good at balancing energy consumption and energy balancing protocols are not always good at reducing energy consumption. In this paper, we propose an energy-aware routing protocol (ERP) for query-based applications in WSNs, which offers a good trade-off between traditional energy balancing and energy saving objectives and supports a soft real time packet delivery. This is achieved by means of fuzzy sets and learning automata techniques along with zonal broadcasting to decrease total energy consumption.

An Energy-Aware Routing Protocol for Query-Based Applications in Wireless Sensor Networks

PubMed Central

Crespi, Noel

2014-01-01

Wireless sensor network (WSN) typically has energy consumption restriction. Designing energy-aware routing protocol can significantly reduce energy consumption in WSNs. Energy-aware routing protocols can be classified into two categories, energy savers and energy balancers. Energy saving protocols are used to minimize the overall energy consumed by a WSN, while energy balancing protocols attempt to efficiently distribute the consumption of energy throughout the network. In general terms, energy saving protocols are not necessarily good at balancing energy consumption and energy balancing protocols are not always good at reducing energy consumption. In this paper, we propose an energy-aware routing protocol (ERP) for query-based applications in WSNs, which offers a good trade-off between traditional energy balancing and energy saving objectives and supports a soft real time packet delivery. This is achieved by means of fuzzy sets and learning automata techniques along with zonal broadcasting to decrease total energy consumption. PMID:24696640

Internet of Things: A Review of Surveys Based on Context Aware Intelligent Services

PubMed Central

Gil, David; Ferrández, Antonio; Mora-Mora, Higinio; Peral, Jesús

2016-01-01

The Internet of Things (IoT) has made it possible for devices around the world to acquire information and store it, in order to be able to use it at a later stage. However, this potential opportunity is often not exploited because of the excessively big interval between the data collection and the capability to process and analyse it. In this paper, we review the current IoT technologies, approaches and models in order to discover what challenges need to be met to make more sense of data. The main goal of this paper is to review the surveys related to IoT in order to provide well integrated and context aware intelligent services for IoT. Moreover, we present a state-of-the-art of IoT from the context aware perspective that allows the integration of IoT and social networks in the emerging Social Internet of Things (SIoT) term. PMID:27409623

Integrated coding-aware intra-ONU scheduling for passive optical networks with inter-ONU traffic

NASA Astrophysics Data System (ADS)

Li, Yan; Dai, Shifang; Wu, Weiwei

2016-12-01

Recently, with the soaring of traffic among optical network units (ONUs), network coding (NC) is becoming an appealing technique for improving the performance of passive optical networks (PONs) with such inter-ONU traffic. However, in the existed NC-based PONs, NC can only be implemented by buffering inter-ONU traffic at the optical line terminal (OLT) to wait for the establishment of coding condition, such passive uncertain waiting severely limits the effect of NC technique. In this paper, we will study integrated coding-aware intra-ONU scheduling in which the scheduling of inter-ONU traffic within each ONU will be undertaken by the OLT to actively facilitate the forming of coding inter-ONU traffic based on the global inter-ONU traffic distribution, and then the performance of PONs with inter-ONU traffic can be significantly improved. We firstly design two report message patterns and an inter-ONU traffic transmission framework as the basis for the integrated coding-aware intra-ONU scheduling. Three specific scheduling strategies are then proposed for adapting diverse global inter-ONU traffic distributions. The effectiveness of the work is finally evaluated by both theoretical analysis and simulations.

Crosstalk-aware virtual network embedding over inter-datacenter optical networks with few-mode fibers

NASA Astrophysics Data System (ADS)

Huang, Haibin; Guo, Bingli; Li, Xin; Yin, Shan; Zhou, Yu; Huang, Shanguo

2017-12-01

Virtualization of datacenter (DC) infrastructures enables infrastructure providers (InPs) to provide novel services like virtual networks (VNs). Furthermore, optical networks have been employed to connect the metro-scale geographically distributed DCs. The synergistic virtualization of the DC infrastructures and optical networks enables the efficient VN service over inter-DC optical networks (inter-DCONs). While the capacity of the used standard single-mode fiber (SSMF) is limited by their nonlinear characteristics. Thus, mode-division multiplexing (MDM) technology based on few-mode fibers (FMFs) could be employed to increase the capacity of optical networks. Whereas, modal crosstalk (XT) introduced by optical fibers and components deployed in the MDM optical networks impacts the performance of VN embedding (VNE) over inter-DCONs with FMFs. In this paper, we propose a XT-aware VNE mechanism over inter-DCONs with FMFs. The impact of XT is considered throughout the VNE procedures. The simulation results show that the proposed XT-aware VNE can achieves better performances of blocking probability and spectrum utilization compared to conventional VNE mechanisms.

Cortical network architecture for context processing in primate brain

PubMed Central

Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

2015-01-01

Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition. DOI: http://dx.doi.org/10.7554/eLife.06121.001 PMID:26416139

Mapping one strong 'Ohana: using network analysis and GIS to enhance the effectiveness of a statewide coalition to prevent child abuse and neglect.

PubMed

Cardazone, Gina; U Sy, Angela; Chik, Ivan; Corlew, Laura Kate

2014-06-01

Network analysis and GIS enable the presentation of meaningful data about organizational relationships and community characteristics, respectively. Together, these tools can provide a concrete representation of the ecological context in which coalitions operate, and may help coalitions identify opportunities for growth and enhanced effectiveness. This study uses network analysis and GIS mapping as part of an evaluation of the One Strong 'Ohana (OSO) campaign. The OSO campaign was launched in 2012 via a partnership between the Hawai'i Children's Trust Fund (HCTF) and the Joyful Heart Foundation. The OSO campaign uses a collaborative approach aimed at increasing public awareness of child maltreatment and protective factors that can prevent maltreatment, as well as enhancing the effectiveness of the HCTF Coalition. This study focuses on three elements of the OSO campaign evaluation: (1) Network analysis exploring the relationships between 24 active Coalition member organizations, (2) GIS mapping of responses to a randomized statewide phone survey (n = 1,450) assessing awareness of factors contributing to child maltreatment, and (3) Combined GIS maps and network data, illustrating opportunities for geographically-targeted coalition building and public awareness activities.

Does a brief state mindfulness induction moderate disgust-driven social avoidance and decision-making? An experimental investigation.

PubMed

Reynolds, Lisa M; Lin, Yee Sing; Zhou, Eric; Consedine, Nathan S

2015-02-01

In this experimental study, we evaluated whether manipulated disgust and mindfulness predicted social avoidance in bowel health contexts. Community participants (n = 101) were randomised to conditions in which disgust and/or state mindfulness were experimentally induced. Tasks assessing social avoidance and perceptions of available social networks in the context of bowel/health problems were conducted. Manipulation checks confirmed the elicitation of disgust and state mindfulness in the applicable conditions. As expected, persons in the disgust condition were more likely to exhibit immediate social avoidance (rejecting a glass of water). State disgust predicted greater socially avoidant decision-making, less decisional conflict, and smaller social network maps. State mindfulness predicted fewer names on inner network circles and amplified the effect of disgust on creating smaller social network maps. This report furthers understanding of disgust and avoidance in bowel health contexts, and suggests the need for caution in mindfulness interventions that raise awareness of emotion without also providing skills in emotional regulation.

Study on Dissemination Patterns in Location-Aware Gossiping Networks

NASA Astrophysics Data System (ADS)

Kami, Nobuharu; Baba, Teruyuki; Yoshikawa, Takashi; Morikawa, Hiroyuki

We study the properties of information dissemination over location-aware gossiping networks leveraging location-based real-time communication applications. Gossiping is a promising method for quickly disseminating messages in a large-scale system, but in its application to information dissemination for location-aware applications, it is important to consider the network topology and patterns of spatial dissemination over the network in order to achieve effective delivery of messages to potentially interested users. To this end, we propose a continuous-space network model extended from Kleinberg's small-world model applicable to actual location-based applications. Analytical and simulation-based study shows that the proposed network achieves high dissemination efficiency resulting from geographically neutral dissemination patterns as well as selective dissemination to proximate users. We have designed a highly scalable location management method capable of promptly updating the network topology in response to node movement and have implemented a distributed simulator to perform dynamic target pursuit experiments as one example of applications that are the most sensitive to message forwarding delay. The experimental results show that the proposed network surpasses other types of networks in pursuit efficiency and achieves the desirable dissemination patterns.

Joint modality fusion and temporal context exploitation for semantic video analysis

NASA Astrophysics Data System (ADS)

Papadopoulos, Georgios Th; Mezaris, Vasileios; Kompatsiaris, Ioannis; Strintzis, Michael G.

2011-12-01

In this paper, a multi-modal context-aware approach to semantic video analysis is presented. Overall, the examined video sequence is initially segmented into shots and for every resulting shot appropriate color, motion and audio features are extracted. Then, Hidden Markov Models (HMMs) are employed for performing an initial association of each shot with the semantic classes that are of interest separately for each modality. Subsequently, a graphical modeling-based approach is proposed for jointly performing modality fusion and temporal context exploitation. Novelties of this work include the combined use of contextual information and multi-modal fusion, and the development of a new representation for providing motion distribution information to HMMs. Specifically, an integrated Bayesian Network is introduced for simultaneously performing information fusion of the individual modality analysis results and exploitation of temporal context, contrary to the usual practice of performing each task separately. Contextual information is in the form of temporal relations among the supported classes. Additionally, a new computationally efficient method for providing motion energy distribution-related information to HMMs, which supports the incorporation of motion characteristics from previous frames to the currently examined one, is presented. The final outcome of this overall video analysis framework is the association of a semantic class with every shot. Experimental results as well as comparative evaluation from the application of the proposed approach to four datasets belonging to the domains of tennis, news and volleyball broadcast video are presented.

Characterizing team performance in network-centric operations: philosophical and methodological issues.

PubMed

Bolia, Robert S; Nelson, W Todd

2007-05-01

The recently promulgated doctrine of network-centric warfare suggests that increases in shared situation awareness and self-synchronization will be emergent properties of densely connected military networks. What it fails to say is how these enhancements are to be measured. The present article frames the discussion as a question of how to characterize team performance, and considers such performance in the context of its hypothetical components: situation awareness, workload, and error. This examination concludes that reliable measures of these constructs are lacking for teams, even when they exist for individual operators, and that this is due to philosophical and/or methodological flaws in their conceptual development. Additional research is recommended to overcome these deficiencies, as well as consideration of novel multidisciplinary approaches that draw on methodologies employed in the social, physical, and biological sciences.

Dividing the Self: Distinct Neural Substrates of Task-Based and Automatic Self-Prioritization after Brain Damage

ERIC Educational Resources Information Center

Sui, Jie; Chechlacz, Magdalena; Humphreys, Glyn W.

2012-01-01

Facial self-awareness is a basic human ability dependent on a distributed bilateral neural network and revealed through prioritized processing of our own over other faces. Using non-prosopagnosic patients we show, for the first time, that facial self-awareness can be fractionated into different component processes. Patients performed two face…

Marketing complementary foods and supplements in Burkina Faso, Madagascar, and Vietnam: lessons learned from the Nutridev program.

PubMed

Bruyeron, Olivier; Denizeau, Mirrdyn; Berger, Jacques; Trèche, Serge

2010-06-01

Sustainable approaches to improving infant and young child feeding are needed. The Nutridev program worked in Vietnam, Madagascar, and Burkina Faso to test different strategies to improve complementary feeding using fortified products sold to families. To review the experiences of programs producing and marketing fortified complementary foods and to report on the feasibility of local production and marketing of fortified complementary foods to increase usage of high-quality foods among children of low-income families in a self-sustaining manner. Project documents, surveys of mothers, and production and sales reports were reviewed. Nutridev experience in Vietnam, Madagascar, and Burkina Faso demonstrates that it is possible to produce affordable, high-quality complementary foods and supplements locally in developing countries. Strategies to make products readily available to the targeted population and to convince this population to consume them yielded mixed results, varying greatly based on the strategy utilized and the context in which it was implemented. In several contexts, the optimal approach appears to be strengthening the existing food distribution network to sell complementary foods and supplements, with the implementation of a temporary promotion and nutrition education network in partnership with local authorities (e.g., health services) to increase awareness among families about the fortified complementary food product and optimal feeding practices. In urban areas, where the density of the population is high, design and implementation of specific networks very close to consumers seems to be a good way to combine economic sustainability and good consumption levels.

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems.

PubMed

Munera, Eduardo; Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Noguera, Juan Fco Blanes

2015-07-24

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client's requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client's requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

Reliable Adaptive Video Streaming Driven by Perceptual Semantics for Situational Awareness

PubMed Central

Pimentel-Niño, M. A.; Saxena, Paresh; Vazquez-Castro, M. A.

2015-01-01

A novel cross-layer optimized video adaptation driven by perceptual semantics is presented. The design target is streamed live video to enhance situational awareness in challenging communications conditions. Conventional solutions for recreational applications are inadequate and novel quality of experience (QoE) framework is proposed which allows fully controlled adaptation and enables perceptual semantic feedback. The framework relies on temporal/spatial abstraction for video applications serving beyond recreational purposes. An underlying cross-layer optimization technique takes into account feedback on network congestion (time) and erasures (space) to best distribute available (scarce) bandwidth. Systematic random linear network coding (SRNC) adds reliability while preserving perceptual semantics. Objective metrics of the perceptual features in QoE show homogeneous high performance when using the proposed scheme. Finally, the proposed scheme is in line with content-aware trends, by complying with information-centric-networking philosophy and architecture. PMID:26247057

On detection and visualization techniques for cyber security situation awareness

NASA Astrophysics Data System (ADS)

Yu, Wei; Wei, Shixiao; Shen, Dan; Blowers, Misty; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe; Zhang, Hanlin; Lu, Chao

2013-05-01

Networking technologies are exponentially increasing to meet worldwide communication requirements. The rapid growth of network technologies and perversity of communications pose serious security issues. In this paper, we aim to developing an integrated network defense system with situation awareness capabilities to present the useful information for human analysts. In particular, we implement a prototypical system that includes both the distributed passive and active network sensors and traffic visualization features, such as 1D, 2D and 3D based network traffic displays. To effectively detect attacks, we also implement algorithms to transform real-world data of IP addresses into images and study the pattern of attacks and use both the discrete wavelet transform (DWT) based scheme and the statistical based scheme to detect attacks. Through an extensive simulation study, our data validate the effectiveness of our implemented defense system.

On Iranian EFL Learners' Pragmatic Competence and Appropriate Use of "Request" in English Contexts

ERIC Educational Resources Information Center

Aliakbari, Mohammad; Gheitasi, Mojtaba

2014-01-01

This paper investigated the extent to which Iranian EFL students are aware of the appropriate use of request speech act in English speaking contexts in terms of formality, politeness and indirectness. A researcher made discourse completion test (DCT) including 16 scenarios was distributed among 130 advanced students in private English institutes…

AI Techniques in a Context-Aware Ubiquitous Environment

NASA Astrophysics Data System (ADS)

Coppola, Paolo; Mea, Vincenzo Della; di Gaspero, Luca; Lomuscio, Raffaella; Mischis, Danny; Mizzaro, Stefano; Nazzi, Elena; Scagnetto, Ivan; Vassena, Luca

Nowadays, the mobile computing paradigm and the widespread diffusion of mobile devices are quickly changing and replacing many common assumptions about software architectures and interaction/communication models. The environment, in particular, or more generally, the so-called user context is claiming a central role in everyday’s use of cellular phones, PDAs, etc. This is due to the huge amount of data “suggested” by the surrounding environment that can be helpful in many common tasks. For instance, the current context can help a search engine to refine the set of results in a useful way, providing the user with a more suitable and exploitable information. Moreover, we can take full advantage of this new data source by “pushing” active contents towards mobile devices, empowering the latter with new features (e.g., applications) that can allow the user to fruitfully interact with the current context. Following this vision, mobile devices become dynamic self-adapting tools, according to the user needs and the possibilities offered by the environment. The present work proposes MoBe: an approach for providing a basic infrastructure for pervasive context-aware applications on mobile devices, in which AI techniques (namely a principled combination of rule-based systems, Bayesian networks and ontologies) are applied to context inference. The aim is to devise a general inferential framework to make easier the development of context-aware applications by integrating the information coming from physical and logical sensors (e.g., position, agenda) and reasoning about this information in order to infer new and more abstract contexts.

Distributed Computer Networks in Support of Complex Group Practices

PubMed Central

Wess, Bernard P.

1978-01-01

The economics of medical computer networks are presented in context with the patient care and administrative goals of medical networks. Design alternatives and network topologies are discussed with an emphasis on medical network design requirements in distributed data base design, telecommunications, satellite systems, and software engineering. The success of the medical computer networking technology is predicated on the ability of medical and data processing professionals to design comprehensive, efficient, and virtually impenetrable security systems to protect data bases, network access and services, and patient confidentiality.

Leveraging Large-Scale Semantic Networks for Adaptive Robot Task Learning and Execution.

PubMed

Boteanu, Adrian; St Clair, Aaron; Mohseni-Kabir, Anahita; Saldanha, Carl; Chernova, Sonia

2016-12-01

This work seeks to leverage semantic networks containing millions of entries encoding assertions of commonsense knowledge to enable improvements in robot task execution and learning. The specific application we explore in this project is object substitution in the context of task adaptation. Humans easily adapt their plans to compensate for missing items in day-to-day tasks, substituting a wrap for bread when making a sandwich, or stirring pasta with a fork when out of spoons. Robot plan execution, however, is far less robust, with missing objects typically leading to failure if the robot is not aware of alternatives. In this article, we contribute a context-aware algorithm that leverages the linguistic information embedded in the task description to identify candidate substitution objects without reliance on explicit object affordance information. Specifically, we show that the task context provided by the task labels within the action structure of a task plan can be leveraged to disambiguate information within a noisy large-scale semantic network containing hundreds of potential object candidates to identify successful object substitutions with high accuracy. We present two extensive evaluations of our work on both abstract and real-world robot tasks, showing that the substitutions made by our system are valid, accepted by users, and lead to a statistically significant reduction in robot learning time. In addition, we report the outcomes of testing our approach with a large number of crowd workers interacting with a robot in real time.

On the Statistical Errors of RADAR Location Sensor Networks with Built-In Wi-Fi Gaussian Linear Fingerprints

PubMed Central

Zhou, Mu; Xu, Yu Bin; Ma, Lin; Tian, Shuo

2012-01-01

The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis. PMID:22737027

On the statistical errors of RADAR location sensor networks with built-in Wi-Fi Gaussian linear fingerprints.

PubMed

Zhou, Mu; Xu, Yu Bin; Ma, Lin; Tian, Shuo

2012-01-01

The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.

A Distributed Ambient Intelligence Based Multi-Agent System for Alzheimer Health Care

NASA Astrophysics Data System (ADS)

Tapia, Dante I.; RodríGuez, Sara; Corchado, Juan M.

This chapter presents ALZ-MAS (Alzheimer multi-agent system), an ambient intelligence (AmI)-based multi-agent system aimed at enhancing the assistance and health care for Alzheimer patients. The system makes use of several context-aware technologies that allow it to automatically obtain information from users and the environment in an evenly distributed way, focusing on the characteristics of ubiquity, awareness, intelligence, mobility, etc., all of which are concepts defined by AmI. ALZ-MAS makes use of a services oriented multi-agent architecture, called flexible user and services oriented multi-agent architecture, to distribute resources and enhance its performance. It is demonstrated that a SOA approach is adequate to build distributed and highly dynamic AmI-based multi-agent systems.

Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics

PubMed Central

Sagl, Günther; Blaschke, Thomas; Beinat, Euro; Resch, Bernd

2012-01-01

Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. PMID:23012571

Context Aware Middleware Architectures: Survey and Challenges

PubMed Central

Li, Xin; Eckert, Martina; Martinez, José-Fernán; Rubio, Gregorio

2015-01-01

Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work. PMID:26307988

A Distributed Value of Information (VoI)-Based Approach for Mission-Adaptive Context-Aware Information Management and Presentation

DTIC Science & Technology

2016-05-16

metrics involve regulating automation of complex systems , such as aircraft .12 Additionally, adaptive management of content in user interfaces has also...both the user and environmental context would aid in deciding how to present the information to the Warfighter. The prototype system currently...positioning system , and rate sensors can provide user - specific context to disambiguate physiologic data. The consumer “quantified self” market has driven

Maximising the Highs and Minimising the Lows: Harm Reduction Guidance within Ecstasy Distribution Networks

PubMed Central

Duterte, Micheline; Sales, Paloma; Murphy, Sheigla

2008-01-01

Background Little is known about how users build and share knowledge concerning the highs and lows of Ecstasy and the role that Ecstasy sellers play in the exchange of this information. Methods These findings are based on a National Institute on Drug Abuse-funded project, “An Exploratory Study of Ecstasy Distribution,” conducted between 2003 and 2006. We completed in-depth interviews with 120 men and women in the San Francisco Bay Area who had sold 5 or more doses 5 or more times in the 6 months prior to the interview. The research focused on buyer-seller relationships and the influence of these relationships on users’ health. Results Users constructed harm reduction strategies in attempts to maximise the Ecstasy high and minimise the risks. The social context of Ecstasy use allowed for the exchange of harm reduction information and advice on how to maximise the pleasurable aspects of Ecstasy. Some participants served as “guides” to ensure that their customers had safe and enjoyable experiences while using Ecstasy. Conclusion These findings suggest that Ecstasy sellers are important points of intervention for the dissemination of harm reduction information as friendship networks were the primary link in creating awareness of safer Ecstasy use. PMID:17964771

Symposium on Applications and the Internet (SAINT 2003) Proceedings (Orlando, Florida, January 27-31, 2003).

ERIC Educational Resources Information Center

Helal, Sumi, Ed.; Oie, Yuji, Ed.; Chang, Carl, Ed.; Murai, Jun, Ed.

This proceedings from the 2003 Symposium on Applications and the Internet (SAINT) contains papers from sessions on: (1) mobile Internet, including a target-driven cache replacement policy, context-awareness for service discovery, and XML transformation; (2) collaboration technology I, including human-network-based filtering, virtual collaboration…

Intergenerational Learning and Social Capital. ERIC Digest.

ERIC Educational Resources Information Center

Kerka, Sandra

The concept of social capital refers to the resources of networks, norms or shared values, and trust to which individuals have access as community members. A reason to consider intergenerational learning in the context of social capital is awareness of unequal access to positive social capital and the risk that social exclusion and disadvantage…

A Context-Aware Mobile User Behavior-Based Neighbor Finding Approach for Preference Profile Construction †

PubMed Central

Gao, Qian; Fu, Deqian; Dong, Xiangjun

2016-01-01

In this paper, a new approach is adopted to update the user preference profile by seeking users with similar interests based on the context obtainable for a mobile network instead of from desktop networks. The trust degree between mobile users is calculated by analyzing their behavior based on the context, and then the approximate neighbors are chosen by combining the similarity of the mobile user preference and the trust degree. The approach first considers the communication behaviors between mobile users, the mobile network services they use as well as the corresponding context information. Then a similarity degree of the preference between users is calculated with the evaluation score of a certain mobile web service provided by a mobile user. Finally, based on the time attenuation function, the users with similar preference are found, through which we can dynamically update the target user’s preference profile. Experiments are then conducted to test the effect of the context on the credibility among mobile users, the effect of time decay factors and trust degree thresholds. Simulation shows that the proposed approach outperforms two other methods in terms of Recall Ratio, Precision Ratio and Mean Absolute Error, because neither of them consider the context mobile information. PMID:26805852

Context-Sensitive Detection of Local Community Structure

DTIC Science & Technology

2011-04-01

characters in the Victor Hugo novel Les Miserables (lesmis).[77 vertices, 254 edges] [Knu93]. • The neural network of the nematode C. Elegans (c.elegans...adjectives and nouns in the Novel David Cop- perfield by Charles Dickens.[112 vertices, 425 edges] [New06]. • Les Miserables . Co-appearance network of...exponential distribution. The degree distributions of the Network Science, Les Miserables , and Word Adjacencies networks display a similar heavy tail. By

A Neural Network Aero Design System for Advanced Turbo-Engines

NASA Technical Reports Server (NTRS)

Sanz, Jose M.

1999-01-01

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Cooperative Management of a Lithium-Ion Battery Energy Storage Network: A Distributed MPC Approach

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

Fang, Huazhen; Wu, Di; Yang, Tao

2016-12-12

This paper presents a study of cooperative power supply and storage for a network of Lithium-ion energy storage systems (LiBESSs). We propose to develop a distributed model predictive control (MPC) approach for two reasons. First, able to account for the practical constraints of a LiBESS, the MPC can enable a constraint-aware operation. Second, a distributed management can cope with a complex network that integrates a large number of LiBESSs over a complex communication topology. With this motivation, we then build a fully distributed MPC algorithm from an optimization perspective, which is based on an extension of the alternating direction methodmore » of multipliers (ADMM) method. A simulation example is provided to demonstrate the effectiveness of the proposed algorithm.« less

Towards an integrated defense system for cyber security situation awareness experiment

NASA Astrophysics Data System (ADS)

Zhang, Hanlin; Wei, Sixiao; Ge, Linqiang; Shen, Dan; Yu, Wei; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe

2015-05-01

In this paper, an implemented defense system is demonstrated to carry out cyber security situation awareness. The developed system consists of distributed passive and active network sensors designed to effectively capture suspicious information associated with cyber threats, effective detection schemes to accurately distinguish attacks, and network actors to rapidly mitigate attacks. Based on the collected data from network sensors, image-based and signals-based detection schemes are implemented to detect attacks. To further mitigate attacks, deployed dynamic firewalls on hosts dynamically update detection information reported from the detection schemes and block attacks. The experimental results show the effectiveness of the proposed system. A future plan to design an effective defense system is also discussed based on system theory.

QOS-aware error recovery in wireless body sensor networks using adaptive network coding.

PubMed

Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah

2014-12-29

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

On effectiveness of network sensor-based defense framework

NASA Astrophysics Data System (ADS)

Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh

2012-06-01

Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

Context-aware personal navigation using embedded sensor fusion in smartphones.

PubMed

Saeedi, Sara; Moussa, Adel; El-Sheimy, Naser

2014-03-25

Context-awareness is an interesting topic in mobile navigation scenarios where the context of the application is highly dynamic. Using context-aware computing, navigation services consider the situation of user, not only in the design process, but in real time while the device is in use. The basic idea is that mobile navigation services can provide different services based on different contexts-where contexts are related to the user's activity and the device placement. Context-aware systems are concerned with the following challenges which are addressed in this paper: context acquisition, context understanding, and context-aware application adaptation. The proposed approach in this paper is using low-cost sensors in a multi-level fusion scheme to improve the accuracy and robustness of context-aware navigation system. The experimental results demonstrate the capabilities of the context-aware Personal Navigation Systems (PNS) for outdoor personal navigation using a smartphone.

Cyber situation awareness as distributed socio-cognitive work

NASA Astrophysics Data System (ADS)

Tyworth, Michael; Giacobe, Nicklaus A.; Mancuso, Vincent

2012-06-01

A key challenge for human cybersecurity operators is to develop an understanding of what is happening within, and to, their network. This understanding, or situation awareness, provides the cognitive basis for human operators to take action within their environments. Yet developing situation awareness of cyberspace (cyber-SA) is understood to be extremely difficult given the scope of the operating environment, the highly dynamic nature of the environment and the absence of physical constraints that serve to bound the cognitive task23. As a result, human cybersecurity operators are often "flying blind" regarding understanding the source, nature, and likely impact of malicious activity on their networked assets. In recent years, many scholars have dedicated their attention to finding ways to improve cyber-SA in human operators. In this paper we present our findings from our ongoing research of how cybersecurity analysts develop and maintain cyber-SA. Drawing from over twenty interviews of analysts working in the military, government, industrial, and educational domains, we find that cyber-SA to be distributed across human operators and technological artifacts operating in different functional areas.

A distributed reasoning engine ecosystem for semantic context-management in smart environments.

PubMed

Almeida, Aitor; López-de-Ipiña, Diego

2012-01-01

To be able to react adequately a smart environment must be aware of the context and its changes. Modeling the context allows applications to better understand it and to adapt to its changes. In order to do this an appropriate formal representation method is needed. Ontologies have proven themselves to be one of the best tools to do it. Semantic inference provides a powerful framework to reason over the context data. But there are some problems with this approach. The inference over semantic context information can be cumbersome when working with a large amount of data. This situation has become more common in modern smart environments where there are a lot sensors and devices available. In order to tackle this problem we have developed a mechanism to distribute the context reasoning problem into smaller parts in order to reduce the inference time. In this paper we describe a distributed peer-to-peer agent architecture of context consumers and context providers. We explain how this inference sharing process works, partitioning the context information according to the interests of the agents, location and a certainty factor. We also discuss the system architecture, analyzing the negotiation process between the agents. Finally we compare the distributed reasoning with the centralized one, analyzing in which situations is more suitable each approach.

Context-Aware Personal Navigation Using Embedded Sensor Fusion in Smartphones

PubMed Central

Saeedi, Sara; Moussa, Adel; El-Sheimy, Naser

2014-01-01

Context-awareness is an interesting topic in mobile navigation scenarios where the context of the application is highly dynamic. Using context-aware computing, navigation services consider the situation of user, not only in the design process, but in real time while the device is in use. The basic idea is that mobile navigation services can provide different services based on different contexts—where contexts are related to the user's activity and the device placement. Context-aware systems are concerned with the following challenges which are addressed in this paper: context acquisition, context understanding, and context-aware application adaptation. The proposed approach in this paper is using low-cost sensors in a multi-level fusion scheme to improve the accuracy and robustness of context-aware navigation system. The experimental results demonstrate the capabilities of the context-aware Personal Navigation Systems (PNS) for outdoor personal navigation using a smartphone. PMID:24670715

Context Relevant Prediction Model for COPD Domain Using Bayesian Belief Network

PubMed Central

Saleh, Lokman; Ajami, Hicham; Mili, Hafedh

2017-01-01

In the last three decades, researchers have examined extensively how context-aware systems can assist people, specifically those suffering from incurable diseases, to help them cope with their medical illness. Over the years, a huge number of studies on Chronic Obstructive Pulmonary Disease (COPD) have been published. However, how to derive relevant attributes and early detection of COPD exacerbations remains a challenge. In this research work, we will use an efficient algorithm to select relevant attributes where there is no proper approach in this domain. Such algorithm predicts exacerbations with high accuracy by adding discretization process, and organizes the pertinent attributes in priority order based on their impact to facilitate the emergency medical treatment. In this paper, we propose an extension of our existing Helper Context-Aware Engine System (HCES) for COPD. This project uses Bayesian network algorithm to depict the dependency between the COPD symptoms (attributes) in order to overcome the insufficiency and the independency hypothesis of naïve Bayesian. In addition, the dependency in Bayesian network is realized using TAN algorithm rather than consulting pneumologists. All these combined algorithms (discretization, selection, dependency, and the ordering of the relevant attributes) constitute an effective prediction model, comparing to effective ones. Moreover, an investigation and comparison of different scenarios of these algorithms are also done to verify which sequence of steps of prediction model gives more accurate results. Finally, we designed and validated a computer-aided support application to integrate different steps of this model. The findings of our system HCES has shown promising results using Area Under Receiver Operating Characteristic (AUC = 81.5%). PMID:28644419

Representing situation awareness in collaborative systems: a case study in the energy distribution domain.

PubMed

Salmon, P M; Stanton, N A; Walker, G H; Jenkins, D; Baber, C; McMaster, R

2008-03-01

The concept of distributed situation awareness (DSA) is currently receiving increasing attention from the human factors community. This article investigates DSA in a collaborative real-world industrial setting by discussing the results derived from a recent naturalistic study undertaken within the UK energy distribution domain. The results describe the DSA-related information used by the networks of agents involved in the scenarios analysed, the sharing of this information between the agents and the salience of different information elements used. Thus, the structure, quality and content of each network's DSA is discussed, along with the implications for DSA theory. The findings reinforce the notion that when viewing situation awareness (SA) in collaborative systems, it is useful to focus on the coordinated behaviour of the system itself, rather than on the individual as the unit of analysis and suggest that the findings from such assessments can potentially be used to inform system, procedure and training design. SA is a critical commodity for teams working in industrial systems and systems, procedures and training programmes should be designed to facilitate efficient system SA acquisition and maintenance. This article presents approaches for describing and understanding SA during real-world collaborative tasks, the outputs from which can potentially be used to inform system, training programmes and procedure design.

Leveraging AMI data for distribution system model calibration and situational awareness

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

Peppanen, Jouni; Reno, Matthew J.; Thakkar, Mohini

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation andmore » regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.« less

Leveraging AMI data for distribution system model calibration and situational awareness

DOE PAGES

Peppanen, Jouni; Reno, Matthew J.; Thakkar, Mohini; ...

2015-01-15

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation andmore » regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.« less

Advanced algorithms for distributed fusion

NASA Astrophysics Data System (ADS)

Gelfand, A.; Smith, C.; Colony, M.; Bowman, C.; Pei, R.; Huynh, T.; Brown, C.

2008-03-01

The US Military has been undergoing a radical transition from a traditional "platform-centric" force to one capable of performing in a "Network-Centric" environment. This transformation will place all of the data needed to efficiently meet tactical and strategic goals at the warfighter's fingertips. With access to this information, the challenge of fusing data from across the batttlespace into an operational picture for real-time Situational Awareness emerges. In such an environment, centralized fusion approaches will have limited application due to the constraints of real-time communications networks and computational resources. To overcome these limitations, we are developing a formalized architecture for fusion and track adjudication that allows the distribution of fusion processes over a dynamically created and managed information network. This network will support the incorporation and utilization of low level tracking information within the Army Distributed Common Ground System (DCGS-A) or Future Combat System (FCS). The framework is based on Bowman's Dual Node Network (DNN) architecture that utilizes a distributed network of interlaced fusion and track adjudication nodes to build and maintain a globally consistent picture across all assets.

Context-Aware Generative Adversarial Privacy

NASA Astrophysics Data System (ADS)

Huang, Chong; Kairouz, Peter; Chen, Xiao; Sankar, Lalitha; Rajagopal, Ram

2017-12-01

Preserving the utility of published datasets while simultaneously providing provable privacy guarantees is a well-known challenge. On the one hand, context-free privacy solutions, such as differential privacy, provide strong privacy guarantees, but often lead to a significant reduction in utility. On the other hand, context-aware privacy solutions, such as information theoretic privacy, achieve an improved privacy-utility tradeoff, but assume that the data holder has access to dataset statistics. We circumvent these limitations by introducing a novel context-aware privacy framework called generative adversarial privacy (GAP). GAP leverages recent advancements in generative adversarial networks (GANs) to allow the data holder to learn privatization schemes from the dataset itself. Under GAP, learning the privacy mechanism is formulated as a constrained minimax game between two players: a privatizer that sanitizes the dataset in a way that limits the risk of inference attacks on the individuals' private variables, and an adversary that tries to infer the private variables from the sanitized dataset. To evaluate GAP's performance, we investigate two simple (yet canonical) statistical dataset models: (a) the binary data model, and (b) the binary Gaussian mixture model. For both models, we derive game-theoretically optimal minimax privacy mechanisms, and show that the privacy mechanisms learned from data (in a generative adversarial fashion) match the theoretically optimal ones. This demonstrates that our framework can be easily applied in practice, even in the absence of dataset statistics.

An Optimized, Data Distribution Service-Based Solution for Reliable Data Exchange Among Autonomous Underwater Vehicles

PubMed Central

Bilbao, Sonia; Martínez, Belén; Frasheri, Mirgita; Cürüklü, Baran

2017-01-01

Major challenges are presented when managing a large number of heterogeneous vehicles that have to communicate underwater in order to complete a global mission in a cooperative manner. In this kind of application domain, sending data through the environment presents issues that surpass the ones found in other overwater, distributed, cyber-physical systems (i.e., low bandwidth, unreliable transport medium, data representation and hardware high heterogeneity). This manuscript presents a Publish/Subscribe-based semantic middleware solution for unreliable scenarios and vehicle interoperability across cooperative and heterogeneous autonomous vehicles. The middleware relies on different iterations of the Data Distribution Service (DDS) software standard and their combined work between autonomous maritime vehicles and a control entity. It also uses several components with different functionalities deemed as mandatory for a semantic middleware architecture oriented to maritime operations (device and service registration, context awareness, access to the application layer) where other technologies are also interweaved with middleware (wireless communications, acoustic networks). Implementation details and test results, both in a laboratory and a deployment scenario, have been provided as a way to assess the quality of the system and its satisfactory performance. PMID:28783049

An Optimized, Data Distribution Service-Based Solution for Reliable Data Exchange Among Autonomous Underwater Vehicles.

PubMed

Rodríguez-Molina, Jesús; Bilbao, Sonia; Martínez, Belén; Frasheri, Mirgita; Cürüklü, Baran

2017-08-05

Major challenges are presented when managing a large number of heterogeneous vehicles that have to communicate underwater in order to complete a global mission in a cooperative manner. In this kind of application domain, sending data through the environment presents issues that surpass the ones found in other overwater, distributed, cyber-physical systems (i.e., low bandwidth, unreliable transport medium, data representation and hardware high heterogeneity). This manuscript presents a Publish/Subscribe-based semantic middleware solution for unreliable scenarios and vehicle interoperability across cooperative and heterogeneous autonomous vehicles. The middleware relies on different iterations of the Data Distribution Service (DDS) software standard and their combined work between autonomous maritime vehicles and a control entity. It also uses several components with different functionalities deemed as mandatory for a semantic middleware architecture oriented to maritime operations (device and service registration, context awareness, access to the application layer) where other technologies are also interweaved with middleware (wireless communications, acoustic networks). Implementation details and test results, both in a laboratory and a deployment scenario, have been provided as a way to assess the quality of the system and its satisfactory performance.

Smart border: ad-hoc wireless sensor networks for border surveillance

NASA Astrophysics Data System (ADS)

He, Jun; Fallahi, Mahmoud; Norwood, Robert A.; Peyghambarian, Nasser

2011-06-01

Wireless sensor networks have been proposed as promising candidates to provide automated monitoring, target tracking, and intrusion detection for border surveillance. In this paper, we demonstrate an ad-hoc wireless sensor network system for border surveillance. The network consists of heterogeneously autonomous sensor nodes that distributively cooperate with each other to enable a smart border in remote areas. This paper also presents energy-aware and sleeping algorithms designed to maximize the operating lifetime of the deployed sensor network. Lessons learned in building the network and important findings from field experiments are shared in the paper.

Team Modelling: Survey of Experimental Platforms (Modelisation d’equipes : Examen de plate-formes experimentales)

DTIC Science & Technology

2006-09-01

Control Force Agility Shared Situational Awareness Attentional Demand Interoperability Network Based Operations Effect Based Operations Speed of...Command Self Synchronization Reach Back Reach Forward Information Superiority Increased Mission Effectiveness Humansystems® Team Modelling...communication effectiveness and Distributed Mission Training (DMT) effectiveness . The NASA Ames Centre - Distributed Research Facilities platform could

Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

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

Simmhan, Yogesh; Agarwal, Vaibhav; Aman, Saim

2012-05-16

Smart Power Grids exemplify an emerging class of Cyber Physical Applications that exhibit dynamic, distributed and data intensive (D3) characteristics along with an always-on paradigm to support operational needs. Smart Grids are an outcome of instrumentation, such as Phasor Measurement Units and Smart Power Meters, that is being deployed across the transmission and distribution network of electric grids. These sensors provide utilities with improved situation awareness on near-realtime electricity usage by individual consumers, and the power quality and stability of the transmission network.

To friend or not to friend: the use of social media in clinical oncology.

PubMed

Wiener, Lori; Crum, Caroline; Grady, Christine; Merchant, Melinda

2012-03-01

Online social networking has replaced more traditional methods of personal and professional communication in many segments of society today. The wide reach and immediacy of social media facilitate dissemination of knowledge in advocacy and cancer education, but the usefulness of social media in personal relationships between patients and providers is still unclear. Although professional guidelines regarding e-mail communication may be relevant to social media, the inherent openness in social networks creates potential boundary and privacy issues in the provider-patient context. This commentary seeks to increase provider awareness of unique issues and challenges raised by the integration of social networking into oncology communications.

"They accept me, because I was one of them": formative qualitative research supporting the feasibility of peer-led outreach for people who use drugs in Dakar, Senegal.

PubMed

Stengel, Camille May; Mane, Famara; Guise, Andrew; Pouye, Magath; Sigrist, Monika; Rhodes, Tim

2018-02-27

Peer outreach harm reduction initiatives are being developed with and for people who use drugs in Dakar, Senegal. This is in response to growing injecting drug use across the West Africa region and linked emerging epidemics of HIV and hepatitis C. We undertook formative qualitative research to explore the feasibility and potential of peer outreach in this context and in particular how outreach could be linked to fostering community-level processes of change. We undertook a total of 44 semi-structured qualitative interviews. Thirty-four interviews were with people who used drugs (comprised of 25 participants who had injected at least once in their life) and included 11 peer educators who delivered "awareness-raising" harm reduction activities. We also interviewed 10 service providers involved in the planning and monitoring of peer outreach initiatives. We used thematic analysis to identify key characteristics of how peer-led outreach is being delivered, beneficiary need, and the nature of the social networks in which the awareness-raising activities operate. Through interviews with peer educators, people who use drugs, and service providers, four main overlapping themes are identified as follows: peer educators as a bridge to responsibilization through awareness-raising activities, awareness-raising activities as an enactment of recovery, awareness raising through social network diffusion, and the contexts and constraints of peer outreach engagement through awareness-raising activities. The study results suggest that peer education is on a trajectory to develop into a central role for harm reduction interventions in Dakar, Senegal. This research shows how peer education is bound in processes of responsibilization and self-change, which link to varying possibilities for risk reduction or recovery. For peer education to achieve a range of significant goals, broader structural and system changes should be implemented in the region. We caution that without such changes, awareness-raising activities and the role of peer educators may instead become part of state- and agency-sponsored processes of seeking to responsibilize individuals for health and harm reduction.

Culturally Aware Agents for Training Environments (CAATE): Phase I Final Report

DTIC Science & Technology

2009-01-01

attitudes, relationships , personality, personal traits, state, social roles, physical context. The initial set of potentially important cultural... relationships that affect culturally situated behavior. For instance, we will want to be able to model interconnections such as familial... relationships , group membership, and attitudes (e.g., trust, dislike). To accomplish this, our design leverages social network modeling technologies provided by

A Vision-Based Approach for Building Telecare and Telerehabilitation Services.

PubMed

Barriga, Angela; Conejero, José M; Hernández, Juan; Jurado, Elena; Moguel, Enrique; Sánchez-Figueroa, Fernando

2016-10-18

In the last few years, telerehabilitation and telecare have become important topics in healthcare since they enable people to remain independent in their own homes by providing person-centered technologies to support the individual. These technologies allows elderly people to be assisted in their home, instead of traveling to a clinic, providing them wellbeing and personalized health care. The literature shows a great number of interesting proposals to address telerehabilitation and telecare scenarios, which may be mainly categorized into two broad groups, namely wearable devices and context-aware systems. However, we believe that these apparently different scenarios may be addressed by a single context-aware approach, concretely a vision-based system that can operate automatically in a non-intrusive way for the elderly, and this is the goal of this paper. We present a general approach based on 3D cameras and neural network algorithms that offers an efficient solution for two different scenarios of telerehabilitation and telecare for elderly people. Our empirical analysis reveals the effectiveness and accuracy of the algorithms presented in our approach and provides more than promising results when the neural network parameters are properly adjusted.

A Vision-Based Approach for Building Telecare and Telerehabilitation Services

PubMed Central

Barriga, Angela; Conejero, José M.; Hernández, Juan; Jurado, Elena; Moguel, Enrique; Sánchez-Figueroa, Fernando

2016-01-01

In the last few years, telerehabilitation and telecare have become important topics in healthcare since they enable people to remain independent in their own homes by providing person-centered technologies to support the individual. These technologies allows elderly people to be assisted in their home, instead of traveling to a clinic, providing them wellbeing and personalized health care. The literature shows a great number of interesting proposals to address telerehabilitation and telecare scenarios, which may be mainly categorized into two broad groups, namely wearable devices and context-aware systems. However, we believe that these apparently different scenarios may be addressed by a single context-aware approach, concretely a vision-based system that can operate automatically in a non-intrusive way for the elderly, and this is the goal of this paper. We present a general approach based on 3D cameras and neural network algorithms that offers an efficient solution for two different scenarios of telerehabilitation and telecare for elderly people. Our empirical analysis reveals the effectiveness and accuracy of the algorithms presented in our approach and provides more than promising results when the neural network parameters are properly adjusted. PMID:27763540

Context Representation and Fusion: Advancements and Opportunities

PubMed Central

Khattak, Asad Masood; Akbar, Noman; Aazam, Mohammad; Ali, Taqdir; Khan, Adil Mehmood; Jeon, Seokhee; Hwang, Myunggwon; Lee, Sungyoung

2014-01-01

The acceptance and usability of context-aware systems have given them the edge of wide use in various domains and has also attracted the attention of researchers in the area of context-aware computing. Making user context information available to such systems is the center of attention. However, there is very little emphasis given to the process of context representation and context fusion which are integral parts of context-aware systems. Context representation and fusion facilitate in recognizing the dependency/relationship of one data source on another to extract a better understanding of user context. The problem is more critical when data is emerging from heterogeneous sources of diverse nature like sensors, user profiles, and social interactions and also at different timestamps. Both the processes of context representation and fusion are followed in one way or another; however, they are not discussed explicitly for the realization of context-aware systems. In other words most of the context-aware systems underestimate the importance context representation and fusion. This research has explicitly focused on the importance of both the processes of context representation and fusion and has streamlined their existence in the overall architecture of context-aware systems’ design and development. Various applications of context representation and fusion in context-aware systems are also highlighted in this research. A detailed review on both the processes is provided in this research with their applications. Future research directions (challenges) are also highlighted which needs proper attention for the purpose of achieving the goal of realizing context-aware systems. PMID:24887042

Multi-scale modularity and motif distributional effect in metabolic networks.

PubMed

Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

2016-01-01

Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks.

Distributed Time Synchronization Algorithms and Opinion Dynamics

NASA Astrophysics Data System (ADS)

Manita, Anatoly; Manita, Larisa

2018-01-01

We propose new deterministic and stochastic models for synchronization of clocks in nodes of distributed networks. An external accurate time server is used to ensure convergence of the node clocks to the exact time. These systems have much in common with mathematical models of opinion formation in multiagent systems. There is a direct analogy between the time server/node clocks pair in asynchronous networks and the leader/follower pair in the context of social network models.

Content-based image exploitation for situational awareness

NASA Astrophysics Data System (ADS)

Gains, David

2008-04-01

Image exploitation is of increasing importance to the enterprise of building situational awareness from multi-source data. It involves image acquisition, identification of objects of interest in imagery, storage, search and retrieval of imagery, and the distribution of imagery over possibly bandwidth limited networks. This paper describes an image exploitation application that uses image content alone to detect objects of interest, and that automatically establishes and preserves spatial and temporal relationships between images, cameras and objects. The application features an intuitive user interface that exposes all images and information generated by the system to an operator thus facilitating the formation of situational awareness.

The Role of Metaphors in Fostering Macrocognitive Processes in Distributed Teams

DTIC Science & Technology

2012-07-30

temporal dynamics, and storytelling towards the goal of improving team coordination and performance in distributed decision making teams. Specifically...better reflect the context of organizational and military teams and 3) to investigate how storytelling (complex form of metaphor) can be used as a...Information Sharing, Situation Awareness, Storytelling , Metaphors, Reflexivity.Team Simulation, NeoCITIES 16. SECURITY CLASSIFICATION OF: a. REPORT b

PAD-MAC: Primary User Activity-Aware Distributed MAC for Multi-Channel Cognitive Radio Networks

PubMed Central

Ali, Amjad; Piran, Md. Jalil; Kim, Hansoo; Yun, Jihyeok; Suh, Doug Young

2015-01-01

Cognitive radio (CR) has emerged as a promising technology to solve problems related to spectrum scarcity and provides a ubiquitous wireless access environment. CR-enabled secondary users (SUs) exploit spectrum white spaces opportunistically and immediately vacate the acquired licensed channels as primary users (PUs) arrive. Accessing the licensed channels without the prior knowledge of PU traffic patterns causes severe throughput degradation due to excessive channel switching and PU-to-SU collisions. Therefore, it is significantly important to design a PU activity-aware medium access control (MAC) protocol for cognitive radio networks (CRNs). In this paper, we first propose a licensed channel usage pattern identification scheme, based on a two-state Markov model, and then estimate the future idle slots using previous observations of the channels. Furthermore, based on these past observations, we compute the rank of each available licensed channel that gives SU transmission success assessment during the estimated idle slot. Secondly, we propose a PU activity-aware distributed MAC (PAD-MAC) protocol for heterogeneous multi-channel CRNs that selects the best channel for each SU to enhance its throughput. PAD-MAC controls SU activities by allowing them to exploit the licensed channels only for the duration of estimated idle slots and enables predictive and fast channel switching. To evaluate the performance of the proposed PAD-MAC, we compare it with the distributed QoS-aware MAC (QC-MAC) and listen-before-talk MAC schemes. Extensive numerical results show the significant improvements of the PAD-MAC in terms of the SU throughput, SU channel switching rate and PU-to-SU collision rate. PMID:25831084

Host-Pathogen Coupled Networks: Model for Bacillus Anthracis Interaction with Host Macrophages

DTIC Science & Technology

2015-09-01

AFB OH 45433-5707 Distribution A : Approved for public release; distribution unlimited. (PA Case No. 88ABW-2015-5572. Date 12 November 2015...www.dtic.mil). (AFRL-RH- -TR- - ) has been reviewed and is approved for publication in accordance with assigned distribution statement. STEPHANIE A . MILLER...Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a

Increasing social capital via local networks: analysis in the context of a surgical practice.

PubMed

Thakur, Anjani; Yang, Isaac; Lee, Michael Y; Goel, Arpan; Ashok, Ashwin; Fonkalsrud, Eric W

2002-09-01

The relationship between social capital (support, trust, patient awareness, and increased practice revenue) and local networks (university hospital) in communities has received little attention. The development of computer-based communication networks (social networks) has added a new dimension to the argument, posing the question of whether local networks can (re-)create social capital in local communities. This relationship is examined through a review of the literature on local networks and social capital and a surgeon's practice management from 1990 to 2001 with respect to repair of pectus chest deformities. With respect to pectus repair there was a consistent but small number of new referrals (15-20 new patients/year), lack of patient awareness (eight to 12 self-referred patients/year), and modest practice revenue. Since the inception of an Internet website (social network) dedicated to pectus repair in 1996 there has been increased social participation (n = 630 hits/year to the website); facilitation of spread of information through E-mail messages (n = 430 messages/year); and a greater participation of groups such as women, minorities, adults, and those with disability (n = 120 patients/year). The dissemination of information via the local network has also allowed an "outward movement" with increased participation by interconnecting communities (n = 698,300 global Internet participants based on statistical ratios). We conclude that local networks have enhanced social networks providing new grounds for the development of relationships based on choice and shared interest.

Network Model of Decreased Context Utilization in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Beversdorf, David Q.; Narayanan, Ananth; Hillier, Ashleigh; Hughes, John D.

2007-01-01

Individuals with autism spectrum disorders (ASD) demonstrate impaired utilization of context, which allows for superior performance on the "false memory" task. We report the application of a simplified parallel distributed processing model of context utilization to the false memory task. For individuals without ASD, experiments support a model…

Network Location-Aware Service Recommendation with Random Walk in Cyber-Physical Systems.

PubMed

Yin, Yuyu; Yu, Fangzheng; Xu, Yueshen; Yu, Lifeng; Mu, Jinglong

2017-09-08

Cyber-physical systems (CPS) have received much attention from both academia and industry. An increasing number of functions in CPS are provided in the way of services, which gives rise to an urgent task, that is, how to recommend the suitable services in a huge number of available services in CPS. In traditional service recommendation, collaborative filtering (CF) has been studied in academia, and used in industry. However, there exist several defects that limit the application of CF-based methods in CPS. One is that under the case of high data sparsity, CF-based methods are likely to generate inaccurate prediction results. In this paper, we discover that mining the potential similarity relations among users or services in CPS is really helpful to improve the prediction accuracy. Besides, most of traditional CF-based methods are only capable of using the service invocation records, but ignore the context information, such as network location, which is a typical context in CPS. In this paper, we propose a novel service recommendation method for CPS, which utilizes network location as context information and contains three prediction models using random walking. We conduct sufficient experiments on two real-world datasets, and the results demonstrate the effectiveness of our proposed methods and verify that the network location is indeed useful in QoS prediction.

To Friend or Not to Friend: The Use of Social Media in Clinical Oncology

PubMed Central

Wiener, Lori; Crum, Caroline; Grady, Christine; Merchant, Melinda

2012-01-01

Online social networking has replaced more traditional methods of personal and professional communication in many segments of society today. The wide reach and immediacy of social media facilitate dissemination of knowledge in advocacy and cancer education, but the usefulness of social media in personal relationships between patients and providers is still unclear. Although professional guidelines regarding e-mail communication may be relevant to social media, the inherent openness in social networks creates potential boundary and privacy issues in the provider-patient context. This commentary seeks to increase provider awareness of unique issues and challenges raised by the integration of social networking into oncology communications. PMID:23077437

A Survey on the Feasibility of Sound Classification on Wireless Sensor Nodes

PubMed Central

Salomons, Etto L.; Havinga, Paul J. M.

2015-01-01

Wireless sensor networks are suitable to gain context awareness for indoor environments. As sound waves form a rich source of context information, equipping the nodes with microphones can be of great benefit. The algorithms to extract features from sound waves are often highly computationally intensive. This can be problematic as wireless nodes are usually restricted in resources. In order to be able to make a proper decision about which features to use, we survey how sound is used in the literature for global sound classification, age and gender classification, emotion recognition, person verification and identification and indoor and outdoor environmental sound classification. The results of the surveyed algorithms are compared with respect to accuracy and computational load. The accuracies are taken from the surveyed papers; the computational loads are determined by benchmarking the algorithms on an actual sensor node. We conclude that for indoor context awareness, the low-cost algorithms for feature extraction perform equally well as the more computationally-intensive variants. As the feature extraction still requires a large amount of processing time, we present four possible strategies to deal with this problem. PMID:25822142

Unsupervised user similarity mining in GSM sensor networks.

PubMed

Shad, Shafqat Ali; Chen, Enhong

2013-01-01

Mobility data has attracted the researchers for the past few years because of its rich context and spatiotemporal nature, where this information can be used for potential applications like early warning system, route prediction, traffic management, advertisement, social networking, and community finding. All the mentioned applications are based on mobility profile building and user trend analysis, where mobility profile building is done through significant places extraction, user's actual movement prediction, and context awareness. However, significant places extraction and user's actual movement prediction for mobility profile building are a trivial task. In this paper, we present the user similarity mining-based methodology through user mobility profile building by using the semantic tagging information provided by user and basic GSM network architecture properties based on unsupervised clustering approach. As the mobility information is in low-level raw form, our proposed methodology successfully converts it to a high-level meaningful information by using the cell-Id location information rather than previously used location capturing methods like GPS, Infrared, and Wifi for profile mining and user similarity mining.

An Anticipatory and Deceptive AI Utilizing Bayesian Belief Networks

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

Lake, Joe E; Allgood, Glenn O; Olama, Mohammed M

The U.S. military defines antiterrorism as the defensive posture taken against terrorist threats. Antiterrorism includes fostering awareness of potential threats, deterring aggressors, developing security measures, planning for future events, interdicting an event in progress, and ultimately mitigating and managing the consequences of an event. Recent events highlight the need for efficient tools for training our military and homeland security officers for anticipating threats posed by terrorists. These tools need to be easy enough so that they are readily usable without substantial training, but still maintain the complexity to allow for a level of deceptive reasoning on the part of themore » opponent. To meet this need, we propose to integrate a Bayesian Belief Network (BBN) model for threat anticipation and deceptive reasoning into training simulation environments currently utilized by several organizations within the Department of Defense (DoD). BBNs have the ability to deal with various types of uncertainties; such as identities, capabilities, target attractiveness, and the combinations of the previous. They also allow for disparate types of data to be fused in a coherent, analytically defensible, and understandable manner. A BBN has been developed by ORNL uses a network engineering process that treats the probability distributions of each node with in the broader context of the system development effort as a whole, and not in isolation. The network will be integrated into the Research Network Inc,(RNI) developed Game Distributed Interactive Simulation (GDIS) as a smart artificial intelligence module. GDIS is utilized by several DoD and civilian organizations as a distributed training tool for a multiplicity of reasons. It has garnered several awards for its realism, ease of use, and popularity. One area that it still has room to excel in, as most video training tools do, is in the area of artificial intelligence of opponent combatants. It is believed that by utilizing BBN as the backbone of the artificial intelligence code, a more realistic and helpful training experience will be available and enemy combatants that move and strategize with purpose will be obtained.« less

Species-free species distribution models describe macroecological properties of protected area networks.

PubMed

Robinson, Jason L; Fordyce, James A

2017-01-01

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.

Scalable Mobile Ad Hoc Network (MANET) to Enhance Situational Awareness in Distributed Small Unit Operations

DTIC Science & Technology

2015-06-01

raspberry pi , robotic operation system (ros), arduino 15. NUMBER OF PAGES 123 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...51  2.  Raspberry Pi ...52  Figure 21.  The Raspberry Pi B+ model, from [24

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems

DTIC Science & Technology

2007-05-03

34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each

Self-Aware Vehicles: Mission and Performance Adaptation to System Health

NASA Technical Reports Server (NTRS)

Gregory, Irene M.; Leonard, Charles; Scotti, Stephen J.

2016-01-01

Advances in sensing (miniaturization, distributed sensor networks) combined with improvements in computational power leading to significant gains in perception, real-time decision making/reasoning and dynamic planning under uncertainty as well as big data predictive analysis have set the stage for realization of autonomous system capability. These advances open the design and operating space for self-aware vehicles that are able to assess their own capabilities and adjust their behavior to either complete the assigned mission or to modify the mission to reflect their current capabilities. This paper discusses the self-aware vehicle concept and associated technologies necessary for full exploitation of the concept. A self-aware aircraft, spacecraft or system is one that is aware of its internal state, has situational awareness of its environment, can assess its capabilities currently and project them into the future, understands its mission objectives, and can make decisions under uncertainty regarding its ability to achieve its mission objectives.

Energy-aware scheduling of surveillance in wireless multimedia sensor networks.

PubMed

Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao

2010-01-01

Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.

Trust and Independence Aware Decision Fusion in Distributed Networks

DTIC Science & Technology

2013-01-01

evidence in order to derive a unified belief where conflicting evidence exists. However, neither DST nor TBM deals with misbehaving data sources and...about the target. The problem is compounded by the misbehaving nodes who supply false data in the network. This work aims at enhancing the accuracy of...derive a unified belief where conflicting evidence exists. However, neither DST nor TBM deals with misbehaving data sources and dependence of fusion

Location-Aware Dynamic Session-Key Management for Grid-Based Wireless Sensor Networks

PubMed Central

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths. PMID:22163606

Location-aware dynamic session-key management for grid-based Wireless Sensor Networks.

PubMed

Chen, Chin-Ling; Lin, I-Hsien

2010-01-01

Security is a critical issue for sensor networks used in hostile environments. When wireless sensor nodes in a wireless sensor network are distributed in an insecure hostile environment, the sensor nodes must be protected: a secret key must be used to protect the nodes transmitting messages. If the nodes are not protected and become compromised, many types of attacks against the network may result. Such is the case with existing schemes, which are vulnerable to attacks because they mostly provide a hop-by-hop paradigm, which is insufficient to defend against known attacks. We propose a location-aware dynamic session-key management protocol for grid-based wireless sensor networks. The proposed protocol improves the security of a secret key. The proposed scheme also includes a key that is dynamically updated. This dynamic update can lower the probability of the key being guessed correctly. Thus currently known attacks can be defended. By utilizing the local information, the proposed scheme can also limit the flooding region in order to reduce the energy that is consumed in discovering routing paths.

Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - An approach based on multiplex networks

NASA Astrophysics Data System (ADS)

Kan, Jia-Qian; Zhang, Hai-Feng

2017-03-01

In this paper, we study the interplay between the epidemic spreading and the diffusion of awareness in multiplex networks. In the model, an infectious disease can spread in one network representing the paths of epidemic spreading (contact network), leading to the diffusion of awareness in the other network (information network), and then the diffusion of awareness will cause individuals to take social distances, which in turn affects the epidemic spreading. As for the diffusion of awareness, we assume that, on the one hand, individuals can be informed by other aware neighbors in information network, on the other hand, the susceptible individuals can be self-awareness induced by the infected neighbors in the contact networks (local information) or mass media (global information). Through Markov chain approach and numerical computations, we find that the density of infected individuals and the epidemic threshold can be affected by the structures of the two networks and the effective transmission rate of the awareness. However, we prove that though the introduction of the self-awareness can lower the density of infection, which cannot increase the epidemic threshold no matter of the local information or global information. Our finding is remarkably different to many previous results on single-layer network: local information based behavioral response can alter the epidemic threshold. Furthermore, our results indicate that the nodes with more neighbors (hub nodes) in information networks are easier to be informed, as a result, their risk of infection in contact networks can be effectively reduced.

Potential System Vulnerabilities of a Network Enabled Force

DTIC Science & Technology

2004-09-01

of trust in information, loss of context and awareness of others’ needs and reduction of social cohesion . Science - (more specifically systems...and Technology Damaging Social Cohesion NCW champions the concept of dispersed forces as a means to generate effects through approaches other than...Mission Grouping Damaging Social Cohesion This is a slight variation on the vulnerability expressed in 3.9.6 above. If we have agility in mission

Social Email: A Framework and Application for More Socially-Aware Communications

NASA Astrophysics Data System (ADS)

Tran, Thomas; Rowe, Jeff; Wu, S. Felix

As online social networks (OSN) attempt to mimic real life social networks, we have made progress towards using OSNs to provide us with data to allow for richer and more robust online communications. In this paper, we present a novel approach towards socially-aware email. Currently, email provides too little control to the recipient. Our approach, dubbed SoEmail, provides social context to messages using an OSN's underlying social graph. This not only gives the recipient control over who can message her, but it also provides her with an understanding of where the message originated from, socially. Furthermore, users who do not wish to use the built-in social aspect of SoEmail, can send and receive emails without any changes to their behavior. The modifications we made to the email application to provide this social context are not invasive and can be easily ignored by any existing email client. We built SoEmail on top of an existing framework, known as Davis Social Links, which allows SoEmail to be completely agnostic about the underlying OSN. We created a web-based, standards-based web client for SoEmail using Facebook and Gmail as the underlying systems which has been released for public use and has had a good adoption rate.

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

NASA Astrophysics Data System (ADS)

Hyman, J. D.; Aldrich, G.; Viswanathan, H.; Makedonska, N.; Karra, S.

2016-08-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

NASA Astrophysics Data System (ADS)

Hyman, J.; Aldrich, G. A.; Viswanathan, H. S.; Makedonska, N.; Karra, S.

2016-12-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semi-correlation, and non-correlation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same.We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.

Context Aware Systems, Methods and Trends in Smart Home Technology

NASA Astrophysics Data System (ADS)

Robles, Rosslin John; Kim, Tai-Hoon

Context aware applications respond and adapt to changes in the computing environment. It is the concept of leveraging information about the end user to improve the quality of the interaction. New technologies in context-enriched services will use location, presence, social attributes, and other environmental information to anticipate an end user's immediate needs, offering more-sophisticated, situation-aware and usable functions. Smart homes connect all the devices and appliances in your home so they can communicate with each other and with you. Context-awareness can be applied to Smart Home technology. In this paper, we discuss the context-aware tools for development of Smart Home Systems.

Introduction to This Special Issue on Context-Aware Computing.

ERIC Educational Resources Information Center

Moran, Thomas P.; Dourish, Paul

2001-01-01

Discusses pervasive, or ubiquitous, computing; explains the notion of context; and defines context-aware computing as the key to disperse and enmesh computation into our lives. Considers context awareness in human-computer interaction and describes the broad topic areas of the essays included in this special issue. (LRW)

A Complex Network Approach to Distributional Semantic Models

PubMed Central

Utsumi, Akira

2015-01-01

A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940

A Q-Learning-Based Delay-Aware Routing Algorithm to Extend the Lifetime of Underwater Sensor Networks.

PubMed

Jin, Zhigang; Ma, Yingying; Su, Yishan; Li, Shuo; Fu, Xiaomei

2017-07-19

Underwater sensor networks (UWSNs) have become a hot research topic because of their various aquatic applications. As the underwater sensor nodes are powered by built-in batteries which are difficult to replace, extending the network lifetime is a most urgent need. Due to the low and variable transmission speed of sound, the design of reliable routing algorithms for UWSNs is challenging. In this paper, we propose a Q-learning based delay-aware routing (QDAR) algorithm to extend the lifetime of underwater sensor networks. In QDAR, a data collection phase is designed to adapt to the dynamic environment. With the application of the Q-learning technique, QDAR can determine a global optimal next hop rather than a greedy one. We define an action-utility function in which residual energy and propagation delay are both considered for adequate routing decisions. Thus, the QDAR algorithm can extend the network lifetime by uniformly distributing the residual energy and provide lower end-to-end delay. The simulation results show that our protocol can yield nearly the same network lifetime, and can reduce the end-to-end delay by 20-25% compared with a classic lifetime-extended routing protocol (QELAR).

A Q-Learning-Based Delay-Aware Routing Algorithm to Extend the Lifetime of Underwater Sensor Networks

PubMed Central

Ma, Yingying; Su, Yishan; Li, Shuo; Fu, Xiaomei

2017-01-01

Underwater sensor networks (UWSNs) have become a hot research topic because of their various aquatic applications. As the underwater sensor nodes are powered by built-in batteries which are difficult to replace, extending the network lifetime is a most urgent need. Due to the low and variable transmission speed of sound, the design of reliable routing algorithms for UWSNs is challenging. In this paper, we propose a Q-learning based delay-aware routing (QDAR) algorithm to extend the lifetime of underwater sensor networks. In QDAR, a data collection phase is designed to adapt to the dynamic environment. With the application of the Q-learning technique, QDAR can determine a global optimal next hop rather than a greedy one. We define an action-utility function in which residual energy and propagation delay are both considered for adequate routing decisions. Thus, the QDAR algorithm can extend the network lifetime by uniformly distributing the residual energy and provide lower end-to-end delay. The simulation results show that our protocol can yield nearly the same network lifetime, and can reduce the end-to-end delay by 20–25% compared with a classic lifetime-extended routing protocol (QELAR). PMID:28753951

The impact of awareness on epidemic spreading in networks.

PubMed

Wu, Qingchu; Fu, Xinchu; Small, Michael; Xu, Xin-Jian

2012-03-01

We explore the impact of awareness on epidemic spreading through a population represented by a scale-free network. Using a network mean-field approach, a mathematical model for epidemic spreading with awareness reactions is proposed and analyzed. We focus on the role of three forms of awareness including local, global, and contact awareness. By theoretical analysis and simulation, we show that the global awareness cannot decrease the likelihood of an epidemic outbreak while both the local awareness and the contact awareness can. Also, the influence degree of the local awareness on disease dynamics is closely related with the contact awareness.

CAreDroid: Adaptation Framework for Android Context-Aware Applications

PubMed Central

Elmalaki, Salma; Wanner, Lucas; Srivastava, Mani

2015-01-01

Context-awareness is the ability of software systems to sense and adapt to their physical environment. Many contemporary mobile applications adapt to changing locations, connectivity states, available computational and energy resources, and proximity to other users and devices. Nevertheless, there is little systematic support for context-awareness in contemporary mobile operating systems. Because of this, application developers must build their own context-awareness adaptation engines, dealing directly with sensors and polluting application code with complex adaptation decisions. In this paper, we introduce CAreDroid, which is a framework that is designed to decouple the application logic from the complex adaptation decisions in Android context-aware applications. In this framework, developers are required— only—to focus on the application logic by providing a list of methods that are sensitive to certain contexts along with the permissible operating ranges under those contexts. At run time, CAreDroid monitors the context of the physical environment and intercepts calls to sensitive methods, activating only the blocks of code that best fit the current physical context. CAreDroid is implemented as part of the Android runtime system. By pushing context monitoring and adaptation into the runtime system, CAreDroid eases the development of context-aware applications and increases their efficiency. In particular, case study applications implemented using CAre-Droid are shown to have: (1) at least half lines of code fewer and (2) at least 10× more efficient in execution time compared to equivalent context-aware applications that use only standard Android APIs. PMID:26834512

CAreDroid: Adaptation Framework for Android Context-Aware Applications.

PubMed

Elmalaki, Salma; Wanner, Lucas; Srivastava, Mani

2015-09-01

Context-awareness is the ability of software systems to sense and adapt to their physical environment. Many contemporary mobile applications adapt to changing locations, connectivity states, available computational and energy resources, and proximity to other users and devices. Nevertheless, there is little systematic support for context-awareness in contemporary mobile operating systems. Because of this, application developers must build their own context-awareness adaptation engines, dealing directly with sensors and polluting application code with complex adaptation decisions. In this paper, we introduce CAreDroid, which is a framework that is designed to decouple the application logic from the complex adaptation decisions in Android context-aware applications. In this framework, developers are required- only-to focus on the application logic by providing a list of methods that are sensitive to certain contexts along with the permissible operating ranges under those contexts. At run time, CAreDroid monitors the context of the physical environment and intercepts calls to sensitive methods, activating only the blocks of code that best fit the current physical context. CAreDroid is implemented as part of the Android runtime system. By pushing context monitoring and adaptation into the runtime system, CAreDroid eases the development of context-aware applications and increases their efficiency. In particular, case study applications implemented using CAre-Droid are shown to have: (1) at least half lines of code fewer and (2) at least 10× more efficient in execution time compared to equivalent context-aware applications that use only standard Android APIs.

Diverse Region-Based CNN for Hyperspectral Image Classification.

PubMed

Zhang, Mengmeng; Li, Wei; Du, Qian

2018-06-01

Convolutional neural network (CNN) is of great interest in machine learning and has demonstrated excellent performance in hyperspectral image classification. In this paper, we propose a classification framework, called diverse region-based CNN, which can encode semantic context-aware representation to obtain promising features. With merging a diverse set of discriminative appearance factors, the resulting CNN-based representation exhibits spatial-spectral context sensitivity that is essential for accurate pixel classification. The proposed method exploiting diverse region-based inputs to learn contextual interactional features is expected to have more discriminative power. The joint representation containing rich spectral and spatial information is then fed to a fully connected network and the label of each pixel vector is predicted by a softmax layer. Experimental results with widely used hyperspectral image data sets demonstrate that the proposed method can surpass any other conventional deep learning-based classifiers and other state-of-the-art classifiers.

Context dependent off loading for cloudlet in mobile ad-hoc network

NASA Astrophysics Data System (ADS)

Bhatt, N.; Nadesh, R. K.; ArivuSelvan, K.

2017-11-01

Cloud Computing in Mobile Ad-hoc network is emerging part of research consideration as the demand and competency of mobile devices increased in last few years. To follow out operation within the remote cloud builds the postponement and influences the administration standard. To keep away from this trouble cloudlet is presented. Cloudlet gives identical support of the devices as cloud at low inactivity however at high transfer speed. Be that as it may, choice of a cloudlet for offloading calculation with flat energy is a noteworthy test if multiple cloud let is accessible adjacent. Here I proposed energy and bandwidth (Traffic overload for communication with cloud) aware cloudlet selection strategy based on the context dependency of the device location. It works on the basis of mobile device location and bandwidth availability of cloudlet. The cloudlet offloading and selection process using given solution is simulated in Cloud ~ Simulator.

A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

PubMed

Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

2015-11-19

Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

Network Location-Aware Service Recommendation with Random Walk in Cyber-Physical Systems

PubMed Central

Yin, Yuyu; Yu, Fangzheng; Xu, Yueshen; Yu, Lifeng; Mu, Jinglong

2017-01-01

Cyber-physical systems (CPS) have received much attention from both academia and industry. An increasing number of functions in CPS are provided in the way of services, which gives rise to an urgent task, that is, how to recommend the suitable services in a huge number of available services in CPS. In traditional service recommendation, collaborative filtering (CF) has been studied in academia, and used in industry. However, there exist several defects that limit the application of CF-based methods in CPS. One is that under the case of high data sparsity, CF-based methods are likely to generate inaccurate prediction results. In this paper, we discover that mining the potential similarity relations among users or services in CPS is really helpful to improve the prediction accuracy. Besides, most of traditional CF-based methods are only capable of using the service invocation records, but ignore the context information, such as network location, which is a typical context in CPS. In this paper, we propose a novel service recommendation method for CPS, which utilizes network location as context information and contains three prediction models using random walking. We conduct sufficient experiments on two real-world datasets, and the results demonstrate the effectiveness of our proposed methods and verify that the network location is indeed useful in QoS prediction. PMID:28885602

Network inference using informative priors

PubMed Central

Mukherjee, Sach; Speed, Terence P.

2008-01-01

Recent years have seen much interest in the study of systems characterized by multiple interacting components. A class of statistical models called graphical models, in which graphs are used to represent probabilistic relationships between variables, provides a framework for formal inference regarding such systems. In many settings, the object of inference is the network structure itself. This problem of “network inference” is well known to be a challenging one. However, in scientific settings there is very often existing information regarding network connectivity. A natural idea then is to take account of such information during inference. This article addresses the question of incorporating prior information into network inference. We focus on directed models called Bayesian networks, and use Markov chain Monte Carlo to draw samples from posterior distributions over network structures. We introduce prior distributions on graphs capable of capturing information regarding network features including edges, classes of edges, degree distributions, and sparsity. We illustrate our approach in the context of systems biology, applying our methods to network inference in cancer signaling. PMID:18799736

Network inference using informative priors.

PubMed

Mukherjee, Sach; Speed, Terence P

2008-09-23

Recent years have seen much interest in the study of systems characterized by multiple interacting components. A class of statistical models called graphical models, in which graphs are used to represent probabilistic relationships between variables, provides a framework for formal inference regarding such systems. In many settings, the object of inference is the network structure itself. This problem of "network inference" is well known to be a challenging one. However, in scientific settings there is very often existing information regarding network connectivity. A natural idea then is to take account of such information during inference. This article addresses the question of incorporating prior information into network inference. We focus on directed models called Bayesian networks, and use Markov chain Monte Carlo to draw samples from posterior distributions over network structures. We introduce prior distributions on graphs capable of capturing information regarding network features including edges, classes of edges, degree distributions, and sparsity. We illustrate our approach in the context of systems biology, applying our methods to network inference in cancer signaling.

Proceedings of the Fourth International Workshop on a Research Agenda for Maintenance and Evolution of Service-Oriented Systems (MESOA 2010)

DTIC Science & Technology

2011-09-01

service -oriented systems • Software -as-a- Service ( SaaS ) • social network infrastructures • Internet marketing • mobile computing • context awareness...Maintenance and Evolution of Service -Oriented Systems (MESOA 2010), organized by members of the Carnegie Mellon Software Engineering Institute’s...CMU/SEI-2011-SR-008 | 1 1 Workshop Introduction The Software Engineering Institute (SEI) started developing a service -oriented architecture

A Software Product Line Process to Develop Agents for the IoT.

PubMed

Ayala, Inmaculada; Amor, Mercedes; Fuentes, Lidia; Troya, José M

2015-07-01

One of the most important challenges of this decade is the Internet of Things (IoT), which aims to enable things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service. IoT systems are usually composed of heterogeneous and interconnected lightweight devices that support applications that are subject to change in their external environment and in the functioning of these devices. The management of the variability of these changes, autonomously, is a challenge in the development of these systems. Agents are a good option for developing self-managed IoT systems due to their distributed nature, context-awareness and self-adaptation. Our goal is to enhance the development of IoT applications using agents and software product lines (SPL). Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language. In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes.

Distributing french seismologic data through the RESIF green IT datacentre

NASA Astrophysics Data System (ADS)

Volcke, P.; Gueguen, P.; Pequegnat, C.; Le Tanou, J.; Enderle, G.; Berthoud, F.

2012-12-01

RESIF is a nationwide french project aimed at building an excellent quality system to observe and understand the inner earth. The ultimate goal is to create a network throughout mainland France comprising 750 seismometers and geodetic measurement instruments, 250 of which will be mobile to enable the observation network to be focused on specific investigation subjects and geographic locations. This project includes the implementation of a data distribution centre hosting seismologic and geodetic data. This datacentre is operated by the Université Joseph Fourier, Grenoble, France. In the context of building the necessary computing infrastructure, the Université Joseph Fourier became the first french university earning the status of "Participant" for the European Union "Code of Conduct for Data Centres". The University commits to energy reporting and implementing best practices for energy efficiency, in a cost effective manner, without hampering mission critical functions. In this context, data currently hosted at the RESIF datacentre include data from french broadband permanent network, strong motion permanent network, and mobile seismological network. These data are freely accessible as realtime streams and continuous validated data, along with instrumental metadata, delivered using widely known formats. Futur developments include tight integration with local super-computing ressources, and setting up modern distribution systems like webservices.

Rethinking Indoor Localization Solutions Towards the Future of Mobile Location-Based Services

NASA Astrophysics Data System (ADS)

Guney, C.

2017-11-01

Satellite navigation systems with GNSS-enabled devices, such as smartphones, car navigation systems, have changed the way users travel in outdoor environment. GNSS is generally not well suited for indoor location and navigation because of two reasons: First, GNSS does not provide a high level of accuracy although indoor applications need higher accuracies. Secondly, poor coverage of satellite signals for indoor environments decreases its accuracy. So rather than using GNSS satellites within closed environments, existing indoor navigation solutions rely heavily on installed sensor networks. There is a high demand for accurate positioning in wireless networks in GNSS-denied environments. However, current wireless indoor positioning systems cannot satisfy the challenging needs of indoor location-aware applications. Nevertheless, access to a user's location indoors is increasingly important in the development of context-aware applications that increases business efficiency. In this study, how can the current wireless location sensing systems be tailored and integrated for specific applications, like smart cities/grids/buildings/cars and IoT applications, in GNSS-deprived areas.

Prestimulus Network Integration of Auditory Cortex Predisposes Near-Threshold Perception Independently of Local Excitability

PubMed Central

Leske, Sabine; Ruhnau, Philipp; Frey, Julia; Lithari, Chrysa; Müller, Nadia; Hartmann, Thomas; Weisz, Nathan

2015-01-01

An ever-increasing number of studies are pointing to the importance of network properties of the brain for understanding behavior such as conscious perception. However, with regards to the influence of prestimulus brain states on perception, this network perspective has rarely been taken. Our recent framework predicts that brain regions crucial for a conscious percept are coupled prior to stimulus arrival, forming pre-established pathways of information flow and influencing perceptual awareness. Using magnetoencephalography (MEG) and graph theoretical measures, we investigated auditory conscious perception in a near-threshold (NT) task and found strong support for this framework. Relevant auditory regions showed an increased prestimulus interhemispheric connectivity. The left auditory cortex was characterized by a hub-like behavior and an enhanced integration into the brain functional network prior to perceptual awareness. Right auditory regions were decoupled from non-auditory regions, presumably forming an integrated information processing unit with the left auditory cortex. In addition, we show for the first time for the auditory modality that local excitability, measured by decreased alpha power in the auditory cortex, increases prior to conscious percepts. Importantly, we were able to show that connectivity states seem to be largely independent from local excitability states in the context of a NT paradigm. PMID:26408799

Value Representations by Rank Order in a Distributed Network of Varying Context Dependency

ERIC Educational Resources Information Center

Mullett, Timothy L.; Tunney, Richard J.

2013-01-01

We report the results of a human fMRI experiment investigating the influence of context upon value judgement. Trials were separated into high and low value blocks such that it is possible to investigate the effect of a change in surrounding trials upon the encoding of financial value. The ventral striatum was dependent upon "local context", with…

Strategies for improving disability awareness and social inclusion of children and young people with cerebral palsy.

PubMed

Lindsay, S; McPherson, A C

2012-11-01

Children and youth with disabilities are at a higher risk of being socially excluded or bullied while at school compared with their typically developing peers. This study explored disabled children's suggestions for improving social inclusion. Fifteen children with cerebral palsy were interviewed or took part in a group discussion about social inclusion and bullying. All interviews and focus groups were audio-recorded and transcribed verbatim. The children and youth described several strategies to help improve social inclusion at school including: (1) disclosure of condition and creating awareness of disability; (2) awareness of bullying; (3) developing a peer support network and building self-confidence; and (4) suggestions on what teachers can do. It is recommended that children's suggestions be considered within the classroom context to enhance the social inclusion and participation of children with disabilities. © 2011 Blackwell Publishing Ltd.

A Novel Approach for Creating Activity-Aware Applications in a Hospital Environment

NASA Astrophysics Data System (ADS)

Bardram, Jakob E.

Context-aware and activity-aware computing has been proposed as a way to adapt the computer to the user’s ongoing activity. However, deductively moving from physical context - like location - to establishing human activity has proved difficult. This paper proposes a novel approach to activity-aware computing. Instead of inferring activities, this approach enables the user to explicitly model their activity, and then use sensor-based events to create, manage, and use these computational activities adjusted to a specific context. This approach was crafted through a user-centered design process in collaboration with a hospital department. We propose three strategies for activity-awareness: context-based activity matching, context-based activity creation, and context-based activity adaptation. We present the implementation of these strategies and present an experimental evaluation of them. The experiments demonstrate that rather than considering context as information, context can be a relational property that links ’real-world activities’ with their ’computational activities’.

A Proposal for IoT Dynamic Routes Selection Based on Contextual Information.

PubMed

Araújo, Harilton da Silva; Filho, Raimir Holanda; Rodrigues, Joel J P C; Rabelo, Ricardo de A L; Sousa, Natanael de C; Filho, José C C L S; Sobral, José V V

2018-01-26

The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information). This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications. In this case, fuzzy logic is used to translate in math terms the imprecise information expressed by a set of linguistic rules. For this purpose, four Objective Functions (OFs) are proposed for the Routing Protocol for Low Power and Loss Networks (RPL); such OFs are dynamically selected based on context information. The aforementioned OFs are generated from the fusion of the following metrics: Expected Transmission Count (ETX), Number of Hops (NH) and Energy Consumed (EC). The experiments performed through simulation, associated with the statistical data analysis, conclude that this proposal provides high reliability by successfully delivering nearly 100% of data packets, low delay for data delivery and increase in QoS. In addition, an 30% improvement is attained in the network life time when using one of proposed objective function, keeping the devices alive for longer duration.

A Novel Energy-Aware Distributed Clustering Algorithm for Heterogeneous Wireless Sensor Networks in the Mobile Environment

PubMed Central

Gao, Ying; Wkram, Chris Hadri; Duan, Jiajie; Chou, Jarong

2015-01-01

In order to prolong the network lifetime, energy-efficient protocols adapted to the features of wireless sensor networks should be used. This paper explores in depth the nature of heterogeneous wireless sensor networks, and finally proposes an algorithm to address the problem of finding an effective pathway for heterogeneous clustering energy. The proposed algorithm implements cluster head selection according to the degree of energy attenuation during the network’s running and the degree of candidate nodes’ effective coverage on the whole network, so as to obtain an even energy consumption over the whole network for the situation with high degree of coverage. Simulation results show that the proposed clustering protocol has better adaptability to heterogeneous environments than existing clustering algorithms in prolonging the network lifetime. PMID:26690440

A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications

PubMed Central

Gomes, Berto de Tácio Pereira; Muniz, Luiz Carlos Melo; dos Santos, Davi Viana; Lopes, Rafael Fernandes; Coutinho, Luciano Reis; Carvalho, Felipe Oliveira; Endler, Markus

2017-01-01

Context aware systems are able to adapt their behavior according to the environment in which the user is. They can be integrated into an Internet of Things (IoT) infrastructure, allowing a better perception of the user’s physical environment by collecting context data from sensors embedded in devices known as smart objects. An IoT extension called the Internet of Mobile Things (IoMT) suggests new scenarios in which smart objects and IoT gateways can move autonomously or be moved easily. In a comprehensive view, Quality of Context (QoC) is a term that can express quality requirements of context aware applications. These requirements can be those related to the quality of information provided by the sensors (e.g., accuracy, resolution, age, validity time) or those referring to the quality of the data distribution service (e.g, reliability, delay, delivery time). Some functionalities of context aware applications and/or decision-making processes of these applications and their users depend on the level of quality of context available, which tend to vary over time for various reasons. Reviewing the literature, it is possible to verify that the quality of context support provided by IoT-oriented middleware systems still has limitations in relation to at least four relevant aspects: (i) quality of context provisioning; (ii) quality of context monitoring; (iii) support for heterogeneous device and technology management; (iv) support for reliable data delivery in mobility scenarios. This paper presents two main contributions: (i) a state-of-the-art survey specifically aimed at analyzing the middleware with quality of context support and; (ii) a new middleware with comprehensive quality of context support for Internet of Things Applications. The proposed middleware was evaluated and the results are presented and discussed in this article, which also shows a case study involving the development of a mobile remote patient monitoring application that was developed using the proposed middleware. This case study highlights how middleware components were used to meet the quality of context requirements of the application. In addition, the proposed middleware was compared to other solutions in the literature. PMID:29292791

A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications.

PubMed

Gomes, Berto de Tácio Pereira; Muniz, Luiz Carlos Melo; da Silva E Silva, Francisco José; Dos Santos, Davi Viana; Lopes, Rafael Fernandes; Coutinho, Luciano Reis; Carvalho, Felipe Oliveira; Endler, Markus

2017-12-08

Context aware systems are able to adapt their behavior according to the environment in which the user is. They can be integrated into an Internet of Things (IoT) infrastructure, allowing a better perception of the user's physical environment by collecting context data from sensors embedded in devices known as smart objects. An IoT extension called the Internet of Mobile Things (IoMT) suggests new scenarios in which smart objects and IoT gateways can move autonomously or be moved easily. In a comprehensive view, Quality of Context (QoC) is a term that can express quality requirements of context aware applications. These requirements can be those related to the quality of information provided by the sensors (e.g., accuracy, resolution, age, validity time) or those referring to the quality of the data distribution service (e.g, reliability, delay, delivery time). Some functionalities of context aware applications and/or decision-making processes of these applications and their users depend on the level of quality of context available, which tend to vary over time for various reasons. Reviewing the literature, it is possible to verify that the quality of context support provided by IoT-oriented middleware systems still has limitations in relation to at least four relevant aspects: (i) quality of context provisioning; (ii) quality of context monitoring; (iii) support for heterogeneous device and technology management; (iv) support for reliable data delivery in mobility scenarios. This paper presents two main contributions: (i) a state-of-the-art survey specifically aimed at analyzing the middleware with quality of context support and; (ii) a new middleware with comprehensive quality of context support for Internet of Things Applications. The proposed middleware was evaluated and the results are presented and discussed in this article, which also shows a case study involving the development of a mobile remote patient monitoring application that was developed using the proposed middleware. This case study highlights how middleware components were used to meet the quality of context requirements of the application. In addition, the proposed middleware was compared to other solutions in the literature.

Me and My 400 Friends: The Anatomy of College Students' Facebook Networks, Their Communication Patterns, and Well-Being

ERIC Educational Resources Information Center

Manago, Adriana M.; Taylor, Tamara; Greenfield, Patricia M.

2012-01-01

Is there a trade-off between having large networks of social connections on social networking sites such as Facebook and the development of intimacy and social support among today's generation of emerging adults? To understand the socialization context of Facebook during the transition to adulthood, an online survey was distributed to college…

Unsupervised User Similarity Mining in GSM Sensor Networks

PubMed Central

Shad, Shafqat Ali; Chen, Enhong

2013-01-01

Mobility data has attracted the researchers for the past few years because of its rich context and spatiotemporal nature, where this information can be used for potential applications like early warning system, route prediction, traffic management, advertisement, social networking, and community finding. All the mentioned applications are based on mobility profile building and user trend analysis, where mobility profile building is done through significant places extraction, user's actual movement prediction, and context awareness. However, significant places extraction and user's actual movement prediction for mobility profile building are a trivial task. In this paper, we present the user similarity mining-based methodology through user mobility profile building by using the semantic tagging information provided by user and basic GSM network architecture properties based on unsupervised clustering approach. As the mobility information is in low-level raw form, our proposed methodology successfully converts it to a high-level meaningful information by using the cell-Id location information rather than previously used location capturing methods like GPS, Infrared, and Wifi for profile mining and user similarity mining. PMID:23576905

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

DOE PAGES

Hyman, Jeffrey De'Haven; Aldrich, Garrett Allen; Viswanathan, Hari S.; ...

2016-08-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected somore » that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. Lastly, these observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.« less

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

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

Hyman, Jeffrey De'Haven; Aldrich, Garrett Allen; Viswanathan, Hari S.

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected somore » that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. Lastly, these observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.« less

An ontology-based system for context-aware and configurable services to support home-based continuous care.

PubMed

Paganelli, Federica; Giuli, Dino

2011-03-01

Continuous care models for chronic diseases pose several technology-oriented challenges for home-based care, where assistance services rely on a close collaboration among different stakeholders, such as health operators, patient relatives, and social community members. This paper describes an ontology-based context model and a related context management system providing a configurable and extensible service-oriented framework to ease the development of applications for monitoring and handling patient chronic conditions. The system has been developed in a prototypal version, and integrated with a service platform for supporting operators of home-based care networks in cooperating and sharing patient-related information and coordinating mutual interventions for handling critical and alarm situations. Finally, we discuss experimentation results and possible further research directions.

Context-aware and locality-constrained coding for image categorization.

PubMed

Xiao, Wenhua; Wang, Bin; Liu, Yu; Bao, Weidong; Zhang, Maojun

2014-01-01

Improving the coding strategy for BOF (Bag-of-Features) based feature design has drawn increasing attention in recent image categorization works. However, the ambiguity in coding procedure still impedes its further development. In this paper, we introduce a context-aware and locality-constrained Coding (CALC) approach with context information for describing objects in a discriminative way. It is generally achieved by learning a word-to-word cooccurrence prior to imposing context information over locality-constrained coding. Firstly, the local context of each category is evaluated by learning a word-to-word cooccurrence matrix representing the spatial distribution of local features in neighbor region. Then, the learned cooccurrence matrix is used for measuring the context distance between local features and code words. Finally, a coding strategy simultaneously considers locality in feature space and context space, while introducing the weight of feature is proposed. This novel coding strategy not only semantically preserves the information in coding, but also has the ability to alleviate the noise distortion of each class. Extensive experiments on several available datasets (Scene-15, Caltech101, and Caltech256) are conducted to validate the superiority of our algorithm by comparing it with baselines and recent published methods. Experimental results show that our method significantly improves the performance of baselines and achieves comparable and even better performance with the state of the arts.

Constructing Media Artifacts in a Social Constructivist Environment to Enhance Students' Environmental Awareness and Activism

NASA Astrophysics Data System (ADS)

Karahan, Engin; Roehrig, Gillian

2015-02-01

Current science education reforms and policy documents highlight the importance of environmental awareness and perceived need for activism. As "environmental problems are socially constructed in terms of their conceptualized effects on individuals, groups, other living things and systems research based on constructivist principles provides not only a coherent framework in which to theorize about learning, but also a context for understanding socially constructed issues" (Palmer and Suggate in Res Pap Educ 19(2), 2004, p. 208). This research study investigated the impacts of the learning processes structured based on the theories of constructionism and social constructivism on students' environmental awareness and perceived need for activism. Students constructed multimedia artifacts expressing their knowledge, attitudes, awareness, and activism about environmental issues through a constructionist design process. In addition, a social networking site was designed and used to promote social interaction among students. Twenty-two high school environmental science students participated in this study. A convergent mixed methods design was implemented to allow for the triangulation of methods by directly comparing and contrasting quantitative results with qualitative findings for corroboration and validation purposes. Using a mixed method approach, quantitative findings are supported with qualitative data (student video projects, writing prompts, blog entries, video projects of the students, observational field notes, and reflective journals) including spontaneous responses in both synchronous and asynchronous conversations on the social network to provide a better understanding of the change in students' environmental awareness and perceived need for activism. The findings of the study indicated that students' environmental awareness and perceived need for activism were improved at different scales (personal, community, global) throughout the constructionist and social constructivist learning processes.

Context-Aware Reviewer Assignment for Trust Enhanced Peer Review

PubMed Central

Li, Lei; Wang, Yan; Liu, Guanfeng; Wang, Meng; Wu, Xindong

2015-01-01

Reviewer assignment is critical to peer review systems, such as peer-reviewed research conferences or peer-reviewed funding applications, and its effectiveness is a deep concern of all academics. However, there are some problems in existing peer review systems during reviewer assignment. For example, some of the reviewers are much more stringent than others, leading to an unfair final decision, i.e., some submissions (i.e., papers or applications) with better quality are rejected. In this paper, we propose a context-aware reviewer assignment for trust enhanced peer review. More specifically, in our approach, we first consider the research area specific expertise of reviewers, and the institution relevance and co-authorship between reviewers and authors, so that reviewers with the right expertise are assigned to the corresponding submissions without potential conflict of interest. In addition, we propose a novel cross-assignment paradigm, and reviewers are cross-assigned in order to avoid assigning a group of stringent reviewers or a group of lenient reviewers to the same submission. More importantly, on top of them, we propose an academic CONtext-aware expertise relevanCe oriEnted Reviewer cross-assignmenT approach (CONCERT), which aims to effectively estimate the “true” ratings of submissions based on the ratings from all reviewers, even though no prior knowledge exists about the distribution of stringent reviewers and lenient reviewers. The experiments illustrate that compared with existing approaches, our proposed CONCERT approach can less likely assign more than one stringent reviewers or lenient reviewers to a submission simultaneously and significantly reduce the influence of ratings from stringent reviewers and lenient reviewers, leading to trust enhanced peer review and selection, no matter what kind of distributions of stringent reviewers and lenient reviewers are. PMID:26090849

User Situational Context: An Essential Challenge to Context Awareness

ERIC Educational Resources Information Center

Mowafi, Yaser Abdallah

2009-01-01

Existing research on context and context awareness has broadly focused on the technical aspects of context acquisition and interpretation of users' surroundings, also called physical or sensor-based context. Such an approach has lacked from reconciling the perception of real-world context exhibited by humans, also known as user context, and…

A reverberation-time-aware DNN approach leveraging spatial information for microphone array dereverberation

NASA Astrophysics Data System (ADS)

Wu, Bo; Yang, Minglei; Li, Kehuang; Huang, Zhen; Siniscalchi, Sabato Marco; Wang, Tong; Lee, Chin-Hui

2017-12-01

A reverberation-time-aware deep-neural-network (DNN)-based multi-channel speech dereverberation framework is proposed to handle a wide range of reverberation times (RT60s). There are three key steps in designing a robust system. First, to accomplish simultaneous speech dereverberation and beamforming, we propose a framework, namely DNNSpatial, by selectively concatenating log-power spectral (LPS) input features of reverberant speech from multiple microphones in an array and map them into the expected output LPS features of anechoic reference speech based on a single deep neural network (DNN). Next, the temporal auto-correlation function of received signals at different RT60s is investigated to show that RT60-dependent temporal-spatial contexts in feature selection are needed in the DNNSpatial training stage in order to optimize the system performance in diverse reverberant environments. Finally, the RT60 is estimated to select the proper temporal and spatial contexts before feeding the log-power spectrum features to the trained DNNs for speech dereverberation. The experimental evidence gathered in this study indicates that the proposed framework outperforms the state-of-the-art signal processing dereverberation algorithm weighted prediction error (WPE) and conventional DNNSpatial systems without taking the reverberation time into account, even for extremely weak and severe reverberant conditions. The proposed technique generalizes well to unseen room size, array geometry and loudspeaker position, and is robust to reverberation time estimation error.

CRAFFT: An Activity Prediction Model based on Bayesian Networks

PubMed Central

Nazerfard, Ehsan; Cook, Diane J.

2014-01-01

Recent advances in the areas of pervasive computing, data mining, and machine learning offer unique opportunities to provide health monitoring and assistance for individuals facing difficulties to live independently in their homes. Several components have to work together to provide health monitoring for smart home residents including, but not limited to, activity recognition, activity discovery, activity prediction, and prompting system. Compared to the significant research done to discover and recognize activities, less attention has been given to predict the future activities that the resident is likely to perform. Activity prediction components can play a major role in design of a smart home. For instance, by taking advantage of an activity prediction module, a smart home can learn context-aware rules to prompt individuals to initiate important activities. In this paper, we propose an activity prediction model using Bayesian networks together with a novel two-step inference process to predict both the next activity features and the next activity label. We also propose an approach to predict the start time of the next activity which is based on modeling the relative start time of the predicted activity using the continuous normal distribution and outlier detection. To validate our proposed models, we used real data collected from physical smart environments. PMID:25937847

CRAFFT: An Activity Prediction Model based on Bayesian Networks.

PubMed

Nazerfard, Ehsan; Cook, Diane J

2015-04-01

Recent advances in the areas of pervasive computing, data mining, and machine learning offer unique opportunities to provide health monitoring and assistance for individuals facing difficulties to live independently in their homes. Several components have to work together to provide health monitoring for smart home residents including, but not limited to, activity recognition, activity discovery, activity prediction, and prompting system. Compared to the significant research done to discover and recognize activities, less attention has been given to predict the future activities that the resident is likely to perform. Activity prediction components can play a major role in design of a smart home. For instance, by taking advantage of an activity prediction module, a smart home can learn context-aware rules to prompt individuals to initiate important activities. In this paper, we propose an activity prediction model using Bayesian networks together with a novel two-step inference process to predict both the next activity features and the next activity label. We also propose an approach to predict the start time of the next activity which is based on modeling the relative start time of the predicted activity using the continuous normal distribution and outlier detection. To validate our proposed models, we used real data collected from physical smart environments.

Network Application Server Using Extensible Mark-Up Language (XML) to Support Distributed Databases and 3D Environments

DTIC Science & Technology

2001-12-01

diides.ncr.disa.mil/xmlreg/user/index.cfm] [ Deitel ] Deitel , H., Deitel , P., Java How to Program 3rd Edition, Prentice Hall, 1999. [DL99...presentation, and data) of information and the programming functionality. The Web framework addressed ability to provide a framework for the distribution...BLANK v ABSTRACT Advances in computer communication technology and an increased awareness of how enhanced information access can lead to improved

Distributed health literacy among people living with type 2 diabetes in Portugal: Defining levels of awareness and support.

PubMed

Abreu, Liliana; Nunes, João Arriscado; Taylor, Peter; Silva, Susana

2018-01-01

This study embraces a patient-centred and narrative-oriented notion of health literacy, exploring how social networks and personal experiences constitute distributed health literacy (DHL) by mapping out health literacy mediators of each individual and how they enable self-management skills and knowledge of health conditions. Semi-structured interviews with 26 patients with type 2 diabetes were conducted in a Primary Care Center of Porto (Portugal) from October 2014 to December 2015. Data were collected based on McGill Illness Narrative Interview (MINI). Following the grounded theory, interviews were analysed as case-based and process-tracing-oriented. Three awareness narratives emerged: (i) a narrative of minimisation revealing minimal impact of diabetes in patients' lives and daily routines, resignation towards "inevitable" consequences of the diagnosis and dependence of a large network of health literacy mediators; (ii) a narrative of empathy, where patients tended to mention readjustments in their lives by following medical recommendations regarding medication without criticism and with few health literacy mediators; (iii) a narrative of disruption, with patients highlighting the huge impact of diabetes on their lives and their individual responsibility and autonomy with respect to the management of diabetes and the search for alternatives to medication, relying on a very restrictive network of mediators. Exploring meanings given to diagnosis, identifying health mediators and analysing the structure of social networks can contribute to understand the distributed nature of health literacy. Assessing DHL can assist health professionals and those providing care in the community in promoting health literacy and providing models for a more patient-centred health system. © 2017 John Wiley & Sons Ltd.

Communication Needs Assessment for Distributed Turbine Engine Control

NASA Technical Reports Server (NTRS)

Culley, Dennis E.; Behbahani, Alireza R.

2008-01-01

Control system architecture is a major contributor to future propulsion engine performance enhancement and life cycle cost reduction. The control system architecture can be a means to effect net weight reduction in future engine systems, provide a streamlined approach to system design and implementation, and enable new opportunities for performance optimization and increased awareness about system health. The transition from a centralized, point-to-point analog control topology to a modular, networked, distributed system is paramount to extracting these system improvements. However, distributed engine control systems are only possible through the successful design and implementation of a suitable communication system. In a networked system, understanding the data flow between control elements is a fundamental requirement for specifying the communication architecture which, itself, is dependent on the functional capability of electronics in the engine environment. This paper presents an assessment of the communication needs for distributed control using strawman designs and relates how system design decisions relate to overall goals as we progress from the baseline centralized architecture, through partially distributed and fully distributed control systems.

Research on information security system of waste terminal disposal process

NASA Astrophysics Data System (ADS)

Zhou, Chao; Wang, Ziying; Guo, Jing; Guo, Yajuan; Huang, Wei

2017-05-01

Informatization has penetrated the whole process of production and operation of electric power enterprises. It not only improves the level of lean management and quality service, but also faces severe security risks. The internal network terminal is the outermost layer and the most vulnerable node of the inner network boundary. It has the characteristics of wide distribution, long depth and large quantity. The user and operation and maintenance personnel technical level and security awareness is uneven, which led to the internal network terminal is the weakest link in information security. Through the implementation of security of management, technology and physics, we should establish an internal network terminal security protection system, so as to fully protect the internal network terminal information security.

Sensor and information fusion for improved hostile fire situational awareness

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.; Ludwig, William D.

2010-04-01

A research-oriented Army Technology Objective (ATO) named Sensor and Information Fusion for Improved Hostile Fire Situational Awareness uniquely focuses on the underpinning technologies to detect and defeat any hostile threat; before, during, and after its occurrence. This is a joint effort led by the Army Research Laboratory, with the Armaments and the Communications and Electronics Research, Development, and Engineering Centers (CERDEC and ARDEC) partners. It addresses distributed sensor fusion and collaborative situational awareness enhancements, focusing on the underpinning technologies to detect/identify potential hostile shooters prior to firing a shot and to detect/classify/locate the firing point of hostile small arms, mortars, rockets, RPGs, and missiles after the first shot. A field experiment conducted addressed not only diverse modality sensor performance and sensor fusion benefits, but gathered useful data to develop and demonstrate the ad hoc networking and dissemination of relevant data and actionable intelligence. Represented at this field experiment were various sensor platforms such as UGS, soldier-worn, manned ground vehicles, UGVs, UAVs, and helicopters. This ATO continues to evaluate applicable technologies to include retro-reflection, UV, IR, visible, glint, LADAR, radar, acoustic, seismic, E-field, narrow-band emission and image processing techniques to detect the threats with very high confidence. Networked fusion of multi-modal data will reduce false alarms and improve actionable intelligence by distributing grid coordinates, detection report features, and imagery of threats.

An adaptive neural swarm approach for intrusion defense in ad hoc networks

NASA Astrophysics Data System (ADS)

Cannady, James

2011-06-01

Wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are being increasingly deployed in critical applications due to the flexibility and extensibility of the technology. While these networks possess numerous advantages over traditional wireless systems in dynamic environments they are still vulnerable to many of the same types of host-based and distributed attacks common to those systems. Unfortunately, the limited power and bandwidth available in WSNs and MANETs, combined with the dynamic connectivity that is a defining characteristic of the technology, makes it extremely difficult to utilize traditional intrusion detection techniques. This paper describes an approach to accurately and efficiently detect potentially damaging activity in WSNs and MANETs. It enables the network as a whole to recognize attacks, anomalies, and potential vulnerabilities in a distributive manner that reflects the autonomic processes of biological systems. Each component of the network recognizes activity in its local environment and then contributes to the overall situational awareness of the entire system. The approach utilizes agent-based swarm intelligence to adaptively identify potential data sources on each node and on adjacent nodes throughout the network. The swarm agents then self-organize into modular neural networks that utilize a reinforcement learning algorithm to identify relevant behavior patterns in the data without supervision. Once the modular neural networks have established interconnectivity both locally and with neighboring nodes the analysis of events within the network can be conducted collectively in real-time. The approach has been shown to be extremely effective in identifying distributed network attacks.

A System to Provide Real-Time Collaborative Situational Awareness by Web Enabling a Distributed Sensor Network

NASA Technical Reports Server (NTRS)

Panangadan, Anand; Monacos, Steve; Burleigh, Scott; Joswig, Joseph; James, Mark; Chow, Edward

2012-01-01

In this paper, we describe the architecture of both the PATS and SAP systems and how these two systems interoperate with each other forming a unified capability for deploying intelligence in hostile environments with the objective of providing actionable situational awareness of individuals. The SAP system works in concert with the UICDS information sharing middleware to provide data fusion from multiple sources. UICDS can then publish the sensor data using the OGC's Web Mapping Service, Web Feature Service, and Sensor Observation Service standards. The system described in the paper is able to integrate a spatially distributed sensor system, operating without the benefit of the Web infrastructure, with a remote monitoring and control system that is equipped to take advantage of SWE.

The Vehicular Information Space Framework

NASA Astrophysics Data System (ADS)

Prinz, Vivian; Schlichter, Johann; Schweiger, Benno

Vehicular networks are distributed, self-organizing and highly mobile ad hoc networks. They allow for providing drivers with up-to-the-minute information about their environment. Therefore, they are expected to be a decisive future enabler for enhancing driving comfort and safety. This article introduces the Vehicular Information Space framework (VIS). Vehicles running the VIS form a kind of distributed database. It enables them to provide information like existing hazards, parking spaces or traffic densities in a location aware and fully distributed manner. In addition, vehicles can retrieve, modify and delete these information items. The underlying algorithm is based on features derived from existing structured Peer-to-Peer algorithms and extended to suit the specific characteristics of highly mobile ad hoc networks. We present, implement and simulate the VIS using a motorway and an urban traffic environment. Simulation studies on VIS message occurrence show that the VIS implies reasonable traffic overhead. Also, overall VIS message traffic is independent from the number of information items provided.

Hierarchy Bayesian model based services awareness of high-speed optical access networks

NASA Astrophysics Data System (ADS)

Bai, Hui-feng

2018-03-01

As the speed of optical access networks soars with ever increasing multiple services, the service-supporting ability of optical access networks suffers greatly from the shortage of service awareness. Aiming to solve this problem, a hierarchy Bayesian model based services awareness mechanism is proposed for high-speed optical access networks. This approach builds a so-called hierarchy Bayesian model, according to the structure of typical optical access networks. Moreover, the proposed scheme is able to conduct simple services awareness operation in each optical network unit (ONU) and to perform complex services awareness from the whole view of system in optical line terminal (OLT). Simulation results show that the proposed scheme is able to achieve better quality of services (QoS), in terms of packet loss rate and time delay.

Toward a generalized theory of epidemic awareness in social networks

NASA Astrophysics Data System (ADS)

Wu, Qingchu; Zhu, Wenfang

We discuss the dynamics of a susceptible-infected-susceptible (SIS) model with local awareness in networks. Individual awareness to the infectious disease is characterized by a general function of epidemic information in its neighborhood. We build a high-accuracy approximate equation governing the spreading dynamics and derive an approximate epidemic threshold above which the epidemic spreads over the whole network. Our results extend the previous work and show that the epidemic threshold is dependent on the awareness function in terms of one infectious neighbor. Interestingly, when a pow-law awareness function is chosen, the epidemic threshold can emerge in infinite networks.

Mapping to Irregular Torus Topologies and Other Techniques for Petascale Biomolecular Simulation

PubMed Central

Phillips, James C.; Sun, Yanhua; Jain, Nikhil; Bohm, Eric J.; Kalé, Laxmikant V.

2014-01-01

Currently deployed petascale supercomputers typically use toroidal network topologies in three or more dimensions. While these networks perform well for topology-agnostic codes on a few thousand nodes, leadership machines with 20,000 nodes require topology awareness to avoid network contention for communication-intensive codes. Topology adaptation is complicated by irregular node allocation shapes and holes due to dedicated input/output nodes or hardware failure. In the context of the popular molecular dynamics program NAMD, we present methods for mapping a periodic 3-D grid of fixed-size spatial decomposition domains to 3-D Cray Gemini and 5-D IBM Blue Gene/Q toroidal networks to enable hundred-million atom full machine simulations, and to similarly partition node allocations into compact domains for smaller simulations using multiple-copy algorithms. Additional enabling techniques are discussed and performance is reported for NCSA Blue Waters, ORNL Titan, ANL Mira, TACC Stampede, and NERSC Edison. PMID:25594075

The application of artificial intelligence techniques to large distributed networks

NASA Technical Reports Server (NTRS)

Dubyah, R.; Smith, T. R.; Star, J. L.

1985-01-01

Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

The hearing ear is always found close to the speaking tongue: Review of the role of the motor system in speech perception.

PubMed

Skipper, Jeremy I; Devlin, Joseph T; Lametti, Daniel R

2017-01-01

Does "the motor system" play "a role" in speech perception? If so, where, how, and when? We conducted a systematic review that addresses these questions using both qualitative and quantitative methods. The qualitative review of behavioural, computational modelling, non-human animal, brain damage/disorder, electrical stimulation/recording, and neuroimaging research suggests that distributed brain regions involved in producing speech play specific, dynamic, and contextually determined roles in speech perception. The quantitative review employed region and network based neuroimaging meta-analyses and a novel text mining method to describe relative contributions of nodes in distributed brain networks. Supporting the qualitative review, results show a specific functional correspondence between regions involved in non-linguistic movement of the articulators, covertly and overtly producing speech, and the perception of both nonword and word sounds. This distributed set of cortical and subcortical speech production regions are ubiquitously active and form multiple networks whose topologies dynamically change with listening context. Results are inconsistent with motor and acoustic only models of speech perception and classical and contemporary dual-stream models of the organization of language and the brain. Instead, results are more consistent with complex network models in which multiple speech production related networks and subnetworks dynamically self-organize to constrain interpretation of indeterminant acoustic patterns as listening context requires. Copyright © 2016. Published by Elsevier Inc.

An Expert System-based Context-Aware Ubiquitous Learning Approach for Conducting Science Learning Activities

ERIC Educational Resources Information Center

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung

2013-01-01

Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…

Learning in a u-Museum: Developing a Context-Aware Ubiquitous Learning Environment

ERIC Educational Resources Information Center

Chen, Chia-Chen; Huang, Tien-Chi

2012-01-01

Context-awareness techniques can support learners in learning without time or location constraints by using mobile devices and associated learning activities in a real learning environment. Enrichment of context-aware technologies has enabled students to learn in an environment that integrates learning resources from both the real world and the…

Low-complex energy-aware image communication in visual sensor networks

NASA Astrophysics Data System (ADS)

Phamila, Yesudhas Asnath Victy; Amutha, Ramachandran

2013-10-01

A low-complex, low bit rate, energy-efficient image compression algorithm explicitly designed for resource-constrained visual sensor networks applied for surveillance, battle field, habitat monitoring, etc. is presented, where voluminous amount of image data has to be communicated over a bandwidth-limited wireless medium. The proposed method overcomes the energy limitation of individual nodes and is investigated in terms of image quality, entropy, processing time, overall energy consumption, and system lifetime. This algorithm is highly energy efficient and extremely fast since it applies energy-aware zonal binary discrete cosine transform (DCT) that computes only the few required significant coefficients and codes them using enhanced complementary Golomb Rice code without using any floating point operations. Experiments are performed using the Atmel Atmega128 and MSP430 processors to measure the resultant energy savings. Simulation results show that the proposed energy-aware fast zonal transform consumes only 0.3% of energy needed by conventional DCT. This algorithm consumes only 6% of energy needed by Independent JPEG Group (fast) version, and it suits for embedded systems requiring low power consumption. The proposed scheme is unique since it significantly enhances the lifetime of the camera sensor node and the network without any need for distributed processing as was traditionally required in existing algorithms.

Fisher's geometrical model emerges as a property of complex integrated phenotypic networks.

PubMed

Martin, Guillaume

2014-05-01

Models relating phenotype space to fitness (phenotype-fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher's geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model "from first principles" is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher's model's assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts.

Sex-specific effects of social networks on the prevalence, awareness, and control of hypertension among older Korean adults.

PubMed

Baek, Jiwon; Hur, Nam Wook; Kim, Hyeon Chang; Youm, Yoosik

2016-07-01

Hypertension is a common chronic disease among older adults, and is associated with medical complications and mortality. This study aimed to examine the effects of social network characteristics on the prevalence, awareness, and control of hypertension among older adults. The Korean Social Life, Health, and Aging Project (KSHAP) interviewed 814 ≥ 60-year-old residents and their spouses from a rural township between December 2011 and March 2012 (response rate: 95%). We evaluated the data from 595 participants. Multivariate logistic regression models were used to assess the effects of network characteristics on hypertension. We observed strong sex-specific network effects on the prevalence, awareness, and control of hypertension. Among older women, network density was associated with hypertension awareness [odds ratio (OR): 2.63, 95% confidence interval (CI): 1.03-5.37] and control (OR: 1.72; 95% CI: 0.94-3.13). Among older men, large networks were associated with a lower prevalence of hypertension (OR: 0.75; 95% CI: 0.58-0.96). Compared to older women, older men with coarse networks exhibited better hypertension awareness (OR: 0.37; 95% CI: 0.14-0.95) and control (OR: 0.42; 95% CI: 0.19-0.91). Network size interacted with density for hypertension control (P = 0.051), with controlled hypertension being associated with large and course networks. A large network was associated with a lower risk for hypertension, and a coarse network was associated with hypertension awareness and control among older men. Older women with dense networks were most likely to exhibit hypertension awareness and control.

Network-Aware Mechanisms for Tolerating Byzantine Failures in Distributed Systems

DTIC Science & Technology

2012-01-01

In Digest, we use SHA-256 as the collision-resistant hash function. We use the realization of SHA-256 from the OpenSSL toolkit [48]. The results...vol. 46, pp. 372–378, 1997. [48] “ Openssl project.” [Online]. Available: http://www.openssl.org/ 154 [49] M. J. Fischer, N. A. Lynch, and M. Merritt

Space Domain Awareness

DTIC Science & Technology

2012-09-01

the Space Surveillance Network has been tracking orbital objects and maintaining a catalog that allows space operators to safely operate satellites ...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...Distribution Unlimited) backward) in time , but the accuracy degrades as the amount of propagation time increases. Thus, the need to maintain a

Development, awareness and inductive selectivity.

PubMed

Hayes, Brett K; Lim, Melissa

2013-05-01

Two studies examined whether adults and children could learn to make context-dependent inferences about novel stimuli and the role of awareness of context cues in such learning. Participants were trained to match probes to targets on the basis of shape or color with the relevant dimension shifting according to item context. A selective induction test then examined context-dependent responding in a more complex matching task. Awareness of the role of context was assessed using a behavioral task and explicit questions. Experiment 1 showed that after training with the procedure described by Sloutsky and Fisher (2008), only a minority of adults showed evidence of context-dependent responding in the selective induction test. Experiment 2 used a modified training protocol that promoted attention to context cues. This led to reliable selective induction in a majority of adults and a sizeable proportion of 4- to 6-year-olds. Crucially, in both age groups, selective induction was dependent on awareness of context. Hence, children as young as 4 can learn to make selective inferences about novel stimuli, but only when they are aware of the relevant context cues. These results challenge previous claims that selective induction in children is the product of implicit learning.

Education on the Electronic Frontier: Teleapprentices in Globally Distributed Educational Contexts. Interactive Technology Laboratory Report #14.

ERIC Educational Resources Information Center

Levin, James A.; And Others

1987-01-01

The instructional media created by microcomputers interconnected by modems to form long-distance networks present some powerful new opportunities for education. While other uses of computers in education have been built on conventional instructional models of classroom interaction, instructional electronic networks facilitate a wider use of…

Education on the Electronic Frontier: Teleapprentices in Globally Distributed Educational Contexts.

ERIC Educational Resources Information Center

Levin, James A.; And Others

1987-01-01

The Inter-cultural Network is an electronic communication network connecting faculty and upper elementary through graduate students in the U.S., Mexico, Japan, and Israel. The students address the problem of water shortage, while learning science concepts and transferring learning. A new form of instruction, teleapprenticeships, is suggested. (GDC)

Situating emotional experience

PubMed Central

Wilson-Mendenhall, Christine D.; Barrett, Lisa Feldman; Barsalou, Lawrence W.

2013-01-01

Psychological construction approaches to emotion suggest that emotional experience is situated and dynamic. Fear, for example, is typically studied in a physical danger context (e.g., threatening snake), but in the real world, it often occurs in social contexts, especially those involving social evaluation (e.g., public speaking). Understanding situated emotional experience is critical because adaptive responding is guided by situational context (e.g., inferring the intention of another in a social evaluation situation vs. monitoring the environment in a physical danger situation). In an fMRI study, we assessed situated emotional experience using a newly developed paradigm in which participants vividly imagine different scenarios from a first-person perspective, in this case scenarios involving either social evaluation or physical danger. We hypothesized that distributed neural patterns would underlie immersion in social evaluation and physical danger situations, with shared activity patterns across both situations in multiple sensory modalities and in circuitry involved in integrating salient sensory information, and with unique activity patterns for each situation type in coordinated large-scale networks that reflect situated responding. More specifically, we predicted that networks underlying the social inference and mentalizing involved in responding to a social threat (in regions that make up the “default mode” network) would be reliably more active during social evaluation situations. In contrast, networks underlying the visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations. The results supported these hypotheses. In line with emerging psychological construction approaches, the findings suggest that coordinated brain networks offer a systematic way to interpret the distributed patterns that underlie the diverse situational contexts characterizing emotional life. PMID:24324420

Sensor Deployment for Geographic, Load Balanced Hierarchical Organization in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Gautam, Amit Kr.; Gautam, Ajay Kr.; Patel, R. B.

2010-11-01

In order to provide load balancing in clustered sensor deployment, the upstream clusters (near the BS) are kept smaller in size as compared to downstream ones (away from BS). Moreover, geographic awareness is also desirable in order to further enhance energy efficiency. But, this must be cost effective, since most of current location awareness strategies are either cost and weight inefficient (GPS) or are complex, inaccurate and unreliable in operation. This paper presents design and implementation of a Geographic LOad BALanced (GLOBAL) Clustering Protocol for Wireless Sensor Networks. A mathematical formulation is provided for determining the number of sensor nodes in each cluster. This enables uniform energy consumption after the multi-hop data transmission towards BS. Either the sensors can be manually deployed or the clusters be so formed that the sensor are efficiently distributed as per formulation. The latter strategy is elaborated in this contribution. Methods to provide static clustering and custom cluster sizes with location awareness are also provided in the given work. Finally, low mobility node applications can also implement the proposed work.

Avoiding the conflict: Metacognitive awareness drives the selection of low-demand contexts.

PubMed

Desender, Kobe; Buc Calderon, Cristian; Van Opstal, Filip; Van den Bussche, Eva

2017-07-01

Previous research attempted to explain how humans strategically adapt behavior in order to achieve successful task performance. Recently, it has been suggested that 1 potential strategy is to avoid tasks that are too demanding. Here, we report 3 experiments that investigate the empirically neglected role of metacognitive awareness in this process. In these experiments, participants could freely choose between performing a task in either a high-demand or a low-demand context. Using subliminal priming, we ensured that participants were not aware of the visual stimuli creating these different demand contexts. Our results showed that participants who noticed a difference in task difficulty (i.e., metacognitive aware participants) developed a clear preference for the low-demand context. In contrast, participants who experienced no difference in task difficulty (i.e., metacognitive unaware participants) based their choices on variables unrelated to cognitive demand (e.g., the color or location associated with a context), and did not develop a preference for the low-demand context. Crucially, this pattern was found despite identical task performance in both metacognitive awareness groups. A multiple regression approach confirmed that metacognitive awareness was the main factor driving the preference for low-demand contexts. These results argue for an important role of metacognitive awareness in the strategic avoidance of demanding tasks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program-Awareness

DTIC Science & Technology

2012-04-30

individualistic , Western view of human behavior. That is, it assumes that people adhere to the individualistic principles of Western culture . What happens to...people with networks rich in structural holes that live/work in environments that adhere to other principles, such as those of a collectivistic ... culture ? •http://orgtheory.wordpress.com/2007/06/19/structural-holes-in-context/ Preferential Attachment (PA) [Barabási & Albert, 1999] • The most

Replacement predictions for drinking water networks through historical data.

PubMed

Malm, Annika; Ljunggren, Olle; Bergstedt, Olof; Pettersson, Thomas J R; Morrison, Gregory M

2012-05-01

Lifetime distribution functions and current network age data can be combined to provide an assessment of the future replacement needs for drinking water distribution networks. Reliable lifetime predictions are limited by a lack of understanding of deterioration processes for different pipe materials under varied conditions. An alternative approach is the use of real historical data for replacement over an extended time series. In this paper, future replacement needs are predicted through historical data representing more than one hundred years of drinking water pipe replacement in Gothenburg, Sweden. The verified data fits well with commonly used lifetime distribution curves. Predictions for the future are discussed in the context of path dependence theory. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ambient awareness: From random noise to digital closeness in online social networks

PubMed Central

Levordashka, Ana; Utz, Sonja

2016-01-01

Ambient awareness refers to the awareness social media users develop of their online network in result of being constantly exposed to social information, such as microblogging updates. Although each individual bit of information can seem like random noise, their incessant reception can amass to a coherent representation of social others. Despite its growing popularity and important implications for social media research, ambient awareness on public social media has not been studied empirically. We provide evidence for the occurrence of ambient awareness and examine key questions related to its content and functions. A diverse sample of participants reported experiencing awareness, both as a general feeling towards their network as a whole, and as knowledge of individual members of the network, whom they had not met in real life. Our results indicate that ambient awareness can develop peripherally, from fragmented information and in the relative absence of extensive one-to-one communication. We report the effects of demographics, media use, and network variables and discuss the implications of ambient awareness for relational and informational processes online. PMID:27375343

Ambient awareness: From random noise to digital closeness in online social networks.

PubMed

Levordashka, Ana; Utz, Sonja

2016-07-01

Ambient awareness refers to the awareness social media users develop of their online network in result of being constantly exposed to social information, such as microblogging updates. Although each individual bit of information can seem like random noise, their incessant reception can amass to a coherent representation of social others. Despite its growing popularity and important implications for social media research, ambient awareness on public social media has not been studied empirically. We provide evidence for the occurrence of ambient awareness and examine key questions related to its content and functions. A diverse sample of participants reported experiencing awareness, both as a general feeling towards their network as a whole, and as knowledge of individual members of the network, whom they had not met in real life. Our results indicate that ambient awareness can develop peripherally, from fragmented information and in the relative absence of extensive one-to-one communication. We report the effects of demographics, media use, and network variables and discuss the implications of ambient awareness for relational and informational processes online.

Using Context-Aware Ubiquitous Learning to Support Students' Understanding of Geometry

ERIC Educational Resources Information Center

Crompton, Helen

2015-01-01

In this study, context-aware ubiquitous learning was used to support 4th grade students as they learn angle concepts. Context-aware ubiquitous learning was provided to students primarily through the use of iPads to access real-world connections and a Dynamic Geometry Environment. Gravemeijer and van Eerde's (2009), design-based research (DBR)…

Technical Feasibility of a Mobile Context-Aware (Social) Learning Schedule Framework

ERIC Educational Resources Information Center

Yau, Jane Y. K.; Joy, Mike

2013-01-01

The purpose of this paper is to show the technical feasibility of implementing their mobile context-aware learning schedule (mCALS) framework as a software application on a mobile device using current technologies, prior to its actual implementation. This process draws a set of compatible mobile and context-aware technologies at present and can be…

A Heuristic Algorithm for Planning Personalized Learning Paths for Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Kuo, Fan-Ray; Yin, Peng-Yeng; Chuang, Kuo-Hsien

2010-01-01

In a context-aware ubiquitous learning environment, learning systems can detect students' learning behaviors in the real-world with the help of context-aware (sensor) technology; that is, students can be guided to observe or operate real-world objects with personalized support from the digital world. In this study, an optimization problem that…

Department Networks and Distributed Leadership in Schools

ERIC Educational Resources Information Center

de Lima, Jorge Avila

2008-01-01

Many schools are organised into departments which function as contexts that frame teachers' professional experiences in important ways. Some educational systems have adopted distributed forms of leadership within schools that rely strongly on the departmental structure and on the role of the department coordinator as teacher leader. This paper…

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics

PubMed Central

Kotevska, Olivera; Kusne, A. Gilad; Samarov, Daniel V.; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today’s cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County. PMID:29250476

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics.

PubMed

Kotevska, Olivera; Kusne, A Gilad; Samarov, Daniel V; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today's cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County.

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

PubMed Central

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

PubMed

Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

2015-01-01

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

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.

Implementation of Context Aware e-Health Environments Based on Social Sensor Networks

PubMed Central

Aguirre, Erik; Led, Santiago; Lopez-Iturri, Peio; Azpilicueta, Leyre; Serrano, Luís; Falcone, Francisco

2016-01-01

In this work, context aware scenarios applied to e-Health and m-Health in the framework of typical households (urban and rural) by means of deploying Social Sensors will be described. Interaction with end-users and social/medical staff is achieved using a multi-signal input/output device, capable of sensing and transmitting environmental, biomedical or activity signals and information with the aid of a combined Bluetooth and Mobile system platform. The devices, which play the role of Social Sensors, are implemented and tested in order to guarantee adequate service levels in terms of multiple signal processing tasks as well as robustness in relation with the use wireless transceivers and channel variability. Initial tests within a Living Lab environment have been performed in order to validate overall system operation. The results obtained show good acceptance of the proposed system both by end users as well as by medical and social staff, increasing interaction, reducing overall response time and social inclusion levels, with a compact and moderate cost solution that can readily be largely deployed. PMID:26938539

Implementation of Context Aware e-Health Environments Based on Social Sensor Networks.

PubMed

Aguirre, Erik; Led, Santiago; Lopez-Iturri, Peio; Azpilicueta, Leyre; Serrano, Luís; Falcone, Francisco

2016-03-01

In this work, context aware scenarios applied to e-Health and m-Health in the framework of typical households (urban and rural) by means of deploying Social Sensors will be described. Interaction with end-users and social/medical staff is achieved using a multi-signal input/output device, capable of sensing and transmitting environmental, biomedical or activity signals and information with the aid of a combined Bluetooth and Mobile system platform. The devices, which play the role of Social Sensors, are implemented and tested in order to guarantee adequate service levels in terms of multiple signal processing tasks as well as robustness in relation with the use wireless transceivers and channel variability. Initial tests within a Living Lab environment have been performed in order to validate overall system operation. The results obtained show good acceptance of the proposed system both by end users as well as by medical and social staff, increasing interaction, reducing overall response time and social inclusion levels, with a compact and moderate cost solution that can readily be largely deployed.

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics

PubMed Central

2017-01-01

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473

Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.

PubMed

Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier

2017-10-21

Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.

A comprehensive survey of energy-aware routing protocols in wireless body area sensor networks.

PubMed

Effatparvar, Mehdi; Dehghan, Mehdi; Rahmani, Amir Masoud

2016-09-01

Wireless body area sensor network is a special purpose wireless sensor network that, employing wireless sensor nodes in, on, or around the human body, makes it possible to measure biological parameters of a person for specific applications. One of the most fundamental concerns in wireless body sensor networks is accurate routing in order to send data promptly and properly, and therefore overcome some of the challenges. Routing protocols for such networks are affected by a large number of factors including energy, topology, temperature, posture, the radio range of sensors, and appropriate quality of service in sensor nodes. Since energy is highly important in wireless body area sensor networks, and increasing the network lifetime results in benefiting greatly from sensor capabilities, improving routing performance with reduced energy consumption presents a major challenge. This paper aims to study wireless body area sensor networks and the related routing methods. It also presents a thorough, comprehensive review of routing methods in wireless body area sensor networks from the perspective of energy. Furthermore, different routing methods affecting the parameter of energy will be classified and compared according to their advantages and disadvantages. In this paper, fundamental concepts of wireless body area sensor networks are provided, and then the advantages and disadvantages of these networks are investigated. Since one of the most fundamental issues in wireless body sensor networks is to perform routing so as to transmit data precisely and promptly, we discuss the same issue. As a result, we propose a classification of the available relevant literature with respect to the key challenge of energy in the routing process. With this end in view, all important papers published between 2000 and 2015 are classified under eight categories including 'Mobility-Aware', 'Thermal-Aware', 'Restriction of Location and Number of Relays', 'Link-aware', 'Cluster- and Tree-Based', 'Cross-Layer', 'Opportunistic', and 'Medium Access Control'. We, then, provide a full description of the statistical analysis of each category in relation to all papers, current hybrid protocols, and the type of simulators used in each paper. Next, we analyze the distribution of papers in each category during various years. Moreover, for each category, the advantages and disadvantages as well as the number of issued papers in different years are given. We also analyze the type of layer and deployment of mathematical models or algorithmic techniques in each category. Finally, after introducing certain important protocols for each category, the goals, advantages, and disadvantages of the protocols are discussed and compared with each other.

MAppERS experience: natural processes and preparedness in the societal context

NASA Astrophysics Data System (ADS)

Frigerio, Simone; Schenato, Luca; Bossi, Giulia; Mantovani, Matteo; Marcato, Gianluca; Pasuto, Alessandro

2016-04-01

Within natural processes responsibilities from central authorities to local levels as first actors of civil protection is a changing pattern. Prevention and preparedness in natural hazards are long-term goals based on capacities of professional volunteers, and improving the awareness of the citizens as local inhabitants. Local people have impacts on their lives but training and involvement towards specific techniques change their role within risk communication and emergency preparedness. A collaborative user environment is useful for emergency response and support in the wake of disasters, feeding updated information on the ground directly to on-site responders. MAppERS (Mobile Application for Emergency Response and Support) is a funded project (2013-2015 Humanitarian Aid and Civil Protection, ECHO A5) based on human role as "crowd-sourced mappers" through smart phone application able to share GPS-localised and detailed parameters. The feedback from testing and the training courses aim to raising public awareness and participation in a networked disaster response. The project implies design and test of smart phone linked with a real-time dashboard platform for rescue services citizens and volunteers of civil protection. Two pilot sites, including trainings on modules functioning control usability and quality of the product. The synchronized platform offers the activity of cloud data collection with a central data dashboard. Information is collected in a context of floods processes, with crowdsourcing action from local population, for proper awareness with own personal flood plan and long-term preparedness. A second context tested pre-emergency actions on field with rescue team, collecting state-of-art and condition of hazards.

A Proposal for IoT Dynamic Routes Selection Based on Contextual Information

PubMed Central

Filho, Raimir Holanda; Rabelo, Ricardo de A. L.; Sousa, Natanael de C.; Filho, José C. C. L. S.

2018-01-01

The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information). This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications. In this case, fuzzy logic is used to translate in math terms the imprecise information expressed by a set of linguistic rules. For this purpose, four Objective Functions (OFs) are proposed for the Routing Protocol for Low Power and Loss Networks (RPL); such OFs are dynamically selected based on context information. The aforementioned OFs are generated from the fusion of the following metrics: Expected Transmission Count (ETX), Number of Hops (NH) and Energy Consumed (EC). The experiments performed through simulation, associated with the statistical data analysis, conclude that this proposal provides high reliability by successfully delivering nearly 100% of data packets, low delay for data delivery and increase in QoS. In addition, an 30% improvement is attained in the network life time when using one of proposed objective function, keeping the devices alive for longer duration. PMID:29373499

Smart learning services based on smart cloud computing.

PubMed

Kim, Svetlana; Song, Su-Mi; Yoon, Yong-Ik

2011-01-01

Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user's behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands context as well. The context-awareness in e-learning may include the awareness of user profile and terminal context. In this paper, we propose a new notion of service that provides context-awareness to smart learning content in a cloud computing environment. We suggest the elastic four smarts (E4S)--smart pull, smart prospect, smart content, and smart push--concept to the cloud services so smart learning services are possible. The E4S focuses on meeting the users' needs by collecting and analyzing users' behavior, prospecting future services, building corresponding contents, and delivering the contents through cloud computing environment. Users' behavior can be collected through mobile devices such as smart phones that have built-in sensors. As results, the proposed smart e-learning model in cloud computing environment provides personalized and customized learning services to its users.

Smart Learning Services Based on Smart Cloud Computing

PubMed Central

Kim, Svetlana; Song, Su-Mi; Yoon, Yong-Ik

2011-01-01

Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user’s behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands context as well. The context-awareness in e-learning may include the awareness of user profile and terminal context. In this paper, we propose a new notion of service that provides context-awareness to smart learning content in a cloud computing environment. We suggest the elastic four smarts (E4S)—smart pull, smart prospect, smart content, and smart push—concept to the cloud services so smart learning services are possible. The E4S focuses on meeting the users’ needs by collecting and analyzing users’ behavior, prospecting future services, building corresponding contents, and delivering the contents through cloud computing environment. Users’ behavior can be collected through mobile devices such as smart phones that have built-in sensors. As results, the proposed smart e-learning model in cloud computing environment provides personalized and customized learning services to its users. PMID:22164048

Holding-time-aware asymmetric spectrum allocation in virtual optical networks

NASA Astrophysics Data System (ADS)

Lyu, Chunjian; Li, Hui; Liu, Yuze; Ji, Yuefeng

2017-10-01

Virtual optical networks (VONs) have been considered as a promising solution to support current high-capacity dynamic traffic and achieve rapid applications deployment. Since most of the network services (e.g., high-definition video service, cloud computing, distributed storage) in VONs are provisioned by dedicated data centers, needing different amount of bandwidth resources in both directions, the network traffic is mostly asymmetric. The common strategy, symmetric provisioning of traffic in optical networks, leads to a waste of spectrum resources in such traffic patterns. In this paper, we design a holding-time-aware asymmetric spectrum allocation module based on SDON architecture and an asymmetric spectrum allocation algorithm based on the module is proposed. For the purpose of reducing spectrum resources' waste, the algorithm attempts to reallocate the idle unidirectional spectrum slots in VONs, which are generated due to the asymmetry of services' bidirectional bandwidth. This part of resources can be exploited by other requests, such as short-time non-VON requests. We also introduce a two-dimensional asymmetric resource model for maintaining idle spectrum resources information of VON in spectrum and time domains. Moreover, a simulation is designed to evaluate the performance of the proposed algorithm, and results show that our proposed asymmetric spectrum allocation algorithm can improve the resource waste and reduce blocking probability.

Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness.

PubMed

Buchler, Norbou; Fitzhugh, Sean M; Marusich, Laura R; Ungvarsky, Diane M; Lebiere, Christian; Gonzalez, Cleotilde

2016-01-01

A common assumption in organizations is that information sharing improves situation awareness and ultimately organizational effectiveness. The sheer volume and rapid pace of information and communications received and readily accessible through computer networks, however, can overwhelm individuals, resulting in data overload from a combination of diverse data sources, multiple data formats, and large data volumes. The current conceptual framework of network enabled operations (NEO) posits that robust networking and information sharing act as a positive feedback loop resulting in greater situation awareness and mission effectiveness in military operations (Alberts and Garstka, 2004). We test this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi-echelon Mission Command staff (one Division and two sub-ordinate Brigades) and assessed the situational awareness of every individual. Results from our exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation awareness. It emerged that higher situation awareness was associated with a lower probability of out-ties, so that broadly sending many messages decreased the likelihood of attaining situation awareness. This challenges the hypothesis that increased information sharing improves situation awareness, at least for those doing the bulk of the sharing. In addition, we observed two trends that reflect a compartmentalizing of networked information sharing as email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between two individuals with dissimilar functions and levels of situation awareness; both those findings can be interpreted to reflect effects of homophily. Our results have major implications that challenge the current conceptual framework of NEO. In addition, the information sharing network was largely imbalanced and dominated by a few key individuals so that most individuals in the network have very few email connections, but a small number of individuals have very many connections. These results highlight several major growing pains for networked organizations and military organizations in particular.

Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

PubMed Central

Buchler, Norbou; Fitzhugh, Sean M.; Marusich, Laura R.; Ungvarsky, Diane M.; Lebiere, Christian; Gonzalez, Cleotilde

2016-01-01

A common assumption in organizations is that information sharing improves situation awareness and ultimately organizational effectiveness. The sheer volume and rapid pace of information and communications received and readily accessible through computer networks, however, can overwhelm individuals, resulting in data overload from a combination of diverse data sources, multiple data formats, and large data volumes. The current conceptual framework of network enabled operations (NEO) posits that robust networking and information sharing act as a positive feedback loop resulting in greater situation awareness and mission effectiveness in military operations (Alberts and Garstka, 2004). We test this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi-echelon Mission Command staff (one Division and two sub-ordinate Brigades) and assessed the situational awareness of every individual. Results from our exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation awareness. It emerged that higher situation awareness was associated with a lower probability of out-ties, so that broadly sending many messages decreased the likelihood of attaining situation awareness. This challenges the hypothesis that increased information sharing improves situation awareness, at least for those doing the bulk of the sharing. In addition, we observed two trends that reflect a compartmentalizing of networked information sharing as email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between two individuals with dissimilar functions and levels of situation awareness; both those findings can be interpreted to reflect effects of homophily. Our results have major implications that challenge the current conceptual framework of NEO. In addition, the information sharing network was largely imbalanced and dominated by a few key individuals so that most individuals in the network have very few email connections, but a small number of individuals have very many connections. These results highlight several major growing pains for networked organizations and military organizations in particular. PMID:27445905

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

PubMed

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

2018-03-05

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

A Context-Aware-Based Audio Guidance System for Blind People Using a Multimodal Profile Model

PubMed Central

Lin, Qing; Han, Youngjoon

2014-01-01

A wearable guidance system is designed to provide context-dependent guidance messages to blind people while they traverse local pathways. The system is composed of three parts: moving scene analysis, walking context estimation and audio message delivery. The combination of a downward-pointing laser scanner and a camera is used to solve the challenging problem of moving scene analysis. By integrating laser data profiles and image edge profiles, a multimodal profile model is constructed to estimate jointly the ground plane, object locations and object types, by using a Bayesian network. The outputs of the moving scene analysis are further employed to estimate the walking context, which is defined as a fuzzy safety level that is inferred through a fuzzy logic model. Depending on the estimated walking context, the audio messages that best suit the current context are delivered to the user in a flexible manner. The proposed system is tested under various local pathway scenes, and the results confirm its efficiency in assisting blind people to attain autonomous mobility. PMID:25302812

Interference Aware Routing Using Spatial Reuse in Wireless Sensor Networks

DTIC Science & Technology

2013-12-01

practice there is no optimal STDMA algorithm due to the computational complexity of the STDMA implementation; therefore, the common approach is to...Applications, Springer Berlin Heidelberg, pp. 653–657, 2001. [26] B. Korte and J. Vygen, “Shortest Paths,” Combinatorial Optimization Theory and...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited INTERFERENCE

Smart sensing surveillance system

NASA Astrophysics Data System (ADS)

Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen

2010-04-01

An effective public safety sensor system for heavily-populated applications requires sophisticated and geographically-distributed infrastructures, centralized supervision, and deployment of large-scale security and surveillance networks. Artificial intelligence in sensor systems is a critical design to raise awareness levels, improve the performance of the system and adapt to a changing scenario and environment. In this paper, a highly-distributed, fault-tolerant, and energy-efficient Smart Sensing Surveillance System (S4) is presented to efficiently provide a 24/7 and all weather security operation in crowded environments or restricted areas. Technically, the S4 consists of a number of distributed sensor nodes integrated with specific passive sensors to rapidly collect, process, and disseminate heterogeneous sensor data from near omni-directions. These distributed sensor nodes can cooperatively work to send immediate security information when new objects appear. When the new objects are detected, the S4 will smartly select the available node with a Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR camera to track the objects and capture associated imagery. The S4 provides applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. Other imaging processes can be updated to meet specific requirements and operations. In the S4, all the sensor nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology. This UWB RF technology can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The Service Oriented Architecture of S4 enables remote applications to interact with the S4 network and use the specific presentation methods. In addition, the S4 is compliant with Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE) standards to efficiently discover, access, use, and control heterogeneous sensors and their metadata. These S4 capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments. The S4 system is directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.

Contention Modeling for Multithreaded Distributed Shared Memory Machines: The Cray XMT

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

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

Distributed Shared Memory (DSM) machines are a wide class of multi-processor computing systems where a large virtually-shared address space is mapped on a network of physically distributed memories. High memory latency and network contention are two of the main factors that limit performance scaling of such architectures. Modern high-performance computing DSM systems have evolved toward exploitation of massive hardware multi-threading and fine-grained memory hashing to tolerate irregular latencies, avoid network hot-spots and enable high scaling. In order to model the performance of such large-scale machines, parallel simulation has been proved to be a promising approach to achieve good accuracy inmore » reasonable times. One of the most critical factors in solving the simulation speed-accuracy trade-off is network modeling. The Cray XMT is a massively multi-threaded supercomputing architecture that belongs to the DSM class, since it implements a globally-shared address space abstraction on top of a physically distributed memory substrate. In this paper, we discuss the development of a contention-aware network model intended to be integrated in a full-system XMT simulator. We start by measuring the effects of network contention in a 128-processor XMT machine and then investigate the trade-off that exists between simulation accuracy and speed, by comparing three network models which operate at different levels of accuracy. The comparison and model validation is performed by executing a string-matching algorithm on the full-system simulator and on the XMT, using three datasets that generate noticeably different contention patterns.« less

Distribution of Amphipods (Gammarus nipponensis Ueno) Among Mountain Headwater Streams with Different Legacies of Debris Flow Occurrence

EPA Science Inventory

To understand the impacts of debris flows on the distribution of an amphipod with limited dispersal ability in the context of stream networks, we surveyed the presence of Gammarus nipponensis in 87 headwater streams with different legacies of debris flow occurrence within an 8.5-...

Real-Time Support on IEEE 802.11 Wireless Ad-Hoc Networks: Reality vs. Theory

NASA Astrophysics Data System (ADS)

Kang, Mikyung; Kang, Dong-In; Suh, Jinwoo

The usable throughput of an IEEE 802.11 system for an application is much less than the raw bandwidth. Although 802.11b has a theoretical maximum of 11Mbps, more than half of the bandwidth is consumed by overhead leaving at most 5Mbps of usable bandwidth. Considering this characteristic, this paper proposes and analyzes a real-time distributed scheduling scheme based on the existing IEEE 802.11 wireless ad-hoc networks, using USC/ISI's Power Aware Sensing Tracking and Analysis (PASTA) hardware platform. We compared the distributed real-time scheduling scheme with the real-time polling scheme to meet deadline, and compared a measured real bandwidth with a theoretical result. The theoretical and experimental results show that the distributed scheduling scheme can guarantee real-time traffic and enhances the performance up to 74% compared with polling scheme.

Architecture of a framework for providing information services for public transport.

PubMed

García, Carmelo R; Pérez, Ricardo; Lorenzo, Alvaro; Quesada-Arencibia, Alexis; Alayón, Francisco; Padrón, Gabino

2012-01-01

This paper presents OnRoute, a framework for developing and running ubiquitous software that provides information services to passengers of public transportation, including payment systems and on-route guidance services. To achieve a high level of interoperability, accessibility and context awareness, OnRoute uses the ubiquitous computing paradigm. To guarantee the quality of the software produced, the reliable software principles used in critical contexts, such as automotive systems, are also considered by the framework. The main components of its architecture (run-time, system services, software components and development discipline) and how they are deployed in the transportation network (stations and vehicles) are described in this paper. Finally, to illustrate the use of OnRoute, the development of a guidance service for travellers is explained.

Networks in ATLAS

NASA Astrophysics Data System (ADS)

McKee, Shawn; ATLAS Collaboration

2017-10-01

Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

A Software Product Line Process to Develop Agents for the IoT

PubMed Central

Ayala, Inmaculada; Amor, Mercedes; Fuentes, Lidia; Troya, José M.

2015-01-01

One of the most important challenges of this decade is the Internet of Things (IoT), which aims to enable things to be connected anytime, anyplace, with anything and anyone, ideally using any path/network and any service. IoT systems are usually composed of heterogeneous and interconnected lightweight devices that support applications that are subject to change in their external environment and in the functioning of these devices. The management of the variability of these changes, autonomously, is a challenge in the development of these systems. Agents are a good option for developing self-managed IoT systems due to their distributed nature, context-awareness and self-adaptation. Our goal is to enhance the development of IoT applications using agents and software product lines (SPL). Specifically, we propose to use Self-StarMASMAS, multi-agent system) agents and to define an SPL process using the Common Variability Language. In this contribution, we propose an SPL process for Self-StarMAS, paying particular attention to agents embedded in sensor motes. PMID:26140350

Framework for Designing Context-Aware Learning Systems

ERIC Educational Resources Information Center

Tortorella, Richard A. W.; Kinshuk; Chen, Nian-Shing

2018-01-01

Today people learn in many diverse locations and contexts, beyond the confines of classical brick and mortar classrooms. This trend is ever increasing, progressing hand-in-hand with the progress of technology. Context-aware learning systems are systems which adapt to the learner's context, providing tailored learning for a particular learning…

A mathematical model for generating bipartite graphs and its application to protein networks

NASA Astrophysics Data System (ADS)

Nacher, J. C.; Ochiai, T.; Hayashida, M.; Akutsu, T.

2009-12-01

Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

YouTube as a participatory culture.

PubMed

Chau, Clement

2010-01-01

There is an explosion of youth subscriptions to original content-media-sharing Web sites such as YouTube. These Web sites combine media production and distribution with social networking features, making them an ideal place to create, connect, collaborate, and circulate. By encouraging youth to become media creators and social networkers, new media platforms such as YouTube offer a participatory culture in which youth can develop, interact, and learn. As youth development researchers, we must be cognizant of this context and critically examine what this platform offers that might be unique to (or redundant of) typical adolescent experiences in other developmental contexts.

Resource Management for Distributed Parallel Systems

NASA Technical Reports Server (NTRS)

Neuman, B. Clifford; Rao, Santosh

1993-01-01

Multiprocessor systems should exist in the the larger context of distributed systems, allowing multiprocessor resources to be shared by those that need them. Unfortunately, typical multiprocessor resource management techniques do not scale to large networks. The Prospero Resource Manager (PRM) is a scalable resource allocation system that supports the allocation of processing resources in large networks and multiprocessor systems. To manage resources in such distributed parallel systems, PRM employs three types of managers: system managers, job managers, and node managers. There exist multiple independent instances of each type of manager, reducing bottlenecks. The complexity of each manager is further reduced because each is designed to utilize information at an appropriate level of abstraction.

Event-triggered output feedback control for distributed networked systems.

PubMed

Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

2016-01-01

This paper addresses the problem of output-feedback communication and control with event-triggered framework in the context of distributed networked control systems. The design problem of the event-triggered output-feedback control is proposed as a linear matrix inequality (LMI) feasibility problem. The scheme is developed for the distributed system where only partial states are available. In this scheme, a subsystem uses local observers and share its information to its neighbors only when the subsystem's local error exceeds a specified threshold. The developed method is illustrated by using a coupled cart example from the literature. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Providing Situational Awareness for Pipeline Control Operations

NASA Astrophysics Data System (ADS)

Butts, Jonathan; Kleinhans, Hugo; Chandia, Rodrigo; Papa, Mauricio; Shenoi, Sujeet

A SCADA system for a single 3,000-mile-long strand of oil or gas pipeline may employ several thousand field devices to measure process parameters and operate equipment. Because of the vital tasks performed by these sensors and actuators, pipeline operators need accurate and timely information about their status and integrity. This paper describes a realtime scanner that provides situational awareness about SCADA devices and control operations. The scanner, with the assistance of lightweight, distributed sensors, analyzes SCADA network traffic, verifies the operational status and integrity of field devices, and identifies anomalous activity. Experimental results obtained using real pipeline control traffic demonstrate the utility of the scanner in industrial settings.

A Service-oriented Approach towards Context-aware Mobile Learning Management Systems

DTIC Science & Technology

2010-07-01

towards a pervasive university. Keywords-context-aware computing, service-oriented archi- tecture, mobile computing, elearning , learn management sys- tem I...usage of device- specific features provide support for various ubiquitous and pervasive eLearning scenarios [2][3]. By knowing where the user currently...data from the mobile device towards a context-aware mobile LMS. II. BASIC CONCEPTS For a better understanding of the presented eLearning sce- narios

Dynamical Interplay between Awareness and Epidemic Spreading in Multiplex Networks

NASA Astrophysics Data System (ADS)

Granell, Clara; Gómez, Sergio; Arenas, Alex

2013-09-01

We present the analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the information awareness to prevent its infection, on top of multiplex networks. This scenario is representative of an epidemic process spreading on a network of persistent real contacts, and a cyclic information awareness process diffusing in the network of virtual social contacts between the same individuals. The topology corresponds to a multiplex network where two diffusive processes are interacting affecting each other. The analysis using a microscopic Markov chain approach reveals the phase diagram of the incidence of the epidemics and allows us to capture the evolution of the epidemic threshold depending on the topological structure of the multiplex and the interrelation with the awareness process. Interestingly, the critical point for the onset of the epidemics has a critical value (metacritical point) defined by the awareness dynamics and the topology of the virtual network, from which the onset increases and the epidemics incidence decreases.

Dynamical interplay between awareness and epidemic spreading in multiplex networks.

PubMed

Granell, Clara; Gómez, Sergio; Arenas, Alex

2013-09-20

We present the analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the information awareness to prevent its infection, on top of multiplex networks. This scenario is representative of an epidemic process spreading on a network of persistent real contacts, and a cyclic information awareness process diffusing in the network of virtual social contacts between the same individuals. The topology corresponds to a multiplex network where two diffusive processes are interacting affecting each other. The analysis using a microscopic Markov chain approach reveals the phase diagram of the incidence of the epidemics and allows us to capture the evolution of the epidemic threshold depending on the topological structure of the multiplex and the interrelation with the awareness process. Interestingly, the critical point for the onset of the epidemics has a critical value (metacritical point) defined by the awareness dynamics and the topology of the virtual network, from which the onset increases and the epidemics incidence decreases.

Cyber situational awareness and differential hardening

NASA Astrophysics Data System (ADS)

Dwivedi, Anurag; Tebben, Dan

2012-06-01

The advent of cyber threats has created a need for a new network planning, design, architecture, operations, control, situational awareness, management, and maintenance paradigms. Primary considerations include the ability to assess cyber attack resiliency of the network, and rapidly detect, isolate, and operate during deliberate simultaneous attacks against the network nodes and links. Legacy network planning relied on automatic protection of a network in the event of a single fault or a very few simultaneous faults in mesh networks, but in the future it must be augmented to include improved network resiliency and vulnerability awareness to cyber attacks. Ability to design a resilient network requires the development of methods to define, and quantify the network resiliency to attacks, and to be able to develop new optimization strategies for maintaining operations in the midst of these newly emerging cyber threats. Ways to quantify resiliency, and its use in visualizing cyber vulnerability awareness and in identifying node or link criticality, are presented in the current work, as well as a methodology of differential network hardening based on the criticality profile of cyber network components.

If it walks like a duck: nanosensor threat assessment

NASA Astrophysics Data System (ADS)

Chachis, George C.

2003-09-01

A convergence of technologies is making deployment of unattended ground nanosensors operationally feasible in terms of energy, communications for both arbitrated and self-organizing distributed, collective behaviors. A number of nano communications technologies are already making network-centric systems possible for MicroElectrical Mechanical (MEM) sensor devices today. Similar technologies may make NanoElectrical Mechanical (NEM) sensor devices operationally feasible a few years from now. Just as organizational behaviors of large numbers of nanodevices can derive strategies from social insects and other group-oriented animals, bio-inspired heuristics for threat assessment provide a conceptual approach for successful integration of nanosensors into unattended smart sensor networks. Biological models such as the organization of social insects or the dynamics of immune systems show promise as biologically-inspired paradigms for protecting nanosensor networks for security scene analysis and battlespace awareness. The paradox of nanosensors is that the smaller the device is the more useful it is but the smaller it is the more vulnerable it is to a variety of threats. In other words simpler means networked nanosensors are more likely to fall prey to a wide-range of attacks including jamming, spoofing, Janisserian recruitment, Pied-Piper distraction, as well as typical attacks computer network security. Thus, unattended sensor technologies call for network architectures that include security and countermeasures to provide reliable scene analysis or battlespace awareness information. Such network centric architectures may well draw upon a variety of bio-inspired approaches to safeguard, validate and make sense of large quantities of information.

A self-organizing neural network for job scheduling in distributed systems

NASA Astrophysics Data System (ADS)

Newman, Harvey B.; Legrand, Iosif C.

2001-08-01

The aim of this work is to describe a possible approach for the optimization of the job scheduling in large distributed systems, based on a self-organizing Neural Network. This dynamic scheduling system should be seen as adaptive middle layer software, aware of current available resources and making the scheduling decisions using the "past experience." It aims to optimize job specific parameters as well as the resource utilization. The scheduling system is able to dynamically learn and cluster information in a large dimensional parameter space and at the same time to explore new regions in the parameters space. This self-organizing scheduling system may offer a possible solution to provide an effective use of resources for the off-line data processing jobs for future HEP experiments.

PLEXIL-DL: Language and Runtime for Context-Aware Robot Behaviour

NASA Astrophysics Data System (ADS)

Moser, Herwig; Reichelt, Toni; Oswald, Norbert; Förster, Stefan

Faced with the growing complexity of application scenarios social robots are involved with, the perception of environmental circumstances and the sentient reactions are becoming more and more important abilities. Rather than regarding both abilities in isolation, the entire transformation process, from context-awareness to purposive behaviour, forms a robot’s adaptivity. While attaining context-awareness has received much attention in literature so far, translating it into appropriate actions still lacks a comprehensive approach. In this paper, we present PLEXIL-DL, an expressive language allowing complex context expressions as an integral part of constructs that define sophisticated behavioural reactions. Our approach extends NASA’s PLEXIL language by Description Logic queries, both in syntax and formal semantics. A prototypical implementation of a PLEXIL-DL interpreter shows the basic mechanisms facilitating the robot’s adaptivity through context-awareness.

Epidemic spreading with activity-driven awareness diffusion on multiplex network.

PubMed

Guo, Quantong; Lei, Yanjun; Jiang, Xin; Ma, Yifang; Huo, Guanying; Zheng, Zhiming

2016-04-01

There has been growing interest in exploring the interplay between epidemic spreading with human response, since it is natural for people to take various measures when they become aware of epidemics. As a proper way to describe the multiple connections among people in reality, multiplex network, a set of nodes interacting through multiple sets of edges, has attracted much attention. In this paper, to explore the coupled dynamical processes, a multiplex network with two layers is built. Specifically, the information spreading layer is a time varying network generated by the activity driven model, while the contagion layer is a static network. We extend the microscopic Markov chain approach to derive the epidemic threshold of the model. Compared with extensive Monte Carlo simulations, the method shows high accuracy for the prediction of the epidemic threshold. Besides, taking different spreading models of awareness into consideration, we explored the interplay between epidemic spreading with awareness spreading. The results show that the awareness spreading can not only enhance the epidemic threshold but also reduce the prevalence of epidemics. When the spreading of awareness is defined as susceptible-infected-susceptible model, there exists a critical value where the dynamical process on the awareness layer can control the onset of epidemics; while if it is a threshold model, the epidemic threshold emerges an abrupt transition with the local awareness ratio α approximating 0.5. Moreover, we also find that temporal changes in the topology hinder the spread of awareness which directly affect the epidemic threshold, especially when the awareness layer is threshold model. Given that the threshold model is a widely used model for social contagion, this is an important and meaningful result. Our results could also lead to interesting future research about the different time-scales of structural changes in multiplex networks.

Epidemic spreading with activity-driven awareness diffusion on multiplex network

NASA Astrophysics Data System (ADS)

Guo, Quantong; Lei, Yanjun; Jiang, Xin; Ma, Yifang; Huo, Guanying; Zheng, Zhiming

2016-04-01

There has been growing interest in exploring the interplay between epidemic spreading with human response, since it is natural for people to take various measures when they become aware of epidemics. As a proper way to describe the multiple connections among people in reality, multiplex network, a set of nodes interacting through multiple sets of edges, has attracted much attention. In this paper, to explore the coupled dynamical processes, a multiplex network with two layers is built. Specifically, the information spreading layer is a time varying network generated by the activity driven model, while the contagion layer is a static network. We extend the microscopic Markov chain approach to derive the epidemic threshold of the model. Compared with extensive Monte Carlo simulations, the method shows high accuracy for the prediction of the epidemic threshold. Besides, taking different spreading models of awareness into consideration, we explored the interplay between epidemic spreading with awareness spreading. The results show that the awareness spreading can not only enhance the epidemic threshold but also reduce the prevalence of epidemics. When the spreading of awareness is defined as susceptible-infected-susceptible model, there exists a critical value where the dynamical process on the awareness layer can control the onset of epidemics; while if it is a threshold model, the epidemic threshold emerges an abrupt transition with the local awareness ratio α approximating 0.5. Moreover, we also find that temporal changes in the topology hinder the spread of awareness which directly affect the epidemic threshold, especially when the awareness layer is threshold model. Given that the threshold model is a widely used model for social contagion, this is an important and meaningful result. Our results could also lead to interesting future research about the different time-scales of structural changes in multiplex networks.

Influence versus intent for predictive analytics in situation awareness

NASA Astrophysics Data System (ADS)

Cui, Biru; Yang, Shanchieh J.; Kadar, Ivan

2013-05-01

Predictive analytics in situation awareness requires an element to comprehend and anticipate potential adversary activities that might occur in the future. Most work in high level fusion or predictive analytics utilizes machine learning, pattern mining, Bayesian inference, and decision tree techniques to predict future actions or states. The emergence of social computing in broader contexts has drawn interests in bringing the hypotheses and techniques from social theory to algorithmic and computational settings for predictive analytics. This paper aims at answering the question on how influence and attitude (some interpreted such as intent) of adversarial actors can be formulated and computed algorithmically, as a higher level fusion process to provide predictions of future actions. The challenges in this interdisciplinary endeavor include drawing existing understanding of influence and attitude in both social science and computing fields, as well as the mathematical and computational formulation for the specific context of situation to be analyzed. The study of `influence' has resurfaced in recent years due to the emergence of social networks in the virtualized cyber world. Theoretical analysis and techniques developed in this area are discussed in this paper in the context of predictive analysis. Meanwhile, the notion of intent, or `attitude' using social theory terminologies, is a relatively uncharted area in the computing field. Note that a key objective of predictive analytics is to identify impending/planned attacks so their `impact' and `threat' can be prevented. In this spirit, indirect and direct observables are drawn and derived to infer the influence network and attitude to predict future threats. This work proposes an integrated framework that jointly assesses adversarial actors' influence network and their attitudes as a function of past actions and action outcomes. A preliminary set of algorithms are developed and tested using the Global Terrorism Database (GTD). Our results reveals the benefits to perform joint predictive analytics with both attitude and influence. At the same time, we discover significant challenges in deriving influence and attitude from indirect observables for diverse adversarial behavior. These observations warrant further investigation of optimal use of influence and attitude for predictive analytics, as well as the potential inclusion of other environmental or capability elements for the actors.

Multifunctional Information Distribution System (MIDS)

DTIC Science & Technology

2013-12-01

Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to...Estimate DoD - Department of Defense DSN - Defense Switched Network Econ - Economic Eng - Engineering Est - Estimating FMS - Foreign Military Sales FY...fighter aircraft, bombers, helicopters, ships, and ground sites . The MIDS Program consists of the MIDS Low Volume Terminal (MIDS-LVT) and the MIDS

Communication Needs Assessment for Distributed Turbine Engine Control (Postprint)

DTIC Science & Technology

2008-07-01

and implementation, and enable new opportunities for performance optimization and increased awareness about system health. The transition from a...must be integrated into the communication network.10 These could include new sensors, actuators, or even complex subsystems for more advanced...No. 0704-0188 The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for

The Asian American Network for Cancer Awareness, Research, and Training’s Role in Cancer Awareness, Research, and Training

PubMed Central

Chen, Moon S.

2006-01-01

Purpose The purpose of this paper is to describe the content for the Asian American Network for Cancer Awareness Research and Training (AANCART) with respect to Asian American demographic characteristics and their cancer burden, highlights of accomplishments in various AANCART regions, aspirations for AANCART, and an interim assessment of AANCART’s activities to date. Methods The author compiled literature and other data references to describe the context for Asian American demographic characteristics and their cancer burden. As the AANCART Principal Investigator, he collected data from internal AANCART reports to depict highlights of accomplishments in various AANCART regions and offer evidence that AANCART’s first two specific aims have been attained. Principal Findings With respect to our first specific aim, we have built an infrastructure for cancer awareness, research and training operationally at a Network-wide basis through program directors for biostatistics, community, clinical, and research and in our four original AANCART regions: New York, Seattle, San Francisco, and Los Angeles. With respect to our second specific aim, we have established partnerships as exemplified by working collaboratively with New York’s Charles B. Wang Community Health Center in securing external funding with them for a tobacco control initiative and nationally with the American Cancer Society. With respect to our third specific aim, we have been fortunate to assist at least eight junior investigators in receiving NCI-funded pilot studies. The most notable change was the transfer of AANCART’s national headquarters from Columbus, Ohio to Sacramento, California along with potentially an increased diversification of Asian American ethnic groups as well as an expansion to Hawaii and Houston. Conclusion As of the end of year 2 of AANCART, AANCART’s two specific aims have been achieved. We are focusing on our third specific aim. PMID:15352772

Sensor Network-Based and User-Friendly User Location Discovery for Future Smart Homes

PubMed Central

Ahvar, Ehsan; Lee, Gyu Myoung; Han, Son N.; Crespi, Noel; Khan, Imran

2016-01-01

User location is crucial context information for future smart homes where many location based services will be proposed. This location necessarily means that User Location Discovery (ULD) will play an important role in future smart homes. Concerns about privacy and the need to carry a mobile or a tag device within a smart home currently make conventional ULD systems uncomfortable for users. Future smart homes will need a ULD system to consider these challenges. This paper addresses the design of such a ULD system for context-aware services in future smart homes stressing the following challenges: (i) users’ privacy; (ii) device-/tag-free; and (iii) fault tolerance and accuracy. On the other hand, emerging new technologies, such as the Internet of Things, embedded systems, intelligent devices and machine-to-machine communication, are penetrating into our daily life with more and more sensors available for use in our homes. Considering this opportunity, we propose a ULD system that is capitalizing on the prevalence of sensors for the home while satisfying the aforementioned challenges. The proposed sensor network-based and user-friendly ULD system relies on different types of inexpensive sensors, as well as a context broker with a fuzzy-based decision-maker. The context broker receives context information from different types of sensors and evaluates that data using the fuzzy set theory. We demonstrate the performance of the proposed system by illustrating a use case, utilizing both an analytical model and simulation. PMID:27355951

Sensor Network-Based and User-Friendly User Location Discovery for Future Smart Homes.

PubMed

Ahvar, Ehsan; Lee, Gyu Myoung; Han, Son N; Crespi, Noel; Khan, Imran

2016-06-27

User location is crucial context information for future smart homes where many location based services will be proposed. This location necessarily means that User Location Discovery (ULD) will play an important role in future smart homes. Concerns about privacy and the need to carry a mobile or a tag device within a smart home currently make conventional ULD systems uncomfortable for users. Future smart homes will need a ULD system to consider these challenges. This paper addresses the design of such a ULD system for context-aware services in future smart homes stressing the following challenges: (i) users' privacy; (ii) device-/tag-free; and (iii) fault tolerance and accuracy. On the other hand, emerging new technologies, such as the Internet of Things, embedded systems, intelligent devices and machine-to-machine communication, are penetrating into our daily life with more and more sensors available for use in our homes. Considering this opportunity, we propose a ULD system that is capitalizing on the prevalence of sensors for the home while satisfying the aforementioned challenges. The proposed sensor network-based and user-friendly ULD system relies on different types of inexpensive sensors, as well as a context broker with a fuzzy-based decision-maker. The context broker receives context information from different types of sensors and evaluates that data using the fuzzy set theory. We demonstrate the performance of the proposed system by illustrating a use case, utilizing both an analytical model and simulation.

Privacy Preservation in Context-Aware Systems

DTIC Science & Technology

2011-01-01

Policies and the Semantic Web The Semantic Web refers to both a vision and a set of technologies. The vision was first articulated by Tim Berners - Lee ... Berners - lee 2005) is a distributed framework for describing and reasoning over policies in the Semantic Web. It supports N3 rules ( Berners - Lee ...Connolly 2008), ( Berners - Lee et al. 2005) for representing intercon- nections between policies and resources and uses the CWM forward-chaining reasoning

Universe Awareness: a global educational programme

NASA Astrophysics Data System (ADS)

Sankatsing Nava, Tibisay; Russo, Pedro

2015-08-01

Universe Awareness (UNAWE) is a global astronomy education programme that uses the beauty and grandeur of the Universe to encourage young children, particularly those from an underprivileged background, to have an interest in science and technology and foster their sense of global citizenship from an early age.UNAWE’s activities consist of four main components:- Coordinating an international network comprised of more than 1000 astronomers, teachers and educators in more than 60 countries- Developing and distributing educational resources such as the inflatable UNAWE Earthball, the Universe-in-a Box educational kit and Space Scoop, the astronomy news service for children.- Providing training activities for teachers and other educators of young children around the world- Providing resources for the evaluation of educational activitiesBetween 2011 and 2013, the European branch of UNAWE, EU-UNAWE, was funded by the European Commission to implement a project in 5 EU countries and South Africa. This project has been concluded successfully. The global project of Universe Awareness coordinated by Leiden University has continued to grow since, with an expanding international network, new educational resources and teacher trainings and an International Workshop in collaboration with ESA in October 2015, among other activities.

A Bayesian Belief Network of Threat Anticipation and Terrorist Motivations

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

Olama, Mohammed M; Allgood, Glenn O; Davenport, Kristen M

Recent events highlight the need for efficient tools for anticipating the threat posed by terrorists, whether individual or groups. Antiterrorism includes fostering awareness of potential threats, deterring aggressors, developing security measures, planning for future events, halting an event in process, and ultimately mitigating and managing the consequences of an event. To analyze such components, one must understand various aspects of threat elements like physical assets and their economic and social impacts. To this aim, we developed a three-layer Bayesian belief network (BBN) model that takes into consideration the relative threat of an attack against a particular asset (physical layer) asmore » well as the individual psychology and motivations that would induce a person to either act alone or join a terrorist group and commit terrorist acts (social and economic layers). After researching the many possible motivations to become a terrorist, the main factors are compiled and sorted into categories such as initial and personal indicators, exclusion factors, and predictive behaviors. Assessing such threats requires combining information from disparate data sources most of which involve uncertainties. BBN combines these data in a coherent, analytically defensible, and understandable manner. The developed BBN model takes into consideration the likelihood and consequence of a threat in order to draw inferences about the risk of a terrorist attack so that mitigation efforts can be optimally deployed. The model is constructed using a network engineering process that treats the probability distributions of all the BBN nodes within the broader context of the system development process.« less

Using Bayesian networks to support decision-focused information retrieval

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

Lehner, P.; Elsaesser, C.; Seligman, L.

This paper has described an approach to controlling the process of pulling data/information from distributed data bases in a way that is specific to a persons specific decision making context. Our prototype implementation of this approach uses a knowledge-based planner to generate a plan, an automatically constructed Bayesian network to evaluate the plan, specialized processing of the network to derive key information items that would substantially impact the evaluation of the plan (e.g., determine that replanning is needed), automated construction of Standing Requests for Information (SRIs) which are automated functions that monitor changes and trends in distributed data base thatmore » are relevant to the key information items. This emphasis of this paper is on how Bayesian networks are used.« less

A survey of body sensor networks.

PubMed

Lai, Xiaochen; Liu, Quanli; Wei, Xin; Wang, Wei; Zhou, Guoqiao; Han, Guangyi

2013-04-24

The technology of sensor, pervasive computing, and intelligent information processing is widely used in Body Sensor Networks (BSNs), which are a branch of wireless sensor networks (WSNs). BSNs are playing an increasingly important role in the fields of medical treatment, social welfare and sports, and are changing the way humans use computers. Existing surveys have placed emphasis on the concept and architecture of BSNs, signal acquisition, context-aware sensing, and system technology, while this paper will focus on sensor, data fusion, and network communication. And we will introduce the research status of BSNs, the analysis of hotspots, and future development trends, the discussion of major challenges and technical problems facing currently. The typical research projects and practical application of BSNs are introduced as well. BSNs are progressing along the direction of multi-technology integration and intelligence. Although there are still many problems, the future of BSNs is fundamentally promising, profoundly changing the human-machine relationships and improving the quality of people's lives.

A Survey of Body Sensor Networks

PubMed Central

Lai, Xiaochen; Liu, Quanli; Wei, Xin; Wang, Wei; Zhou, Guoqiao; Han, Guangyi

2013-01-01

The technology of sensor, pervasive computing, and intelligent information processing is widely used in Body Sensor Networks (BSNs), which are a branch of wireless sensor networks (WSNs). BSNs are playing an increasingly important role in the fields of medical treatment, social welfare and sports, and are changing the way humans use computers. Existing surveys have placed emphasis on the concept and architecture of BSNs, signal acquisition, context-aware sensing, and system technology, while this paper will focus on sensor, data fusion, and network communication. And we will introduce the research status of BSNs, the analysis of hotspots, and future development trends, the discussion of major challenges and technical problems facing currently. The typical research projects and practical application of BSNs are introduced as well. BSNs are progressing along the direction of multi-technology integration and intelligence. Although there are still many problems, the future of BSNs is fundamentally promising, profoundly changing the human-machine relationships and improving the quality of people's lives. PMID:23615581

THREAT ANTICIPATION AND DECEPTIVE REASONING USING BAYESIAN BELIEF NETWORKS

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

Allgood, Glenn O; Olama, Mohammed M; Lake, Joe E

Recent events highlight the need for tools to anticipate threats posed by terrorists. Assessing these threats requires combining information from disparate data sources such as analytic models, simulations, historical data, sensor networks, and user judgments. These disparate data can be combined in a coherent, analytically defensible, and understandable manner using a Bayesian belief network (BBN). In this paper, we develop a BBN threat anticipatory model based on a deceptive reasoning algorithm using a network engineering process that treats the probability distributions of the BBN nodes within the broader context of the system development process.

Promoting Social Network Awareness: A Social Network Monitoring System

ERIC Educational Resources Information Center

Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

2010-01-01

To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

The neural basis of impaired self-awareness after traumatic brain injury

PubMed Central

Ham, Timothy E.; Bonnelle, Valerie; Hellyer, Peter; Jilka, Sagar; Robertson, Ian H.; Leech, Robert

2014-01-01

Self-awareness is commonly impaired after traumatic brain injury. This is an important clinical issue as awareness affects long-term outcome and limits attempts at rehabilitation. It can be investigated by studying how patients respond to their errors and monitor their performance on tasks. As awareness is thought to be an emergent property of network activity, we tested the hypothesis that impaired self-awareness is associated with abnormal brain network function. We investigated a group of subjects with traumatic brain injury (n = 63) split into low and high performance-monitoring groups based on their ability to recognize and correct their own errors. Brain network function was assessed using resting-state and event-related functional magnetic resonance imaging. This allowed us to investigate baseline network function, as well as the evoked response of networks to specific events including errors. The low performance-monitoring group underestimated their disability and showed broad attentional deficits. Neural activity within what has been termed the fronto-parietal control network was abnormal in patients with impaired self-awareness. The dorsal anterior cingulate cortex is a key part of this network that is involved in performance-monitoring. This region showed reduced functional connectivity to the rest of the fronto-parietal control network at ‘rest’. In addition, the anterior insulae, which are normally tightly linked to the dorsal anterior cingulate cortex, showed increased activity following errors in the impaired group. Interestingly, the traumatic brain injury patient group with normal performance-monitoring showed abnormally high activation of the right middle frontal gyrus, putamen and caudate in response to errors. The impairment of self-awareness was not explained either by the location of focal brain injury, or the amount of traumatic axonal injury as demonstrated by diffusion tensor imaging. The results suggest that impairments of self-awareness after traumatic brain injury result from breakdown of functional interactions between nodes within the fronto-parietal control network. PMID:24371217

The neural basis of impaired self-awareness after traumatic brain injury.

PubMed

Ham, Timothy E; Bonnelle, Valerie; Hellyer, Peter; Jilka, Sagar; Robertson, Ian H; Leech, Robert; Sharp, David J

2014-02-01

Self-awareness is commonly impaired after traumatic brain injury. This is an important clinical issue as awareness affects long-term outcome and limits attempts at rehabilitation. It can be investigated by studying how patients respond to their errors and monitor their performance on tasks. As awareness is thought to be an emergent property of network activity, we tested the hypothesis that impaired self-awareness is associated with abnormal brain network function. We investigated a group of subjects with traumatic brain injury (n = 63) split into low and high performance-monitoring groups based on their ability to recognize and correct their own errors. Brain network function was assessed using resting-state and event-related functional magnetic resonance imaging. This allowed us to investigate baseline network function, as well as the evoked response of networks to specific events including errors. The low performance-monitoring group underestimated their disability and showed broad attentional deficits. Neural activity within what has been termed the fronto-parietal control network was abnormal in patients with impaired self-awareness. The dorsal anterior cingulate cortex is a key part of this network that is involved in performance-monitoring. This region showed reduced functional connectivity to the rest of the fronto-parietal control network at 'rest'. In addition, the anterior insulae, which are normally tightly linked to the dorsal anterior cingulate cortex, showed increased activity following errors in the impaired group. Interestingly, the traumatic brain injury patient group with normal performance-monitoring showed abnormally high activation of the right middle frontal gyrus, putamen and caudate in response to errors. The impairment of self-awareness was not explained either by the location of focal brain injury, or the amount of traumatic axonal injury as demonstrated by diffusion tensor imaging. The results suggest that impairments of self-awareness after traumatic brain injury result from breakdown of functional interactions between nodes within the fronto-parietal control network.

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

PubMed

Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

2015-01-01

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection

PubMed Central

Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

2015-01-01

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

The correlation of metrics in complex networks with applications in functional brain networks

NASA Astrophysics Data System (ADS)

Li, C.; Wang, H.; de Haan, W.; Stam, C. J.; Van Mieghem, P.

2011-11-01

An increasing number of network metrics have been applied in network analysis. If metric relations were known better, we could more effectively characterize networks by a small set of metrics to discover the association between network properties/metrics and network functioning. In this paper, we investigate the linear correlation coefficients between widely studied network metrics in three network models (Bárabasi-Albert graphs, Erdös-Rényi random graphs and Watts-Strogatz small-world graphs) as well as in functional brain networks of healthy subjects. The metric correlations, which we have observed and theoretically explained, motivate us to propose a small representative set of metrics by including only one metric from each subset of mutually strongly dependent metrics. The following contributions are considered important. (a) A network with a given degree distribution can indeed be characterized by a small representative set of metrics. (b) Unweighted networks, which are obtained from weighted functional brain networks with a fixed threshold, and Erdös-Rényi random graphs follow a similar degree distribution. Moreover, their metric correlations and the resultant representative metrics are similar as well. This verifies the influence of degree distribution on metric correlations. (c) Most metric correlations can be explained analytically. (d) Interestingly, the most studied metrics so far, the average shortest path length and the clustering coefficient, are strongly correlated and, thus, redundant. Whereas spectral metrics, though only studied recently in the context of complex networks, seem to be essential in network characterizations. This representative set of metrics tends to both sufficiently and effectively characterize networks with a given degree distribution. In the study of a specific network, however, we have to at least consider the representative set so that important network properties will not be neglected.

Improving situation awareness with the Android Team Awareness Kit (ATAK)

NASA Astrophysics Data System (ADS)

Usbeck, Kyle; Gillen, Matthew; Loyall, Joseph; Gronosky, Andrew; Sterling, Joshua; Kohler, Ralph; Hanlon, Kelly; Scally, Andrew; Newkirk, Richard; Canestrare, David

2015-05-01

To make appropriate, timely decisions in the field, Situational Awareness (SA) needs to be conveyed in a decentralized manner to the users at the edge of the network as well as at operations centers. Sharing real-time SA efficiently between command centers and operational troops poses many challenges, including handling heterogeneous and dynamic networks, resource constraints, and varying needs for the collection, dissemination, and display of information, as well as recording that information. A mapping application that allows teams to share relevant geospatial information efficiently and to communicate effectively with one another and command centers has wide applicability to many vertical markets across the Department of Defense, as well as a wide variety of federal, state local, and non-profit agencies that need to share locations, text, photos, and video. This paper describes the Android Team Awareness Kit (ATAK), an advanced, distributed tool for commercial- off-the-shelf (COTS) mobile devices such as smartphones and tablets. ATAK provides a variety of useful SA functions for soldiers, law enforcement, homeland defense, and civilian collaborative use; including mapping and navigation, range and bearing, text chat, force tracking, geospatial markup tools, image and file sharing, video playback, site surveys, and many others. This paper describes ATAK, the SA tools that ATAK has built-in, and the ways it is being used by a variety of military, homeland security, and law enforcement users.

A Social Approach to High-Level Context Generation for Supporting Context-Aware M-Learning

ERIC Educational Resources Information Center

Pan, Xu-Wei; Ding, Ling; Zhu, Xi-Yong; Yang, Zhao-Xiang

2017-01-01

In m-learning environments, context-awareness is for wide use where learners' situations are varied, dynamic and unpredictable. We are facing the challenge of requirements of both generality and depth in generating and processing high-level context. In this paper, we present a social approach which exploits social dynamics and social computing for…

Understanding social disparities in hypertension prevalence, awareness, treatment, and control: the role of neighborhood context.

PubMed

Morenoff, Jeffrey D; House, James S; Hansen, Ben B; Williams, David R; Kaplan, George A; Hunte, Haslyn E

2007-11-01

The spatial segregation of the US population by socioeconomic position and especially race/ethnicity suggests that the social contexts or "neighborhoods" in which people live may substantially contribute to social disparities in hypertension. The Chicago Community Adult Health Study did face-to-face interviews, including direct measurement of blood pressure, with a representative probability sample of adults in Chicago. These data were used to estimate socioeconomic and racial-ethnic disparities in the prevalence, awareness, treatment, and control of hypertension, and to analyze how these disparities are related to the areas in which people live. Hypertension was significantly negatively associated with neighborhood affluence/gentrification, and adjustments for context eliminated the highly significant disparity between blacks/African-Americans and whites, and reduced the significant educational disparity by 10-15% to borderline statistical significance. Awareness of hypertension was significantly higher in more disadvantaged neighborhoods and in places with higher concentrations of blacks (and lower concentrations of Hispanics and immigrants). Adjustment for context completely eliminated blacks' greater awareness, but slightly accentuated the lesser awareness of Hispanics and the greater levels of awareness among the less educated. There was no consistent evidence of either social disparities in or contextual associations with treatment of hypertension, given awareness. Among those on medication, blacks were only 40-50% as likely as whites to have their hypertension controlled, but context played little or no role in either the level of or disparities in control of hypertension. In sum, residential contexts potentially play a large role in accounting for racial/ethnic and, to a lesser degree, socioeconomic disparities in hypertension prevalence and, in a different way, awareness, but not in treatment or control of diagnosed hypertension.

Understanding Social Disparities in Hypertension Prevalence, Awareness, Treatment, and Control: The Role of Neighborhood Context

PubMed Central

House, James S; Hansen, Ben B; Williams, David R; Kaplan, George A; Hunte, Haslyn E

2007-01-01

The spatial segregation of the U.S. population by socioeconomic position and especially race-ethnicity suggests that the social contexts or “neighborhoods” in which people live may substantially contribute to social disparities in hypertension. The Chicago Community Adult Health Study did face-to-face interviews, including direct measurement of blood pressure, with a representative probability sample of adults in Chicago. These data were used to estimate socioeconomic and racial-ethnic disparities in the prevalence, awareness, treatment, and control of hypertension, and to analyze how these disparities are related to the areas in which people live. Hypertension was significantly negatively associated with neighborhood affluence/gentrification, and adjustments for context eliminated the highly significant disparity between blacks/African-Americans and whites, and reduced the significant educational disparity by 10–15% to borderline statistical significance. Awareness of hypertension was significantly higher in more disadvantaged neighborhoods and in places with higher concentrations of blacks (and lower concentrations of Hispanics and immigrants). Adjustment for context completely eliminated blacks’ greater awareness, but slightly accentuated the lesser awareness of Hispanics and the greater levels of awareness among the less educated. There was no consistent evidence of either social disparities in or contextual associations with treatment of hypertension, given awareness. Among those on medication, blacks were only 40–50% as likely as whites to have their hypertension controlled, but context played little or no role in either the level of or disparities in control of hypertension. In sum, residential contexts potentially play a large role in accounting for racial-ethnic, and to a lesser degree, socioeconomic disparities in hypertension prevalence and, in a different way, awareness, but not in treatment or control of diagnosed hypertension. PMID:17640788

Sonification of network traffic flow for monitoring and situational awareness

PubMed Central

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543

Sonification of network traffic flow for monitoring and situational awareness.

PubMed

Debashi, Mohamed; Vickers, Paul

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.

A planetary nervous system for social mining and collective awareness

NASA Astrophysics Data System (ADS)

Giannotti, F.; Pedreschi, D.; Pentland, A.; Lukowicz, P.; Kossmann, D.; Crowley, J.; Helbing, D.

2012-11-01

We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good.

Periodically Launched, Dedicated CubeSats/SmallSats for Space Situational Awareness Through NASA Communications Networks

NASA Astrophysics Data System (ADS)

Stromberg, E. M.; Shaw, H.; Estabrook, P.; Neilsen, T. L.; Gunther, J.; Swenson, C.; Fish, C. S.; Schaire, S. H.

2014-12-01

Space Situational Awareness (SSA) is an area where spaceflight activities and missions can directly influence the quality of life on earth. The combination of space weather, near earth orbiting objects, atmospheric conditions at the space boundary, and other phenomena can have significant short-term and long-term implications for the inhabitants of this planet. The importance of SSA has led to increased activity in this area from both space and ground based platforms. The emerging capability of CubeSats and SmallSats provides an opportunity for these low-cost, versatile platforms to augment the SSA infrastructure. The CubeSats and SmallSats can be launched opportunistically with shorter lead times than larger missions. They can be organized both as constellations or individual sensor elements. Combining CubeSats and SmallSats with the existing NASA communications networks (TDRS Space Network, Deep Space Network and the Near Earth Network) provide a backbone structure for SSA which can be tied to a SSA portal for data distribution and management. In this poster we will describe the instruments and sensors needed for CubeSat and SmallSat SSA missions. We will describe the architecture and concept of operations for a set of opportunistic, periodically launched, SSA CubeSats and SmallSats. We will also describe the integrated communications infrastructure to support end-to-end data delivery and management to a SSA portal.

Self-Organized Link State Aware Routing for Multiple Mobile Agents in Wireless Network

NASA Astrophysics Data System (ADS)

Oda, Akihiro; Nishi, Hiroaki

Recently, the importance of data sharing structures in autonomous distributed networks has been increasing. A wireless sensor network is used for managing distributed data. This type of distributed network requires effective information exchanging methods for data sharing. To reduce the traffic of broadcasted messages, reduction of the amount of redundant information is indispensable. In order to reduce packet loss in mobile ad-hoc networks, QoS-sensitive routing algorithm have been frequently discussed. The topology of a wireless network is likely to change frequently according to the movement of mobile nodes, radio disturbance, or fading due to the continuous changes in the environment. Therefore, a packet routing algorithm should guarantee QoS by using some quality indicators of the wireless network. In this paper, a novel information exchanging algorithm developed using a hash function and a Boolean operation is proposed. This algorithm achieves efficient information exchanges by reducing the overhead of broadcasting messages, and it can guarantee QoS in a wireless network environment. It can be applied to a routing algorithm in a mobile ad-hoc network. In the proposed routing algorithm, a routing table is constructed by using the received signal strength indicator (RSSI), and the neighborhood information is periodically broadcasted depending on this table. The proposed hash-based routing entry management by using an extended MAC address can eliminate the overhead of message flooding. An analysis of the collision of hash values contributes to the determination of the length of the hash values, which is minimally required. Based on the verification of a mathematical theory, an optimum hash function for determining the length of hash values can be given. Simulations are carried out to evaluate the effectiveness of the proposed algorithm and to validate the theory in a general wireless network routing algorithm.

PS-CARA: Context-Aware Resource Allocation Scheme for Mobile Public Safety Networks.

PubMed

Kaleem, Zeeshan; Khaliq, Muhammad Zubair; Khan, Ajmal; Ahmad, Ishtiaq; Duong, Trung Q

2018-05-08

The fifth-generation (5G) communications systems are expecting to support users with diverse quality-of-service (QoS) requirements. Beside these requirements, the task with utmost importance is to support the emergency communication services during natural or man-made disasters. Most of the conventional base stations are not properly functional during a disaster situation, so deployment of emergency base stations such as mobile personal cell (mPC) is crucial. An mPC having moving capability can move in the disaster area to provide emergency communication services. However, mPC deployment causes severe co-channel interference to the users in its vicinity. The problem in the existing resource allocation schemes is its support for static environment, that does not fit well for mPC. So, a resource allocation scheme for mPC users is desired that can dynamically allocate resources based on users’ location and its connection establishment priority. In this paper, we propose a public safety users priority-based context-aware resource allocation (PS-CARA) scheme for users sum-rate maximization in disaster environment. Simulations results demonstrate that the proposed PS-CARA scheme can increase the user average and edge rate around 10.3% and 32.8% , respectively because of context information availability and by prioritizing the public safety users. The simulation results ensure that call blocking probability is also reduced considerably under the PS-CARA scheme.

PS-CARA: Context-Aware Resource Allocation Scheme for Mobile Public Safety Networks

PubMed Central

Khaliq, Muhammad Zubair; Khan, Ajmal; Ahmad, Ishtiaq

2018-01-01

The fifth-generation (5G) communications systems are expecting to support users with diverse quality-of-service (QoS) requirements. Beside these requirements, the task with utmost importance is to support the emergency communication services during natural or man-made disasters. Most of the conventional base stations are not properly functional during a disaster situation, so deployment of emergency base stations such as mobile personal cell (mPC) is crucial. An mPC having moving capability can move in the disaster area to provide emergency communication services. However, mPC deployment causes severe co-channel interference to the users in its vicinity. The problem in the existing resource allocation schemes is its support for static environment, that does not fit well for mPC. So, a resource allocation scheme for mPC users is desired that can dynamically allocate resources based on users’ location and its connection establishment priority. In this paper, we propose a public safety users priority-based context-aware resource allocation (PS-CARA) scheme for users sum-rate maximization in disaster environment. Simulations results demonstrate that the proposed PS-CARA scheme can increase the user average and edge rate around 10.3% and 32.8% , respectively because of context information availability and by prioritizing the public safety users. The simulation results ensure that call blocking probability is also reduced considerably under the PS-CARA scheme. PMID:29738499

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach.

PubMed

Julie, E Golden; Selvi, S Tamil

2016-01-01

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach

PubMed Central

Julie, E. Golden; Selvi, S. Tamil

2016-01-01

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes. PMID:26881269

Architecture of a Framework for Providing Information Services for Public Transport

PubMed Central

García, Carmelo R.; Pérez, Ricardo; Lorenzo, Álvaro; Quesada-Arencibia, Alexis; Alayón, Francisco; Padrón, Gabino

2012-01-01

This paper presents OnRoute, a framework for developing and running ubiquitous software that provides information services to passengers of public transportation, including payment systems and on-route guidance services. To achieve a high level of interoperability, accessibility and context awareness, OnRoute uses the ubiquitous computing paradigm. To guarantee the quality of the software produced, the reliable software principles used in critical contexts, such as automotive systems, are also considered by the framework. The main components of its architecture (run-time, system services, software components and development discipline) and how they are deployed in the transportation network (stations and vehicles) are described in this paper. Finally, to illustrate the use of OnRoute, the development of a guidance service for travellers is explained. PMID:22778585

The Role of Caretakers in Disease Dynamics

NASA Astrophysics Data System (ADS)

Noble, Charleston; Bagrow, James P.; Brockmann, Dirk

2013-08-01

One of the key challenges in modeling the dynamics of contagion phenomena is to understand how the structure of social interactions shapes the time course of a disease. Complex network theory has provided significant advances in this context. However, awareness of an epidemic in a population typically yields behavioral changes that correspond to changes in the network structure on which the disease evolves. This feedback mechanism has not been investigated in depth. For example, one would intuitively expect susceptible individuals to avoid other infecteds. However, doctors treating patients or parents tending sick children may also increase the amount of contact made with an infecteds, in an effort to speed up recovery but also exposing themselves to higher risks of infection. We study the role of these caretaker links in an adaptive network models where individuals react to a disease by increasing or decreasing the amount of contact they make with infected individuals. We find that, for both homogeneous networks and networks possessing large topological variability, disease prevalence is decreased for low concentrations of caretakers whereas a high prevalence emerges if caretaker concentration passes a well defined critical value.

Multiple Factors-Aware Diffusion in Social Networks

DTIC Science & Technology

2015-05-22

Multiple Factors-Aware Diffusion in Social Networks Chung-Kuang Chou(B) and Ming-Syan Chen Department of Electrical Engineering, National Taiwan...propagates from nodes to nodes over a social network . The behavior that a node adopts an information piece in a social network can be affected by...Twitter dataset. Keywords: Social networks · Diffusion models 1 Introduction Information diffusion in social networks has been an active research field

Energy-aware virtual network embedding in flexi-grid networks.

PubMed

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng

2017-11-27

Network virtualization technology has been proposed to allow multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network, which increases the utilization of the substrate network. Efficiently mapping VNs on the substrate network is a major challenge on account of the VN embedding (VNE) problem. Meanwhile, energy efficiency has been widely considered in the network design in terms of operation expenses and the ecological awareness. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the electricity cost of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low electricity cost. Numerical results show that the heuristic algorithm performs closely to the ILP for a small size network, and we also demonstrate its applicability to larger networks.

Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

NASA Technical Reports Server (NTRS)

Rahmani, Amirreza; Mesbahi, Mehran; Fathpour, Nanaz; Hadaegh, Fred Y.

2008-01-01

In this work, we develop an approach to formation estimation by explicitly characterizing formation's system-theoretic attributes in terms of the underlying inter-spacecraft information-exchange network. In particular, we approach the formation observer/estimator design by relaxing the accessibility to the global state information by a centralized observer/estimator- and in turn- providing an analysis and synthesis framework for formation observers/estimators that rely on local measurements. The noveltyof our approach hinges upon the explicit examination of the underlying distributed spacecraft network in the realm of guidance, navigation, and control algorithmic analysis and design. The overarching goal of our general research program, some of whose results are reported in this paper, is the development of distributed spacecraft estimation algorithms that are scalable, modular, and robust to variations inthe topology and link characteristics of the formation information exchange network. In this work, we consider the observability of a spacecraft formation from a single observation node and utilize the agreement protocol as a mechanism for observing formation states from local measurements. Specifically, we show how the symmetry structure of the network, characterized in terms of its automorphism group, directly relates to the observability of the corresponding multi-agent system The ramification of this notion of observability over networks is then explored in the context of distributed formation estimation.

Self-organizing intelligent network of smart electrical heating devices as an alternative to traditional ways of heating

NASA Astrophysics Data System (ADS)

Zaslavsky, Aleksander M.; Tkachov, Viktor V.; Protsenko, Stanislav M.; Bublikov, Andrii V.; Suleimenov, Batyrbek; Orshubekov, Nurbek; Gromaszek, Konrad

2017-08-01

The paper considers the problem of automated decentralized distribution of the electric energy among unlimited-power electric heaters providing the given temperature distribution within the zones of monitored object heating in the context of maximum use of electric power which limiting level is time-dependent randomly. Principles of collective selforganization automata for solving the problem are analyzed. It has been shown that after all the automata make decision, equilibrium of Nash type is attained when unused power within the electric network is not more than a power of any non-energized electric heater.

Using a Context-aware Medical Application to Address Information Needs for Extubation Decisions

PubMed Central

Zhu, Xinxin; Lord, William

2005-01-01

Information overload has been one of the causes of preventable medical errors [1] and escalating costs [2]. A context-aware application with embedded clinical knowledge is proposed to provide practitioners with the appropriate amount of information and content. We developed a prototype of a context-aware medical application to address clinicians’ information needs that arise in a data-intensive unit, the Cardio-Thoracic Intensive Care Unit (CTICU). A major clinical decision supported by the prototype, the extubation decision, is illustrated. PMID:16779455

A Knowledge-Based Approach to Retrieving Teaching Materials for Context-Aware Learning

ERIC Educational Resources Information Center

Shih, Wen-Chung; Tseng, Shian-Shyong

2009-01-01

With the rapid development of wireless communication and sensor technologies, ubiquitous learning has become a promising solution to educational problems. In context-aware ubiquitous learning environments, it is required that learning content is retrieved according to environmental contexts, such as learners' location. Also, a learning content…

How emotion context modulates unconscious goal activation during motor force exertion.

PubMed

Blakemore, Rebekah L; Neveu, Rémi; Vuilleumier, Patrik

2017-02-01

Priming participants with emotional or action-related concepts influences goal formation and motor force output during effort exertion tasks, even without awareness of priming information. However, little is known about neural processes underpinning how emotional cues interact with action (or inaction) goals to motivate (or demotivate) motor behaviour. In a novel functional neuroimaging paradigm, visible emotional images followed by subliminal action or inaction word primes were presented before participants performed a maximal force exertion. In neutral emotional contexts, maximum force was lower following inaction than action primes. However, arousing emotional images had interactive motivational effects on the motor system: Unpleasant images prior to inaction primes increased force output (enhanced effort exertion) relative to control primes, and engaged a motivation-related network involving ventral striatum, extended amygdala, as well as right inferior frontal cortex. Conversely, pleasant images presented before action (versus control) primes decreased force and activated regions of the default-mode network, including inferior parietal lobule and medial prefrontal cortex. These findings show that emotional context can determine how unconscious goal representations influence motivational processes and are transformed into actual motor output, without direct rewarding contingencies. Furthermore, they provide insight into altered motor behaviour in psychopathological disorders with dysfunctional motivational processes. Copyright © 2016 Elsevier Inc. All rights reserved.

Sensor & Model Enabled Water Quality & Security Assessment System for Situational Awareness of Water Distribution Networks

DTIC Science & Technology

2010-06-01

Scenario – 12 gallons of readily available toxic substance – pump ($150 rental) – wrench to open a fire hydrant ($10)  One (1) terrorist, or...6 Gallons Water General Comments Aflatoxin 7.6 Potent Carcinogen Aldicarb 1.1 Cycloheximide 2.1 LSD 0.2 Highly Toxic , Psychoactive Mercuric Chloride...Chlorfenvinphos, Formetanate Hydrochloride, Acrolein, Chloropicrin, Sodium chloroacetate, Thyoglycolate medium, Crotoxyphos, Glyphosate , Jimsonweed, Methanol

Network Policy Languages: A Survey and a New Approach

DTIC Science & Technology

2000-08-01

go, throwing a community into economic chaos. These events could result from discontinued funding from Silicon Valley investors who became aware of...prevented. C. POLICY HIERARCHIES FOR DISTRIBUTED SYSTEMS MANAGEMENT In [23], Moffett and Sloman form a policy hierarchy is by refining general high...management behavior of a system, without coding the behavior into the manager agents. Lupu and Sloman focus on techniques and tool support for off-line

Network structure of subway passenger flows

NASA Astrophysics Data System (ADS)

Xu, Q.; Mao, B. H.; Bai, Y.

2016-03-01

The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.

ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

NASA Astrophysics Data System (ADS)

Bedrina, T.; Parodi, A.; Quarati, A.; Clematis, A.

2012-06-01

It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT) is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR). Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS) networks, capable to provide almost real-time, location aware, weather data. Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps. This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in decision support systems and Civil Protection applications. As a significant case study, we analysed the rainfall data observed during the severe flash-flood event of 4 November 2011 over Liguria region, Italy. The joint use of official observation network with PWS networks and meteorological radar allowed for the making of evident finger-like convection structure.

Face to (face)book: the two faces of social behavior?

PubMed

Ivcevic, Zorana; Ambady, Nalini

2013-06-01

Social networking sites such as Facebook represent a unique and dynamic social environment. This study addresses three theoretical issues in personality psychology in the context of online social networking sites: (a) the temporal consistency of Facebook activity, (b) people's awareness of their online behavior, and (c) comparison of social behavior on Facebook with self- and informant-reported behavior in real life. Facebook Wall pages of 99 college students (mean age = 19.72) were downloaded six times during 3 weeks and coded for quantity and quality of activity. Everyday social interactions were assessed by self- and friend report. Facebook activity showed significant consistency across time, and people demonstrated awareness of their online behavior. There was significant similarity between everyday traits and interactions and Facebook behavior (e.g., more posts by friends are related to Agreeableness). Some differences between online and everyday interactions warrant further research (e.g., individuals with more positive offline relationships are less likely to engage in back-and-forth conversations on Facebook). The results indicate substantial similarity between online and offline social behavior and identify avenues for future research on the possible use of Facebook to compensate for difficulty in everyday interactions. © 2012 Wiley Periodicals, Inc.

Achieving High Performance With TCP Over 40 GbE on NUMA Architectures for CMS Data Acquisition

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

Bawej, Tomasz; et al.

2014-01-01

TCP and the socket abstraction have barely changed over the last two decades, but at the network layer there has been a giant leap from a few megabits to 100 gigabits in bandwidth. At the same time, CPU architectures have evolved into the multicore era and applications are expected to make full use of all available resources. Applications in the data acquisition domain based on the standard socket library running in a Non-Uniform Memory Access (NUMA) architecture are unable to reach full efficiency and scalability without the software being adequately aware about the IRQ (Interrupt Request), CPU and memory affinities.more » During the first long shutdown of LHC, the CMS DAQ system is going to be upgraded for operation from 2015 onwards and a new software component has been designed and developed in the CMS online framework for transferring data with sockets. This software attempts to wrap the low-level socket library to ease higher-level programming with an API based on an asynchronous event driven model similar to the DAT uDAPL API. It is an event-based application with NUMA optimizations, that allows for a high throughput of data across a large distributed system. This paper describes the architecture, the technologies involved and the performance measurements of the software in the context of the CMS distributed event building.« less

A Computational Methodology to Support Reimbursement Requests Analysis Concerning Electrical Damages

NASA Astrophysics Data System (ADS)

Almeida Junior, Afonso Bernardino; Gondim, Isaque Nogueira; Rezende, Paulo Henrique Oliveira; Oliveira, José Carlos

2015-12-01

In light of the growing number of reimbursement requests processed from consumers for electrical damage to equipment, supposedly caused through the manifestation of anomalies on the power grid, there comes the need for reliable means for providing a decision on the issues highlighted herein. Through the recognition that in the current context, the procedures used are based on reviews, information and records of occurrences in the field, there has been significant inadequacy and fragility in the issuing of conclusive advice or opinions. In particular, the search for mechanisms grounded in classical principles and accepted in electrical engineering presents itself as an important challenge on which to base the decision making process in full awareness of its incumbent science and technology. Therefore, with the aim of meeting these assumptions, the study in question excels in its presentation of the principles that guided the software analysis, which intend above all else to correlate cause and effect. The elaborated strategy involves modelling stages as well as studies aimed at: distribution supply reproduction; characterization of the distribution network to the complainant consumer; representation of the diverse electro-electronic appliances and lastly, a proposal for correlating the disturbances impacting on equipment with their dielectric and thermal supportability requirements. For the purpose of illustrating the software process, an actual case study coupled with a loss and claim scenario is presented.

Understanding cultural influences on back pain and back pain research.

PubMed

Henschke, Nicholas; Lorenz, Eva; Pokora, Roman; Michaleff, Zoe A; Quartey, Jonathan N A; Oliveira, Vinicius Cunha

2016-12-01

Low back pain is highly prevalent and places a considerable burden on individuals, their families and communities. This back pain burden is unequally distributed around the world and within populations. Clinicians and researchers addressing back pain should be aware of the cultural, social and political context of back pain patients and how this context can influence pain perception, disability and health care use. Culture, which influences the beliefs and behaviour of individuals within a social group, could be considered an important contributor to the unequal distribution of back pain. However, there is paucity of high-quality research exploring the influence of culture on the experience and management of back pain. Further development and testing of specific tools, assessment methods and communication strategies are needed to improve our understanding of how cultural practices, values and identifications affect those dealing with back pain. Copyright © 2017 Elsevier Ltd. All rights reserved.

Impact of Network Activity Levels on the Performance of Passive Network Service Dependency Discovery

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

Carroll, Thomas E.; Chikkagoudar, Satish; Arthur-Durett, Kristine M.

Network services often do not operate alone, but instead, depend on other services distributed throughout a network to correctly function. If a service fails, is disrupted, or degraded, it is likely to impair other services. The web of dependencies can be surprisingly complex---especially within a large enterprise network---and evolve with time. Acquiring, maintaining, and understanding dependency knowledge is critical for many network management and cyber defense activities. While automation can improve situation awareness for network operators and cyber practitioners, poor detection accuracy reduces their confidence and can complicate their roles. In this paper we rigorously study the effects of networkmore » activity levels on the detection accuracy of passive network-based service dependency discovery methods. The accuracy of all except for one method was inversely proportional to network activity levels. Our proposed cross correlation method was particularly robust to the influence of network activity. The proposed experimental treatment will further advance a more scientific evaluation of methods and provide the ability to determine their operational boundaries.« less

Children's quality of life in a noisy world

NASA Astrophysics Data System (ADS)

Schulte-Fortkamp, Brigitte

2004-05-01

On 30 April 2003 during the International Forum Noise Awareness Day European experts from the fields of medicine, acoustics, sociology, psychology, city planning, and traffic regulation led the current discussion on the risks of noise pollution for children at the Institute of Technical Acoustics at the Berlin Technical University, Germany. Studies probing into the negative effects of noise exposure upon the psychic, cognitive, and emotional functions of children are of a quite recent date. Even the quality of life of children as auto-directed experience and functionality is only now starting to get recognized; of special interest are the changes in self-awareness, performance, and health. The Forum focused upon methodological reflections for the collection of data as well as studies regarding the living conditions of children under sound exposure from different perspectives. In this context the research of sound effects has taken initial tentative steps to break away from the tried-and-true procedures of the last 30 years. Next to applied science, investigating fundamentals will need to be considered. Aiming at a networking process is one of the goals conducting the ``Tag gegen Lrm-International Noise Awareness Day.''

Efficient data communication protocols for wireless networks

NASA Astrophysics Data System (ADS)

Zeydan, Engin

In this dissertation, efficient decentralized algorithms are investigated for cost minimization problems in wireless networks. For wireless sensor networks, we investigate both the reduction in the energy consumption and throughput maximization problems separately using multi-hop data aggregation for correlated data in wireless sensor networks. The proposed algorithms exploit data redundancy using a game theoretic framework. For energy minimization, routes are chosen to minimize the total energy expended by the network using best response dynamics to local data. The cost function used in routing takes into account distance, interference and in-network data aggregation. The proposed energy-efficient correlation-aware routing algorithm significantly reduces the energy consumption in the network and converges in a finite number of steps iteratively. For throughput maximization, we consider both the interference distribution across the network and correlation between forwarded data when establishing routes. Nodes along each route are chosen to minimize the interference impact in their neighborhood and to maximize the in-network data aggregation. The resulting network topology maximizes the global network throughput and the algorithm is guaranteed to converge with a finite number of steps using best response dynamics. For multiple antenna wireless ad-hoc networks, we present distributed cooperative and regret-matching based learning schemes for joint transmit beanformer and power level selection problem for nodes operating in multi-user interference environment. Total network transmit power is minimized while ensuring a constant received signal-to-interference and noise ratio at each receiver. In cooperative and regret-matching based power minimization algorithms, transmit beanformers are selected from a predefined codebook to minimize the total power. By selecting transmit beamformers judiciously and performing power adaptation, the cooperative algorithm is shown to converge to pure strategy Nash equilibrium with high probability throughout the iterations in the interference impaired network. On the other hand, the regret-matching learning algorithm is noncooperative and requires minimum amount of overhead. The proposed cooperative and regret-matching based distributed algorithms are also compared with centralized solutions through simulation results.

Awareware: Narrowcasting Attributes for Selective Attention, Privacy, and Multipresence

NASA Astrophysics Data System (ADS)

Cohen, Michael; Newton Fernando, Owen Noel

The domain of cscw, computer-supported collaborative work, and DSC, distributed synchronous collaboration, spans real-time interactive multiuser systems, shared information spaces, and applications for teleexistence and artificial reality, including collaborative virtual environments ( cves) (Benford et al., 2001). As presence awareness systems emerge, it is important to develop appropriate interfaces and architectures for managing multimodal multiuser systems. Especially in consideration of the persistent connectivity enabled by affordable networked communication, shared distributed environments require generalized control of media streams, techniques to control source → sink transmissions in synchronous groupware, including teleconferences and chatspaces, online role-playing games, and virtual concerts.

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

PubMed

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

Interplay of network dynamics and heterogeneity of ties on spreading dynamics.

PubMed

Ferreri, Luca; Bajardi, Paolo; Giacobini, Mario; Perazzo, Silvia; Venturino, Ezio

2014-07-01

The structure of a network dramatically affects the spreading phenomena unfolding upon it. The contact distribution of the nodes has long been recognized as the key ingredient in influencing the outbreak events. However, limited knowledge is currently available on the role of the weight of the edges on the persistence of a pathogen. At the same time, recent works showed a strong influence of temporal network dynamics on disease spreading. In this work we provide an analytical understanding, corroborated by numerical simulations, about the conditions for infected stable state in weighted networks. In particular, we reveal the role of heterogeneity of edge weights and of the dynamic assignment of weights on the ties in the network in driving the spread of the epidemic. In this context we show that when weights are dynamically assigned to ties in the network, a heterogeneous distribution is able to hamper the diffusion of the disease, contrary to what happens when weights are fixed in time.

Classroom Peer Relationships and Behavioral Engagement in Elementary School: The Role of Social Network Equity

PubMed Central

Cappella, Elise; Kim, Ha Yeon; Neal, Jennifer W.; Jackson, Daisy R.

2014-01-01

Applying social capital and systems theories of social processes, we examine the role of the classroom peer context in the behavioral engagement of low-income students (N = 80) in urban elementary school classrooms (N = 22). Systematic child observations were conducted to assess behavioral engagement among second to fifth graders in the fall and spring of the same school year. Classroom observations, teacher and child questionnaires, and social network data were collected in the fall. Confirming prior research, results from multilevel models indicate that students with more behavioral difficulties or less academic motivation in the fall were less behaviorally engaged in the spring. Extending prior research, classrooms with more equitably distributed and interconnected social ties—social network equity—had more behaviorally engaged students in the spring, especially in classrooms with higher levels of observed organization (i.e., effective management of behavior, time, and attention). Moreover, social network equity attenuated the negative relation between student behavioral difficulties and behavioral engagement, suggesting that students with behavioral difficulties were less disengaged in classrooms with more equitably distributed and interconnected social ties. Findings illuminate the need to consider classroom peer contexts in future research and intervention focused on the behavioral engagement of students in urban elementary schools. PMID:24081319

The study of disaster situation awareness based on volunteered geographic information

NASA Astrophysics Data System (ADS)

Zhao, Qiansheng; Chen, Zi; Li, Shengming; Luo, Nianxue

2015-12-01

As the development of Web 2.0, the social media like microblog, blogs and social network have supplied a bunch of information with locations (Volunteered Geographical Information, VGI).Recent years many cases have shown that, if disaster happened, the cyber citizens will get together very quickly and share the disaster information, this results a bunch of volunteered geographical information about disaster situation which is very valuable for disaster response if this VGIs are used efficiently and properly. This project will take typhoon disaster as case study. In this paper, we study the relations between weibo messages and the real typhoon situation, we proposed an analysis framework for mine the relations between weibo messages distribution and physical space. We found that the number of the weibo messages, key words frequency and spatial temporary distribution of the messages have strong relations with the disaster spread in the real world, and this research results can improve our disaster situation awareness in the future. The achievement of the study will give a method for typhoon disaster situation awareness based on VGI from the bottom up, and will locate the disaster spot and evolution quickly which is very important for disaster response and recover.

Theorizing College Governance across Epistemic Differences: Awareness Contexts of College Administrators and Faculty

ERIC Educational Resources Information Center

Muzzin, Linda

2016-01-01

Awareness contexts are useful concepts in symbolic interactionist research, which focusses on how everyday realities are constructed. To provide a fresh perspective on governance in Canada's colleges, I sorted vignettes in interview data collected from administrators and faculty into four types of contexts originally derived from observation of…

Development, Awareness and Inductive Selectivity

ERIC Educational Resources Information Center

Hayes, Brett K.; Lim, Melissa

2013-01-01

Two studies examined whether adults and children could learn to make context-dependent inferences about novel stimuli and the role of awareness of context cues in such learning. Participants were trained to match probes to targets on the basis of shape or color with the relevant dimension shifting according to item context. A selective induction…

A Review of Barriers to Minorities' Participation in Cancer Clinical Trials: Implications for Future Cancer Research.

PubMed

Salman, Ali; Nguyen, Claire; Lee, Yi-Hui; Cooksey-James, Tawna

2016-04-01

To enhance nurses' awareness and competencies in practice and research by reporting the common barriers to participation of minorities in cancer clinical trials and discussing facilitators and useful strategies for recruitment. Several databases were searched for articles published in peer reviewed journals. Some of the barriers to minorities' participation in clinical trials were identified within the cultural social-context of cancer patients. The involvement of community networking was suggested as the most effective strategy for the recruitment of minorities in cancer clinical trials. Using culturally sensitive approaches to enhance ethnic minorities' participation is important for advancing cancer care and eliminating health disparities. Awareness of barriers and potential facilitators to the enrollment of ethnic minority cancer patients may contribute to enhancing nurses' competencies of recruiting ethnic minorities in nursing research, playing efficient roles in cancer clinical trials team, and providing culturally competent quality care.

QoS-aware health monitoring system using cloud-based WBANs.

PubMed

Almashaqbeh, Ghada; Hayajneh, Thaier; Vasilakos, Athanasios V; Mohd, Bassam J

2014-10-01

Wireless Body Area Networks (WBANs) are amongst the best options for remote health monitoring. However, as standalone systems WBANs have many limitations due to the large amount of processed data, mobility of monitored users, and the network coverage area. Integrating WBANs with cloud computing provides effective solutions to these problems and promotes the performance of WBANs based systems. Accordingly, in this paper we propose a cloud-based real-time remote health monitoring system for tracking the health status of non-hospitalized patients while practicing their daily activities. Compared with existing cloud-based WBAN frameworks, we divide the cloud into local one, that includes the monitored users and local medical staff, and a global one that includes the outer world. The performance of the proposed framework is optimized by reducing congestion, interference, and data delivery delay while supporting users' mobility. Several novel techniques and algorithms are proposed to accomplish our objective. First, the concept of data classification and aggregation is utilized to avoid clogging the network with unnecessary data traffic. Second, a dynamic channel assignment policy is developed to distribute the WBANs associated with the users on the available frequency channels to manage interference. Third, a delay-aware routing metric is proposed to be used by the local cloud in its multi-hop communication to speed up the reporting process of the health-related data. Fourth, the delay-aware metric is further utilized by the association protocols used by the WBANs to connect with the local cloud. Finally, the system with all the proposed techniques and algorithms is evaluated using extensive ns-2 simulations. The simulation results show superior performance of the proposed architecture in optimizing the end-to-end delay, handling the increased interference levels, maximizing the network capacity, and tracking user's mobility.

How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness.

PubMed

Naro, Antonino; Leo, Antonino; Manuli, Alfredo; Cannavò, Antonino; Bramanti, Alessia; Bramanti, Placido; Calabrò, Rocco Salvatore

2017-05-04

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Intelligent Context-Aware and Adaptive Interface for Mobile LBS

PubMed Central

Liu, Yanhong

2015-01-01

Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results. PMID:26457077

Smart sensing surveillance system

NASA Astrophysics Data System (ADS)

Hsu, Charles; Chu, Kai-Dee; O'Looney, James; Blake, Michael; Rutar, Colleen

2010-04-01

Unattended ground sensor (UGS) networks have been widely used in remote battlefield and other tactical applications over the last few decades due to the advances of the digital signal processing. The UGS network can be applied in a variety of areas including border surveillance, special force operations, perimeter and building protection, target acquisition, situational awareness, and force protection. In this paper, a highly-distributed, fault-tolerant, and energyefficient Smart Sensing Surveillance System (S4) is presented to efficiently provide 24/7 and all weather security operation in a situation management environment. The S4 is composed of a number of distributed nodes to collect, process, and disseminate heterogeneous sensor data. Nearly all S4 nodes have passive sensors to provide rapid omnidirectional detection. In addition, Pan- Tilt- Zoom- (PTZ) Electro-Optics EO/IR cameras are integrated to selected nodes to track the objects and capture associated imagery. These S4 camera-connected nodes will provide applicable advanced on-board digital image processing capabilities to detect and track the specific objects. The imaging detection operations include unattended object detection, human feature and behavior detection, and configurable alert triggers, etc. In the S4, all the nodes are connected with a robust, reconfigurable, LPI/LPD (Low Probability of Intercept/ Low Probability of Detect) wireless mesh network using Ultra-wide band (UWB) RF technology, which can provide an ad-hoc, secure mesh network and capability to relay network information, communicate and pass situational awareness and messages. The S4 utilizes a Service Oriented Architecture such that remote applications can interact with the S4 network and use the specific presentation methods. The S4 capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments and near perimeters and borders. The S4 is compliant with Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE®) standards. It would be directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.

A neuronal network model for context-dependence of pitch change perception.

PubMed

Huang, Chengcheng; Englitz, Bernhard; Shamma, Shihab; Rinzel, John

2015-01-01

Many natural stimuli have perceptual ambiguities that can be cognitively resolved by the surrounding context. In audition, preceding context can bias the perception of speech and non-speech stimuli. Here, we develop a neuronal network model that can account for how context affects the perception of pitch change between a pair of successive complex tones. We focus especially on an ambiguous comparison-listeners experience opposite percepts (either ascending or descending) for an ambiguous tone pair depending on the spectral location of preceding context tones. We developed a recurrent, firing-rate network model, which detects frequency-change-direction of successively played stimuli and successfully accounts for the context-dependent perception demonstrated in behavioral experiments. The model consists of two tonotopically organized, excitatory populations, E up and E down, that respond preferentially to ascending or descending stimuli in pitch, respectively. These preferences are generated by an inhibitory population that provides inhibition asymmetric in frequency to the two populations; context dependence arises from slow facilitation of inhibition. We show that contextual influence depends on the spectral distribution of preceding tones and the tuning width of inhibitory neurons. Further, we demonstrate, using phase-space analysis, how the facilitated inhibition from previous stimuli and the waning inhibition from the just-preceding tone shape the competition between the E up and E down populations. In sum, our model accounts for contextual influences on the pitch change perception of an ambiguous tone pair by introducing a novel decoding strategy based on direction-selective units. The model's network architecture and slow facilitating inhibition emerge as predictions of neuronal mechanisms for these perceptual dynamics. Since the model structure does not depend on the specific stimuli, we show that it generalizes to other contextual effects and stimulus types.

Eavesdropping-aware routing and spectrum allocation based on multi-flow virtual concatenation for confidential information service in elastic optical networks

NASA Astrophysics Data System (ADS)

Bai, Wei; Yang, Hui; Yu, Ao; Xiao, Hongyun; He, Linkuan; Feng, Lei; Zhang, Jie

2018-01-01

The leakage of confidential information is one of important issues in the network security area. Elastic Optical Networks (EON) as a promising technology in the optical transport network is under threat from eavesdropping attacks. It is a great demand to support confidential information service (CIS) and design efficient security strategy against the eavesdropping attacks. In this paper, we propose a solution to cope with the eavesdropping attacks in routing and spectrum allocation. Firstly, we introduce probability theory to describe eavesdropping issue and achieve awareness of eavesdropping attacks. Then we propose an eavesdropping-aware routing and spectrum allocation (ES-RSA) algorithm to guarantee information security. For further improving security and network performance, we employ multi-flow virtual concatenation (MFVC) and propose an eavesdropping-aware MFVC-based secure routing and spectrum allocation (MES-RSA) algorithm. The presented simulation results show that the proposed two RSA algorithms can both achieve greater security against the eavesdropping attacks and MES-RSA can also improve the network performance efficiently.

Principles and processes behind promoting awareness of rights for quality maternal care services: a synthesis of stakeholder experiences and implementation factors.

PubMed

George, Asha S; Branchini, Casey

2017-08-31

Promoting awareness of rights is a value-based process that entails a different way of thinking and acting, which is at times misunderstood or deemed as aspirational. Guided by the SURE framework, we undertook a secondary analysis of 26 documents identified by an earlier systematic review on promoting awareness of rights to increase use of maternity care services. We thematically analysed stakeholder experiences and implementation factors across the diverse initiatives to derive common elements to guide future efforts. Interventions that promote awareness of rights for maternal health varied in nature, methodological orientation, depth and quality. Materials included booklets, posters, pamphlets/ briefs and service standards/charters. Target populations included women, family members, communities, community structures, community-based and non governmental organizations, health providers and administrators, as well as elected representatives. While one initiative only focused on raising awareness, most were embedded within larger efforts to improve the accountability and responsiveness of service delivery through community monitoring and advocacy, with a few aiming to change policies and contest elections. Underlying these action oriented forms of promoting awareness of rights, was a critical consciousness and attitudinal change gained through iterative capacity-building for all stakeholders; materials and processes that supported group discussion and interaction; the formation or strengthening of community groups; situational analysis to ensure adaptation to local context; facilitation to ensure common ground and language across stakeholders; and strategic networking and alliance building across health system levels. While many positive experiences are discussed, few challenges or barriers to implementation are documented. The limited documentation and poor quality of information found indicate that while various examples of promoting awareness of rights for maternal health exists, research partnerships to systematically evaluate their processes, learning and effects are lacking. Rather than being aspirational, several examples of promoting awareness of women's rights for quality maternity care services exist. More than mainly disseminate information, they aim to change stakeholder mindsets and relationships across health system levels. Due to their transformatory intent they require sustained investment, with strategic planning, concrete operationalization and political adeptness to manage dynamic stakeholder expectations and reactions overtime. More investment is also required in research partnerships that support such initiatives and better elucidate their context specific variations.

Delivery of video-on-demand services using local storages within passive optical networks.

PubMed

Abeywickrama, Sandu; Wong, Elaine

2013-01-28

At present, distributed storage systems have been widely studied to alleviate Internet traffic build-up caused by high-bandwidth, on-demand applications. Distributed storage arrays located locally within the passive optical network were previously proposed to deliver Video-on-Demand services. As an added feature, a popularity-aware caching algorithm was also proposed to dynamically maintain the most popular videos in the storage arrays of such local storages. In this paper, we present a new dynamic bandwidth allocation algorithm to improve Video-on-Demand services over passive optical networks using local storages. The algorithm exploits the use of standard control packets to reduce the time taken for the initial request communication between the customer and the central office, and to maintain the set of popular movies in the local storage. We conduct packet level simulations to perform a comparative analysis of the Quality-of-Service attributes between two passive optical networks, namely the conventional passive optical network and one that is equipped with a local storage. Results from our analysis highlight that strategic placement of a local storage inside the network enables the services to be delivered with improved Quality-of-Service to the customer. We further formulate power consumption models of both architectures to examine the trade-off between enhanced Quality-of-Service performance versus the increased power requirement from implementing a local storage within the network.

A wearable context aware system for ubiquitous healthcare.

PubMed

Kang, Dong-Oh; Lee, Hyung-Jik; Ko, Eun-Jung; Kang, Kyuchang; Lee, Jeunwoo

2006-01-01

Recent developments of information technologies are leading the advent of the era of ubiquitous healthcare, which means healthcare services at any time and at any places. The ubiquitous healthcare service needs a wearable system for more continual measurement of biological signals of a user, which gives information of the user from wearable sensors. In this paper, we propose a wearable context aware system for ubiquitous healthcare, and its systematic design process of a ubiquitous healthcare service. Some wearable sensor systems are introduced with Zigbee communication. We develop a context aware framework to send information from wearable sensors to healthcare service entities as a middleware to solve the interoperability problem between sensor makers and healthcare service providers. And, we propose a systematic process of design of ubiquitous healthcare services with the context aware framework. In order to show the feasibility of the proposed system, some application examples are given, which are applied to remote monitoring, and a self check service.

Traffic sign recognition based on a context-aware scale-invariant feature transform approach

NASA Astrophysics Data System (ADS)

Yuan, Xue; Hao, Xiaoli; Chen, Houjin; Wei, Xueye

2013-10-01

A new context-aware scale-invariant feature transform (CASIFT) approach is proposed, which is designed for the use in traffic sign recognition (TSR) systems. The following issues remain in previous works in which SIFT is used for matching or recognition: (1) SIFT is unable to provide color information; (2) SIFT only focuses on local features while ignoring the distribution of global shapes; (3) the template with the maximum number of matching points selected as the final result is instable, especially for images with simple patterns; and (4) SIFT is liable to result in errors when different images share the same local features. In order to resolve these problems, a new CASIFT approach is proposed. The contributions of the work are as follows: (1) color angular patterns are used to provide the color distinguishing information; (2) a CASIFT which effectively combines local and global information is proposed; and (3) a method for computing the similarity between two images is proposed, which focuses on the distribution of the matching points, rather than using the traditional SIFT approach of selecting the template with maximum number of matching points as the final result. The proposed approach is particularly effective in dealing with traffic signs which have rich colors and varied global shape distribution. Experiments are performed to validate the effectiveness of the proposed approach in TSR systems, and the experimental results are satisfying even for images containing traffic signs that have been rotated, damaged, altered in color, have undergone affine transformations, or images which were photographed under different weather or illumination conditions.

A Context-Aware Self-Adaptive Fractal Based Generalized Pedagogical Agent Framework for Mobile Learning

ERIC Educational Resources Information Center

Boulehouache, Soufiane; Maamri, Ramdane; Sahnoun, Zaidi

2015-01-01

The Pedagogical Agents (PAs) for Mobile Learning (m-learning) must be able not only to adapt the teaching to the learner knowledge level and profile but also to ensure the pedagogical efficiency within unpredictable changing runtime contexts. Therefore, to deal with this issue, this paper proposes a Context-aware Self-Adaptive Fractal Component…

Improving Understanding and Trust with Intelligibility in Context-Aware Applications

ERIC Educational Resources Information Center

Lim, Brian Y.

2012-01-01

To facilitate everyday activities, context-aware applications use sensors to detect what is happening and use increasingly complex mechanisms ( e.g., by using big rule-sets or machine learning) to infer the user's context and intent. For example, a mobile application can recognize that the user is in a conversation and suppress any incoming…

Activity Theory Approach to Developing Context-Aware Mobile Learning Systems for Understanding Scientific Phenomenon and Theories

ERIC Educational Resources Information Center

Uden, Lorna; Hwang, Gwo-Jen

2013-01-01

Mobile computing offers potential opportunities for students' learning especially when it combines a sensing device such as RFID (Radio Frequency Identification). Researchers have indicated that a key feature of in-field learning supported by mobile devices and technology is context awareness, with which context and functionality provided by…

Demonstrating the CollaTrEx Framework for Collaborative Context-Aware Mobile Training and Exploration

ERIC Educational Resources Information Center

Botev, Jean

2016-01-01

The CollaTrEx framework for collaborative context-aware mobile training and exploration is designed for the in-situ collaboration within groups of learners performing together diverse educational activities to explore their environment in a fun and intuitive way. It employs both absolute and relative spatio-temporal context for determining…

The Ozone Widget Framework: towards modularity of C2 human interfaces

NASA Astrophysics Data System (ADS)

Hellar, David Benjamin; Vega, Laurian C.

2012-05-01

The Ozone Widget Framework (OWF) is a common webtop environment for distribution across the enterprise. A key mission driver for OWF is to enable rapid capability delivery by lowering time-to-market with lightweight components. OWF has been released as Government Open Source Software and has been deployed in a variety of C2 net-centric contexts ranging from real-time analytics, cyber-situational awareness, to strategic and operational planning. This paper discusses the current and future evolution of OWF including the availability of the OZONE Marketplace (OMP), useractivity driven metrics, and architecture enhancements for accessibility. Together, OWF is moving towards the rapid delivery of modular human interfaces supporting modern and future command and control contexts.

Integrated System Health Management (ISHM) and Autonomy

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Walker, Mark G.

2018-01-01

Systems capabilities on ISHM (Integrated System Health Management) and autonomy have traditionally been addressed separately. This means that ISHM functions, such as anomaly detection, diagnostics, prognostics, and comprehensive system awareness have not been considered traditionally in the context of autonomy functions such as planning, scheduling, and mission execution. One key reason is that although they address systems capabilities, both ISHM and autonomy have traditionally individually been approached as independent strategies and models for analysis. Additionally, to some degree, a unified paradigm for ISHM and autonomy has been difficult to implement due to limitations of hardware and software. This paper explores a unified treatment of ISHM and autonomy in the context of distributed hierarchical autonomous operations.

Privacy in Georeferenced Context-Aware Services: A Survey

NASA Astrophysics Data System (ADS)

Riboni, Daniele; Pareschi, Linda; Bettini, Claudio

Location based services (LBS) are a specific instance of a broader class of Internet services that are predicted to become popular in a near future: context-aware services. The privacy concerns that LBS have raised are likely to become even more serious when several context data, other than location and time, are sent to service providers as part of an Internet request. This paper provides a classification and a brief survey of the privacy preservation techniques that have been proposed for this type of services. After identifying the benefits and shortcomings of each class of techniques, the paper proposes a combined approach to achieve a more comprehensive solution for privacy preservation in georeferenced context-aware services.

M Dwarf Exoplanet Survey by the Falcon Telescope Network

NASA Astrophysics Data System (ADS)

Carlson, Randall E.

2016-10-01

The Falcon Telescope Network (FTN) consists of twelve automated 20-inch telescopes located around the globe. We control it at the US Air Force Academy in Colorado Springs, Colorado from the Cadet Space Operations Center. We have installed 10 of the 12 sites and anticipate full operational capability by the beginning of 2017. The network's worldwide geographic distribution provides advantages. The primary mission of the FTN is Space Situational Awareness and studying Near Earth Objects. However, we are employing the FTN with its 11' x 11' field-of-view for a five-year, M dwarf exoplanet survey. Specifically, we are searching for Earth-radius exoplanets. We describe the FTN, design considerations going into the FTN's M dwarf exoplanet survey including automated operations, and initial results of the survey.

75 FR 2836 - Schools and Libraries Universal Service Support Mechanism

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-19

... networking websites and in chat rooms and cyberbullying awareness and response, as required by the Protecting... interacting with other individuals on social networking Web sites and in chat rooms and cyberbullying... networking websites and in chat rooms and cyberbullying awareness and response. We seek comment on this...

College Students' Health Information Activities on Facebook: Investigating the Impacts of Health Topic Sensitivity, Information Sources, and Demographics.

PubMed

Syn, Sue Yeon; Kim, Sung Un

2016-07-01

College students tend to lack access to health information. Because social networking sites (SNSs) are popularly adopted by college students, SNSs are considered to be good media channels for college students to obtain health-related information. This study examines the factors that influence college students' health information-seeking and -sharing activities on Facebook. An online survey was distributed to college students between the ages of 18 and 29 to determine intentions pertaining to health information activities according to the factors identified for the study. The factors included both contextual factors (such as health topic sensitivity and health information sources) as well as user factors (such as demographics). Our findings showed that college students are willing to read and post health-related information on Facebook when the health topic is not sensitive. In addition, there are clear differences in preferences between professional sources and personal sources as health information sources. It was found that most user factors, except gender, have no influence on health information activities. The impacts of SNS contexts, awareness of information sources, types of interlocutors, and privacy concerns are further discussed.

Sentient networks

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

Chapline, G.

1998-03-01

The engineering problems of constructing autonomous networks of sensors and data processors that can provide alerts for dangerous situations provide a new context for debating the question whether man-made systems can emulate the cognitive capabilities of the mammalian brain. In this paper we consider the question whether a distributed network of sensors and data processors can form ``perceptions`` based on sensory data. Because sensory data can have exponentially many explanations, the use of a central data processor to analyze the outputs from a large ensemble of sensors will in general introduce unacceptable latencies for responding to dangerous situations. A bettermore » idea is to use a distributed ``Helmholtz machine`` architecture in which the sensors are connected to a network of simple processors, and the collective state of the network as a whole provides an explanation for the sensory data. In general communication within such a network will require time division multiplexing, which opens the door to the possibility that with certain refinements to the Helmholtz machine architecture it may be possible to build sensor networks that exhibit a form of artificial consciousness.« less

Optimization of active distribution networks: Design and analysis of significative case studies for enabling control actions of real infrastructure

NASA Astrophysics Data System (ADS)

Moneta, Diana; Mora, Paolo; Viganò, Giacomo; Alimonti, Gianluca

2014-12-01

The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER - DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of "case studies", that are the combination of network topology, technical constraints and targets, load and generation profiles and "costs" of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications.

Group-oriented coordination models for distributed client-server computing

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Hughes, Craig S.

1994-01-01

This paper describes group-oriented control models for distributed client-server interactions. These models transparently coordinate requests for services that involve multiple servers, such as queries across distributed databases. Specific capabilities include: decomposing and replicating client requests; dispatching request subtasks or copies to independent, networked servers; and combining server results into a single response for the client. The control models were implemented by combining request broker and process group technologies with an object-oriented communication middleware tool. The models are illustrated in the context of a distributed operations support application for space-based systems.

Advanced visualization platform for surgical operating room coordination: distributed video board system.

PubMed

Hu, Peter F; Xiao, Yan; Ho, Danny; Mackenzie, Colin F; Hu, Hao; Voigt, Roger; Martz, Douglas

2006-06-01

One of the major challenges for day-of-surgery operating room coordination is accurate and timely situation awareness. Distributed and secure real-time status information is key to addressing these challenges. This article reports on the design and implementation of a passive status monitoring system in a 19-room surgical suite of a major academic medical center. Key design requirements considered included integrated real-time operating room status display, access control, security, and network impact. The system used live operating room video images and patient vital signs obtained through monitors to automatically update events and operating room status. Images were presented on a "need-to-know" basis, and access was controlled by identification badge authorization. The system delivered reliable real-time operating room images and status with acceptable network impact. Operating room status was visualized at 4 separate locations and was used continuously by clinicians and operating room service providers to coordinate operating room activities.

Pervasive community care platform: Ambient Intelligence leveraging sensor networks and mobile agents

NASA Astrophysics Data System (ADS)

Su, Chuan-Jun; Chiang, Chang-Yu

2014-04-01

Several powerful trends are contributing to an aging of much of the world's population, especially in economically developed countries. To mitigate the negative effects of rapidly ageing populations, societies must act early to plan for the welfare, medical care and residential arrangements of their senior citizens, and for the manpower and associated training needed to execute these plans. This paper describes the development of an Ambient Intelligent Community Care Platform (AICCP), which creates an environment of Ambient Intelligence through the use of sensor network and mobile agent (MA) technologies. The AICCP allows caregivers to quickly and accurately locate their charges; access, update and share critical treatment and wellness data; and automatically archive all records. The AICCP presented in this paper is expected to enable caregivers and communities to offer pervasive, accurate and context-aware care services.

Synchronous wearable wireless body sensor network composed of autonomous textile nodes.

PubMed

Vanveerdeghem, Peter; Van Torre, Patrick; Stevens, Christiaan; Knockaert, Jos; Rogier, Hendrik

2014-10-09

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system.

Synchronous Wearable Wireless Body Sensor Network Composed of Autonomous Textile Nodes

PubMed Central

Vanveerdeghem, Peter; Van Torre, Patrick; Stevens, Christiaan; Knockaert, Jos; Rogier, Hendrik

2014-01-01

A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system. PMID:25302808

Topology for Dominance for Network of Multi-Agent System

NASA Astrophysics Data System (ADS)

Szeto, K. Y.

2007-05-01

The resource allocation problem in evolving two-dimensional point patterns is investigated for the existence of good strategies for the construction of initial configuration that leads to fast dominance of the pattern by one single species, which can be interpreted as market dominance by a company in the context of multi-agent systems in econophysics. For hexagonal lattice, certain special topological arrangements of the resource in two-dimensions, such as rings, lines and clusters have higher probability of dominance, compared to random pattern. For more complex networks, a systematic way to search for a stable and dominant strategy of resource allocation in the changing environment is found by means of genetic algorithm. Five typical features can be summarized by means of the distribution function for the local neighborhood of friends and enemies as well as the local clustering coefficients: (1) The winner has more triangles than the loser has. (2) The winner likes to form clusters as the winner tends to connect with other winner rather than with losers; while the loser tends to connect with winners rather than losers. (3) The distribution function of friends as well as enemies for the winner is broader than the corresponding distribution function for the loser. (4) The connectivity at which the peak of the distribution of friends for the winner occurs is larger than that of the loser; while the peak values for friends for winners is lower. (5) The connectivity at which the peak of the distribution of enemies for the winner occurs is smaller than that of the loser; while the peak values for enemies for winners is lower. These five features appear to be general, at least in the context of two-dimensional hexagonal lattices of various sizes, hierarchical lattice, Voronoi diagrams, as well as high-dimensional random networks. These general local topological properties of networks are relevant to strategists aiming at dominance in evolving patterns when the interaction between the agents is local.

Issues and Experiments in Electronic Publishing and Dissemination.

ERIC Educational Resources Information Center

Hunter, Karen

1994-01-01

Examines three topics related to electronic publishing and distribution: the national context, including NREN (National Education and Research Network); issues of market readiness, funding, delivery standards, access software, intellectual property concerns, and pricing and licensing models that must be resolved; and descriptions of seven services…

Cortical networks involved in visual awareness independent of visual attention.

PubMed

Webb, Taylor W; Igelström, Kajsa M; Schurger, Aaron; Graziano, Michael S A

2016-11-29

It is now well established that visual attention, as measured with standard spatial attention tasks, and visual awareness, as measured by report, can be dissociated. It is possible to attend to a stimulus with no reported awareness of the stimulus. We used a behavioral paradigm in which people were aware of a stimulus in one condition and unaware of it in another condition, but the stimulus drew a similar amount of spatial attention in both conditions. The paradigm allowed us to test for brain regions active in association with awareness independent of level of attention. Participants performed the task in an MRI scanner. We looked for brain regions that were more active in the aware than the unaware trials. The largest cluster of activity was obtained in the temporoparietal junction (TPJ) bilaterally. Local independent component analysis (ICA) revealed that this activity contained three distinct, but overlapping, components: a bilateral, anterior component; a left dorsal component; and a right dorsal component. These components had brain-wide functional connectivity that partially overlapped the ventral attention network and the frontoparietal control network. In contrast, no significant activity in association with awareness was found in the banks of the intraparietal sulcus, a region connected to the dorsal attention network and traditionally associated with attention control. These results show the importance of separating awareness and attention when testing for cortical substrates. They are also consistent with a recent proposal that awareness is associated with ventral attention areas, especially in the TPJ.

A radio-aware routing algorithm for reliable directed diffusion in lossy wireless sensor networks.

PubMed

Kim, Yong-Pyo; Jung, Euihyun; Park, Yong-Jin

2009-01-01

In Wireless Sensor Networks (WSNs), transmission errors occur frequently due to node failure, battery discharge, contention or interference by objects. Although Directed Diffusion has been considered as a prominent data-centric routing algorithm, it has some weaknesses due to unexpected network errors. In order to address these problems, we proposed a radio-aware routing algorithm to improve the reliability of Directed Diffusion in lossy WSNs. The proposed algorithm is aware of the network status based on the radio information from MAC and PHY layers using a cross-layer design. The cross-layer design can be used to get detailed information about current status of wireless network such as a link quality or transmission errors of communication links. The radio information indicating variant network conditions and link quality was used to determine an alternative route that provides reliable data transmission under lossy WSNs. According to the simulation result, the radio-aware reliable routing algorithm showed better performance in both grid and random topologies with various error rates. The proposed solution suggested the possibility of providing a reliable transmission method for QoS requests in lossy WSNs based on the radio-awareness. The energy and mobility issues will be addressed in the future work.

The impact of vaccine success and awareness on epidemic dynamics

NASA Astrophysics Data System (ADS)

Juang, Jonq; Liang, Yu-Hao

2016-11-01

The role of vaccine success is introduced into an epidemic spreading model consisting of three states: susceptible, infectious, and vaccinated. Moreover, the effect of three types, namely, contact, local, and global, of infection awareness and immunization awareness is also taken into consideration. The model generalizes those considered in Pastor-Satorras and Vespignani [Phys. Rev. E 63, 066117 (2001)], Pastor-Satorras and Vespignani [Phys. Rev. E 65, 036104 (2002)], Moreno et al. [Eur. Phys. J. B 26, 521-529 (2002)], Wu et al. [Chaos 22, 013101 (2012)], and Wu et al. [Chaos 24, 023108 (2014)]. Our main results contain the following. First, the epidemic threshold is explicitly obtained. In particular, we show that, for any initial conditions, the epidemic eventually dies out regardless of what other factors are whenever some type of immunization awareness is considered, and vaccination has a perfect success. Moreover, the threshold is independent of the global type of awareness. Second, we compare the effect of contact and local types of awareness on the epidemic thresholds between heterogeneous networks and homogeneous networks. Specifically, we find that the epidemic threshold for the homogeneous network can be lower than that of the heterogeneous network in an intermediate regime for intensity of contact infection awareness while it is higher otherwise. In summary, our results highlight the important and crucial roles of both vaccine success and contact infection awareness on epidemic dynamics.

NEAT: an efficient network enrichment analysis test.

PubMed

Signorelli, Mirko; Vinciotti, Veronica; Wit, Ernst C

2016-09-05

Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat ).

Hybrid context aware recommender systems

NASA Astrophysics Data System (ADS)

Jain, Rajshree; Tyagi, Jaya; Singh, Sandeep Kumar; Alam, Taj

2017-10-01

Recommender systems and context awareness is currently a vital field of research. Most hybrid recommendation systems implement content based and collaborative filtering techniques whereas this work combines context and collaborative filtering. The paper presents a hybrid context aware recommender system for books and movies that gives recommendations based on the user context as well as user or item similarity. It also addresses the issue of dimensionality reduction using weighted pre filtering based on dynamically entered user context and preference of context. This unique step helps to reduce the size of dataset for collaborative filtering. Bias subtracted collaborative filtering is used so as to consider the relative rating of a particular user and not the absolute values. Cosine similarity is used as a metric to determine the similarity between users or items. The unknown ratings are calculated and evaluated using MSE (Mean Squared Error) in test and train datasets. The overall process of recommendation has helped to personalize recommendations and give more accurate results with reduced complexity in collaborative filtering.

Resource-aware system architecture model for implementation of quantum aided Byzantine agreement on quantum repeater networks

NASA Astrophysics Data System (ADS)

Taherkhani, Mohammand Amin; Navi, Keivan; Van Meter, Rodney

2018-01-01

Quantum aided Byzantine agreement is an important distributed quantum algorithm with unique features in comparison to classical deterministic and randomized algorithms, requiring only a constant expected number of rounds in addition to giving a higher level of security. In this paper, we analyze details of the high level multi-party algorithm, and propose elements of the design for the quantum architecture and circuits required at each node to run the algorithm on a quantum repeater network (QRN). Our optimization techniques have reduced the quantum circuit depth by 44% and the number of qubits in each node by 20% for a minimum five-node setup compared to the design based on the standard arithmetic circuits. These improvements lead to a quantum system architecture with 160 qubits per node, space-time product (an estimate of the required fidelity) {KQ}≈ 1.3× {10}5 per node and error threshold 1.1× {10}-6 for the total nodes in the network. The evaluation of the designed architecture shows that to execute the algorithm once on the minimum setup, we need to successfully distribute a total of 648 Bell pairs across the network, spread evenly between all pairs of nodes. This framework can be considered a starting point for establishing a road-map for light-weight demonstration of a distributed quantum application on QRNs.

FleXConf: A Flexible Conference Assistant Using Context-Aware Notification Services

NASA Astrophysics Data System (ADS)

Armenatzoglou, Nikos; Marketakis, Yannis; Kriara, Lito; Apostolopoulos, Elias; Papavasiliou, Vicky; Kampas, Dimitris; Kapravelos, Alexandros; Kartsonakis, Eythimis; Linardakis, Giorgos; Nikitaki, Sofia; Bikakis, Antonis; Antoniou, Grigoris

Integrating context-aware notification services to ubiquitous computing systems aims at the provision of the right information to the right users, at the right time, in the right place, and on the right device, and constitutes a significant step towards the realization of the Ambient Intelligence vision. In this paper, we present FlexConf, a semantics-based system that supports location-based, personalized notification services for the assistance of conference attendees. Its special features include an ontology-based representation model, rule-based context-aware reasoning, and a novel positioning system for indoor environments.

Distributed Compression in Camera Sensor Networks

DTIC Science & Technology

2006-02-13

complicated in this context. This effort will make use of the correlation structure of the data given by the plenoptic function n the case of multi-camera...systems. In many cases the structure of the plenoptic function can be estimated without requiring inter-sensor communications, but by using some a...priori global geometrical information. Once the structure of the plenoptic function has been predicted, it is possible to develop specific distributed

Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks

PubMed Central

Hieu, Tran Dinh; Dung, Le The; Kim, Byung-Seo

2016-01-01

A new generation of wireless sensor networks that harvest energy from environmental sources such as solar, vibration, and thermoelectric to power sensor nodes is emerging to solve the problem of energy limitation. Based on the photo-voltaic model, this research proposes a stability-aware geographic routing for reliable data transmissions in energy-harvesting wireless sensor networks (EH-WSNs) to provide a reliable routes selection method and potentially achieve an unlimited network lifetime. Specifically, the influences of link quality, represented by the estimated packet reception rate, on network performance is investigated. Simulation results show that the proposed method outperforms an energy-harvesting-aware method in terms of energy consumption, the average number of hops, and the packet delivery ratio. PMID:27187414

A Fine-Grained API Link Prediction Approach Supporting CMDA Mashup Recommendation

NASA Astrophysics Data System (ADS)

Zhang, J.; Bao, Q.; Lee, T. J.; Ramachandran, R.; Lee, S.; Pan, L.; Gatlin, P. N.; Maskey, M.

2017-12-01

Service (API) discovery and recommendation is key to the wide spread of service oriented architecture and service oriented software engineering. Service recommendation typically relies on service linkage prediction calculated by the semantic distances (or similarities) among services based on their collection of inherent attributes. Given a specific context (mashup goal), however, different attributes may contribute differently to a service linkage. In this work, instead of training a model for all attributes as a whole, a novel approach is presented to simultaneously train separate models for individual attributes. Our contributions are summarized in three-fold. First is that we have developed a scalable attribute-level data model, featuring scalability and extensibility. We have extended Multiplicative Attribute Graph (MAG) model to represent node profiles featuring rich categorical attributes, while relaxing its constraint of requiring a priori knowledge of predefined attributes. LDA is leveraged to dynamically identify attributes based on attribute modeling, and multiple Gaussian fit is applied to find global optimal values. The second contribution is that we have seamlessly integrated the latent relationships between API attributes as well as observed network structure based on historical API usage data. Such a layered information model enables us to predict the probability of a link between two APIs based on their attribute link affinities carrying a variety of information including meta data, semantic data, historical usage data, as well as crowdsourcing user comments and annotations. The third contribution is that we have developed a finegrained context-aware mashup-API recommendation technique. On top of individual models trained for separate attributes, a dedicated layer is trained to represent the latent attribute distribution regarding mashup purpose, i.e., sensitivity of attributes to context. Thus, given the description of an intended mashup, the attributes sensitive to the goal will be identified, and corresponding attribute models will be exploited to compute the possibility of API linkages under the context. Such a layered model increases search accuracy.

Self-recognition, theory-of-mind, and self-awareness: what side are you on?

PubMed

Morin, Alain

2011-05-01

A fashionable view in comparative psychology states that primates possess self-awareness because they exhibit mirror self-recognition (MSR), which in turn makes it possible to infer mental states in others ("theory-of-mind"; ToM). In cognitive neuroscience, an increasingly popular position holds that the right hemisphere represents the centre of self-awareness because MSR and ToM tasks presumably increase activity in that hemisphere. These two claims are critically assessed here as follows: (1) MSR should not be equated with full-blown self-awareness, as it most probably only requires kinaesthetic self-knowledge and does not involve access to one's mental events; (2) ToM and self-awareness are fairly independent and should also not be taken as equivalent notions; (3) MSR and ToM tasks engage medial and left brain areas; (4) other self-awareness tasks besides MSR and ToM tasks (e.g., self-description, autobiography) mostly recruit medial and left brain areas; (5) and recent neuropsychological evidence implies that inner speech (produced by the left hemisphere) plays a significant role in self-referential activity. The main conclusions reached based on this analysis are that (a) organisms that display MSR most probably do not possess introspective self-awareness, and (b) self-related processes most likely engage a distributed network of brain regions situated in both hemispheres.

Energy star compliant voice over internet protocol (VoIP) telecommunications network including energy star compliant VoIP devices

DOEpatents

Kouchri, Farrokh Mohammadzadeh

2012-11-06

A Voice over Internet Protocol (VoIP) communications system, a method of managing a communications network in such a system and a program product therefore. The system/network includes an ENERGY STAR (E-star) aware softswitch and E-star compliant communications devices at system endpoints. The E-star aware softswitch allows E-star compliant communications devices to enter and remain in power saving mode. The E-star aware softswitch spools messages and forwards only selected messages (e.g., calls) to the devices in power saving mode. When the E-star compliant communications devices exit power saving mode, the E-star aware softswitch forwards spooled messages.

Investigation into the use of satellite remote sensing data products as part of a multi-modal marine environmental monitoring network

NASA Astrophysics Data System (ADS)

O'Connor, Edel; Smeaton, Alan F.; O'Connor, Noel E.; Regan, Fiona

2012-09-01

In this paper it is investigated how conventional in-situ sensor networks can be complemented by the satellite data streams available through numerous platforms orbiting the earth and the combined analyses products available through services such as MyOcean. Despite the numerous benefits associated with the use of satellite remote sensing data products, there are a number of limitations with their use in coastal zones. Here the ability of these data sources to provide contextual awareness, redundancy and increased efficiency to an in-situ sensor network is investigated. The potential use of a variety of chlorophyll and SST data products as additional data sources in the SmartBay monitoring network in Galway Bay, Ireland is analysed. The ultimate goal is to investigate the ability of these products to create a smarter marine monitoring network with increased efficiency. Overall it was found that while care needs to be taken in choosing these products, there was extremely promising performance from a number of these products that would be suitable in the context of a number of applications especially in relation to SST. It was more difficult to come to conclusive results for the chlorophyll analysis.

Quantifying the propagation of distress and mental disorders in social networks.

PubMed

Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro

2018-03-22

Heterogeneity of human beings leads to think and react differently to social phenomena. Awareness and homophily drive people to weigh interactions in social multiplex networks, influencing a potential contagion effect. To quantify the impact of heterogeneity on spreading dynamics, we propose a model of coevolution of social contagion and awareness, through the introduction of statistical estimators, in a weighted multiplex network. Multiplexity of networked individuals may trigger propagation enough to produce effects among vulnerable subjects experiencing distress, mental disorder, which represent some of the strongest predictors of suicidal behaviours. The exposure to suicide is emotionally harmful, since talking about it may give support or inadvertently promote it. To disclose the complex effect of the overlapping awareness on suicidal ideation spreading among disordered people, we also introduce a data-driven approach by integrating different types of data. Our modelling approach unveils the relationship between distress and mental disorders propagation and suicidal ideation spreading, shedding light on the role of awareness in a social network for suicide prevention. The proposed model is able to quantify the impact of overlapping awareness on suicidal ideation spreading and our findings demonstrate that it plays a dual role on contagion, either reinforcing or delaying the contagion outbreak.

A new method for developing compassionate communities and cities movement-"Todos Contigo" Programme (We are All With You): experience in Spain and Latin America countries.

PubMed

Librada Flores, Silvia

2018-01-01

Todos Contigo (We are All With You) is a programme for social awareness, training, and implementation of care networks for citizens to support, accompany and care for those who face advanced chronic disease and end of life situations. From New Health Foundation this programme collaborates with the Public Health and Palliative Care International Charter of Compassionate Communities. It seeks to promote a new integrated palliative care model in the daily lives of individuals, to make families and health/social professionals the main promoters of compassionate communities and compassionate cities movement. This workshop aims to: (I) describe the methodology of the programme: required tools and steps for building and developing a compassionate city or community; (II) identify stakeholders and organizations to join the compassionate community as networking agents; (III) sharing experiences from the implementation of this project in various contexts while providing specific examples and lessons learned from the perspective of various roles; (IV) explain the process of becoming a part of the project and of getting the official recognition for being a compassionate city. This workshop aims to share a new methodology "Todos Contigo" (We are all with you) Programme for the development of compassionate communities and cities movement. We describe our experiences in Spain and Latin American countries. The method is based on creating community networks, carrying out social awareness and training programmes related to end of life care.

A practical indoor context-aware surveillance system with multi-Kinect sensors

NASA Astrophysics Data System (ADS)

Jia, Lili; You, Ying; Li, Tiezhu; Zhang, Shun

2014-11-01

In this paper we develop a novel practical application, which give scalable services to the end users when abnormal actives are happening. Architecture of the application has been presented consisting of network infrared cameras and a communication module. In this intelligent surveillance system we use Kinect sensors as the input cameras. Kinect is an infrared laser camera which its user can access the raw infrared sensor stream. We install several Kinect sensors in one room to track the human skeletons. Each sensor returns the body positions with 15 coordinates in its own coordinate system. We use calibration algorithms to calibrate all the body positions points into one unified coordinate system. With the body positions points, we can infer the surveillance context. Furthermore, the messages from the metadata index matrix will be sent to mobile phone through communication module. User will instantly be aware of an abnormal case happened in the room without having to check the website. In conclusion, theoretical analysis and experimental results in this paper show that the proposed system is reasonable and efficient. And the application method introduced in this paper is not only to discourage the criminals and assist police in the apprehension of suspects, but also can enabled the end-users monitor the indoor environments anywhere and anytime by their phones.

A Semantic Approach with Decision Support for Safety Service in Smart Home Management

PubMed Central

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-01-01

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

PubMed

Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

2016-08-03

Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

Systems Modeling to Implement Integrated System Health Management Capability

NASA Technical Reports Server (NTRS)

Figueroa, Jorge F.; Walker, Mark; Morris, Jonathan; Smith, Harvey; Schmalzel, John

2007-01-01

ISHM capability includes: detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, and user interfaces that enable integrated awareness (past, present, and future) by users. This is achieved by focused management of data, information and knowledge (DIaK) that will likely be distributed across networks. Management of DIaK implies storage, sharing (timely availability), maintaining, evolving, and processing. Processing of DIaK encapsulates strategies, methodologies, algorithms, etc. focused on achieving high ISHM Functional Capability Level (FCL). High FCL means a high degree of success in detecting anomalies, diagnosing causes, predicting future anomalies, and enabling health integrated awareness by the user. A model that enables ISHM capability, and hence, DIaK management, is denominated the ISHM Model of the System (IMS). We describe aspects of the IMS that focus on processing of DIaK. Strategies, methodologies, and algorithms require proper context. We describe an approach to define and use contexts, implementation in an object-oriented software environment (G2), and validation using actual test data from a methane thruster test program at NASA SSC. Context is linked to existence of relationships among elements of a system. For example, the context to use a strategy to detect leak is to identify closed subsystems (e.g. bounded by closed valves and by tanks) that include pressure sensors, and check if the pressure is changing. We call these subsystems Pressurizable Subsystems. If pressure changes are detected, then all members of the closed subsystem become suspect of leakage. In this case, the context is defined by identifying a subsystem that is suitable for applying a strategy. Contexts are defined in many ways. Often, a context is defined by relationships of function (e.g. liquid flow, maintaining pressure, etc.), form (e.g. part of the same component, connected to other components, etc.), or space (e.g. physically close, touching the same common element, etc.). The context might be defined dynamically (if conditions for the context appear and disappear dynamically) or statically. Although this approach is akin to case-based reasoning, we are implementing it using a software environment that embodies tools to define and manage relationships (of any nature) among objects in a very intuitive manner. Context for higher level inferences (that use detected anomalies or events), primarily for diagnosis and prognosis, are related to causal relationships. This is useful to develop root-cause analysis trees showing an event linked to its possible causes and effects. The innovation pertaining to RCA trees encompasses use of previously defined subsystems as well as individual elements in the tree. This approach allows more powerful implementations of RCA capability in object-oriented environments. For example, if a pressurizable subsystem is leaking, its root-cause representation within an RCA tree will show that the cause is that all elements of that subsystem are suspect of leak. Such a tree would apply to all instances of leak-events detected and all elements in all pressurizable subsystems in the system. Example subsystems in our environment to build IMS include: Pressurizable Subsystem, Fluid-Fill Subsystem, Flow-Thru-Valve Subsystem, and Fluid Supply Subsystem. The software environment for IMS is designed to potentially allow definition of any relationship suitable to create a context to achieve ISHM capability.

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification.

PubMed

Razzaq, Muhammad Asif; Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Ali Khan, Wajahat

2017-10-24

The emerging research on automatic identification of user's contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user's contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts.

mlCAF: Multi-Level Cross-Domain Semantic Context Fusioning for Behavior Identification

PubMed Central

Villalonga, Claudia; Lee, Sungyoung; Akhtar, Usman; Ali, Maqbool; Kim, Eun-Soo; Khattak, Asad Masood; Seung, Hyonwoo; Hur, Taeho; Kim, Dohyeong; Ali Khan, Wajahat

2017-01-01

The emerging research on automatic identification of user’s contexts from the cross-domain environment in ubiquitous and pervasive computing systems has proved to be successful. Monitoring the diversified user’s contexts and behaviors can help in controlling lifestyle associated to chronic diseases using context-aware applications. However, availability of cross-domain heterogeneous contexts provides a challenging opportunity for their fusion to obtain abstract information for further analysis. This work demonstrates extension of our previous work from a single domain (i.e., physical activity) to multiple domains (physical activity, nutrition and clinical) for context-awareness. We propose multi-level Context-aware Framework (mlCAF), which fuses the multi-level cross-domain contexts in order to arbitrate richer behavioral contexts. This work explicitly focuses on key challenges linked to multi-level context modeling, reasoning and fusioning based on the mlCAF open-source ontology. More specifically, it addresses the interpretation of contexts from three different domains, their fusioning conforming to richer contextual information. This paper contributes in terms of ontology evolution with additional domains, context definitions, rules and inclusion of semantic queries. For the framework evaluation, multi-level cross-domain contexts collected from 20 users were used to ascertain abstract contexts, which served as basis for behavior modeling and lifestyle identification. The experimental results indicate a context recognition average accuracy of around 92.65% for the collected cross-domain contexts. PMID:29064459

Distributed state-space generation of discrete-state stochastic models

NASA Technical Reports Server (NTRS)

Ciardo, Gianfranco; Gluckman, Joshua; Nicol, David

1995-01-01

High-level formalisms such as stochastic Petri nets can be used to model complex systems. Analysis of logical and numerical properties of these models of ten requires the generation and storage of the entire underlying state space. This imposes practical limitations on the types of systems which can be modeled. Because of the vast amount of memory consumed, we investigate distributed algorithms for the generation of state space graphs. The distributed construction allows us to take advantage of the combined memory readily available on a network of workstations. The key technical problem is to find effective methods for on-the-fly partitioning, so that the state space is evenly distributed among processors. In this paper we report on the implementation of a distributed state-space generator that may be linked to a number of existing system modeling tools. We discuss partitioning strategies in the context of Petri net models, and report on performance observed on a network of workstations, as well as on a distributed memory multi-computer.

Prototyping context-aware nursing support mobile system.

PubMed

Esashi, Misa; Nakano, Tomohiro; Onose, Nao; Sato, Kikue; Hikita, Tomoko; Hoya, Reiko; Okamoto, Kazuya; Ohboshi, Naoki; Kuroda, Tomohiro

2016-08-01

A context aware nursing support system to push right information to the right person at the right moment is the key to increase clinical safety under a computerized hospital. We prototyped a system which obtains context from positions of nurses and list of expected clinical procedures. A WoZ test showed that the proposed approach has potential to decrease incidents caused by information delivery error.

Semantic Web Technologies for Mobile Context-Aware Services

DTIC Science & Technology

2006-03-01

for Context-Aware Service Provisioning 6 Communication toolkit (http, e-mail, IM, etc.) User interaction manager Platform manager White & yellow ...NAICS] North American Industry Classification System , http://www.census.gov/epcd/www/naics.html [OS00] Opermann, R., and Specht , M., A Context...toolkit (http, e-mail, IM, etc.) User interaction manager Platform manager White & yellow pages MAS administration toolkit N ET W O R K knowledge

Maximum entropy methods for extracting the learned features of deep neural networks.

PubMed

Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

An Overview of Data Routing Approaches for Wireless Sensor Networks

PubMed Central

Anisi, Mohammad Hossein; Abdullah, Abdul Hanan; Razak, Shukor Abd; Ngadi, Md. Asri

2012-01-01

Recent years have witnessed a growing interest in deploying large populations of microsensors that collaborate in a distributed manner to gather and process sensory data and deliver them to a sink node through wireless communications systems. Currently, there is a lot of interest in data routing for Wireless Sensor Networks (WSNs) due to their unique challenges compared to conventional routing in wired networks. In WSNs, each data routing approach follows a specific goal (goals) according to the application. Although the general goal of every data routing approach in WSNs is to extend the network lifetime and every approach should be aware of the energy level of the nodes, data routing approaches may focus on one (or some) specific goal(s) depending on the application. Thus, existing approaches can be categorized according to their routing goals. In this paper, the main goals of data routing approaches in sensor networks are described. Then, the best known and most recent data routing approaches in WSNs are classified and studied according to their specific goals. PMID:23443040

Privacy-Related Context Information for Ubiquitous Health

PubMed Central

Nykänen, Pirkko; Ruotsalainen, Pekka

2014-01-01

Background Ubiquitous health has been defined as a dynamic network of interconnected systems. A system is composed of one or more information systems, their stakeholders, and the environment. These systems offer health services to individuals and thus implement ubiquitous computing. Privacy is the key challenge for ubiquitous health because of autonomous processing, rich contextual metadata, lack of predefined trust among participants, and the business objectives. Additionally, regulations and policies of stakeholders may be unknown to the individual. Context-sensitive privacy policies are needed to regulate information processing. Objective Our goal was to analyze privacy-related context information and to define the corresponding components and their properties that support privacy management in ubiquitous health. These properties should describe the privacy issues of information processing. With components and their properties, individuals can define context-aware privacy policies and set their privacy preferences that can change in different information-processing situations. Methods Scenarios and user stories are used to analyze typical activities in ubiquitous health to identify main actors, goals, tasks, and stakeholders. Context arises from an activity and, therefore, we can determine different situations, services, and systems to identify properties for privacy-related context information in information-processing situations. Results Privacy-related context information components are situation, environment, individual, information technology system, service, and stakeholder. Combining our analyses and previously identified characteristics of ubiquitous health, more detailed properties for the components are defined. Properties define explicitly what context information for different components is needed to create context-aware privacy policies that can control, limit, and constrain information processing. With properties, we can define, for example, how data can be processed or how components are regulated or in what kind of environment data can be processed. Conclusions This study added to the vision of ubiquitous health by analyzing information processing from the viewpoint of an individual’s privacy. We learned that health and wellness-related activities may happen in several environments and situations with multiple stakeholders, services, and systems. We have provided new knowledge regarding privacy-related context information and corresponding components by analyzing typical activities in ubiquitous health. With the identified components and their properties, individuals can define their personal preferences on information processing based on situational information, and privacy services can capture privacy-related context of the information-processing situation. PMID:25100084

Privacy-related context information for ubiquitous health.

PubMed

Seppälä, Antto; Nykänen, Pirkko; Ruotsalainen, Pekka

2014-03-11

Ubiquitous health has been defined as a dynamic network of interconnected systems. A system is composed of one or more information systems, their stakeholders, and the environment. These systems offer health services to individuals and thus implement ubiquitous computing. Privacy is the key challenge for ubiquitous health because of autonomous processing, rich contextual metadata, lack of predefined trust among participants, and the business objectives. Additionally, regulations and policies of stakeholders may be unknown to the individual. Context-sensitive privacy policies are needed to regulate information processing. Our goal was to analyze privacy-related context information and to define the corresponding components and their properties that support privacy management in ubiquitous health. These properties should describe the privacy issues of information processing. With components and their properties, individuals can define context-aware privacy policies and set their privacy preferences that can change in different information-processing situations. Scenarios and user stories are used to analyze typical activities in ubiquitous health to identify main actors, goals, tasks, and stakeholders. Context arises from an activity and, therefore, we can determine different situations, services, and systems to identify properties for privacy-related context information in information-processing situations. Privacy-related context information components are situation, environment, individual, information technology system, service, and stakeholder. Combining our analyses and previously identified characteristics of ubiquitous health, more detailed properties for the components are defined. Properties define explicitly what context information for different components is needed to create context-aware privacy policies that can control, limit, and constrain information processing. With properties, we can define, for example, how data can be processed or how components are regulated or in what kind of environment data can be processed. This study added to the vision of ubiquitous health by analyzing information processing from the viewpoint of an individual's privacy. We learned that health and wellness-related activities may happen in several environments and situations with multiple stakeholders, services, and systems. We have provided new knowledge regarding privacy-related context information and corresponding components by analyzing typical activities in ubiquitous health. With the identified components and their properties, individuals can define their personal preferences on information processing based on situational information, and privacy services can capture privacy-related context of the information-processing situation.

Cognitive effort is modulated outside of the explicit awareness of conflict frequency: Evidence from pupillometry.

PubMed

Diede, Nathaniel T; Bugg, Julie M

2017-05-01

Classic theories of cognitive control conceptualized controlled processes as slow, strategic, and willful, with automatic processes being fast and effortless. The context-specific proportion compatibility (CSPC) effect, the reduction in the compatibility effect in a context (e.g., location) associated with a high relative to low likelihood of conflict, challenged classic theories by demonstrating fast and flexible control that appears to operate outside of conscious awareness. Two theoretical questions yet to be addressed are whether the CSPC effect is accompanied by context-dependent variation in effort, and whether the exertion of effort depends on explicit awareness of context-specific task demands. To address these questions, pupil diameter was measured during a CSPC paradigm. Stimuli were randomly presented in either a mostly compatible location or a mostly incompatible location. Replicating prior research, the CSPC effect was found. The novel finding was that pupil diameter was greater in the mostly incompatible location compared to the mostly compatible location, despite participants' lack of awareness of context-specific task demands. Additionally, this difference occurred regardless of trial type or a preceding switch in location. These patterns support the view that context (location) dictates selection of optimal attentional settings in the CSPC paradigm, and varying levels of effort and performance accompany these settings. Theoretically, these patterns imply that cognitive control may operate fast, flexibly, and outside of awareness, but not effortlessly. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Beyond Music Sharing: An Evaluation of Peer-to-Peer Data Dissemination Techniques in Large Scientific Collaborations

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

Ripeanu, Matei; Al-Kiswany, Samer; Iamnitchi, Adriana

2009-03-01

The avalanche of data from scientific instruments and the ensuing interest from geographically distributed users to analyze and interpret it accentuates the need for efficient data dissemination. A suitable data distribution scheme will find the delicate balance between conflicting requirements of minimizing transfer times, minimizing the impact on the network, and uniformly distributing load among participants. We identify several data distribution techniques, some successfully employed by today's peer-to-peer networks: staging, data partitioning, orthogonal bandwidth exploitation, and combinations of the above. We use simulations to explore the performance of these techniques in contexts similar to those used by today's data-centric scientificmore » collaborations and derive several recommendations for efficient data dissemination. Our experimental results show that the peer-to-peer solutions that offer load balancing and good fault tolerance properties and have embedded participation incentives lead to unjustified costs in today's scientific data collaborations deployed on over-provisioned network cores. However, as user communities grow and these deployments scale, peer-to-peer data delivery mechanisms will likely outperform other techniques.« less

Staff's awareness of abuse in health care varies according to context and possibilities to act.

PubMed

Swahnberg, Katarina; Wijma, Barbro

2011-06-01

The aim of this study was to explore awareness of abuse in health care (AHC) from a staff perspective. Patient evaluation studies often focus on patient satisfaction, and serious negative experiences might therefore be obscured. In our research, we have found that abuse in health care (AHC) is commonly reported by male and female patients, when asked for in a strait way, but so far no intervention studies against AHC have been published. Investigating staff's awareness of AHC is our first step toward developing interventions against AHC. Data were collected at a Swedish clinic of obstetrics and gynecology. Qualitative interviews with 21 informants were analysed with constant comparative analyses. The core category - 'Staff's awareness of AHC varies according to context and possibilities to act' - was derived from the interaction between five categories; Moral imagination, Relativism, Explanations, Dissociation from AHC and Acting against AHC. Awareness of AHC was not a permanent state that did/did not exist as all participants displayed both high and low awareness; depending on the context. Staff's awareness depends on more than personal characteristics; therefore, AHC interventions have to target individual behavior as well as cultures and structures in health care.

A probabilistic dynamic energy model for ad-hoc wireless sensors network with varying topology

NASA Astrophysics Data System (ADS)

Al-Husseini, Amal

In this dissertation we investigate the behavior of Wireless Sensor Networks (WSNs) from the degree distribution and evolution perspective. In specific, we focus on implementation of a scale-free degree distribution topology for energy efficient WSNs. WSNs is an emerging technology that finds its applications in different areas such as environment monitoring, agricultural crop monitoring, forest fire monitoring, and hazardous chemical monitoring in war zones. This technology allows us to collect data without human presence or intervention. Energy conservation/efficiency is one of the major issues in prolonging the active life WSNs. Recently, many energy aware and fault tolerant topology control algorithms have been presented, but there is dearth of research focused on energy conservation/efficiency of WSNs. Therefore, we study energy efficiency and fault-tolerance in WSNs from the degree distribution and evolution perspective. Self-organization observed in natural and biological systems has been directly linked to their degree distribution. It is widely known that scale-free distribution bestows robustness, fault-tolerance, and access efficiency to system. Fascinated by these properties, we propose two complex network theoretic self-organizing models for adaptive WSNs. In particular, we focus on adopting the Barabasi and Albert scale-free model to fit into the constraints and limitations of WSNs. We developed simulation models to conduct numerical experiments and network analysis. The main objective of studying these models is to find ways to reducing energy usage of each node and balancing the overall network energy disrupted by faulty communication among nodes. The first model constructs the wireless sensor network relative to the degree (connectivity) and remaining energy of every individual node. We observed that it results in a scale-free network structure which has good fault tolerance properties in face of random node failures. The second model considers additional constraints on the maximum degree of each node as well as the energy consumption relative to degree changes. This gives more realistic results from a dynamical network perspective. It results in balanced network-wide energy consumption. The results show that networks constructed using the proposed approach have good properties for different centrality measures. The outcomes of the presented research are beneficial to building WSN control models with greater self-organization properties which leads to optimal energy consumption.

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

Dorier, Matthieu; Mubarak, Misbah; Ross, Rob

Two-tiered direct network topologies such as Dragonflies have been proposed for future post-petascale and exascale machines, since they provide a high-radix, low-diameter, fast interconnection network. Such topologies call for redesigning MPI collective communication algorithms in order to attain the best performance. Yet as increasingly more applications share a machine, it is not clear how these topology-aware algorithms will react to interference with concurrent jobs accessing the same network. In this paper, we study three topology-aware broadcast algorithms, including one designed by ourselves. We evaluate their performance through event-driven simulation for small- and large-sized broadcasts (in terms of both data sizemore » and number of processes). We study the effect of different routing mechanisms on the topology-aware collective algorithms, as well as their sensitivity to network contention with other jobs. Our results show that while topology-aware algorithms dramatically reduce link utilization, their advantage in terms of latency is more limited.« less

Raising Cultural Awareness in the English Language Classroom

ERIC Educational Resources Information Center

Frank, Jerrold

2013-01-01

This article discusses how teachers can incorporate cultural knowledge into English language classes, exploring elements of culture, intercultural phenomena, and high-context and low-context cultures. Activities offered by the author to raise cultural awareness include web quests, role plays, cultural observations, and culture journals.

Growth and containment of a hierarchical criminal network

NASA Astrophysics Data System (ADS)

Marshak, Charles Z.; Rombach, M. Puck; Bertozzi, Andrea L.; D'Orsogna, Maria R.

2016-02-01

We model the hierarchical evolution of an organized criminal network via antagonistic recruitment and pursuit processes. Within the recruitment phase, a criminal kingpin enlists new members into the network, who in turn seek out other affiliates. New recruits are linked to established criminals according to a probability distribution that depends on the current network structure. At the same time, law enforcement agents attempt to dismantle the growing organization using pursuit strategies that initiate on the lower level nodes and that unfold as self-avoiding random walks. The global details of the organization are unknown to law enforcement, who must explore the hierarchy node by node. We halt the pursuit when certain local criteria of the network are uncovered, encoding if and when an arrest is made; the criminal network is assumed to be eradicated if the kingpin is arrested. We first analyze recruitment and study the large scale properties of the growing network; later we add pursuit and use numerical simulations to study the eradication probability in the case of three pursuit strategies, the time to first eradication, and related costs. Within the context of this model, we find that eradication becomes increasingly costly as the network increases in size and that the optimal way of arresting the kingpin is to intervene at the early stages of network formation. We discuss our results in the context of dark network disruption and their implications on possible law enforcement strategies.

Growth and containment of a hierarchical criminal network.

PubMed

Marshak, Charles Z; Rombach, M Puck; Bertozzi, Andrea L; D'Orsogna, Maria R

2016-02-01

We model the hierarchical evolution of an organized criminal network via antagonistic recruitment and pursuit processes. Within the recruitment phase, a criminal kingpin enlists new members into the network, who in turn seek out other affiliates. New recruits are linked to established criminals according to a probability distribution that depends on the current network structure. At the same time, law enforcement agents attempt to dismantle the growing organization using pursuit strategies that initiate on the lower level nodes and that unfold as self-avoiding random walks. The global details of the organization are unknown to law enforcement, who must explore the hierarchy node by node. We halt the pursuit when certain local criteria of the network are uncovered, encoding if and when an arrest is made; the criminal network is assumed to be eradicated if the kingpin is arrested. We first analyze recruitment and study the large scale properties of the growing network; later we add pursuit and use numerical simulations to study the eradication probability in the case of three pursuit strategies, the time to first eradication, and related costs. Within the context of this model, we find that eradication becomes increasingly costly as the network increases in size and that the optimal way of arresting the kingpin is to intervene at the early stages of network formation. We discuss our results in the context of dark network disruption and their implications on possible law enforcement strategies.

Two-stage effects of awareness cascade on epidemic spreading in multiplex networks

NASA Astrophysics Data System (ADS)

Guo, Quantong; Jiang, Xin; Lei, Yanjun; Li, Meng; Ma, Yifang; Zheng, Zhiming

2015-01-01

Human awareness plays an important role in the spread of infectious diseases and the control of propagation patterns. The dynamic process with human awareness is called awareness cascade, during which individuals exhibit herd-like behavior because they are making decisions based on the actions of other individuals [Borge-Holthoefer et al., J. Complex Networks 1, 3 (2013), 10.1093/comnet/cnt006]. In this paper, to investigate the epidemic spreading with awareness cascade, we propose a local awareness controlled contagion spreading model on multiplex networks. By theoretical analysis using a microscopic Markov chain approach and numerical simulations, we find the emergence of an abrupt transition of epidemic threshold βc with the local awareness ratio α approximating 0.5 , which induces two-stage effects on epidemic threshold and the final epidemic size. These findings indicate that the increase of α can accelerate the outbreak of epidemics. Furthermore, a simple 1D lattice model is investigated to illustrate the two-stage-like sharp transition at αc≈0.5 . The results can give us a better understanding of why some epidemics cannot break out in reality and also provide a potential access to suppressing and controlling the awareness cascading systems.

Design and Evaluation of a Widget-Based Dashboard for Awareness Support in Research Networks

ERIC Educational Resources Information Center

Reinhardt, Wolfgang; Mletzko, Christian; Drachsler, Hendrik; Sloep, Peter B.

2014-01-01

In this article, we describe the rationale, design and evaluation of a widget-based dashboard to support scholars' awareness of their Research Networks. We introduce the concept of a Research Network and discuss Personal Research Environments that are built of as a development parallel to Personal Learning Environments. Based on the results…

Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

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

Wang, Hong; Aziz, H M Abdul; Young, Stan

Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections.more » In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.« less

A multilayer network dataset of interaction and influence spreading in a virtual world

NASA Astrophysics Data System (ADS)

Jankowski, Jarosław; Michalski, Radosław; Bródka, Piotr

2017-10-01

Presented data contains the record of five spreading campaigns that occurred in a virtual world platform. Users distributed avatars between each other during the campaigns. The processes varied in time and range and were either incentivized or not incentivized. Campaign data is accompanied by events. The data can be used to build a multilayer network to place the campaigns in a wider context. To the best of the authors' knowledge, the study is the first publicly available dataset containing a complete real multilayer social network together, along with five complete spreading processes in it.

AANCART best practices: cancer awareness activities for Seattle's Combodian community.

PubMed

Seng, Paularita; Acorda, Elizabeth; Carey Jackson, J; Marchand, Ann; Thai, Hue; Tu, Shin-Ping; Taylor, Vicky

2005-12-15

Census data indicate that Cambodian Americans are economically disadvantaged and linguistically isolated. In addition, cancer registry data show that Southeast Asians experience several cancer-related health disparities (e.g., markedly elevated risks of cervical and liver cancer). The Seattle regional Asian American Network for Cancer, Awareness, Research, and Training (AANCART) site has implemented a community-based cancer awareness program for Cambodian immigrants in collaboration with a Cambodian community coalition. Our cancer awareness program has the following goals: to assist individuals and organizations in advocating for a healthy community, to provide information within a cultural context, and to deliver information in ways that are useful and meaningful to the community. The program was guided by a community assessment that included the use of published data as well as information from qualitative interviews, focus groups, and quantitative surveys. Examples of community awareness activities include group presentations at community-based organizations (e.g., during English as a second language classes), health fair participation (including at nontraditional venues such as a farmers' market serving Cambodians), and educational displays in neighborhood locations (e.g., at Cambodian video stores). In addition, the Seattle AANCART site has both inventoried and developed culturally appropriate Khmer language cancer education materials and disseminated materials through the ETHNO-MED website. Our approach recognizes that limited English language proficiency may preclude many Cambodians from understanding publicly disseminated information, and Cambodian immigrants are often isolated and tend to stay close to their own neighborhoods. Cancer 2005. (c) 2005 American Cancer Society.

Smart unattended sensor networks with scene understanding capabilities

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2006-05-01

Unattended sensor systems are new technologies that are supposed to provide enhanced situation awareness to military and law enforcement agencies. A network of such sensors cannot be very effective in field conditions only if it can transmit visual information to human operators or alert them on motion. In the real field conditions, events may happen in many nodes of a network simultaneously. But the real number of control personnel is always limited, and attention of human operators can be simply attracted to particular network nodes, while more dangerous threat may be unnoticed at the same time in the other nodes. Sensor networks would be more effective if equipped with a system that is similar to human vision in its abilities to understand visual information. Human vision uses for that a rough but wide peripheral system that tracks motions and regions of interests, narrow but precise foveal vision that analyzes and recognizes objects in the center of selected region of interest, and visual intelligence that provides scene and object contexts and resolves ambiguity and uncertainty in the visual information. Biologically-inspired Network-Symbolic models convert image information into an 'understandable' Network-Symbolic format, which is similar to relational knowledge models. The equivalent of interaction between peripheral and foveal systems in the network-symbolic system is achieved via interaction between Visual and Object Buffers and the top-level knowledge system.

Towards Pervasive Augmented Reality: Context-Awareness in Augmented Reality.

PubMed

Grubert, Jens; Langlotz, Tobias; Zollmann, Stefanie; Regenbrecht, Holger

2017-06-01

Augmented Reality is a technique that enables users to interact with their physical environment through the overlay of digital information. While being researched for decades, more recently, Augmented Reality moved out of the research labs and into the field. While most of the applications are used sporadically and for one particular task only, current and future scenarios will provide a continuous and multi-purpose user experience. Therefore, in this paper, we present the concept of Pervasive Augmented Reality, aiming to provide such an experience by sensing the user's current context and adapting the AR system based on the changing requirements and constraints. We present a taxonomy for Pervasive Augmented Reality and context-aware Augmented Reality, which classifies context sources and context targets relevant for implementing such a context-aware, continuous Augmented Reality experience. We further summarize existing approaches that contribute towards Pervasive Augmented Reality. Based our taxonomy and survey, we identify challenges for future research directions in Pervasive Augmented Reality.

Open Online Spaces of Professional Learning: Context, Personalisation and Facilitation

ERIC Educational Resources Information Center

Evans, Peter

2015-01-01

This article explores professional learning through online discussion events as sites of communities of learning. The rise of distributed work places and networked labour coincides with a privileging of individualised professional learning. Alongside this focus on the individual has been a growth in informal online learning communities and…

Information Sharing in the Field of Design Research

ERIC Educational Resources Information Center

Pilerot, Ola

2015-01-01

Introduction: This paper reports on an extensive research project which aimed at exploring information sharing activities in a scholarly context. The paper presents and synthesises findings from a literature review and three qualitative case studies. The empirical setting is a geographically distributed Nordic network of design scholars. Method:…

Intelligent Systems Technologies and Utilization of Earth Observation Data

NASA Technical Reports Server (NTRS)

Ramapriyan, H. K.; McConaughy, G. R.; Morse, H. S.

2004-01-01

The addition of raw data and derived geophysical parameters from several Earth observing satellites over the last decade to the data held by NASA data centers has created a data rich environment for the Earth science research and applications communities. The data products are being distributed to a large and diverse community of users. Due to advances in computational hardware, networks and communications, information management and software technologies, significant progress has been made in the last decade in archiving and providing data to users. However, to realize the full potential of the growing data archives, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system (KBS). Potential Intelligent Archive concepts include: 1) Mining archived data holdings to improve metadata to facilitate data access and usability; 2) Building intelligence about transformations on data, information, knowledge, and accompanying services; 3) Recognizing the value of results, indexing and formatting them for easy access; 4) Interacting as a cooperative node in a web of distributed systems to perform knowledge building; and 5) Being aware of other nodes in the KBS, participating in open systems interfaces and protocols for virtualization, and achieving collaborative interoperability.

A Bio-Inspired Model-Based Approach for Context-Aware Post-WIMP Tele-Rehabilitation.

PubMed

López-Jaquero, Víctor; Rodríguez, Arturo C; Teruel, Miguel A; Montero, Francisco; Navarro, Elena; Gonzalez, Pascual

2016-10-13

Tele-rehabilitation is one of the main domains where Information and Communication Technologies (ICT) have been proven useful to move healthcare from care centers to patients' home. Moreover, patients, especially those carrying out a physical therapy, cannot use a traditional Window, Icon, Menu, Pointer (WIMP) system, but they need to interact in a natural way, that is, there is a need to move from WIMP systems to Post-WIMP ones. Moreover, tele-rehabilitation systems should be developed following the context-aware approach, so that they are able to adapt to the patients' context to provide them with usable and effective therapies. In this work a model-based approach is presented to assist stakeholders in the development of context-aware Post-WIMP tele-rehabilitation systems. It entails three different models: (i) a task model for designing the rehabilitation tasks; (ii) a context model to facilitate the adaptation of these tasks to the context; and (iii) a bio-inspired presentation model to specify thoroughly how such tasks should be performed by the patients. Our proposal overcomes one of the limitations of the model-based approach for the development of context-aware systems supporting the specification of non-functional requirements. Finally, a case study is used to illustrate how this proposal can be put into practice to design a real world rehabilitation task.

Application of the JDL data fusion process model for cyber security

NASA Astrophysics Data System (ADS)

Giacobe, Nicklaus A.

2010-04-01

A number of cyber security technologies have proposed the use of data fusion to enhance the defensive capabilities of the network and aid in the development of situational awareness for the security analyst. While there have been advances in fusion technologies and the application of fusion in intrusion detection systems (IDSs), in particular, additional progress can be made by gaining a better understanding of a variety of data fusion processes and applying them to the cyber security application domain. This research explores the underlying processes identified in the Joint Directors of Laboratories (JDL) data fusion process model and further describes them in a cyber security context.

A Routing Path Construction Method for Key Dissemination Messages in Sensor Networks

PubMed Central

Moon, Soo Young; Cho, Tae Ho

2014-01-01

Authentication is an important security mechanism for detecting forged messages in a sensor network. Each cluster head (CH) in dynamic key distribution schemes forwards a key dissemination message that contains encrypted authentication keys within its cluster to next-hop nodes for the purpose of authentication. The forwarding path of the key dissemination message strongly affects the number of nodes to which the authentication keys in the message are actually distributed. We propose a routing method for the key dissemination messages to increase the number of nodes that obtain the authentication keys. In the proposed method, each node selects next-hop nodes to which the key dissemination message will be forwarded based on secret key indexes, the distance to the sink node, and the energy consumption of its neighbor nodes. The experimental results show that the proposed method can increase by 50–70% the number of nodes to which authentication keys in each cluster are distributed compared to geographic and energy-aware routing (GEAR). In addition, the proposed method can detect false reports earlier by using the distributed authentication keys, and it consumes less energy than GEAR when the false traffic ratio (FTR) is ≥10%. PMID:25136649

Smart Grid Communications System Blueprint

NASA Astrophysics Data System (ADS)

Clark, Adrian; Pavlovski, Chris

2010-10-01

Telecommunications operators are well versed in deploying 2G and 3G wireless networks. These networks presently support the mobile business user and/or retail consumer wishing to place conventional voice calls and data connections. The electrical power industry has recently commenced transformation of its distribution networks by deploying smart monitoring and control devices throughout their networks. This evolution of the network into a `smart grid' has also motivated the need to deploy wireless technologies that bridge the communication gap between the smart devices and information technology systems. The requirements of these networks differ from traditional wireless networks that communications operators have deployed, which have thus far forced energy companies to consider deploying their own wireless networks. We present our experience in deploying wireless networks to support the smart grid and highlight the key properties of these networks. These characteristics include application awareness, support for large numbers of simultaneous cell connections, high service coverage and prioritized routing of data. We also outline our target blueprint architecture that may be useful to the industry in building wireless and fixed networks to support the smart grid. By observing our experiences, telecommunications operators and equipment manufacturers will be able to augment their current networks and products in a way that accommodates the needs of the emerging industry of smart grids and intelligent electrical networks.

Self-referenced processing, neurodevelopment and joint attention in autism.

PubMed

Mundy, Peter; Gwaltney, Mary; Henderson, Heather

2010-09-01

This article describes a parallel and distributed processing model (PDPM) of joint attention, self-referenced processing and autism. According to this model, autism involves early impairments in the capacity for rapid, integrated processing of self-referenced (proprioceptive and interoceptive) and other-referenced (exteroceptive) information. Measures of joint attention have proven useful in research on autism because they are sensitive to the early development of the 'parallel' and integrated processing of self- and other-referenced stimuli. Moreover, joint attention behaviors are a consequence, but also an organizer of the functional development of a distal distributed cortical system involving anterior networks including the prefrontal and insula cortices, as well as posterior neural networks including the temporal and parietal cortices. Measures of joint attention provide early behavioral indicators of atypical development in this parallel and distributed processing system in autism. In addition it is proposed that an early, chronic disturbance in the capacity for integrating self- and other-referenced information may have cascading effects on the development of self awareness in autism. The assumptions, empirical support and future research implications of this model are discussed.

Effect of hydro mechanical coupling on natural fracture network formation in sedimentary basins

NASA Astrophysics Data System (ADS)

Ouraga, Zady; Guy, Nicolas; Pouya, Amade

2018-05-01

In sedimentary basin context, numerous phenomena, depending on the geological time span, can result in natural fracture network formation. In this paper, fracture network and dynamic fracture spacing triggered by significant sedimentation rate are studied considering mode I fracture propagation using a coupled hydro-mechanical numerical methods. The focus is put on synthetic geological structure under a constant sedimentation rate on its top. This model contains vertical fracture network initially closed and homogeneously distributed. The fractures are modelled with cohesive zone model undergoing damage and the flow is described by Poiseuille's law. The effect of the behaviour of the rock is studied and the analysis leads to a pattern of fracture network and fracture spacing in the geological layer.

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

Kurt Derr; Milos Manic

Location Based Services (LBS), context aware applications, and people and object tracking depend on the ability to locate mobile devices, also known as localization, in the wireless landscape. Localization enables a diverse set of applications that include, but are not limited to, vehicle guidance in an industrial environment, security monitoring, self-guided tours, personalized communications services, resource tracking, mobile commerce services, guiding emergency workers during fire emergencies, habitat monitoring, environmental surveillance, and receiving alerts. This paper presents a new neural network approach (LENSR) based on a competitive topological Counter Propagation Network (CPN) with k-nearest neighborhood vector mapping, for indoor location estimationmore » based on received signal strength. The advantage of this approach is both speed and accuracy. The tested accuracy of the algorithm was 90.6% within 1 meter and 96.4% within 1.5 meters. Several approaches for location estimation using WLAN technology were reviewed for comparison of results.« less

Using electronic health record alerts to provide public health situational awareness to clinicians.

PubMed

Lurio, Joseph; Morrison, Frances P; Pichardo, Michelle; Berg, Rachel; Buck, Michael D; Wu, Winfred; Kitson, Kwame; Mostashari, Farzad; Calman, Neil

2010-01-01

Alerting providers to public health situations requires timeliness and context-relevance, both lacking in current systems. Incorporating decision support tools into electronic health records may provide a way to deploy public health alerts to clinicians at the point of care. A timely process for responding to Health Alert Network messages sent by the New York City Department of Health and Mental Hygiene was developed by a network of community health centers. Alerts with order sets and recommended actions were created to notify primary care providers of local disease outbreaks. The process, effect, and lessons learned from alerts for Legionella, toxogenic E coli, and measles outbreaks are described. Electronic alerts have the potential to improve management of diseases during an outbreak, including appropriate laboratory testing, management guidance, and diagnostic assistance as well as to enhance bi-directional data exchange between clinical and public health organizations.

Using electronic health record alerts to provide public health situational awareness to clinicians

PubMed Central

Lurio, Joseph; Pichardo, Michelle; Berg, Rachel; Buck, Michael D; Wu, Winfred; Kitson, Kwame; Mostashari, Farzad; Calman, Neil

2010-01-01

Alerting providers to public health situations requires timeliness and context-relevance, both lacking in current systems. Incorporating decision support tools into electronic health records may provide a way to deploy public health alerts to clinicians at the point of care. A timely process for responding to Health Alert Network messages sent by the New York City Department of Health and Mental Hygiene was developed by a network of community health centers. Alerts with order sets and recommended actions were created to notify primary care providers of local disease outbreaks. The process, effect, and lessons learned from alerts for Legionella, toxogenic E coli, and measles outbreaks are described. Electronic alerts have the potential to improve management of diseases during an outbreak, including appropriate laboratory testing, management guidance, and diagnostic assistance as well as to enhance bi-directional data exchange between clinical and public health organizations. PMID:20190067

Mapping, Awareness, And Virtualization Network Administrator Training Tool Virtualization Module

DTIC Science & Technology

2016-03-01

AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL VIRTUALIZATION MODULE by Erik W. Berndt March 2016 Thesis Advisor: John Gibson...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MAPPING, AWARENESS, AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL... VIRTUALIZATION MODULE 5. FUNDING NUMBERS 6. AUTHOR(S) Erik W. Berndt 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School

Performance evaluation of time-aware enhanced software defined networking (TeSDN) for elastic data center optical interconnection.

PubMed

Yang, Hui; Zhang, Jie; Zhao, Yongli; Ji, Yuefeng; Li, Hui; Lin, Yi; Li, Gang; Han, Jianrui; Lee, Young; Ma, Teng

2014-07-28

Data center interconnection with elastic optical networks is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. We previously implemented enhanced software defined networking over elastic optical network for data center application [Opt. Express 21, 26990 (2013)]. On the basis of it, this study extends to consider the time-aware data center service scheduling with elastic service time and service bandwidth according to the various time sensitivity requirements. A novel time-aware enhanced software defined networking (TeSDN) architecture for elastic data center optical interconnection has been proposed in this paper, by introducing a time-aware resources scheduling (TaRS) scheme. The TeSDN can accommodate the data center services with required QoS considering the time dimensionality, and enhance cross stratum optimization of application and elastic optical network stratums resources based on spectrum elasticity, application elasticity and time elasticity. The overall feasibility and efficiency of the proposed architecture is experimentally verified on our OpenFlow-based testbed. The performance of TaRS scheme under heavy traffic load scenario is also quantitatively evaluated based on TeSDN architecture in terms of blocking probability and resource occupation rate.

Differences in Connection Strength between Mental Symptoms Might Be Explained by Differences in Variance: Reanalysis of Network Data Did Not Confirm Staging.

PubMed

Terluin, Berend; de Boer, Michiel R; de Vet, Henrica C W

2016-01-01

The network approach to psychopathology conceives mental disorders as sets of symptoms causally impacting on each other. The strengths of the connections between symptoms are key elements in the description of those symptom networks. Typically, the connections are analysed as linear associations (i.e., correlations or regression coefficients). However, there is insufficient awareness of the fact that differences in variance may account for differences in connection strength. Differences in variance frequently occur when subgroups are based on skewed data. An illustrative example is a study published in PLoS One (2013;8(3):e59559) that aimed to test the hypothesis that the development of psychopathology through "staging" was characterized by increasing connection strength between mental states. Three mental states (negative affect, positive affect, and paranoia) were studied in severity subgroups of a general population sample. The connection strength was found to increase with increasing severity in six of nine models. However, the method used (linear mixed modelling) is not suitable for skewed data. We reanalysed the data using inverse Gaussian generalized linear mixed modelling, a method suited for positively skewed data (such as symptoms in the general population). The distribution of positive affect was normal, but the distributions of negative affect and paranoia were heavily skewed. The variance of the skewed variables increased with increasing severity. Reanalysis of the data did not confirm increasing connection strength, except for one of nine models. Reanalysis of the data did not provide convincing evidence in support of staging as characterized by increasing connection strength between mental states. Network researchers should be aware that differences in connection strength between symptoms may be caused by differences in variances, in which case they should not be interpreted as differences in impact of one symptom on another symptom.

Analyzing the Effects of Context-Aware Mobile Design Principles on Student Learning

ERIC Educational Resources Information Center

Seneca, Eric

2014-01-01

The adoption of mobile technology is rapidly transforming how individuals obtain information. Learning occurs when content is accessed in a recursive process of awareness, exploration, reflection and resolution within one's social context. Specifically, the most visible, current definitions of mobile learning provide an overview of the learning…

Visualisation of Interaction Footprints for Engagement in Online Communities

ERIC Educational Resources Information Center

Glahn, Christian; Specht, Marcus; Koper, Rob

2009-01-01

Contextualised and ubiquitous learning are relatively new research areas that combine the latest developments in ubiquitous and context aware computing with educational approaches in order to provide structure to more situated and context aware learning. The majority of recent activities in contextualised and ubiquitous learning focus on mobile…

Augmenting Traditional Books with Context-Aware Learning Supports from Online Learning Communities

ERIC Educational Resources Information Center

Chen, Gwo-Dong; Chao, Po-Yao

2008-01-01

Recent advances in ubiquitous computing technologies have brought reality augmentation of traditional objects to context-aware and social supports. Although a significant proportion of students prefer poring over traditional paper textbooks over electronic books, few studies have enhanced reading practice of traditional books with ubiquitous…

Criteria, Strategies and Research Issues of Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Tsai, Chin-Chung; Yang, Stephen J. H.

2008-01-01

Recent progress in wireless and sensor technologies has lead to a new development of learning environments, called context-aware ubiquitous learning environment, which is able to sense the situation of learners and provide adaptive supports. Many researchers have been investigating the development of such new learning environments; nevertheless,…

Energy-aware virtual network embedding in flexi-grid optical networks

NASA Astrophysics Data System (ADS)

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng; Chen, Bin

2018-01-01

Virtual network embedding (VNE) problem is to map multiple heterogeneous virtual networks (VN) on a shared substrate network, which mitigate the ossification of the substrate network. Meanwhile, energy efficiency has been widely considered in the network design. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the power increment of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low energy consumption. Numerical results show the functionality of the heuristic algorithm in a 24-node network.

Effect of risk perception on epidemic spreading in temporal networks

NASA Astrophysics Data System (ADS)

Moinet, Antoine; Pastor-Satorras, Romualdo; Barrat, Alain

2018-01-01

Many progresses in the understanding of epidemic spreading models have been obtained thanks to numerous modeling efforts and analytical and numerical studies, considering host populations with very different structures and properties, including complex and temporal interaction networks. Moreover, a number of recent studies have started to go beyond the assumption of an absence of coupling between the spread of a disease and the structure of the contacts on which it unfolds. Models including awareness of the spread have been proposed, to mimic possible precautionary measures taken by individuals that decrease their risk of infection, but have mostly considered static networks. Here, we adapt such a framework to the more realistic case of temporal networks of interactions between individuals. We study the resulting model by analytical and numerical means on both simple models of temporal networks and empirical time-resolved contact data. Analytical results show that the epidemic threshold is not affected by the awareness but that the prevalence can be significantly decreased. Numerical studies on synthetic temporal networks highlight, however, the presence of very strong finite-size effects, resulting in a significant shift of the effective epidemic threshold in the presence of risk awareness. For empirical contact networks, the awareness mechanism leads as well to a shift in the effective threshold and to a strong reduction of the epidemic prevalence.

Integrated situational awareness for cyber attack detection, analysis, and mitigation

NASA Astrophysics Data System (ADS)

Cheng, Yi; Sagduyu, Yalin; Deng, Julia; Li, Jason; Liu, Peng

2012-06-01

Real-time cyberspace situational awareness is critical for securing and protecting today's enterprise networks from various cyber threats. When a security incident occurs, network administrators and security analysts need to know what exactly has happened in the network, why it happened, and what actions or countermeasures should be taken to quickly mitigate the potential impacts. In this paper, we propose an integrated cyberspace situational awareness system for efficient cyber attack detection, analysis and mitigation in large-scale enterprise networks. Essentially, a cyberspace common operational picture will be developed, which is a multi-layer graphical model and can efficiently capture and represent the statuses, relationships, and interdependencies of various entities and elements within and among different levels of a network. Once shared among authorized users, this cyberspace common operational picture can provide an integrated view of the logical, physical, and cyber domains, and a unique visualization of disparate data sets to support decision makers. In addition, advanced analyses, such as Bayesian Network analysis, will be explored to address the information uncertainty, dynamic and complex cyber attack detection, and optimal impact mitigation issues. All the developed technologies will be further integrated into an automatic software toolkit to achieve near real-time cyberspace situational awareness and impact mitigation in large-scale computer networks.

Conflict-Aware Scheduling Algorithm

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Borden, Chester

2006-01-01

conflict-aware scheduling algorithm is being developed to help automate the allocation of NASA s Deep Space Network (DSN) antennas and equipment that are used to communicate with interplanetary scientific spacecraft. The current approach for scheduling DSN ground resources seeks to provide an equitable distribution of tracking services among the multiple scientific missions and is very labor intensive. Due to the large (and increasing) number of mission requests for DSN services, combined with technical and geometric constraints, the DSN is highly oversubscribed. To help automate the process, and reduce the DSN and spaceflight project labor effort required for initiating, maintaining, and negotiating schedules, a new scheduling algorithm is being developed. The scheduling algorithm generates a "conflict-aware" schedule, where all requests are scheduled based on a dynamic priority scheme. The conflict-aware scheduling algorithm allocates all requests for DSN tracking services while identifying and maintaining the conflicts to facilitate collaboration and negotiation between spaceflight missions. These contrast with traditional "conflict-free" scheduling algorithms that assign tracks that are not in conflict and mark the remainder as unscheduled. In the case where full schedule automation is desired (based on mission/event priorities, fairness, allocation rules, geometric constraints, and ground system capabilities/ constraints), a conflict-free schedule can easily be created from the conflict-aware schedule by removing lower priority items that are in conflict.

Achieving Optimal Privacy in Trust-Aware Social Recommender Systems

NASA Astrophysics Data System (ADS)

Dokoohaki, Nima; Kaleli, Cihan; Polat, Huseyin; Matskin, Mihhail

Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers proposed for utilization of interpersonal trust between users, to alleviate many of these crucial shortcomings. Till now, attention has been mainly paid to strong points about trust-aware recommenders such as alleviating profile sparsity or calculation cost efficiency, while least attention has been paid on investigating the notion of privacy surrounding the disclosure of individual ratings and most importantly protection of trust computation across social networks forming the backbone of these systems. To contribute to addressing problem of privacy in trust-aware recommenders, within this paper, first we introduce a framework for enabling privacy-preserving trust-aware recommendation generation. While trust mechanism aims at elevating recommender's accuracy, to preserve privacy, accuracy of the system needs to be decreased. Since within this context, privacy and accuracy are conflicting goals we show that a Pareto set can be found as an optimal setting for both privacy-preserving and trust-enabling mechanisms. We show that this Pareto set, when used as the configuration for measuring the accuracy of base collaborative filtering engine, yields an optimized tradeoff between conflicting goals of privacy and accuracy. We prove this concept along with applicability of our framework by experimenting with accuracy and privacy factors, and we show through experiment how such optimal set can be inferred.

Brain Connectivity in Pathological and Pharmacological Coma

PubMed Central

Noirhomme, Quentin; Soddu, Andrea; Lehembre, Rémy; Vanhaudenhuyse, Audrey; Boveroux, Pierre; Boly, Mélanie; Laureys, Steven

2010-01-01

Recent studies in patients with disorders of consciousness (DOC) tend to support the view that awareness is not related to activity in a single brain region but to thalamo-cortical connectivity in the frontoparietal network. Functional neuroimaging studies have shown preserved albeit disconnected low-level cortical activation in response to external stimulation in patients in a “vegetative state” or unresponsive wakefulness syndrome. While activation of these “primary” sensory cortices does not necessarily reflect conscious awareness, activation in higher-order associative cortices in minimally conscious state patients seems to herald some residual perceptual awareness. PET studies have identified a metabolic dysfunction in a widespread frontoparietal “global neuronal workspace” in DOC patients including the midline default mode network (“intrinsic” system) and the lateral frontoparietal cortices or “extrinsic system.” Recent studies have investigated the relation of awareness to the functional connectivity within intrinsic and extrinsic networks, and with the thalami in both pathological and pharmacological coma. In brain damaged patients, connectivity in all default network areas was found to be non-linearly correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative, coma, and brain dead patients. Anesthesia-induced loss of consciousness was also shown to correlate with a global decrease in cortico-cortical and thalamo-cortical connectivity in both intrinsic and extrinsic networks, but not in auditory, or visual networks. In anesthesia, unconsciousness was also associated with a loss of cross-modal interactions between networks. These results suggest that conscious awareness critically depends on the functional integrity of thalamo-cortical and cortico-cortical frontoparietal connectivity within and between “intrinsic” and “extrinsic” brain networks. PMID:21191476

Basketball Teams as Strategic Networks

PubMed Central

Fewell, Jennifer H.; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S.

2012-01-01

We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness. PMID:23139744

Basketball teams as strategic networks.

PubMed

Fewell, Jennifer H; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S

2012-01-01

We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as "uphill/downhill" flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.

Hidden Connectivity in Networks with Vulnerable Classes of Nodes

NASA Astrophysics Data System (ADS)

Krause, Sebastian M.; Danziger, Michael M.; Zlatić, Vinko

2016-10-01

In many complex systems representable as networks, nodes can be separated into different classes. Often these classes can be linked to a mutually shared vulnerability. Shared vulnerabilities may be due to a shared eavesdropper or correlated failures. In this paper, we show the impact of shared vulnerabilities on robust connectivity and how the heterogeneity of node classes can be exploited to maintain functionality by utilizing multiple paths. Percolation is the field of statistical physics that is generally used to analyze connectivity in complex networks, but in its existing forms, it cannot treat the heterogeneity of multiple vulnerable classes. To analyze the connectivity under these constraints, we describe each class as a color and develop a "color-avoiding" percolation. We present an analytic theory for random networks and a numerical algorithm for all networks, with which we can determine which nodes are color-avoiding connected and whether the maximal set percolates in the system. We find that the interaction of topology and color distribution implies a rich critical behavior, with critical values and critical exponents depending both on the topology and on the color distribution. Applying our physics-based theory to the Internet, we show how color-avoiding percolation can be used as the basis for new topologically aware secure communication protocols. Beyond applications to cybersecurity, our framework reveals a new layer of hidden structure in a wide range of natural and technological systems.

The Virtual Learning Commons: Supporting the Fuzzy Front End of Scientific Research with Emerging Technologies

NASA Astrophysics Data System (ADS)

Pennington, D. D.; Gandara, A.; Gris, I.

2012-12-01

The Virtual Learning Commons (VLC), funded by the National Science Foundation Office of Cyberinfrastructure CI-Team Program, is a combination of Semantic Web, mash up, and social networking tools that supports knowledge sharing and innovation across scientific disciplines in research and education communities and networks. The explosion of scientific resources (data, models, algorithms, tools, and cyberinfrastructure) challenges the ability of researchers to be aware of resources that might benefit them. Even when aware, it can be difficult to understand enough about those resources to become potential adopters or re-users. Often scientific data and emerging technologies have little documentation, especially about the context of their use. The VLC tackles this challenge by providing mechanisms for individuals and groups of researchers to organize Web resources into virtual collections, and engage each other around those collections in order to a) learn about potentially relevant resources that are available; b) design research that leverages those resources; and c) develop initial work plans. The VLC aims to support the "fuzzy front end" of innovation, where novel ideas emerge and there is the greatest potential for impact on research design. It is during the fuzzy front end that conceptual collisions across disciplines and exposure to diverse perspectives provide opportunity for creative thinking that can lead to inventive outcomes. The VLC integrates Semantic Web functionality for structuring distributed information, mash up functionality for retrieving and displaying information, and social media for discussing/rating information. We are working to provide three views of information that support researchers in different ways: 1. Innovation Marketplace: supports users as they try to understand what research is being conducted, who is conducting it, where they are located, and who they collaborate with; 2. Conceptual Mapper: supports users as they organize their thinking about their own and related research; 3. Workflow Designer: supports users as they generate task-level analytical designs and consider data/methods/tools that could be relevant. This presentation will discuss the innovation theories that have informed design of the VLC, hypotheses about the use of emerging technologies to support the process of innovation, and will include a brief demonstration of these capabilities.

QoS-aware integrated fiber-wireless standard compliant architecture based on XGPON and EDCA

NASA Astrophysics Data System (ADS)

Kaur, Ravneet; Srivastava, Anand

2018-01-01

Converged Fiber-Wireless (FiWi) broadband access network proves to be a promising candidate that is reliable, robust, cost efficient, ubiquitous and capable of providing huge amount of bandwidth. To meet the ever-increasing bandwidth requirements, it has become very crucial to investigate the performance issues that arise with the deployment of next-generation Passive Optical Network (PON) and its integration with various wireless technologies. Apart from providing high speed internet access for mass use, this combined architecture aims to enable delivery of high quality and effective e-services in different categories including health, education, finance, banking, agriculture and e-government. In this work, we present an integrated architecture of 10-Gigabit-capable PON (XG-PON) and Enhanced Distributed Channel Access (EDCA) that combines the benefits of both technologies to meet the QoS demands of subscribers. Performance evaluation of the standards-compliant hybrid network is done using discrete-event Network Simulator-3 (NS-3) and results are reported in terms of throughput, average delay, average packet loss rate and fairness index. Per-class throughput signifies effectiveness of QoS distribution whereas aggregate throughput indicates effective utilization of wireless channel. This work has not been reported so far to the best of our knowledge.

Using Network Dynamical Influence to Drive Consensus

NASA Astrophysics Data System (ADS)

Punzo, Giuliano; Young, George F.; MacDonald, Malcolm; Leonard, Naomi E.

2016-05-01

Consensus and decision-making are often analysed in the context of networks, with many studies focusing attention on ranking the nodes of a network depending on their relative importance to information routing. Dynamical influence ranks the nodes with respect to their ability to influence the evolution of the associated network dynamical system. In this study it is shown that dynamical influence not only ranks the nodes, but also provides a naturally optimised distribution of effort to steer a network from one state to another. An example is provided where the “steering” refers to the physical change in velocity of self-propelled agents interacting through a network. Distinct from other works on this subject, this study looks at directed and hence more general graphs. The findings are presented with a theoretical angle, without targeting particular applications or networked systems; however, the framework and results offer parallels with biological flocks and swarms and opportunities for design of technological networks.

An appraisal of students' awareness of "self-reflection" in a first-year pathology course of undergraduate medical/dental education.

PubMed

Kanthan, Rani; Senger, Jenna-Lynn B

2011-09-23

Self-reflection and reflective practice are increasingly considered as essential attributes of competent professionals functioning in complex and ever-changing healthcare systems of the 21st century. The aim of this study was to determine the extent of students' awareness and understanding of the reflective process and the meaning of 'self-reflection' within the contextual framework of their learning environment in the first-year of their medical/dental education. We endorse that the introduction of such explicit educational tasks at this early stage enhances and promotes students' awareness, understanding, and proficiency of this skill in their continuing life-long health professional learning. Over two years, students registered in first-year pathology at the University of Saskatchewan were introduced to a self-reflection assignment which comprised in the submission of a one-page reflective document to a template of reflective questions provided in the given context of their learning environment. This was a mandatory but ungraded component at the midterm and final examinations. These documents were individually analyzed and thematically categorized to a "5 levels-of-reflection-awareness" scale using a specially-designed rubric based on the accepted major theories of reflection that included students' identification of: 1) personal abilities, 2) personal learning styles 3) relationships between course material and student history 4) emotional responses and 5) future applications. 410 self-reflection documents were analyzed. The student self-awareness on personal learning style (72.7% level 3+) and course content (55.2% level 3+) were well-reflected. Reflections at a level 1 awareness included identification of a) specific teaching strategies utilized to enhance learning (58.4%), b) personal strengths/weaknesses (53%), and c) emotional responses, values, and beliefs (71.5%). Students' abilities to connect information to life experiences and to future events with understanding were more evenly distributed across all 5 levels of reflection-awareness. Exposure to self-reflection assignments in the early years of undergraduate medical education increases student awareness and promotes the creation of personal meaning of one's reactions, values, and premises in the context of student learning environments. Early introduction with repetition to such cognitive processes as practice tools increases engagement in reflection that may facilitate proficiency in mastering this competency leading to the creation of future reflective health professionals.

An appraisal of students' awareness of "self-reflection" in a first-year pathology course of undergraduate medical/dental education

PubMed Central

2011-01-01

Background Self-reflection and reflective practice are increasingly considered as essential attributes of competent professionals functioning in complex and ever-changing healthcare systems of the 21st century. The aim of this study was to determine the extent of students' awareness and understanding of the reflective process and the meaning of 'self-reflection' within the contextual framework of their learning environment in the first-year of their medical/dental education. We endorse that the introduction of such explicit educational tasks at this early stage enhances and promotes students' awareness, understanding, and proficiency of this skill in their continuing life-long health professional learning. Methods Over two years, students registered in first-year pathology at the University of Saskatchewan were introduced to a self-reflection assignment which comprised in the submission of a one-page reflective document to a template of reflective questions provided in the given context of their learning environment. This was a mandatory but ungraded component at the midterm and final examinations. These documents were individually analyzed and thematically categorized to a "5 levels-of-reflection-awareness" scale using a specially-designed rubric based on the accepted major theories of reflection that included students' identification of: 1) personal abilities, 2) personal learning styles 3) relationships between course material and student history 4) emotional responses and 5) future applications. Results 410 self-reflection documents were analyzed. The student self-awareness on personal learning style (72.7% level 3+) and course content (55.2% level 3+) were well-reflected. Reflections at a level 1 awareness included identification of a) specific teaching strategies utilized to enhance learning (58.4%), b) personal strengths/weaknesses (53%), and c) emotional responses, values, and beliefs (71.5%). Students' abilities to connect information to life experiences and to future events with understanding were more evenly distributed across all 5 levels of reflection-awareness. Conclusions Exposure to self-reflection assignments in the early years of undergraduate medical education increases student awareness and promotes the creation of personal meaning of one's reactions, values, and premises in the context of student learning environments. Early introduction with repetition to such cognitive processes as practice tools increases engagement in reflection that may facilitate proficiency in mastering this competency leading to the creation of future reflective health professionals. PMID:21943239

Situational awareness, relational coordination and integrated care delivery to hospitalized elderly in The Netherlands: a comparison between hospitals

PubMed Central

2014-01-01

Background It is known that interprofessional collaboration is crucial for integrated care delivery, yet we are still unclear about the underlying mechanisms explaining effectiveness of integrated care delivery to older patients. In addition, we lack research comparing integrated care delivery between hospitals. Therefore, this study aims to (i) provide insight into the underlying components ‘relational coordination’ and ‘situational awareness’ of integrated care delivery and the role of team and organizational context in integrated care delivery; and (ii) compare situational awareness, relational coordination, and integrated care delivery of different hospitals in the Netherlands. Methods This cross-sectional study took place in 2012 among professionals from three different hospitals involved in the delivery of care to older patients. A total of 215 professionals filled in the questionnaire (42% response rate).Descriptive statistics and paired-sample t-tests were used to investigate the level of situational awareness, relational coordination, and integrated care delivery in the three different hospitals. Correlation and multilevel analyses were used to investigate the relationship between background characteristics, team context, organizational context, situational awareness, relational coordination and integrated care delivery. Results No differences in background characteristics, team context, organizational context, situational awareness, relational coordination and integrated care delivery were found among the three hospitals. Correlational analysis revealed that situational awareness (r = 0.30; p < 0.01), relational coordination (r = 0.17; p < 0.05), team climate (r = 0.29; p < 0.01), formal internal communication (r = 0.46; p < 0.01), and informal internal communication (r = 0.36; p < 0.01) were positively associated with integrated care delivery. Stepwise multilevel analyses showed that formal internal communication (p < 0.001) and situational awareness (p < 0.01) were associated with integrated care delivery. Team climate was not significantly associated with integrated care delivery when situational awareness and relational coordination were included in the equation. Thus situational awareness acted as mediator between team climate and integrated care delivery among professionals delivering care to older hospitalized patients. Conclusions The results of this study show the importance of formal internal communication and situational awareness for quality of care delivery to hospitalized older patients. PMID:24410889

75 FR 78722 - Intent To Prepare Programmatic Environmental Assessment Statement for the Nationwide...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-16

... sensor network and provide extended sensor network and components to fill critical situational awareness... different agencies), and share resources. The IOCs will improve tactical decision-making, situational awareness, operations monitoring/ interoperability, rules-based processing, and joint planning in a...

A Context-Aware Solution in Mobile Language Learning

ERIC Educational Resources Information Center

Fatahipour, Majid; Ghaseminajm, Mahnaz

2014-01-01

Despite obvious benefits, some challenges exist in the way of sustainable utilization of mobile phone technology for language learning tasks. This paper shows how these challenges can be better addressed in the light of recent advancements in mobile phone technology, like context aware mobile learning, informed with a sound pedagogical basis for…

A Context Awareness System for Online Learning: Design Based Research

ERIC Educational Resources Information Center

Laffey, James; Amelung, Chris; Goggins, Sean

2009-01-01

A design based research strategy examining the impressions and behavior of members of courses taught entirely online is used for refining a context-aware activity notification system (CANS). The findings show that CANS must address substantial variety in courses and members while also fitting with multitasking between online and real world…

The impact of multiple information on coupled awareness-epidemic dynamics in multiplex networks

NASA Astrophysics Data System (ADS)

Pan, Yaohui; Yan, Zhijun

2018-02-01

Growing interest has emerged in the study of the interplay between awareness and epidemics in multiplex networks. However, previous studies on this issue usually assume that all aware individuals take the same level of precautions, ignoring individual heterogeneity. In this paper, we investigate the coupled awareness-epidemic dynamics in multiplex networks considering individual heterogeneity. Here, the precaution levels are heterogeneous and depend on three types of information: contact information and local and global prevalence information. The results show that contact-based precautions can decrease the epidemic prevalence and augment the epidemic threshold, but prevalence-based precautions, regardless of local or global information, can only decrease the epidemic prevalence. Moreover, unlike previous studies in single-layer networks, we do not find a greater impact of local prevalence information on the epidemic prevalence compared to global prevalence information. In addition, we find that the altruistic behaviors of infected individuals can effectively suppress epidemic spreading, especially when the level of contact-based precaution is high.

a Context-Aware Tourism Recommender System Based on a Spreading Activation Method

NASA Astrophysics Data System (ADS)

Bahramian, Z.; Abbaspour, R. Ali; Claramunt, C.

2017-09-01

Users planning a trip to a given destination often search for the most appropriate points of interest location, this being a non-straightforward task as the range of information available is very large and not very well structured. The research presented by this paper introduces a context-aware tourism recommender system that overcomes the information overload problem by providing personalized recommendations based on the user's preferences. It also incorporates contextual information to improve the recommendation process. As previous context-aware tourism recommender systems suffer from a lack of formal definition to represent contextual information and user's preferences, the proposed system is enhanced using an ontology approach. We also apply a spreading activation technique to contextualize user preferences and learn the user profile dynamically according to the user's feedback. The proposed method assigns more effect in the spreading process for nodes which their preference values are assigned directly by the user. The results show the overall performance of the proposed context-aware tourism recommender systems by an experimental application to the city of Tehran.

Asymmetries in commitment in an avian communication network.

PubMed

Randler, Christoph; Vollmer, Christian

2013-02-01

Mobbing of predators occurs within a conspecific and heterospecific context but has not been quantified within the framework of a communication network and analysed with respect to heterospecific reciprocity. Here, we used playbacks of mobbing calls to show that mobbing is unequally distributed within a community of deciduous forest birds. Five species (great tit Parus major, blue tit Cyanistes caeruleus, marsh tit Poecile palustris, nuthatch Sitta europaea and chaffinch Fringilla coelebs) responded to each other's playbacks of mobbing calls. Commitment to mob was measured by minimum distance, response latency and uttering of calls. Commitment was higher when conspecific calls were broadcast. Yet, responses to heterospecific calls were significantly different between the five species. Chaffinches had the lowest commitment, and blue tits tended to have the highest. The communication network is asymmetric. Some species invest more than they receive from other species. As mobbing might incur costs, these are unequally distributed across the community.

Quantification and Segmentation of Brain Tissues from MR Images: A Probabilistic Neural Network Approach

PubMed Central

Wang, Yue; Adalý, Tülay; Kung, Sun-Yuan; Szabo, Zsolt

2007-01-01

This paper presents a probabilistic neural network based technique for unsupervised quantification and segmentation of brain tissues from magnetic resonance images. It is shown that this problem can be solved by distribution learning and relaxation labeling, resulting in an efficient method that may be particularly useful in quantifying and segmenting abnormal brain tissues where the number of tissue types is unknown and the distributions of tissue types heavily overlap. The new technique uses suitable statistical models for both the pixel and context images and formulates the problem in terms of model-histogram fitting and global consistency labeling. The quantification is achieved by probabilistic self-organizing mixtures and the segmentation by a probabilistic constraint relaxation network. The experimental results show the efficient and robust performance of the new algorithm and that it outperforms the conventional classification based approaches. PMID:18172510

Data-driven modeling of solar-powered urban microgrids

PubMed Central

Halu, Arda; Scala, Antonio; Khiyami, Abdulaziz; González, Marta C.

2016-01-01

Distributed generation takes center stage in today’s rapidly changing energy landscape. Particularly, locally matching demand and generation in the form of microgrids is becoming a promising alternative to the central distribution paradigm. Infrastructure networks have long been a major focus of complex networks research with their spatial considerations. We present a systemic study of solar-powered microgrids in the urban context, obeying real hourly consumption patterns and spatial constraints of the city. We propose a microgrid model and study its citywide implementation, identifying the self-sufficiency and temporal properties of microgrids. Using a simple optimization scheme, we find microgrid configurations that result in increased resilience under cost constraints. We characterize load-related failures solving power flows in the networks, and we show the robustness behavior of urban microgrids with respect to optimization using percolation methods. Our findings hint at the existence of an optimal balance between cost and robustness in urban microgrids. PMID:26824071

Asymmetries in commitment in an avian communication network

NASA Astrophysics Data System (ADS)

Randler, Christoph; Vollmer, Christian

2013-02-01

Mobbing of predators occurs within a conspecific and heterospecific context but has not been quantified within the framework of a communication network and analysed with respect to heterospecific reciprocity. Here, we used playbacks of mobbing calls to show that mobbing is unequally distributed within a community of deciduous forest birds. Five species (great tit Parus major, blue tit Cyanistes caeruleus, marsh tit Poecile palustris, nuthatch Sitta europaea and chaffinch Fringilla coelebs) responded to each other's playbacks of mobbing calls. Commitment to mob was measured by minimum distance, response latency and uttering of calls. Commitment was higher when conspecific calls were broadcast. Yet, responses to heterospecific calls were significantly different between the five species. Chaffinches had the lowest commitment, and blue tits tended to have the highest. The communication network is asymmetric. Some species invest more than they receive from other species. As mobbing might incur costs, these are unequally distributed across the community.

Data-driven modeling of solar-powered urban microgrids.

PubMed

Halu, Arda; Scala, Antonio; Khiyami, Abdulaziz; González, Marta C

2016-01-01

Distributed generation takes center stage in today's rapidly changing energy landscape. Particularly, locally matching demand and generation in the form of microgrids is becoming a promising alternative to the central distribution paradigm. Infrastructure networks have long been a major focus of complex networks research with their spatial considerations. We present a systemic study of solar-powered microgrids in the urban context, obeying real hourly consumption patterns and spatial constraints of the city. We propose a microgrid model and study its citywide implementation, identifying the self-sufficiency and temporal properties of microgrids. Using a simple optimization scheme, we find microgrid configurations that result in increased resilience under cost constraints. We characterize load-related failures solving power flows in the networks, and we show the robustness behavior of urban microgrids with respect to optimization using percolation methods. Our findings hint at the existence of an optimal balance between cost and robustness in urban microgrids.

Connectivist Learning Objects and Learning Styles

ERIC Educational Resources Information Center

del Moral, M. Esther; Cernea, Ana; Villalustre, Lourdes

2013-01-01

The Web 2.0 brought in the use of social tools at a large scale in every area: a transformation which led to redefining the teaching-learning process. In this new context knowledge is distributed over network connections in an uncontrolled way - thus learning consists of recognizing relevant information patterns and constructing new connections.…

Japan InK: Distributing the Information Networked Knowledge (InK) Base to the Japanese Research Community.

ERIC Educational Resources Information Center

Naito, Eisuke

This paper discusses knowledge management (KM) in relation to a shared cataloging system in Japanese university libraries. The first section describes the Japanese scene related to knowledge management and the working environment, including the SECI (Socialization, Externalization, Combination, Internalization) model, the context of knowledge, and…

Integration science and distributed networks

NASA Astrophysics Data System (ADS)

Landauer, Christopher; Bellman, Kirstie L.

2002-07-01

Our work on integration of data and knowledge sources is based in a common theoretical treatment of 'Integration Science', which leads to systematic processes for combining formal logical and mathematical systems, computational and physical systems, and human systems and organizations. The theory is based on the processing of explicit meta-knowledge about the roles played by the different knowledge sources and the methods of analysis and semantic implications of the different data values, together with information about the context in which and the purpose for which they are being combined. The research treatment is primarily mathematical, and though this kind of integration mathematics is still under development, there are some applicable common threads that have emerged already. Instead of describing the current state of the mathematical investigations, since they are not yet crystallized enough for formalisms, we describe our applications of the approach in several different areas, including our focus area of 'Constructed Complex Systems', which are complex heterogeneous systems managed or mediated by computing systems. In this context, it is important to remember that all systems are embedded, all systems are autonomous, and that all systems are distributed networks.

Assessing user engagement in a health promotion website using social networking.

PubMed

Tague, Rhys; Maeder, Anthony J; Vandelanotte, Corneel; Kolt, Gregory S; Caperchione, Cristina M; Rosenkranz, Richard R; Savage, Trevor N; Van Itallie, Anetta

2014-01-01

Remote provision of supportive mechanisms for preventive health is a fast-growing area in eHealth. Web-based interventions have been suggested as an effective way to increase adoption and maintenance of healthy lifestyle behaviours. This paper describes results obtained in the "Walk 2.0" trial to promote physical activity through a self-managed walking programme, using a social networking website that provided an online collaborative environment. Engagement of participants with the website was assessed by monitoring usage of the individual social networking functions (e.g. status post). The results demonstrate that users generally preferred contributing non-interactive public posts of information concerned with their individual physical activity levels, and more occasionally communicating privately to friends. Further analysis of topics within posts was done by classifying word usage frequencies. Results indicated that the dominant topics are well aligned with the social environment within which physical activity takes place. Topics centred around four main areas: description of the activity, timing of the activity, affective response to the activity, and context within which the activity occurs. These findings suggest that strong levels of user awareness and communication occur in the social networking setting, indicative of beneficial self-image and self-actualisation effects.

Complex networks in confined comminution

NASA Astrophysics Data System (ADS)

Walker, David M.; Tordesillas, Antoinette; Einav, Itai; Small, Michael

2011-08-01

The physical process of confined comminution is investigated within the framework of complex networks. We first characterize the topology of the unweighted contact networks as generated by the confined comminution process. We find this process gives rise to an ultimate contact network which exhibits a scale-free degree distribution and small world properties. In particular, if viewed in the context of networks through which information travels along shortest paths, we find that the global average of the node vulnerability decreases as the comminution process continues, with individual node vulnerability correlating with grain size. A possible application to the design of synthetic networks (e.g., sensor networks) is highlighted. Next we turn our attention to the physics of the granular comminution process and examine force transmission with respect to the weighted contact networks, where each link is weighted by the inverse magnitude of the normal force acting at the associated contact. We find that the strong forces (i.e., force chains) are transmitted along pathways in the network which are mainly following shortest-path routing protocols, as typically found, for example, in communication systems. Motivated by our earlier studies of the building blocks for self-organization in dense granular systems, we also explore the properties of the minimal contact cycles. The distribution of the contact strain energy intensity of 4-cycle motifs in the ultimate state of the confined comminution process is shown to be consistent with a scale-free distribution with infinite variance, thereby suggesting that 4-cycle arrangements of grains are capable of storing vast amounts of energy in their contacts without breaking.

Game-based versus storyboard-based evaluations of crew support prototypes for long duration missions

NASA Astrophysics Data System (ADS)

Smets, N. J. J. M.; Abbing, M. S.; Neerincx, M. A.; Lindenberg, J.; van Oostendorp, H.

2010-03-01

The Mission Execution Crew Assistant (MECA) is developing a distributed system of electronic partners (ePartners) to support astronauts performing nominal and off- nominal actions in long duration missions. The ePartners' support should adequately deal with the dynamics of the context, operations, team and personal conditions, which will change over time substantially. Such support—with the concerning context effects—should be thoroughly tested in all stages of the development process. A major question is how to address the context effects of in-space operations for evaluations of crew support prototypes. Via game-technology, the prototype can be tested with astronauts or their representatives, immersed in the envisioned, simulated context. We investigated if a game-based evaluation better addresses the context effects by producing a more elaborate, in-depth and realistic user experience than a "classical" storyboard-based evaluation. In the game-based evaluation, the participants showed higher arousal levels where expected, a more intense feeling of spatial presence, better situation awareness, and faster performance where needed. Such an evaluation can be used as an alternative or complement of field or micro-world tests when context dynamics cannot be simulated in these last tests cost-efficiently.

Advanced Weather Awareness and Reporting Enhancements

NASA Technical Reports Server (NTRS)

Busquets, Anthony M. (Technical Monitor); Ruokangas, Corinne Clinton; Kelly, Wallace E., III

2005-01-01

AWARE (Aviation Weather Awareness and Reporting Enhancements) was a NASA Cooperative Research and Development program conducted jointly by Rockwell Scientific, Rockwell Collins, and NASA. The effort culminated in an enhanced weather briefing and reporting tool prototype designed to integrate graphical and text-based aviation weather data to provide clear situational awareness in the context of a specific pilot, flight and equipment profile. The initial implementation of AWARE was as a web-based preflight planning tool, specifically for general aviation pilots, who do not have access to support such as the dispatchers available for commercial airlines. Initial usability tests showed that for VFR (Visual Flight Rules) pilots, AWARE provided faster and more effective weather evaluation. In a subsequent formal usability test for IFR (Instrument Flight Rules) pilots, all users finished the AWARE tests faster than the parallel DUAT tests, and all subjects graded AWARE higher for effectiveness, efficiency, and usability. The decision analysis basis of AWARE differentiates it from other aviation safety programs, providing analysis of context-sensitive data in a personalized graphical format to aid pilots/dispatchers in their complex flight requirements.

Percolation and Reinforcement on Complex Networks

NASA Astrophysics Data System (ADS)

Yuan, Xin

Complex networks appear in almost every aspect of our daily life and are widely studied in the fields of physics, mathematics, finance, biology and computer science. This work utilizes percolation theory in statistical physics to explore the percolation properties of complex networks and develops a reinforcement scheme on improving network resilience. This dissertation covers two major parts of my Ph.D. research on complex networks: i) probe--in the context of both traditional percolation and k-core percolation--the resilience of complex networks with tunable degree distributions or directed dependency links under random, localized or targeted attacks; ii) develop and propose a reinforcement scheme to eradicate catastrophic collapses that occur very often in interdependent networks. We first use generating function and probabilistic methods to obtain analytical solutions to percolation properties of interest, such as the giant component size and the critical occupation probability. We study uncorrelated random networks with Poisson, bi-Poisson, power-law, and Kronecker-delta degree distributions and construct those networks which are based on the configuration model. The computer simulation results show remarkable agreement with theoretical predictions. We discover an increase of network robustness as the degree distribution broadens and a decrease of network robustness as directed dependency links come into play under random attacks. We also find that targeted attacks exert the biggest damage to the structure of both single and interdependent networks in k-core percolation. To strengthen the resilience of interdependent networks, we develop and propose a reinforcement strategy and obtain the critical amount of reinforced nodes analytically for interdependent Erdḧs-Renyi networks and numerically for scale-free and for random regular networks. Our mechanism leads to improvement of network stability of the West U.S. power grid. This dissertation provides us with a deeper understanding of the effects of structural features on network stability and fresher insights into designing resilient interdependent infrastructure networks.

Recruitment and retention of blood donors in four Canadian cities: an analysis of the role of community and social networks.

PubMed

Smith, André; Matthews, Ralph; Fiddler, Jay

2013-12-01

This study approaches the decision to donate blood as a dynamic process involving interplay between blood donors' personal motives, donors' social contexts, and the donor recruitment and retention activities of blood collection agencies. Data were gathered from four blood donation clinics using in-depth interviews with Canadian Blood Services employees, donors, and nondonors in 25 organizations participating in Life Link, a donor recruitment program that supports organizations to educate employees about the benefits of blood donation. Further data were obtained from ethnographic observations of blood collection and donor recruitment activities. Thematic analysis resulted in three umbrella themes: leveraging social networks, embedding the clinic in the community, and donating blood and social reciprocity. Donor recruitment activities at all four clinics enhanced awareness of blood donation in the workplace by using experienced donors to motivate their coworkers in making a first-time donation. Clinic employees reported varying success in improving awareness of blood donation in the broader community, in part because of varying employee engagement in community-wide activities and celebrations. Altruistic motives were mentioned by experienced donors, who also identified a desire to reciprocate to their community as another strong motive. This study contextualizes donor recruitment and retention as involving activities that tie blood donation to meaningful aspects of donors' social networks and community. The findings point to the need for further analyses of the institutional dimensions of blood donation to develop effective strategies beyond appeals to altruism. © 2013 American Association of Blood Banks.

Common Capabilities for Trust and Security in Service Oriented Infrastructures

NASA Astrophysics Data System (ADS)

Brossard, David; Colombo, Maurizio

In order to achieve agility of the enterprise and shorter concept-to-market timescales for new services, IT and communication providers and their customers increasingly use technologies and concepts which come together under the banner of the Service Oriented Infrastructure (SOI) approach. In this paper we focus on the challenges relating to SOI security. The solutions presented cover the following areas: i) identity federation, ii) distributed usage & access management, and iii) context-aware secure messaging, routing & transformation. We use a scenario from the collaborative engineering space to illustrate the challenges and the solutions.

Rapid and highly resolving associative affective learning: convergent electro- and magnetoencephalographic evidence from vision and audition.

PubMed

Steinberg, Christian; Bröckelmann, Ann-Kathrin; Rehbein, Maimu; Dobel, Christian; Junghöfer, Markus

2013-03-01

Various pathway models for emotional processing suggest early prefrontal contributions to affective stimulus evaluation. Yet, electrophysiological evidence for such rapid modulations is still sparse. In a series of four MEG/EEG studies which investigated associative learning in vision and audition using a novel MultiCS Conditioning paradigm, many different neutral stimuli (faces, tones) were paired with aversive and appetitive events in only two to three learning instances. Electrophysiological correlates of neural activity revealed highly significant amplified processing for conditioned stimuli within distributed prefrontal and sensory cortical networks. In both, vision and audition, affect-specific responses occurred in two successive waves of rapid (vision: 50-80 ms, audition: 25-65 ms) and mid-latency (vision: >130 ms, audition: >100 ms) processing. Interestingly, behavioral measures indicated that MultiCS Conditioning successfully prevented contingency awareness. We conclude that affective processing rapidly recruits highly elaborate and widely distributed networks with substantial capacity for fast learning and excellent resolving power. Copyright © 2012 Elsevier B.V. All rights reserved.

The new alchemy: Online networking, data sharing and research activity distribution tools for scientists

PubMed Central

Williams, Antony J.; Peck, Lou; Ekins, Sean

2017-01-01

There is an abundance of free online tools accessible to scientists and others that can be used for online networking, data sharing and measuring research impact. Despite this, few scientists know how these tools can be used or fail to take advantage of using them as an integrated pipeline to raise awareness of their research outputs. In this article, the authors describe their experiences with these tools and how they can make best use of them to make their scientific research generally more accessible, extending its reach beyond their own direct networks, and communicating their ideas to new audiences. These efforts have the potential to drive science by sparking new collaborations and interdisciplinary research projects that may lead to future publications, funding and commercial opportunities. The intent of this article is to: describe some of these freely accessible networking tools and affiliated products; demonstrate from our own experiences how they can be utilized effectively; and, inspire their adoption by new users for the benefit of science. PMID:28928951

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models. [Sparse, Distributed Memory

NASA Technical Reports Server (NTRS)

Keeler, James D.

1988-01-01

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

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.

Awareness of pre-exposure prophylaxis (PrEP) among women who inject drugs in NYC: the importance of networks and syringe exchange programs for HIV prevention.

PubMed

Walters, Suzan M; Reilly, Kathleen H; Neaigus, Alan; Braunstein, Sarah

2017-06-29

Women who inject drugs (WWID) are at heightened risk for HIV due to biological, behavioral, and structural factors. Pre-exposure prophylaxis (PrEP) could aid in HIV prevention for WWID. However, little is known about WWID awareness of PrEP, which is a necessary step that must occur before PrEP uptake. We report factors associated with greater awareness among WWID to identify efficient means of awareness dissemination. Data from the 2015 National HIV Behavioral Surveillance (NHBS) system cycle on injection drug use collected in New York City (NYC) were used. Bivariable analyses, using chi-squared statistics, were conducted to examine correlates of awareness of PrEP with socio-demographic, behavioral, and health care variables. Multivariable logistic regression was used to estimate adjusted associations and determine differences in awareness of PrEP. The analysis consisted of 118 WWID. Awareness of PrEP was relatively low (31%), and risk factors were high. In the last 12 months, almost two thirds (65%) reported condomless sex, approximately one third (31%) reported transactional sex, and one third (32%) reported sharing injection equipment. In multivariable logistic regression, increased PrEP awareness was associated with reported transactional sex (AOR 3.32, 95% CI 1.22-9.00) and having a conversation about HIV prevention at a syringe exchange program (SEP) (AOR 7.61, 95% CI 2.65-21.84). We did not find race, education, household income, age, binge drinking, or sexual identity to be significantly associated with PrEP awareness. Large proportions of WWID were unaware of PrEP. These findings suggest that social networks (specifically sex work and SEP networks) are an efficient means for disseminating messaging about prevention materials such as PrEP. We recommend that SEP access increase, SEP processes be adopted in other health care settings, and WWID networks be utilized to increase PrEP awareness.

The Ability of Atmospheric Data to Reduce Disagreements in Wetland Methane Flux Estimates over North America

NASA Astrophysics Data System (ADS)

Miller, S. M.; Andrews, A. E.; Benmergui, J. S.; Commane, R.; Dlugokencky, E. J.; Janssens-Maenhout, G.; Melton, J. R.; Michalak, A. M.; Sweeney, C.; Worthy, D. E. J.

2015-12-01

Existing estimates of methane fluxes from wetlands differ in both magnitude and distribution across North America. We discuss seven different bottom-up methane estimates in the context of atmospheric methane data collected across the US and Canada. In the first component of this study, we explore whether the observation network can even detect a methane pattern from wetlands. We find that the observation network can identify a methane pattern from Canadian wetlands but not reliably from US wetlands. Over Canada, the network can even identify spatial patterns at multi-provence scales. Over the US, by contrast, anthropogenic emissions and modeling errors obscure atmospheric patterns from wetland fluxes. In the second component of the study, we then use these observations to reconcile disagreements in the magnitude, seasonal cycle, and spatial distribution of existing estimates. Most existing estimates predict fluxes that are too large with a seasonal cycle that is too narrow. A model known as LPJ-Bern has a spatial distribution most consistent with atmospheric observations. By contrast, a spatially-constant model outperforms the distribution of most existing flux estimates across Canada. The results presented here provide several pathways to reduce disagreements among existing wetland flux estimates across North America.

On investigating social dynamics in tactical opportunistic mobile networks

NASA Astrophysics Data System (ADS)

Gao, Wei; Li, Yong

2014-06-01

The efficiency of military mobile network operations at the tactical edge is challenging due to the practical Disconnected, Intermittent, and Limited (DIL) environments at the tactical edge which make it hard to maintain persistent end-to-end wireless network connectivity. Opportunistic mobile networks are hence devised to depict such tactical networking scenarios. Social relations among warfighters in tactical opportunistic mobile networks are implicitly represented by their opportunistic contacts via short-range radios, but were inappropriately considered as stationary over time by the conventional wisdom. In this paper, we develop analytical models to probabilistically investigate the temporal dynamics of this social relationship, which is critical to efficient mobile communication in the battlespace. We propose to formulate such dynamics by developing various sociological metrics, including centrality and community, with respect to the opportunistic mobile network contexts. These metrics investigate social dynamics based on the experimentally validated skewness of users' transient contact distributions over time.

Mapping biological process relationships and disease perturbations within a pathway network.

PubMed

Stoney, Ruth; Robertson, David L; Nenadic, Goran; Schwartz, Jean-Marc

2018-01-01

Molecular interaction networks are routinely used to map the organization of cellular function. Edges represent interactions between genes, proteins, or metabolites. However, in living cells, molecular interactions are dynamic, necessitating context-dependent models. Contextual information can be integrated into molecular interaction networks through the inclusion of additional molecular data, but there are concerns about completeness and relevance of this data. We developed an approach for representing the organization of human cellular processes using pathways as the nodes in a network. Pathways represent spatial and temporal sets of context-dependent interactions, generating a high-level network when linked together, which incorporates contextual information without the need for molecular interaction data. Analysis of the pathway network revealed linked communities representing functional relationships, comparable to those found in molecular networks, including metabolism, signaling, immunity, and the cell cycle. We mapped a range of diseases onto this network and find that pathways associated with diseases tend to be functionally connected, highlighting the perturbed functions that result in disease phenotypes. We demonstrated that disease pathways cluster within the network. We then examined the distribution of cancer pathways and showed that cancer pathways tend to localize within the signaling, DNA processes and immune modules, although some cancer-associated nodes are found in other network regions. Altogether, we generated a high-confidence functional network, which avoids some of the shortcomings faced by conventional molecular models. Our representation provides an intuitive functional interpretation of cellular organization, which relies only on high-quality pathway and Gene Ontology data. The network is available at https://data.mendeley.com/datasets/3pbwkxjxg9/1.

A Context-Aware Ubiquitous Learning Approach for Providing Instant Learning Support in Personal Computer Assembly Activities

ERIC Educational Resources Information Center

Hsu, Ching-Kun; Hwang, Gwo-Jen

2014-01-01

Personal computer assembly courses have been recognized as being essential in helping students understand computer structure as well as the functionality of each computer component. In this study, a context-aware ubiquitous learning approach is proposed for providing instant assistance to individual students in the learning activity of a…

Using Ubiquitous Games in an English Listening and Speaking Course: Impact on Learning Outcomes and Motivation

ERIC Educational Resources Information Center

Liu, Tsung-Yu; Chu, Yu-Ling

2010-01-01

This paper reports the results of a study which aimed to investigate how ubiquitous games influence English learning achievement and motivation through a context-aware ubiquitous learning environment. An English curriculum was conducted on a school campus by using a context-aware ubiquitous learning environment called the Handheld English Language…

A Decision-Tree-Oriented Guidance Mechanism for Conducting Nature Science Observation Activities in a Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chu, Hui-Chun; Shih, Ju-Ling; Huang, Shu-Hsien; Tsai, Chin-Chung

2010-01-01

A context-aware ubiquitous learning environment is an authentic learning environment with personalized digital supports. While showing the potential of applying such a learning environment, researchers have also indicated the challenges of providing adaptive and dynamic support to individual students. In this paper, a decision-tree-oriented…

Impact of Contextuality on Mobile Learning Acceptance: An Empirical Study Based on a Language Learning App

ERIC Educational Resources Information Center

Böhm, Stephan; Constantine, Georges Philip

2015-01-01

The mobility of both the device and the learner will determine how mobile learning takes place. Mobile learning offers new educational opportunities that allow for autonomous, personalized and context aware learning. This paper focuses on contextualized features for mobile language learning apps. Context-awareness is seen as a particularly…

Constructing a User-Friendly and Smart Ubiquitous Personalized Learning Environment by Using a Context-Aware Mechanism

ERIC Educational Resources Information Center

Yao, Ching-Bang

2017-01-01

Although m-learning applications have been widely researched, few studies have investigated applying adaptive learning content to various learning environments and efficient input interfaces. This study combined a context-aware mechanism, which can be used to provide suitable learning information anytime and anyplace by using GPS technology, with…

College Students' Conceptions of Context-Aware Ubiquitous Learning: A Phenomenographic Analysis

ERIC Educational Resources Information Center

Tsai, Pei-Shan; Tsai, Chin-Chung; Hwang, Gwo-Haur

2011-01-01

The purpose of this study was to explore students' conceptions of context-aware ubiquitous learning (u-learning). The students participated in a u-learning exercise using PDAs equipped with RFID readers. The data were collected from individual interviews with each of the students by a trained researcher, and the responses of the interviewees were…

A hierarchical framework for investigating epiphyte assemblages: networks, meta-communities, and scale.

PubMed

Burns, K C; Zotz, G

2010-02-01

Epiphytes are an important component of many forested ecosystems, yet our understanding of epiphyte communities lags far behind that of terrestrial-based plant communities. This discrepancy is exacerbated by the lack of a theoretical context to assess patterns in epiphyte community structure. We attempt to fill this gap by developing an analytical framework to investigate epiphyte assemblages, which we then apply to a data set on epiphyte distributions in a Panamanian rain forest. On a coarse scale, interactions between epiphyte species and host tree species can be viewed as bipartite networks, similar to pollination and seed dispersal networks. On a finer scale, epiphyte communities on individual host trees can be viewed as meta-communities, or suites of local epiphyte communities connected by dispersal. Similar analytical tools are typically employed to investigate species interaction networks and meta-communities, thus providing a unified analytical framework to investigate coarse-scale (network) and fine-scale (meta-community) patterns in epiphyte distributions. Coarse-scale analysis of the Panamanian data set showed that most epiphyte species interacted with fewer host species than expected by chance. Fine-scale analyses showed that epiphyte species richness on individual trees was lower than null model expectations. Therefore, epiphyte distributions were clumped at both scales, perhaps as a result of dispersal limitations. Scale-dependent patterns in epiphyte species composition were observed. Epiphyte-host networks showed evidence of negative co-occurrence patterns, which could arise from adaptations among epiphyte species to avoid competition for host species, while most epiphyte meta-communities were distributed at random. Application of our "meta-network" analytical framework in other locales may help to identify general patterns in the structure of epiphyte assemblages and their variation in space and time.

Adolescents, Health Education, and Computers: The Body Awareness Resource Network (BARN).

ERIC Educational Resources Information Center

Bosworth, Kris; And Others

1983-01-01

The Body Awareness Resource Network (BARN) is a computer-based system designed as a confidential, nonjudgmental source of health information for adolescents. Topics include alcohol and other drugs, diet and activity, family communication, human sexuality, smoking, and stress management; programs are available for high school and middle school…

Do the coach and athlete have the same "picture" of the situation? Distributed Situation Awareness in an elite sport context.

PubMed

Macquet, Anne-Claire; Stanton, Neville A

2014-05-01

Athletes and their coach interpret the training situations differently and this can have important implications for the development of an elite athlete's performance. It is argued that, from a schema-theoretic perspective, the difference in these interpretations needs to be better understood. A post-performance, self-confrontation, interview was conducted with a number of athletes and their coaches. The interviews revealed differences between the athlete and their coach in the information they are aware of. In comparison with athletes, coaches more frequently compared the phenotype with genotype schemata rather than just describing the phenotype schemata. Results suggest SA information elements showed some common ground but also revealed some important differences between the athlete and coach. The awareness was directed externally towards the environment and internally, towards the individual, depending on his/her role. The investigation showed that the schemata used to 'frame' the information elements were different, but compatible, between athlete and coach. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Supporting awareness through collaborative brushing and linking of tabular data.

PubMed

Hajizadeh, Amir Hossein; Tory, Melanie; Leung, Rock

2013-12-01

Maintaining an awareness of collaborators' actions is critical during collaborative work, including during collaborative visualization activities. Particularly when collaborators are located at a distance, it is important to know what everyone is working on in order to avoid duplication of effort, share relevant results in a timely manner and build upon each other's results. Can a person's brushing actions provide an indication of their queries and interests in a data set? Can these actions be revealed to a collaborator without substantially disrupting their own independent work? We designed a study to answer these questions in the context of distributed collaborative visualization of tabular data. Participants in our study worked independently to answer questions about a tabular data set, while simultaneously viewing brushing actions of a fictitious collaborator, shown directly within a shared workspace. We compared three methods of presenting the collaborator's actions: brushing & linking (i.e. highlighting exactly what the collaborator would see), selection (i.e. showing only a selected item), and persistent selection (i.e. showing only selected items but having them persist for some time). Our results demonstrated that persistent selection enabled some awareness of the collaborator's activities while causing minimal interference with independent work. Other techniques were less effective at providing awareness, and brushing & linking caused substantial interference. These findings suggest promise for the idea of exploiting natural brushing actions to provide awareness in collaborative work.

Responses to a questionnaire on networking between OIE Reference Laboratories and OIE Collaborating Centres.

PubMed

Brückner, G K; Linnane, S; Diaz, F; Vallat, B

2007-01-01

Two separate questionnaires were distributed to 20 OIE Collaborating Centres and 160 OIE Reference Laboratories to assess the current status of networking and collaboration among OIE Reference Laboratories and between OIE Reference Laboratories and OIE Collaborating Centres. The questionnaire for the OIE Reference Laboratories contained 7 sections with questions on networking between laboratories, reporting of information, biosecurity quality control, and financing. Emphasis was placed in obtaining information on inter-laboratory relationships and exchange of expertise, training needs and sharing of data and information. The questionnaire for the OIE Collaborating Centres contained six sections with the emphasis on aspects related to awareness of services that can be provided, expertise that could be made available, sharing of information and the relationship with the national veterinary services of the countries concerned. The responses to the questionnaires were collated, categorised and statistically evaluated to allow for tentative inferences on the data provided. Valuable information emanated from the data identifying the current status of networking and indicating possible shortcomings that could be addressed to improve networking.

Discrete event command and control for networked teams with multiple missions

NASA Astrophysics Data System (ADS)

Lewis, Frank L.; Hudas, Greg R.; Pang, Chee Khiang; Middleton, Matthew B.; McMurrough, Christopher

2009-05-01

During mission execution in military applications, the TRADOC Pamphlet 525-66 Battle Command and Battle Space Awareness capabilities prescribe expectations that networked teams will perform in a reliable manner under changing mission requirements, varying resource availability and reliability, and resource faults. In this paper, a Command and Control (C2) structure is presented that allows for computer-aided execution of the networked team decision-making process, control of force resources, shared resource dispatching, and adaptability to change based on battlefield conditions. A mathematically justified networked computing environment is provided called the Discrete Event Control (DEC) Framework. DEC has the ability to provide the logical connectivity among all team participants including mission planners, field commanders, war-fighters, and robotic platforms. The proposed data management tools are developed and demonstrated on a simulation study and an implementation on a distributed wireless sensor network. The results show that the tasks of multiple missions are correctly sequenced in real-time, and that shared resources are suitably assigned to competing tasks under dynamically changing conditions without conflicts and bottlenecks.

ContextProvider: Context awareness for medical monitoring applications.

PubMed

Mitchell, Michael; Meyers, Christopher; Wang, An-I Andy; Tyson, Gary

2011-01-01

Smartphones are sensor-rich and Internet-enabled. With their on-board sensors, web services, social media, and external biosensors, smartphones can provide contextual information about the device, user, and environment, thereby enabling the creation of rich, biologically driven applications. We introduce ContextProvider, a framework that offers a unified, query-able interface to contextual data on the device. Unlike other context-based frameworks, ContextProvider offers interactive user feedback, self-adaptive sensor polling, and minimal reliance on third-party infrastructure. ContextProvider also allows for rapid development of new context and bio-aware applications. Evaluation of ContextProvider shows the incorporation of an additional monitoring sensor into the framework with fewer than 100 lines of Java code. With adaptive sensor monitoring, power consumption per sensor can be reduced down to 1% overhead. Finally, through the use of context, accuracy of data interpretation can be improved by up to 80%.

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks.

PubMed

Gholami, Mohammad; Brennan, Robert W

2016-01-06

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency.

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks

PubMed Central

Gholami, Mohammad; Brennan, Robert W.

2016-01-01

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency. PMID:26751447

Classification of complex networks based on similarity of topological network features

NASA Astrophysics Data System (ADS)

Attar, Niousha; Aliakbary, Sadegh

2017-09-01

Over the past few decades, networks have been widely used to model real-world phenomena. Real-world networks exhibit nontrivial topological characteristics and therefore, many network models are proposed in the literature for generating graphs that are similar to real networks. Network models reproduce nontrivial properties such as long-tail degree distributions or high clustering coefficients. In this context, we encounter the problem of selecting the network model that best fits a given real-world network. The need for a model selection method reveals the network classification problem, in which a target-network is classified into one of the candidate network models. In this paper, we propose a novel network classification method which is independent of the network size and employs an alignment-free metric of network comparison. The proposed method is based on supervised machine learning algorithms and utilizes the topological similarities of networks for the classification task. The experiments show that the proposed method outperforms state-of-the-art methods with respect to classification accuracy, time efficiency, and robustness to noise.

Facebook network structure and awareness of preexposure prophylaxis among young men who have sex with men.

PubMed

Khanna, Aditya S; Schumm, Phil; Schneider, John A

2017-03-01

Young Black men who have sex with men (YBMSM) are the only population in the United States who have experienced rising human immunodeficiency virus incidence over the past decade. Consistent pre-exposure prophylaxis (PrEP) use can substantially reduce the risk of human immunodeficiency virus acquisition. What differentiates those who become aware of PrEP, and those who do not, remains largely unknown. The social networks of YBMSM can impact their awareness of PrEP; to examine this impact, we used two waves of Facebook data from "uConnect"-a longitudinal cohort study of YBMSM in Chicago (n = 266). While PrEP awareness increased from 45% at baseline to 75% at follow-up, its use remained low (4% and 6%). There were 88 PrEP-unaware individuals at baseline who became aware (BA) by follow-up, and 56 who remained persistently unaware. While the persistently unawares had a higher median number of total Facebook friends, the BAs had a higher median numbers of friends who participated in uConnect, who were PrEP-aware, and who practiced behaviors previously found to be associated with individual-level awareness of PrEP at baseline. The BAs also had substantially more "influential" friends. These findings demonstrate the potential of social networks in raising PrEP awareness and use among YBMSM. Copyright © 2016 Elsevier Inc. All rights reserved.

A comparison of temporal Facebook networks of young men who have sex with men (MSM), differentiated by awareness and use of preexposure prophylaxis (PrEP)

PubMed Central

Khanna, Aditya S.; Schumm, Phil; Schneider, John A.

2016-01-01

Young Black men who have sex with men (YBMSM) are the only population in the U.S. who have experienced rising HIV incidence over the past decade. Consistent preexposure prophylaxis (PrEP) use can substantially reduce the risk of HIV acquisition. What differentiates those who become aware of PrEP, and those who do not, remains largely unknown. The social networks of YBMSM can impact their awareness of PrEP; to examine this impact, we used two waves of Facebook data from the “uConnect” study – a longitudinal cohort study of YBMSM in Chicago (n=266). While PrEP awareness increased from 45% at baseline to 75% at follow-up, its use remained low (4% and 6%). There were 88 PrEP-unaware individuals at baseline who became aware (BA) by follow-up, and 56 who remained persistently unaware (PU). While the PUs had a higher median number of total Facebook friends, the BAs had a higher median numbers of friends who participated in uConnect, who were PrEP-aware, and who practiced behaviors previously found to be associated with individual-level awareness of PrEP at baseline. The BAs also had substantially more “influential” friends. These findings demonstrate the potential of social networks in raising PrEP awareness and use among YBMSM. PMID:28003117

Epidemic spread in bipartite network by considering risk awareness

NASA Astrophysics Data System (ADS)

Han, She; Sun, Mei; Ampimah, Benjamin Chris; Han, Dun

2018-02-01

Human awareness plays an important role in the spread of infectious diseases and the control of propagation patterns. Exploring the interplay between human awareness and epidemic spreading is a topic that has been receiving increasing attention. Considering the fact, some well-known diseases only spread between different species we propose a theoretical analysis of the Susceptible-Infected-Susceptible (SIS) epidemic spread from the perspective of bipartite network and risk aversion. Using mean field theory, the epidemic threshold is calculated theoretically. Simulation results are consistent with the proposed analytic model. The results show that, the final infection density is negative linear with the value of individuals' risk awareness. Therefore, the epidemic spread could be effectively suppressed by improving individuals' risk awareness.

Modeling epidemic spread with awareness and heterogeneous transmission rates in networks.

PubMed

Shang, Yilun

2013-06-01

During an epidemic outbreak in a human population, susceptibility to infection can be reduced by raising awareness of the disease. In this paper, we investigate the effects of three forms of awareness (i.e., contact, local, and global) on the spread of a disease in a random network. Connectivity-correlated transmission rates are assumed. By using the mean-field theory and numerical simulation, we show that both local and contact awareness can raise the epidemic thresholds while the global awareness cannot, which mirrors the recent results of Wu et al. The obtained results point out that individual behaviors in the presence of an infectious disease has a great influence on the epidemic dynamics. Our method enriches mean-field analysis in epidemic models.

Breakdown of the brain’s functional network modularity with awareness

PubMed Central

Godwin, Douglass; Barry, Robert L.; Marois, René

2015-01-01

Neurobiological theories of awareness propose divergent accounts of the spatial extent of brain changes that support conscious perception. Whereas focal theories posit mostly local regional changes, global theories propose that awareness emerges from the propagation of neural signals across a broad extent of sensory and association cortex. Here we tested the scalar extent of brain changes associated with awareness using graph theoretical analysis applied to functional connectivity data acquired at ultra-high field while subjects performed a simple masked target detection task. We found that awareness of a visual target is associated with a degradation of the modularity of the brain’s functional networks brought about by an increase in intermodular functional connectivity. These results provide compelling evidence that awareness is associated with truly global changes in the brain’s functional connectivity. PMID:25759440

The experience of living with advanced-stage cancer: a thematic synthesis of the literature.

PubMed

García-Rueda, N; Carvajal Valcárcel, A; Saracíbar-Razquin, M; Arantzamendi Solabarrieta, M

2016-07-01

The aim of the study was to understand the experience of people living with advanced-stage cancer through literature. The search included The Cochrane Library, PubMed, PsycInfo, CINAHL and Cuiden. Thirteen studies were included. A qualitative meta-synthesis was conducted. One thread emerged from the thematic synthesis: the desire to live as normally as possible, despite being aware of the proximity of death. Three themes also emerged: "a process that is unique" with its four sub-themes; "support network" and "health context," each of them having two sub-themes. This study concludes that living with advanced-stage cancer is a unique and complex process which has both positive and negative aspects. The review provides a comprehensive view of the experience, which considers the importance of the support network and the health context in which the person lives. In this study, "normalcy" is the adjustment to the new reality and living as closely as possible to the way one lived before the disease, while developing a new relationship with being finite and death. A better understanding of the experience of living with advanced-stage cancer will help health professionals to identify the needs of the patients in order to plan individual, high-quality care. © 2016 John Wiley & Sons Ltd.

Competing spreading processes on multiplex networks: awareness and epidemics.

PubMed

Granell, Clara; Gómez, Sergio; Arenas, Alex

2014-07-01

Epidemiclike spreading processes on top of multilayered interconnected complex networks reveal a rich phase diagram of intertwined competition effects. A recent study by the authors [C. Granell et al., Phys. Rev. Lett. 111, 128701 (2013).] presented an analysis of the interrelation between two processes accounting for the spreading of an epidemic, and the spreading of information awareness to prevent infection, on top of multiplex networks. The results in the case in which awareness implies total immunization to the disease revealed the existence of a metacritical point at which the critical onset of the epidemics starts, depending on completion of the awareness process. Here we present a full analysis of these critical properties in the more general scenario where the awareness spreading does not imply total immunization, and where infection does not imply immediate awareness of it. We find the critical relation between the two competing processes for a wide spectrum of parameters representing the interaction between them. We also analyze the consequences of a massive broadcast of awareness (mass media) on the final outcome of the epidemic incidence. Importantly enough, the mass media make the metacritical point disappear. The results reveal that the main finding, i.e., existence of a metacritical point, is rooted in the competition principle and holds for a large set of scenarios.

Competition in the domain of wireless networks security

NASA Astrophysics Data System (ADS)

Bednarczyk, Mariusz

2017-04-01

Wireless networks are very popular and have found wide spread usage amongst various segments, also in military environment. The deployment of wireless infrastructures allow to reduce the time it takes to install and dismantle communications networks. With wireless, users are more mobile and can easily get access to the network resources all the time. However, wireless technologies like WiFi or Bluetooth have security issues that hackers have extensively exploited over the years. In the paper several serious security flaws in wireless technologies are presented. Most of them enable to get access to the internal networks and easily carry out man-in-the-middle attacks. Very often, they are used to launch massive denial of service attacks that target the physical infrastructure as well as the RF spectrum. For instance, there are well known instances of Bluetooth connection spoofing in order to steal WiFi password stored in the mobile device. To raise the security awareness and protect wireless networks against an adversary attack, an analysis of attack methods and tools over time is presented in the article. The particular attention is paid to the severity, possible targets as well as the ability to persist in the context of protective measures. Results show that an adversary can take complete control of the victims' mobile device features if the users forget to use simple safety principles.

Assessing Development of Meta-Pragmatic Awareness in Study Abroad

ERIC Educational Resources Information Center

Kinginger, Celeste; Farrell, Kathleen

2004-01-01

In this paper, the authors explore a methodology for assessing learners' meta-pragmatic awareness of variation in French language use. "Meta-pragmatic awareness" is defined as knowledge of the social meaning of variable second language forms and awareness of the ways in which these forms mark different aspects of social contexts, and is therefore…

Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

DTIC Science & Technology

2016-06-22

this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi...exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation... email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between

Designing, Building, and Connecting Networks to Support Distributed Collaborative Empirical Writing Research

ERIC Educational Resources Information Center

Brunk-Chavez, Beth; Pigg, Stacey; Moore, Jessie; Rosinski, Paula; Grabill, Jeffrey T.

2018-01-01

To speak to diverse audiences about how people learn to write and how writing works inside and outside the academy, we must conduct research across geographical, institutional, and cultural contexts as well as research that enables comparison when appropriate. Large-scale empirical research is useful for both of these moves; however, we must…

Factors affecting RFID adoption in the agricultural product distribution industry: empirical evidence from China.

PubMed

Shi, Ping; Yan, Bo

2016-01-01

We conducted an exploratory investigation of factors influencing the adoption of radio frequency identification (RFID) methods in the agricultural product distribution industry. Through a literature review and field research, and based on the technology-organization-environment (TOE) theoretical framework, this paper analyzes factors influencing RFID adoption in the agricultural product distribution industry in reference to three contexts: technological, organizational, and environmental contexts. An empirical analysis of the TOE framework was conducted by applying structural equation modeling based on actual data from a questionnaire survey on the agricultural product distribution industry in China. The results show that employee resistance and uncertainty are not supported by the model. Technological compatibility, perceived effectiveness, organizational size, upper management support, trust between enterprises, technical knowledge, competitive pressure and support from the Chinese government, which are supported by the model, have significantly positive effects on RFID adoption. Meanwhile, organizational size has the strongest positive effect, while competitive pressure levels have the smallest effect. Technological complexities and costs have significantly negative effects on RFID adoption, with cost being the most significantly negative influencing factor. These research findings will afford enterprises in the agricultural products supply chain with a stronger understanding of the factors that influence RFID adoption in the agricultural product distribution industry. In addition, these findings will help enterprises remain aware of how these factors affect RFID adoption and will thus help enterprises make more accurate and rational decisions by promoting RFID application in the agricultural product distribution industry.

Racial disparities in hypertension awareness and management: Are there differences among African Americans and Whites living in similar social and healthcare resource environments?

PubMed Central

Thorpe, R. J.; Bowie, J. V.; Smolen, J. R.; Bell, C. N.; Jenkins, M. L.; Jackson, J.; LaVeist, T. A.

2015-01-01

Background Although racial disparities in hypertension awareness and management are well documented, studies have not accounted for the differing social contexts in which whites and African Americans live. Objective To examine the nature of disparities in hypertension awareness, treatment, and control within a sample of whites and African Americans living in the same social context and with access to the same healthcare environment. Design Cross-sectional study. Participants 949 hypertensive African American and white adults in the Exploring Health Disparities in Integrated Communities-Southwest Baltimore (EHDIC-SWB) Study. Measurements Logistic regression models were conducted to estimate the association between race and hypertension awareness, treatment and control adjusting for potential confounders. Results African Americans had greater odds of being aware of their hypertension than whites (odds ratio=1.44; 95% confidence interval 1:04, 2.01). However, African Americans and whites had similar odds of being treated for hypertension, and having their hypertension under control. Discussion Within this racially integrated sample of hypertensive adults who share similar healthcare market, race differences in treatment and control of hypertension were eliminated. Accounting for the social context should be considered in public health campaigns targeting hypertension awareness and management. PMID:25065066

Security-Enhanced Autonomous Network Management

NASA Technical Reports Server (NTRS)

Zeng, Hui

2015-01-01

Ensuring reliable communication in next-generation space networks requires a novel network management system to support greater levels of autonomy and greater awareness of the environment and assets. Intelligent Automation, Inc., has developed a security-enhanced autonomous network management (SEANM) approach for space networks through cross-layer negotiation and network monitoring, analysis, and adaptation. The underlying technology is bundle-based delay/disruption-tolerant networking (DTN). The SEANM scheme allows a system to adaptively reconfigure its network elements based on awareness of network conditions, policies, and mission requirements. Although SEANM is generically applicable to any radio network, for validation purposes it has been prototyped and evaluated on two specific networks: a commercial off-the-shelf hardware test-bed using Institute of Electrical Engineers (IEEE) 802.11 Wi-Fi devices and a military hardware test-bed using AN/PRC-154 Rifleman Radio platforms. Testing has demonstrated that SEANM provides autonomous network management resulting in reliable communications in delay/disruptive-prone environments.

Biological instability in a chlorinated drinking water distribution network.

PubMed

Nescerecka, Alina; Rubulis, Janis; Vital, Marius; Juhna, Talis; Hammes, Frederik

2014-01-01

The purpose of a drinking water distribution system is to deliver drinking water to the consumer, preferably with the same quality as when it left the treatment plant. In this context, the maintenance of good microbiological quality is often referred to as biological stability, and the addition of sufficient chlorine residuals is regarded as one way to achieve this. The full-scale drinking water distribution system of Riga (Latvia) was investigated with respect to biological stability in chlorinated drinking water. Flow cytometric (FCM) intact cell concentrations, intracellular adenosine tri-phosphate (ATP), heterotrophic plate counts and residual chlorine measurements were performed to evaluate the drinking water quality and stability at 49 sampling points throughout the distribution network. Cell viability methods were compared and the importance of extracellular ATP measurements was examined as well. FCM intact cell concentrations varied from 5×10(3) cells mL(-1) to 4.66×10(5) cells mL(-1) in the network. While this parameter did not exceed 2.1×10(4) cells mL(-1) in the effluent from any water treatment plant, 50% of all the network samples contained more than 1.06×10(5) cells mL(-1). This indisputably demonstrates biological instability in this particular drinking water distribution system, which was ascribed to a loss of disinfectant residuals and concomitant bacterial growth. The study highlights the potential of using cultivation-independent methods for the assessment of chlorinated water samples. In addition, it underlines the complexity of full-scale drinking water distribution systems, and the resulting challenges to establish the causes of biological instability.

Biological Instability in a Chlorinated Drinking Water Distribution Network

PubMed Central

Nescerecka, Alina; Rubulis, Janis; Vital, Marius; Juhna, Talis; Hammes, Frederik

2014-01-01

The purpose of a drinking water distribution system is to deliver drinking water to the consumer, preferably with the same quality as when it left the treatment plant. In this context, the maintenance of good microbiological quality is often referred to as biological stability, and the addition of sufficient chlorine residuals is regarded as one way to achieve this. The full-scale drinking water distribution system of Riga (Latvia) was investigated with respect to biological stability in chlorinated drinking water. Flow cytometric (FCM) intact cell concentrations, intracellular adenosine tri-phosphate (ATP), heterotrophic plate counts and residual chlorine measurements were performed to evaluate the drinking water quality and stability at 49 sampling points throughout the distribution network. Cell viability methods were compared and the importance of extracellular ATP measurements was examined as well. FCM intact cell concentrations varied from 5×103 cells mL−1 to 4.66×105 cells mL−1 in the network. While this parameter did not exceed 2.1×104 cells mL−1 in the effluent from any water treatment plant, 50% of all the network samples contained more than 1.06×105 cells mL−1. This indisputably demonstrates biological instability in this particular drinking water distribution system, which was ascribed to a loss of disinfectant residuals and concomitant bacterial growth. The study highlights the potential of using cultivation-independent methods for the assessment of chlorinated water samples. In addition, it underlines the complexity of full-scale drinking water distribution systems, and the resulting challenges to establish the causes of biological instability. PMID:24796923

The intelligent OR: design and validation of a context-aware surgical working environment.

PubMed

Franke, Stefan; Rockstroh, Max; Hofer, Mathias; Neumuth, Thomas

2018-05-24

Interoperability of medical devices based on standards starts to establish in the operating room (OR). Devices share their data and control functionalities. Yet, the OR technology rarely implements cooperative, intelligent behavior, especially in terms of active cooperation with the OR team. Technical context-awareness will be an essential feature of the next generation of medical devices to address the increasing demands to clinicians in information seeking, decision making, and human-machine interaction in complex surgical working environments. The paper describes the technical validation of an intelligent surgical working environment for endoscopic ear-nose-throat surgery. We briefly summarize the design of our framework for context-aware system's behavior in integrated OR and present example realizations of novel assistance functionalities. In a study on patient phantoms, twenty-four procedures were implemented in the proposed intelligent surgical working environment based on recordings of real interventions. Subsequently, the whole processing pipeline for context-awareness from workflow recognition to the final system's behavior is analyzed. Rule-based behavior that considers multiple perspectives on the procedure can partially compensate recognition errors. A considerable robustness could be achieved with a reasonable quality of the recognition. Overall, reliable reactive as well as proactive behavior of the surgical working environment can be implemented in the proposed environment. The obtained validation results indicate the suitability of the overall approach. The setup is a reliable starting point for a subsequent evaluation of the proposed context-aware assistance. The major challenge for future work will be to implement the complex approach in a cross-vendor setting.

Awareness Programs and Change in Taste-Based Caste Prejudice

PubMed Central

Banerjee, Ritwik; Datta Gupta, Nabanita

2015-01-01

Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution - the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste. PMID:25902290

Awareness programs and change in taste-based caste prejudice.

PubMed

Banerjee, Ritwik; Datta Gupta, Nabanita

2015-01-01

Becker's theory of taste-based discrimination predicts that relative employment of the discriminated social group will improve if there is a decrease in the level of prejudice for the marginally discriminating employer. In this paper we experimentally test this prediction offered by Garry Becker in his seminal work on taste based discrimination, in the context of caste in India, with management students (potential employers in the near future) as subjects. First, we measure caste prejudice and show that awareness through a TV social program reduces implicit prejudice against the lower caste and the reduction is sustained over time. Second, we find that the treatment reduces the prejudice levels of those in the left tail of the prejudice distribution--the group which can potentially affect real outcomes as predicted by the theory. And finally, a larger share of the treatment group subjects exhibit favorable opinion about reservation in jobs for the lower caste.

"He Is Intelligent but Different": Stakeholders' Perspectives on Children on the Autism Spectrum in an Urban Indian School Context

ERIC Educational Resources Information Center

Taneja Johansson, Shruti

2014-01-01

This article explores stakeholders' awareness of autism and their perspectives on children with autism, in an urban Indian school context. Using an interpretive framework, the article draws on interview data from a study conducted in Kolkata. Findings indicated varying but limited awareness of autism among school staff. Teachers instead described…

An Adaptive Navigation Support System for Conducting Context-Aware Ubiquitous Learning in Museums

ERIC Educational Resources Information Center

Chiou, Chuang-Kai; Tseng, Judy C. R.; Hwang, Gwo-Jen; Heller, Shelly

2010-01-01

In context-aware ubiquitous learning, students are guided to learn in the real world with personalized supports from the learning system. As the learning resources are realistic objects in the real world, certain physical constraints, such as the limitation of stream of people who visit the same learning object, the time for moving from one object…

Development and Evaluation of a Web 2.0-Based Ubiquitous Learning Platform for Schoolyard Plant Identification

ERIC Educational Resources Information Center

Hwang, Gwo-Haur; Chu, Hui-Chun; Chen, Beyin; Cheng, Zheng Shan

2014-01-01

The rapid progress of wireless communication, sensing, and mobile technologies has enabled students to learn in an environment that combines learning resources from both the real world and the digital world. It can be viewed as a new learning style which has been called context-aware ubiquitous learning. Most context-aware ubiquitous learning…

A Phenomenological Investigation of Social Networking Privacy Awareness through a Media Literacy Lens

ERIC Educational Resources Information Center

Magolis, David; Briggs, Audra

2016-01-01

This research study focused on the social networking site (SNS) awareness of undergraduate students, examining their experiences through the type and extent of the information shared on their SNSs in order to discover the students' experiences with SNS privacy. A phenomenological research approach was used to interview eight undergraduates to…

Study on the potential for delay tolerant networks by health workers in low resource settings.

PubMed

Syed-Abdul, Shabbir; Scholl, Jeremiah; Lee, Peisan; Jian, Wen-Shan; Liou, Der-Ming; Li, Yu-Chuan

2012-09-01

Medical Informatics Systems (MIS) have been suggested as having great potential to improve health care delivery in low resource settings. One of the major barriers for adopting MIS in this context is a lack of adequate network/communication infrastructure. Delay Tolerant Networking (DTN) is an approach for establishing network connectivity in situations where it is possible to support physical transport of the digital information. To date most DTN research has been technically oriented, and very few services have been implemented to support healthcare systems using the technology. It is thus unclear about the potential that DTN may have for supporting MIS systems in low resource settings. The goals of the paper are twofold, first, to gain an initial estimate of interest in different services that can be supported by DTN. Second, to find out the necessary frequency associated with each service for supporting health work in low resource settings. Fifty questionnaires were distributed to attendants at the International Conference on Global Health that had acknowledged having health work experience in a poor connectivity context. The respondents were using a 5-point Likert scale regarding if 9 different potential DTN services "would be useful". They also were asked how often data delivery would be necessary for these services to be useful. The Chi square was calculated to measure acceptance. 37 responses were received, aggregating the response rate of 74%. The respondents represented having work experience from 8 months to 15 years from 35 resource poor countries. The Chi square test showed very high statistical significance for "strongly agree and agree" for the potential usefulness of the proposed DTN services, with a p-value less than 0.001. The frequency of data delivery that would be necessary for services to be useful varied considerably. This study provides evidence of potential for DTN to support useful services that support health work in low resource settings, and that services like access to email, notification of lab results, backup of EHR and teleconsultation are seem to be most important services that can be supported by DTN. The necessary frequency of data delivery for each service, will be highly dependent on context. In a low resource setting with limited mobility, the physical transport of digital data at a frequency of less than once per week should still be sufficient for useful services like notification of lab results and ordering of medical supplies. Research comparing different methods for delivery of DTN data should thus be useful. Further research and collaboration between MIS and Computer Science research communities is recommended in order to help develop DTN services that can be evaluated. Efforts to enhance awareness among stakeholders about how DTN can be used to support health services should be worthwhile. Copyright © 2011. Published by Elsevier Ireland Ltd.

Never blame the umpire - a review of Situation Awareness models and methods for examining the performance of officials in sport.

PubMed

Neville, Timothy J; Salmon, Paul M

2016-07-01

As sport becomes more complex, there is potential for ergonomics concepts to help enhance the performance of sports officials. The concept of Situation Awareness (SA) appears pertinent given the requirement for officials to understand what is going on in order to make decisions. Although numerous models exist, none have been applied to examine officials, and only several recent examples have been applied to sport. This paper examines SA models and methods to identify if any have applicability to officials in sport (OiS). Evaluation of the models and methods identified potential applications of individual, team and systems models of SA. The paper further demonstrates that the Distributed Situation Awareness model is suitable for studying officials in fastball sports. It is concluded that the study of SA represents a key area of multidisciplinary research for both ergonomics and sports science in the context of OiS. Practitioner Summary: Despite obvious synergies, applications of cognitive ergonomics concepts in sport are sparse. This is especially so for Officials in Sport (OiS). This article presents an evaluation of Situation Awareness models and methods, providing practitioners with guidance on which are the most suitable for OiS system design and evaluation.

Traffic-engineering-aware shortest-path routing and its application in IP-over-WDM networks [Invited

NASA Astrophysics Data System (ADS)

Lee, Youngseok; Mukherjee, Biswanath

2004-03-01

Single shortest-path routing is known to perform poorly for Internet traffic engineering (TE) where the typical optimization objective is to minimize the maximum link load. Splitting traffic uniformly over equal-cost multiple shortest paths in open shortest path first and intermediate system-intermediate system protocols does not always minimize the maximum link load when multiple paths are not carefully selected for the global traffic demand matrix. However, a TE-aware shortest path among all the equal-cost multiple shortest paths between each ingress-egress pair can be selected such that the maximum link load is significantly reduced. IP routers can use the globally optimal TE-aware shortest path without any change to existing routing protocols and without any serious configuration overhead. While calculating TE-aware shortest paths, the destination-based forwarding constraint at a node should be satisfied, because an IP router will forward a packet to the next hop toward the destination by looking up the destination prefix. We present a mathematical problem formulation for finding a set of TE-aware shortest paths for the given network as an integer linear program, and we propose a simple heuristic for solving large instances of the problem. Then we explore the usage of our proposed algorithm for the integrated TE method in IP-over-WDM networks. The proposed algorithm is evaluated through simulations in IP networks as well as in IP-over-WDM networks.

Onset of anomalous diffusion from local motion rules

NASA Astrophysics Data System (ADS)

de Nigris, Sarah; Carletti, Timoteo; Lambiotte, Renaud

2017-02-01

Anomalous diffusion processes, in particular superdiffusive ones, are known to be efficient strategies for searching and navigation in animals and also in human mobility. One way to create such regimes are Lévy flights, where the walkers are allowed to perform jumps, the "flights," that can eventually be very long as their length distribution is asymptotically power-law distributed. In our work, we present a model in which walkers are allowed to perform, on a one-dimensional lattice, "cascades" of n unitary steps instead of one jump of a randomly generated length, as in the Lévy case, where n is drawn from a cascade distribution pn. We show that this local mechanism may give rise to superdiffusion or normal diffusion when pn is distributed as a power law. We also introduce waiting times that are power-law distributed as well and therefore the probability distribution scaling is steered by the two local distributions power-law exponents. As a perspective, our approach may engender a possible generalization of anomalous diffusion in context where distances are difficult to define, as in the case of complex networks, and also provide an interesting model for diffusion in temporal networks.

Radiology: "killer app" for next generation networks?

PubMed

McNeill, Kevin M

2004-03-01

The core principles of digital radiology were well developed by the end of the 1980 s. During the following decade tremendous improvements in computer technology enabled realization of those principles at an affordable cost. In this decade work can focus on highly distributed radiology in the context of the integrated health care enterprise. Over the same period computer networking has evolved from a relatively obscure field used by a small number of researchers across low-speed serial links to a pervasive technology that affects nearly all facets of society. Development directions in network technology will ultimately provide end-to-end data paths with speeds that match or exceed the speeds of data paths within the local network and even within workstations. This article describes key developments in Next Generation Networks, potential obstacles, and scenarios in which digital radiology can become a "killer app" that helps to drive deployment of new network infrastructure.

Metrics for Operator Situation Awareness, Workload, and Performance in Automated Separation Assurance Systems

NASA Technical Reports Server (NTRS)

Strybel, Thomas Z.; Vu, Kim-Phuong L.; Battiste, Vernol; Dao, Arik-Quang; Dwyer, John P.; Landry, Steven; Johnson, Walter; Ho, Nhut

2011-01-01

A research consortium of scientists and engineers from California State University Long Beach (CSULB), San Jose State University Foundation (SJSUF), California State University Northridge (CSUN), Purdue University, and The Boeing Company was assembled to evaluate the impact of changes in roles and responsibilities and new automated technologies, being introduced in the Next Generation Air Transportation System (NextGen), on operator situation awareness (SA) and workload. To meet these goals, consortium members performed systems analyses of NextGen concepts and airspace scenarios, and concurrently evaluated SA, workload, and performance measures to assess their appropriateness for evaluations of NextGen concepts and tools. The following activities and accomplishments were supported by the NRA: a distributed simulation, metric development, systems analysis, part-task simulations, and large-scale simulations. As a result of this NRA, we have gained a greater understanding of situation awareness and its measurement, and have shared our knowledge with the scientific community. This network provides a mechanism for consortium members, colleagues, and students to pursue research on other topics in air traffic management and aviation, thus enabling them to make greater contributions to the field

Condom distribution in Bali: assuring supply meets demand.

PubMed

Merati, T P

1994-01-01

Hundreds of thousands of tourists visit Bali each year, many of whom pay to have sex with local residents. Kuta, one of Bali's major tourist resort towns, has manifested an higher demand for condoms than other studied areas in Indonesia. Such demand is laudable in the context of a growing HIV/AIDS epidemic, but demand must encounter supply to be worthwhile. The Citra Usadha Indonesia Foundation (YCUI) has been conducting outreach education in Kuta and other areas of Bali since February 1992. Over that time, outreach workers have found that street youths' and prostitutes' main sources for condoms, pharmacies, supermarkets, and YCUI outreach workers, are either closed or potentially unavailable at night, when most sexual transactions occur. Pharmacies and supermarkets close at 10 pm. YCUI therefore initiated a six-month condom distribution program in 1994 to encourage the approximately 150 street vendors working in Kuta to sell condoms. Street vendors who enrolled in the program were provided with a monthly supply of 30 free condoms for the period of six months and invited to sell them to the public at whatever price the market set. Concurrently, YCUI promoted condom sales and increased awareness of the new condom source through social marketing techniques and their network of outreach workers. After six months, 122 vendors had participated in the program selling 10,255 condoms. Vendors were able to sell more and more condoms as the program progressed. A final evaluation will be conducted October 1994 to determine how many vendors still sell condoms now that the free supplies have been discontinued.

Introduction

NASA Astrophysics Data System (ADS)

de Laat, Cees; Develder, Chris; Jukan, Admela; Mambretti, Joe

This topic is devoted to communication issues in scalable compute and storage systems, such as parallel computers, networks of workstations, and clusters. All aspects of communication in modern systems were solicited, including advances in the design, implementation, and evaluation of interconnection networks, network interfaces, system and storage area networks, on-chip interconnects, communication protocols, routing and communication algorithms, and communication aspects of parallel and distributed algorithms. In total 15 papers were submitted to this topic of which we selected the 7 strongest papers. We grouped the papers in two sessions of 3 papers each and one paper was selected for the best paper session. We noted a number of papers dealing with changing topologies, stability and forwarding convergence in source routing based cluster interconnect network architectures. We grouped these for the first session. The authors of the paper titled: “Implementing a Change Assimilation Mechanism for Source Routing Interconnects” propose a mechanism that can obtain the new topology, and compute and distribute a new set of fabric paths to the source routed network end points to minimize the impact on the forwarding service. The article entitled “Dependability Analysis of a Fault-tolerant Network Reconfiguration Strateg” reports on a case study analyzing the effects of network size, mean time to node failure, mean time to node repair, mean time to network repair and coverage of the failure when using a 2D mesh network with a fault-tolerant mechanism (similar to the one used in the BlueGene/L system), that is able to remove rows and/or columns in the presence of failures. The last paper in this session: “RecTOR: A New and Efficient Method for Dynamic Network Reconfiguration” presents a new dynamic reconfiguration method, that ensures deadlock-freedom during the reconfiguration without causing performance degradation such as increased latency or decreased throughput. The second session groups 3 papers presenting methods, protocols and architectures that enhance capacities in the Networks. The paper titled: “NIC-assisted Cache-Efficient Receive Stack for Message Passing over Ethernet” presents the addition of multiqueue support in the Open-MX receive stack so that all incoming packets for the same process are treated on the same core. It then introduces the idea of binding the target end process near its dedicated receive queue. In general this multiqueue receive stack performs better than the original single queue stack, especially on large communication patterns where multiple processes are involved and manual binding is difficult. The authors of: “A Multipath Fault-Tolerant Routing Method for High-Speed Interconnection Networks” focus on the problem of fault tolerance for high-speed interconnection networks by designing a fault tolerant routing method. The goal was to solve a certain number of link and node failures, considering its impact, and occurrence probability. Their experiments show that their method allows applications to successfully finalize their execution in the presence of several faults, with an average performance value of 97% with respect to the fault-free scenarios. The paper: “Hardware implementation study of the Self-Clocked Fair Queuing Credit Aware (SCFQ-CA) and Deficit Round Robin Credit Aware (DRR-CA) scheduling algorithms” proposes specific implementations of the two schedulers taking into account the characteristics of current high-performance networks. A comparison is presented on the complexity of these two algorithms in terms of silicon area and computation delay. Finally we selected one paper for the special paper session: “A Case Study of Communication Optimizations on 3D Mesh Interconnects”. In this paper the authors present topology aware mapping as a technique to optimize communication on 3-dimensional mesh interconnects and hence improve performance. Results are presented for OpenAtom on up to 16,384 processors of Blue Gene/L, 8,192 processors of Blue Gene/P and 2,048 processors of Cray XT3.

Exploring the dynamics of collective cognition using a computational model of cognitive dissonance

NASA Astrophysics Data System (ADS)

Smart, Paul R.; Sycara, Katia; Richardson, Darren P.

2013-05-01

The socially-distributed nature of cognitive processing in a variety of organizational settings means that there is increasing scientific interest in the factors that affect collective cognition. In military coalitions, for example, there is a need to understand how factors such as communication network topology, trust, cultural differences and the potential for miscommunication affects the ability of distributed teams to generate high quality plans, to formulate effective decisions and to develop shared situation awareness. The current paper presents a computational model and associated simulation capability for performing in silico experimental analyses of collective sensemaking. This model can be used in combination with the results of human experimental studies in order to improve our understanding of the factors that influence collective sensemaking processes.

Awareness and Use of Folic Acid among Women in the Lower Mississippi Delta

ERIC Educational Resources Information Center

Robbins, James M.; Hopkins, Sarah E.; Mosley, Bridget S.; Casey, Patrick H.; Cleves, Mario A.; Hobbs, Charlotte A.

2006-01-01

Context: National and state efforts to increase folic acid awareness and use may not be reaching large segments of the population. Purpose: This study examines folic acid awareness and use among women of childbearing age in a representative, economically at-risk rural sample and identifies factors that influence awareness and use. Methods: A…

Review of Self-Awareness and Its Clinical Application in Stroke Rehabilitation

ERIC Educational Resources Information Center

Leung, Daniel P. K.; Liu, Karen P. Y.

2011-01-01

The objectives of this study were (i) to explore, following a literature review, the concepts of self-awareness, its assessment, and intervention for self-awareness deficits, as well as its clinical significance in stroke rehabilitation; and (ii) to apply the concepts of self-awareness in the context of a rehabilitation program. The search was…

A context management system for a cost-efficient smart home platform

NASA Astrophysics Data System (ADS)

Schneider, J.; Klein, A.; Mannweiler, C.; Schotten, H. D.

2012-09-01

This paper presents an overview of state-of-the-art architectures for integrating wireless sensor and actuators networks into the Future Internet. Furthermore, we will address advantages and disadvantages of the different architectures. With respect to these criteria, we develop a new architecture overcoming these weaknesses. Our system, called Smart Home Context Management System, will be used for intelligent home utilities, appliances, and electronics and includes physical, logical as well as network context sources within one concept. It considers important aspects and requirements of modern context management systems for smart X applications: plug and play as well as plug and trust capabilities, scalability, extensibility, security, and adaptability. As such, it is able to control roller blinds, heating systems as well as learn, for example, the user's taste w.r.t. to home entertainment (music, videos, etc.). Moreover, Smart Grid applications and Ambient Assisted Living (AAL) functions are applicable. With respect to AAL, we included an Emergency Handling function. It assures that emergency calls (police, ambulance or fire department) are processed appropriately. Our concept is based on a centralized Context Broker architecture, enhanced by a distributed Context Broker system. The goal of this concept is to develop a simple, low-priced, multi-functional, and save architecture affordable for everybody. Individual components of the architecture are well tested. Implementation and testing of the architecture as a whole is in progress.

"We get by with a little help from our friends": Small-scale informal and large-scale formal peer distribution networks of sterile injecting equipment in Australia.

PubMed

Newland, Jamee; Newman, Christy; Treloar, Carla

2016-08-01

In Australia, sterile needles and syringes are distributed to people who inject drugs (PWID) through formal services for the purposes of preventing blood borne viruses (BBV). Peer distribution involves people acquiring needles from formal services and redistributing them to others. This paper investigates the dynamics of the distribution of sterile injecting equipment among networks of people who inject drugs in four sites in New South Wales (NSW), Australia. Qualitative data exploring the practice of peer distribution were collected through in-depth, semi-structured interviews and participatory social network mapping. These interviews explored injecting equipment demand, access to services, relationship pathways through which peer distribution occurred, an estimate of the size of the different peer distribution roles and participants' understanding of the illegality of peer distribution in NSW. Data were collected from 32 participants, and 31 (98%) reported participating in peer distribution in the months prior to interview. Of those 31 participants, five reported large-scale formal distribution, with an estimated volume of 34,970 needles and syringes annually. Twenty-two participated in reciprocal exchange, where equipment was distributed and received on an informal basis that appeared dependent on context and circumstance and four participants reported recipient peer distribution as their only access to sterile injecting equipment. Most (n=27) were unaware that it was illegal to distribute injecting equipment to their peers. Peer distribution was almost ubiquitous amongst the PWID participating in the study, and although five participants reported taking part in the highly organised, large-scale distribution of injecting equipment for altruistic reasons, peer distribution was more commonly reported to take place in small networks of friends and/or partners for reasons of convenience. The law regarding the illegality of peer distribution needs to change so that NSPs can capitalise on peer distribution to increase the options available to PWID and to acknowledge PWID as essential harm reduction agents in the prevention of BBVs. Copyright © 2016 Elsevier B.V. All rights reserved.