Development concepts of a Smart Cyber Operating Theater (SCOT) using ORiN technology.

PubMed

Okamoto, Jun; Masamune, Ken; Iseki, Hiroshi; Muragaki, Yoshihiro

2018-02-23

Currently, networking has not progressed in the treatment room. Almost every medical device in the treatment room operates as a stand-alone device. In this project, we aim to develop a networked operating room called "Smart Cyber Operating Theater (SCOT)". Medical devices are connected using Open Resource interface for the Network (ORiN) technology. In this paper, we describe the concept of the SCOT project. SCOT is integrated using the communication interface ORiN, which was originally developed for industry. One feature of ORiN is that the system can be constructed flexibly. ORiN creates abstracts of the same type of devices and increases the robustness of the system for device exchange. By using ORiN technology, we are developing new applications, such as decision-making navigation or a precision guided treatment system.

Similarity-based Regularized Latent Feature Model for Link Prediction in Bipartite Networks.

PubMed

Wang, Wenjun; Chen, Xue; Jiao, Pengfei; Jin, Di

2017-12-05

Link prediction is an attractive research topic in the field of data mining and has significant applications in improving performance of recommendation system and exploring evolving mechanisms of the complex networks. A variety of complex systems in real world should be abstractly represented as bipartite networks, in which there are two types of nodes and no links connect nodes of the same type. In this paper, we propose a framework for link prediction in bipartite networks by combining the similarity based structure and the latent feature model from a new perspective. The framework is called Similarity Regularized Nonnegative Matrix Factorization (SRNMF), which explicitly takes the local characteristics into consideration and encodes the geometrical information of the networks by constructing a similarity based matrix. We also develop an iterative scheme to solve the objective function based on gradient descent. Extensive experiments on a variety of real world bipartite networks show that the proposed framework of link prediction has a more competitive, preferable and stable performance in comparison with the state-of-art methods.

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

PubMed Central

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

2017-01-01

ABSTRACT The increase in public online databases dedicated to fungal identification is noteworthy. This can be attributed to improved access to molecular approaches to characterize fungi, as well as to delineate species within specific fungal groups in the last 2 decades, leading to an ever-increasing complexity of taxonomic assortments and nomenclatural reassignments. Thus, well-curated fungal databases with substantial accurate sequence data play a pivotal role for further research and diagnostics in the field of mycology. This minireview aims to provide an overview of currently available online databases for the taxonomy and identification of human and animal-pathogenic fungi and calls for the establishment of a cloud-based dynamic data network platform. PMID:28179406

Neural Networks for the Classification of Building Use from Street-View Imagery

NASA Astrophysics Data System (ADS)

Laupheimer, D.; Tutzauer, P.; Haala, N.; Spicker, M.

2018-05-01

Within this paper we propose an end-to-end approach for classifying terrestrial images of building facades into five different utility classes (commercial, hybrid, residential, specialUse, underConstruction) by using Convolutional Neural Networks (CNNs). For our examples we use images provided by Google Street View. These images are automatically linked to a coarse city model, including the outlines of the buildings as well as their respective use classes. By these means an extensive dataset is available for training and evaluation of our Deep Learning pipeline. The paper describes the implemented end-to-end approach for classifying street-level images of building facades and discusses our experiments with various CNNs. In addition to the classification results, so-called Class Activation Maps (CAMs) are evaluated. These maps give further insights into decisive facade parts that are learned as features during the training process. Furthermore, they can be used for the generation of abstract presentations which facilitate the comprehension of semantic image content. The abstract representations are a result of the stippling method, an importance-based image rendering.

A comparative analysis of the statistical properties of large mobile phone calling networks.

PubMed

Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

2014-05-30

Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

Detecting trends in academic research from a citation network using network representation learning

PubMed Central

Mori, Junichiro; Ochi, Masanao; Sakata, Ichiro

2018-01-01

Several network features and information retrieval methods have been proposed to elucidate the structure of citation networks and to detect important nodes. However, it is difficult to retrieve information related to trends in an academic field and to detect cutting-edge areas from the citation network. In this paper, we propose a novel framework that detects the trend as the growth direction of a citation network using network representation learning(NRL). We presume that the linear growth of citation network in latent space obtained by NRL is the result of the iterative edge additional process of a citation network. On APS datasets and papers of some domains of the Web of Science, we confirm the existence of trends by observing that an academic field grows in a specific direction linearly in latent space. Next, we calculate each node’s degree of trend-following as an indicator called the intrinsic publication year (IPY). As a result, there is a correlation between the indicator and the number of future citations. Furthermore, a word frequently used in the abstracts of cutting-edge papers (high-IPY paper) is likely to be used often in future publications. These results confirm the validity of the detected trend for predicting citation network growth. PMID:29782521

New Abstraction Networks and a New Visualization Tool in Support of Auditing the SNOMED CT Content

PubMed Central

Geller, James; Ochs, Christopher; Perl, Yehoshua; Xu, Junchuan

2012-01-01

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT. PMID:23304293

New abstraction networks and a new visualization tool in support of auditing the SNOMED CT content.

PubMed

Geller, James; Ochs, Christopher; Perl, Yehoshua; Xu, Junchuan

2012-01-01

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT.

Information Flow in Interaction Networks II: Channels, Path Lengths, and Potentials

PubMed Central

Stojmirović, Aleksandar

2012-01-01

Abstract In our previous publication, a framework for information flow in interaction networks based on random walks with damping was formulated with two fundamental modes: emitting and absorbing. While many other network analysis methods based on random walks or equivalent notions have been developed before and after our earlier work, one can show that they can all be mapped to one of the two modes. In addition to these two fundamental modes, a major strength of our earlier formalism was its accommodation of context-specific directed information flow that yielded plausible and meaningful biological interpretation of protein functions and pathways. However, the directed flow from origins to destinations was induced via a potential function that was heuristic. Here, with a theoretically sound approach called the channel mode, we extend our earlier work for directed information flow. This is achieved by constructing a potential function facilitating a purely probabilistic interpretation of the channel mode. For each network node, the channel mode combines the solutions of emitting and absorbing modes in the same context, producing what we call a channel tensor. The entries of the channel tensor at each node can be interpreted as the amount of flow passing through that node from an origin to a destination. Similarly to our earlier model, the channel mode encompasses damping as a free parameter that controls the locality of information flow. Through examples involving the yeast pheromone response pathway, we illustrate the versatility and stability of our new framework. PMID:22409812

Evidence That Calls-Based and Mobility Networks Are Isomorphic

PubMed Central

Coscia, Michele; Hausmann, Ricardo

2015-01-01

Social relations involve both face-to-face interaction as well as telecommunications. We can observe the geography of phone calls and of the mobility of cell phones in space. These two phenomena can be described as networks of connections between different points in space. We use a dataset that includes billions of phone calls made in Colombia during a six-month period. We draw the two networks and find that the call-based network resembles a higher order aggregation of the mobility network and that both are isomorphic except for a higher spatial decay coefficient of the mobility network relative to the call-based network: when we discount distance effects on the call connections with the same decay observed for mobility connections, the two networks are virtually indistinguishable. PMID:26713730

Complexity measures to track the evolution of a SNOMED hierarchy.

PubMed

Wei, Duo; Wang, Yue; Perl, Yehoshua; Xu, Junchuan; Halper, Michael; Spackman, Kent A; Spackman, Kent

2008-11-06

SNOMED CT is an extensive terminology with an attendant amount of complexity. Two measures are proposed for quantifying that complexity. Both are based on abstraction networks, called the area taxonomy and the partial-area taxonomy, that provide, for example, distributions of the relationships within a SNOMED hierarchy. The complexity measures are employed specifically to track the complexity of versions of the Specimen hierarchy of SNOMED before and after it is put through an auditing process. The pre-audit and post-audit versions are compared. The results show that the auditing process indeed leads to a simplification of the terminology's structure.

The Social Context Network Model in Psychiatric and Neurological Diseases.

PubMed

Baez, Sandra; García, Adolfo M; Ibanez, Agustín

2017-01-01

The role of contextual modulations has been extensively studied in basic sensory and cognitive processes. However, little is known about their impact on social cognition, let alone their disruption in disorders compromising such a domain. In this chapter, we flesh out the social context network model (SCNM), a neuroscientific proposal devised to address the issue. In SCNM terms, social context effects rely on a fronto-temporo-insular network in charge of (a) updating context cues to make predictions, (b) consolidating context-target associative learning, and (c) coordinating internal and external milieus. First, we characterize various social cognition domains as context-dependent phenomena. Then, we review behavioral and neural evidence of social context impairments in behavioral variant frontotemporal dementia (bvFTD) and autism spectrum disorder (ASD), highlighting their relation with key SCNM hubs. Next, we show that other psychiatric and neurological conditions involve context-processing impairments following damage to the brain regions included in the model. Finally, we call for an ecological approach to social cognition assessment, moving beyond widespread abstract and decontextualized methods.

A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies

PubMed Central

Ochs, Christopher; Geller, James; Perl, Yehoshua; Musen, Mark A.

2016-01-01

Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving “live partial-area taxonomies” is demonstrated. PMID:27345947

A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies.

PubMed

Ochs, Christopher; Geller, James; Perl, Yehoshua; Musen, Mark A

2016-08-01

Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving "live partial-area taxonomies" is demonstrated. Copyright © 2016 Elsevier Inc. All rights reserved.

Quality assurance of the gene ontology using abstraction networks.

PubMed

Ochs, Christopher; Perl, Yehoshua; Halper, Michael; Geller, James; Lomax, Jane

2016-06-01

The gene ontology (GO) is used extensively in the field of genomics. Like other large and complex ontologies, quality assurance (QA) efforts for GO's content can be laborious and time consuming. Abstraction networks (AbNs) are summarization networks that reveal and highlight high-level structural and hierarchical aggregation patterns in an ontology. They have been shown to successfully support QA work in the context of various ontologies. Two kinds of AbNs, called the area taxonomy and the partial-area taxonomy, are developed for GO hierarchies and derived specifically for the biological process (BP) hierarchy. Within this framework, several QA heuristics, based on the identification of groups of anomalous terms which exhibit certain taxonomy-defined characteristics, are introduced. Such groups are expected to have higher error rates when compared to other terms. Thus, by focusing QA efforts on anomalous terms one would expect to find relatively more erroneous content. By automatically identifying these potential problem areas within an ontology, time and effort will be saved during manual reviews of GO's content. BP is used as a testbed, with samples of three kinds of anomalous BP terms chosen for a taxonomy-based QA review. Additional heuristics for QA are demonstrated. From the results of this QA effort, it is observed that different kinds of inconsistencies in the modeling of GO can be exposed with the use of the proposed heuristics. For comparison, the results of QA work on a sample of terms chosen from GO's general population are presented.

Quorum-Sensing Signal-Response Systems in Gram-Negative Bacteria

PubMed Central

Papenfort, Kai; Bassler, Bonnie

2016-01-01

Abstract / Preface Bacteria use quorum sensing to orchestrate gene expression programmes that underlie collective behaviours. Quorum sensing relies on the production, release, detection and group-level response to extracellular signalling molecules, which are called autoinducers. Recent work has discovered new autoinducers in Gram-negative bacteria, shown how these molecules are recognized by cognate receptors, revealed new regulatory components that are embedded in canonical signalling circuits and identified novel regulatory network designs. In this Review we examine how, together, these features of quorum sensing signal–response systems combine to control collective behaviours in Gram-negative bacteria and we discuss the implications for host–microbial associations and antibacterial therapy. PMID:27510864

Mitigating Handoff Call Dropping in Wireless Cellular Networks: A Call Admission Control Technique

NASA Astrophysics Data System (ADS)

Ekpenyong, Moses Effiong; Udoh, Victoria Idia; Bassey, Udoma James

2016-06-01

Handoff management has been an important but challenging issue in the field of wireless communication. It seeks to maintain seamless connectivity of mobile users changing their points of attachment from one base station to another. This paper derives a call admission control model and establishes an optimal step-size coefficient (k) that regulates the admission probability of handoff calls. An operational CDMA network carrier was investigated through the analysis of empirical data collected over a period of 1 month, to verify the performance of the network. Our findings revealed that approximately 23 % of calls in the existing system were lost, while 40 % of the calls (on the average) were successfully admitted. A simulation of the proposed model was then carried out under ideal network conditions to study the relationship between the various network parameters and validate our claim. Simulation results showed that increasing the step-size coefficient degrades the network performance. Even at optimum step-size (k), the network could still be compromised in the presence of severe network crises, but our model was able to recover from these problems and still functions normally.

Harvesting Ego-Network Data from Facebook: Using the CEMAP Facebook Profile in ORA

DTIC Science & Technology

2009-02-02

Keywords: Facebook , CEMAP, social network , ORA, dynamic network analysis Abstract...The Facebook social networking site (www.facebook.com) has become a popular phenomenon over the past five years. By its nature, Facebook has...tableset. The Facebook tableset is the CEMAP abstraction of the various levels of technology to harvest the social network data, via the Facebook developer

CALL FOR ABSTRACTS - PIT LAKES 2004

EPA Science Inventory

This call for abstracts is for the 11/16-18/2004 Pit Lakes 2004 meeting held in Reno, NV. This conference will provide a forum for the exchange of scientific information on current domestic and international pit lake approaches, including pit lakes from arid and wet regions throu...

Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.

PubMed

Ochs, Christopher; He, Zhe; Zheng, Ling; Geller, James; Perl, Yehoshua; Hripcsak, George; Musen, Mark A

2016-06-01

An Abstraction Network is a compact summary of an ontology's structure and content. In previous research, we showed that Abstraction Networks support quality assurance (QA) of biomedical ontologies. The development of an Abstraction Network and its associated QA methodologies, however, is a labor-intensive process that previously was applicable only to one ontology at a time. To improve the efficiency of the Abstraction-Network-based QA methodology, we introduced a QA framework that uses uniform Abstraction Network derivation techniques and QA methodologies that are applicable to whole families of structurally similar ontologies. For the family-based framework to be successful, it is necessary to develop a method for classifying ontologies into structurally similar families. We now describe a structural meta-ontology that classifies ontologies according to certain structural features that are commonly used in the modeling of ontologies (e.g., object properties) and that are important for Abstraction Network derivation. Each class of the structural meta-ontology represents a family of ontologies with identical structural features, indicating which types of Abstraction Networks and QA methodologies are potentially applicable to all of the ontologies in the family. We derive a collection of 81 families, corresponding to classes of the structural meta-ontology, that enable a flexible, streamlined family-based QA methodology, offering multiple choices for classifying an ontology. The structure of 373 ontologies from the NCBO BioPortal is analyzed and each ontology is classified into multiple families modeled by the structural meta-ontology. Copyright © 2016 Elsevier Inc. All rights reserved.

FUSE: a profit maximization approach for functional summarization of biological networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes; Yu, Hanry

2012-03-21

The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein interaction network (PPI) using graph theoretic analysis. Despite the recent progress, systems level analysis of PPIS remains a daunting task as it is challenging to make sense out of the deluge of high-dimensional interaction data. Specifically, techniques that automatically abstract and summarize PPIS at multiple resolutions to provide high level views of its functional landscape are still lacking. We present a novel data-driven and generic algorithm called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions, through a pro t maximization approach that exploits Minimum Description Length (MDL) principle to maximize information gain of the summary graph while satisfying the level of detail constraint. We evaluate the performance of FUSE on several real-world PPIS. We also compare FUSE to state-of-the-art graph clustering methods with GO term enrichment by constructing the biological process landscape of the PPIS. Using AD network as our case study, we further demonstrate the ability of FUSE to quickly summarize the network and identify many different processes and complexes that regulate it. Finally, we study the higher-order connectivity of the human PPI. By simultaneously evaluating interaction and annotation data, FUSE abstracts higher-order interaction maps by reducing the details of the underlying PPI to form a functional summary graph of interconnected functional clusters. Our results demonstrate its effectiveness and superiority over state-of-the-art graph clustering methods with GO term enrichment.

Minimum spanning tree analysis of the human connectome

PubMed Central

Sommer, Iris E.; Bohlken, Marc M.; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A.; Douw, Linda; Otte, Willem M.; Mandl, René C.W.; Stam, Cornelis J.

2018-01-01

Abstract One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion‐weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null‐model. The MST of individual subjects matched this reference MST for a mean 58%–88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so‐called rich club nodes (a subset of high‐degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical–subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. PMID:29468769

CALL FOR ABSTRACTS FOR WORKSHOP ON MINING IMPACTED NATIVE AMERICAN LANDS 2003

EPA Science Inventory

This is a Call for Abstracts for a workshop 9/9-11/2003 in Reno, NV, to unite Tribal members and representatives, and other government officials to examine technical and policy issues related to historic, current, and future mining impacts on Native American Lands.

Infection dynamics on spatial small-world network models

NASA Astrophysics Data System (ADS)

Iotti, Bryan; Antonioni, Alberto; Bullock, Seth; Darabos, Christian; Tomassini, Marco; Giacobini, Mario

2017-11-01

The study of complex networks, and in particular of social networks, has mostly concentrated on relational networks, abstracting the distance between nodes. Spatial networks are, however, extremely relevant in our daily lives, and a large body of research exists to show that the distances between nodes greatly influence the cost and probability of establishing and maintaining a link. A random geometric graph (RGG) is the main type of synthetic network model used to mimic the statistical properties and behavior of many social networks. We propose a model, called REDS, that extends energy-constrained RGGs to account for the synergic effect of sharing the cost of a link with our neighbors, as is observed in real relational networks. We apply both the standard Watts-Strogatz rewiring procedure and another method that conserves the degree distribution of the network. The second technique was developed to eliminate unwanted forms of spatial correlation between the degree of nodes that are affected by rewiring, limiting the effect on other properties such as clustering and assortativity. We analyze both the statistical properties of these two network types and their epidemiological behavior when used as a substrate for a standard susceptible-infected-susceptible compartmental model. We consider and discuss the differences in properties and behavior between RGGs and REDS as rewiring increases and as infection parameters are changed. We report considerable differences both between the network types and, in the case of REDS, between the two rewiring schemes. We conclude that REDS represent, with the application of these rewiring mechanisms, extremely useful and interesting tools in the study of social and epidemiological phenomena in synthetic complex networks.

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application

PubMed Central

Rodríguez-Molina, Jesús; Martínez, José-Fernán; Castillejo, Pedro; López, Lourdes

2013-01-01

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained. PMID:23385405

Combining wireless sensor networks and semantic middleware for an Internet of Things-based sportsman/woman monitoring application.

PubMed

Rodríguez-Molina, Jesús; Martínez, José-Fernán; Castillejo, Pedro; López, Lourdes

2013-01-31

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

Professional Preparation of Teachers for Rural Schools: Abstracts of Addresses Delivered at a Conference Called by the United States Commissioner of Education, at the Lenox Hotel, Boston, February 25, 1928. Bulletin, 1928, No. 6

ERIC Educational Resources Information Center

Cook, Katherine M.

1928-01-01

This bulletin contains abstracts of the addresses delivered at a conference called by the United States Commissioner of Education to consider problems concerned with the professional preparation of teachers for rural schools. They were prepared from copies of the addresses or abstracts of them furnished by the speakers who prepared or delivered…

An Improved Call Admission Control Mechanism with Prioritized Handoff Queuing Scheme for BWA Networks

NASA Astrophysics Data System (ADS)

Chowdhury, Prasun; Saha Misra, Iti

2014-10-01

Nowadays, due to increased demand for using the Broadband Wireless Access (BWA) networks in a satisfactory manner a promised Quality of Service (QoS) is required to manage the seamless transmission of the heterogeneous handoff calls. To this end, this paper proposes an improved Call Admission Control (CAC) mechanism with prioritized handoff queuing scheme that aims to reduce dropping probability of handoff calls. Handoff calls are queued when no bandwidth is available even after the allowable bandwidth degradation of the ongoing calls and get admitted into the network when an ongoing call is terminated with a higher priority than the newly originated call. An analytical Markov model for the proposed CAC mechanism is developed to analyze various performance parameters. Analytical results show that our proposed CAC with handoff queuing scheme prioritizes the handoff calls effectively and reduces dropping probability of the system by 78.57% for real-time traffic without degrading the number of failed new call attempts. This results in the increased bandwidth utilization of the network.

Online social network response to studies on antidepressant use in pregnancy.

PubMed

Vigod, Simone N; Bagheri, Ebrahim; Zarrinkalam, Fattane; Brown, Hilary K; Mamdani, Muhammad; Ray, Joel G

2018-03-01

About 8% of U.S women are prescribed antidepressant medications around the time of pregnancy. Decisions about medication use in pregnancy can be swayed by the opinion of family, friends and online media, sometimes beyond the advice offered by healthcare providers. Exploration of the online social network response to research on antidepressant use in pregnancy could provide insight about how to optimize decision-making in this complex area. For all 17 research articles published on the safety of antidepressant use in pregnancy in 2012, we sought to explore online social network activity regarding antidepressant use in pregnancy, via Twitter, in the 48h after a study was published, compared to the social network activity in the same period 1week prior to each article's publication. Online social network activity about antidepressants in pregnancy quickly doubled upon study publication. The increased activity was driven by studies demonstrating harm associated with antidepressants, lower-quality studies, and studies where abstracts presented relative versus absolute risks. These findings support a call for leadership from medical journals to consider how to best incentivize and support a balanced and clear translation of knowledge around antidepressant safety in pregnancy to their readership and the public. Copyright © 2018 Elsevier Inc. All rights reserved.

Linking smokers to a quitline: randomized controlled effectiveness trial of a support person intervention that targets non-smokers

PubMed Central

Patten, Christi A.; Boyle, Raymond; Tinkelman, David; Brockman, Tabetha A.; Lukowski, Amy; Decker, Paul A.; D’Silva, Joanne; Lichtenstein, Edward; Zhu, Shu-Hong

2017-01-01

Abstract Evidence-based treatments (e.g. quitlines) are greatly underutilized by smokers limiting their public health impact. A three-session phone intervention for nonsmoking family members and friends (i.e. support persons) was successful for increasing smoker quitline enrollment. To enhance the intervention’s potential translatability, in this study, we delivered treatment for the non-smoker within ongoing quitline services and compared the efficacy of the three-call intervention to a streamlined version (one call). A total of 704 adult non-smokers (85% female, 95% White) wanting to help a smoker quit and recruited statewide in Minnesota participated in this randomized controlled trial with parallel groups. Non-smokers received mailed written materials and were randomly assigned to a control condition (no additional treatment, n = 235), or to a one- (n = 233) or three-call (n = 236) intervention delivered by quitline coaches. The main outcome was smoker quitline enrollment through 7-month follow-up. Smoker quitline enrollment was similar for those linked to non-smokers in the one- and three-call interventions (14.6% [34/233] and 14.8% [35/236]), and higher than for smokers linked to control participants (6.4% [15/235]), P = 0.006. Just one quitline coaching call delivered to non-smokers increased treatment enrollment among smokers. The reach of quitlines could be enhanced by targeting the social support network of smokers. PMID:28854569

47 CFR 51.5 - Terms and definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

.... The Communications Act of 1934, as amended. Advanced intelligent network. Advanced intelligent network is a telecommunications network architecture in which call processing, call routing, and network... carrier's network. Advanced services. The term “advanced services” is defined as high speed, switched...

CD-ROM source data uploaded to the operating and storage devices of an IBM 3090 mainframe through a PC terminal.

PubMed

Boros, L G; Lepow, C; Ruland, F; Starbuck, V; Jones, S; Flancbaum, L; Townsend, M C

1992-07-01

A powerful method of processing MEDLINE and CINAHL source data uploaded to the IBM 3090 mainframe computer through an IBM/PC is described. Data are first downloaded from the CD-ROM's PC devices to floppy disks. These disks then are uploaded to the mainframe computer through an IBM/PC equipped with WordPerfect text editor and computer network connection (SONNGATE). Before downloading, keywords specifying the information to be accessed are typed at the FIND prompt of the CD-ROM station. The resulting abstracts are downloaded into a file called DOWNLOAD.DOC. The floppy disks containing the information are simply carried to an IBM/PC which has a terminal emulation (TELNET) connection to the university-wide computer network (SONNET) at the Ohio State University Academic Computing Services (OSU ACS). The WordPerfect (5.1) processes and saves the text into DOS format. Using the File Transfer Protocol (FTP, 130,000 bytes/s) of SONNET, the entire text containing the information obtained through the MEDLINE and CINAHL search is transferred to the remote mainframe computer for further processing. At this point, abstracts in the specified area are ready for immediate access and multiple retrieval by any PC having network switch or dial-in connection after the USER ID, PASSWORD and ACCOUNT NUMBER are specified by the user. The system provides the user an on-line, very powerful and quick method of searching for words specifying: diseases, agents, experimental methods, animals, authors, and journals in the research area downloaded. The user can also copy the TItles, AUthors and SOurce with optional parts of abstracts into papers under edition. This arrangement serves the special demands of a research laboratory by handling MEDLINE and CINAHL source data resulting after a search is performed with keywords specified for ongoing projects. Since the Ohio State University has a centrally founded mainframe system, the data upload, storage and mainframe operations are free.

PRELIMINARY ANNOUNCEMENT AND CALL FOR ABSTRACTS - WORKSHOP ON THE FATE, TRANSPORT, AND TRANSFORMATION OF MERCURY IN AQUATIC AND TERRESTRIAL ENVIRONMENTS

EPA Science Inventory

This publication is a preliminary announcement and call-for-abstracts for the 5/2001 Workshop on the Fate, Transport, and Transformation of Mercury in Aquatic and Terrestrial Environments. This workshop will 1) describe the current state of knowledge, gaps, and areas of consensus...

Data Imputation in Epistatic MAPs by Network-Guided Matrix Completion

PubMed Central

Žitnik, Marinka; Zupan, Blaž

2015-01-01

Abstract Epistatic miniarray profile (E-MAP) is a popular large-scale genetic interaction discovery platform. E-MAPs benefit from quantitative output, which makes it possible to detect subtle interactions with greater precision. However, due to the limits of biotechnology, E-MAP studies fail to measure genetic interactions for up to 40% of gene pairs in an assay. Missing measurements can be recovered by computational techniques for data imputation, in this way completing the interaction profiles and enabling downstream analysis algorithms that could otherwise be sensitive to missing data values. We introduce a new interaction data imputation method called network-guided matrix completion (NG-MC). The core part of NG-MC is low-rank probabilistic matrix completion that incorporates prior knowledge presented as a collection of gene networks. NG-MC assumes that interactions are transitive, such that latent gene interaction profiles inferred by NG-MC depend on the profiles of their direct neighbors in gene networks. As the NG-MC inference algorithm progresses, it propagates latent interaction profiles through each of the networks and updates gene network weights toward improved prediction. In a study with four different E-MAP data assays and considered protein–protein interaction and gene ontology similarity networks, NG-MC significantly surpassed existing alternative techniques. Inclusion of information from gene networks also allowed NG-MC to predict interactions for genes that were not included in original E-MAP assays, a task that could not be considered by current imputation approaches. PMID:25658751

OSI Network-layer Abstraction: Analysis of Simulation Dynamics and Performance Indicators

NASA Astrophysics Data System (ADS)

Lawniczak, Anna T.; Gerisch, Alf; Di Stefano, Bruno

2005-06-01

The Open Systems Interconnection (OSI) reference model provides a conceptual framework for communication among computers in a data communication network. The Network Layer of this model is responsible for the routing and forwarding of packets of data. We investigate the OSI Network Layer and develop an abstraction suitable for the study of various network performance indicators, e.g. throughput, average packet delay, average packet speed, average packet path-length, etc. We investigate how the network dynamics and the network performance indicators are affected by various routing algorithms and by the addition of randomly generated links into a regular network connection topology of fixed size. We observe that the network dynamics is not simply the sum of effects resulting from adding individual links to the connection topology but rather is governed nonlinearly by the complex interactions caused by the existence of all randomly added and already existing links in the network. Data for our study was gathered using Netzwerk-1, a C++ simulation tool that we developed for our abstraction.

Spatial-temporal modeling of malware propagation in networks.

PubMed

Chen, Zesheng; Ji, Chuanyi

2005-09-01

Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.

Individual brain structure and modelling predict seizure propagation

PubMed Central

Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K.

2017-01-01

Abstract See Lytton (doi:10.1093/awx018) for a scientific commentary on this article. Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. PMID:28364550

Management software for a universal device communication controller: application to monitoring and computerized infusions.

PubMed

Coussaert, E J; Cantraine, F R

1996-11-01

We designed a virtual device for a local area network observing, operating and connecting devices to a personal computer. To keep the widest field of application, we proceeded by using abstraction and specification rules of software engineering in the design and implementation of the hardware and software for the Infusion Monitor. We specially built a box of hardware to interface multiple medical instruments with different communication protocols to a PC via a single serial port. We called that box the Universal Device Communication Controller (UDCC). The use of the virtual device driver is illustrated by the Infusion Monitor implemented for the anaesthesia and intensive care workstation.

Cyber Analogies

DTIC Science & Technology

2014-02-28

distribution is unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT This anthology of cyber analogies will resonate with readers whose duties call for them...THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT This anthology of cyber analogies will resonate with readers...fresh insights. THE CASE FOR ANALOGIES All of us on the cyber analogies team hope that this anthol- ogy will resonate with readers whose duties call

Neural network submodel as an abstraction tool: relating network performance to combat outcome

NASA Astrophysics Data System (ADS)

Jablunovsky, Greg; Dorman, Clark; Yaworsky, Paul S.

2000-06-01

Simulation of Command and Control (C2) networks has historically emphasized individual system performance with little architectural context or credible linkage to `bottom- line' measures of combat outcomes. Renewed interest in modeling C2 effects and relationships stems from emerging network intensive operational concepts. This demands improved methods to span the analytical hierarchy between C2 system performance models and theater-level models. Neural network technology offers a modeling approach that can abstract the essential behavior of higher resolution C2 models within a campaign simulation. The proposed methodology uses off-line learning of the relationships between network state and campaign-impacting performance of a complex C2 architecture and then approximation of that performance as a time-varying parameter in an aggregated simulation. Ultimately, this abstraction tool offers an increased fidelity of C2 system simulation that captures dynamic network dependencies within a campaign context.

Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

PubMed

Shen, Zeqian; Ma, Kwan-Liu; Eliassi-Rad, Tina

2006-01-01

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks

PubMed Central

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P.; Gerstein, Mark

2010-01-01

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers’ continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems. PMID:20439753

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

PubMed

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

2010-05-18

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.

Tracking fin whales in the northeast Pacific Ocean with a seafloor seismic network.

PubMed

Wilcock, William S D

2012-10-01

Ocean bottom seismometer (OBS) networks represent a tool of opportunity to study fin and blue whales. A small OBS network on the Juan de Fuca Ridge in the northeast Pacific Ocean in ~2.3 km of water recorded an extensive data set of 20-Hz fin whale calls. An automated method has been developed to identify arrival times based on instantaneous frequency and amplitude and to locate calls using a grid search even in the presence of a few bad arrival times. When only one whale is calling near the network, tracks can generally be obtained up to distances of ~15 km from the network. When the calls from multiple whales overlap, user supervision is required to identify tracks. The absolute and relative amplitudes of arrivals and their three-component particle motions provide additional constraints on call location but are not useful for extending the distance to which calls can be located. The double-difference method inverts for changes in relative call locations using differences in residuals for pairs of nearby calls recorded on a common station. The method significantly reduces the unsystematic component of the location error, especially when inconsistencies in arrival time observations are minimized by cross-correlation.

Structural Measures to Track the Evolution of SNOMED CT Hierarchies

PubMed Central

Wei, Duo; Gu, Huanying (Helen); Perl, Yehoshua; Halper, Michael; Ochs, Christopher; Elhanan, Gai; Chen, Yan

2015-01-01

The Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) is an extensive reference terminology with an attendant amount of complexity. It has been updated continuously and revisions have been released semi-annually to meet users’ needs and to reflect the results of quality assurance (QA) activities. Two measures based on structural features are proposed to track the effects of both natural terminology growth and QA activities based on aspects of the complexity of SNOMED CT. These two measures, called the structural density measure and accumulated structural measure, are derived based on two abstraction networks, the area taxonomy and the partial-area taxonomy. The measures derive from attribute relationship distributions and various concept groupings that are associated with the abstraction networks. They are used to track the trends in the complexity of structures as SNOMED CT changes over time. The measures were calculated for consecutive releases of five SNOMED CT hierarchies, including the Specimen hierarchy. The structural density measure shows that natural growth tends to move a hierarchy’s structure toward a more complex state, whereas the accumulated structural measure shows that QA processes tend to move a hierarchy’s structure toward a less complex state. It is also observed that both the structural density and accumulated structural measures are useful tools to track the evolution of an entire SNOMED CT hierarchy and reveal internal concept migration within it. PMID:26260003

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

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

Dasari, Venkat; Sadlier, Ronald J; Geerhart, Mr. Billy

Well-defined and stable quantum networks are essential to realize functional quantum applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. We develop new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

Method and system for conserving power in a telecommunications network during emergency situations

DOEpatents

Conrad, Stephen H [Algodones, NM; O'Reilly, Gerard P [Manalapan, NJ

2011-10-11

Disclosed is a method and apparatus for conserving power in a telecommunications network during emergency situations. A permissible number list of emergency and/or priority numbers is stored in the telecommunications network. In the event of an emergency or power failure, input digits of a call to the telecommunications network are compared to the permissible number list. The call is processed in the telecommunications network and routed to its destination if the input digits match an entry in the permissible number list. The call is dropped without any further processing if the input digits do not match an entry in the permissible number list. Thus, power can be conserved in emergency situations by only allowing emergency and/or priority calls.

Auditing complex concepts of SNOMED using a refined hierarchical abstraction network.

PubMed

Wang, Yue; Halper, Michael; Wei, Duo; Gu, Huanying; Perl, Yehoshua; Xu, Junchuan; Elhanan, Gai; Chen, Yan; Spackman, Kent A; Case, James T; Hripcsak, George

2012-02-01

Auditors of a large terminology, such as SNOMED CT, face a daunting challenge. To aid them in their efforts, it is essential to devise techniques that can automatically identify concepts warranting special attention. "Complex" concepts, which by their very nature are more difficult to model, fall neatly into this category. A special kind of grouping, called a partial-area, is utilized in the characterization of complex concepts. In particular, the complex concepts that are the focus of this work are those appearing in intersections of multiple partial-areas and are thus referred to as overlapping concepts. In a companion paper, an automatic methodology for identifying and partitioning the entire collection of overlapping concepts into disjoint, singly-rooted groups, that are more manageable to work with and comprehend, has been presented. The partitioning methodology formed the foundation for the development of an abstraction network for the overlapping concepts called a disjoint partial-area taxonomy. This new disjoint partial-area taxonomy offers a collection of semantically uniform partial-areas and is exploited herein as the basis for a novel auditing methodology. The review of the overlapping concepts is done in a top-down order within semantically uniform groups. These groups are themselves reviewed in a top-down order, which proceeds from the less complex to the more complex overlapping concepts. The results of applying the methodology to SNOMED's Specimen hierarchy are presented. Hypotheses regarding error ratios for overlapping concepts and between different kinds of overlapping concepts are formulated. Two phases of auditing the Specimen hierarchy for two releases of SNOMED are reported on. With the use of the double bootstrap and Fisher's exact test (two-tailed), the auditing of concepts and especially roots of overlapping partial-areas is shown to yield a statistically significant higher proportion of errors. Copyright © 2011 Elsevier Inc. All rights reserved.

Auditing Complex Concepts of SNOMED using a Refined Hierarchical Abstraction Network

PubMed Central

Wang, Yue; Halper, Michael; Wei, Duo; Gu, Huanying; Perl, Yehoshua; Xu, Junchuan; Elhanan, Gai; Chen, Yan; Spackman, Kent A.; Case, James T.; Hripcsak, George

2012-01-01

Auditors of a large terminology, such as SNOMED CT, face a daunting challenge. To aid them in their efforts, it is essential to devise techniques that can automatically identify concepts warranting special attention. “Complex” concepts, which by their very nature are more difficult to model, fall neatly into this category. A special kind of grouping, called a partial-area, is utilized in the characterization of complex concepts. In particular, the complex concepts that are the focus of this work are those appearing in intersections of multiple partial-areas and are thus referred to as overlapping concepts. In a companion paper, an automatic methodology for identifying and partitioning the entire collection of overlapping concepts into disjoint, singly-rooted groups, that are more manageable to work with and comprehend, has been presented. The partitioning methodology formed the foundation for the development of an abstraction network for the overlapping concepts called a disjoint partial-area taxonomy. This new disjoint partial-area taxonomy offers a collection of semantically uniform partial-areas and is exploited herein as the basis for a novel auditing methodology. The review of the overlapping concepts is done in a top-down order within semantically uniform groups. These groups are themselves reviewed in a top-down order, which proceeds from the less complex to the more complex overlapping concepts. The results of applying the methodology to SNOMED’s Specimen hierarchy are presented. Hypotheses regarding error ratios for overlapping concepts and between different kinds of overlapping concepts are formulated. Two phases of auditing the Specimen hierarchy for two releases of SNOMED are reported on. With the use of the double bootstrap and Fisher’s exact test (two-tailed), the auditing of concepts and especially roots of overlapping partial-areas is shown to yield a statistically significant higher proportion of errors. PMID:21907827

IP Infrastructure Geolocation

DTIC Science & Technology

2015-03-01

unlimited 13. ABSTRACT (maximum 200 words) Physical network maps are important to critical infrastructure defense and planning. Current state-of...the-art network infrastructure geolocation relies on Domain Name System (DNS) inferences. However, not only is using the DNS relatively inaccurate for...INTENTIONALLY LEFT BLANK iv ABSTRACT Physical network maps are important to critical infrastructure defense and planning. Cur- rent state-of-the-art

Boosting compound-protein interaction prediction by deep learning.

PubMed

Tian, Kai; Shao, Mingyu; Wang, Yang; Guan, Jihong; Zhou, Shuigeng

2016-11-01

The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear and imbalanced nature of biological data, many machine learning approaches have their own limitations. Recently, deep learning techniques show advantages over many state-of-the-art machine learning methods in some applications. In this study, we aim at improving the performance of CPI prediction based on deep learning, and propose a method called DL-CPI (the abbreviation of Deep Learning for Compound-Protein Interactions prediction), which employs deep neural network (DNN) to effectively learn the representations of compound-protein pairs. Extensive experiments show that DL-CPI can learn useful features of compound-protein pairs by a layerwise abstraction, and thus achieves better prediction performance than existing methods on both balanced and imbalanced datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

Entropy of dynamical social networks

NASA Astrophysics Data System (ADS)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

An approach to efficient mobility management in intelligent networks

NASA Technical Reports Server (NTRS)

Murthy, K. M. S.

1995-01-01

Providing personal communication systems supporting full mobility require intelligent networks for tracking mobile users and facilitating outgoing and incoming calls over different physical and network environments. In realizing the intelligent network functionalities, databases play a major role. Currently proposed network architectures envision using the SS7-based signaling network for linking these DB's and also for interconnecting DB's with switches. If the network has to support ubiquitous, seamless mobile services, then it has to support additionally mobile application parts, viz., mobile origination calls, mobile destination calls, mobile location updates and inter-switch handovers. These functions will generate significant amount of data and require them to be transferred between databases (HLR, VLR) and switches (MSC's) very efficiently. In the future, the users (fixed or mobile) may use and communicate with sophisticated CPE's (e.g. multimedia, multipoint and multisession calls) which may require complex signaling functions. This will generate volumness service handling data and require efficient transfer of these message between databases and switches. Consequently, the network providers would be able to add new services and capabilities to their networks incrementally, quickly and cost-effectively.

Brain network response underlying decisions about abstract reinforcers.

PubMed

Mills-Finnerty, Colleen; Hanson, Catherine; Hanson, Stephen Jose

2014-12-01

Decision making studies typically use tasks that involve concrete action-outcome contingencies, in which subjects do something and get something. No studies have addressed decision making involving abstract reinforcers, where there are no action-outcome contingencies and choices are entirely hypothetical. The present study examines these kinds of choices, as well as whether the same biases that exist for concrete reinforcer decisions, specifically framing effects, also apply during abstract reinforcer decisions. We use both General Linear Model as well as Bayes network connectivity analysis using the Independent Multi-sample Greedy Equivalence Search (IMaGES) algorithm to examine network response underlying choices for abstract reinforcers under positive and negative framing. We find for the first time that abstract reinforcer decisions activate the same network of brain regions as concrete reinforcer decisions, including the striatum, insula, anterior cingulate, and VMPFC, results that are further supported via comparison to a meta-analysis of decision making studies. Positive and negative framing activated different parts of this network, with stronger activation in VMPFC during negative framing and in DLPFC during positive, suggesting different decision making pathways depending on frame. These results were further clarified using connectivity analysis, which revealed stronger connections between anterior cingulate, insula, and accumbens during negative framing compared to positive. Taken together, these results suggest that not only do abstract reinforcer decisions rely on the same brain substrates as concrete reinforcers, but that the response underlying framing effects on abstract reinforcers also resemble those for concrete reinforcers, specifically increased limbic system connectivity during negative frames. Copyright © 2014 Elsevier Inc. All rights reserved.

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

NASA Astrophysics Data System (ADS)

Dasari, Venkat R.; Sadlier, Ronald J.; Geerhart, Billy E.; Snow, Nikolai A.; Williams, Brian P.; Humble, Travis S.

2017-05-01

Well-defined and stable quantum networks are essential to realize functional quantum communication applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. In this paper, we describe new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

Novel interpretation of the mean structure of feroxyhyte

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

Sestu, Matteo, E-mail: msestu@unica.it; Carta, Daniela; Casula, Maria F.

2015-05-15

The structure of the iron oxyhydroxide called feroxyhyte (δ-FeOOH), which shows an elusive X-ray powder diffraction pattern, has been represented so far using models describing a mean structure based on the crystalline network of the iron(III) oxide hematite (α-Fe{sub 2}O{sub 3}). In this paper, a novel description of the mean structure of feroxyhyte is presented, which is based on the structure of the thermodynamically stable iron oxyhydroxide goethite. Starting from different local arrangements present in the goethite network, a mean structural model is determined which shows an X-ray powder diffraction pattern almost coincident with previous studies. This outcome enables tomore » integrate the structure of feroxyhyte among those of other well characterized iron oxyhydroxides. - Graphical abstract: The structure of the iron oxy-hydroxide feroxyhyte can be described by local arrangements present in the goethite network. - Highlights: • The structure of feroxyhyte (δ-FeOOH) proposed in literature is discussed. • The structure of goethite (α-FeOOH) is analyzed. • A structural relationship between feroxyhyte and goethite is found. • New interpretation of the mean structure of δ-FeOOH is given.« less

Voice over internet protocol with prepaid calling card solutions

NASA Astrophysics Data System (ADS)

Gunadi, Tri

2001-07-01

The VoIP technology is growing up rapidly, it has big network impact on PT Telkom Indonesia, the bigger telecommunication operator in Indonesia. Telkom has adopted VoIP and one other technology, Intelligent Network (IN). We develop those technologies together in one service product, called Internet Prepaid Calling Card (IPCC). IPCC is becoming new breakthrough for the Indonesia telecommunication services especially on VoIP and Prepaid Calling Card solutions. Network architecture of Indonesia telecommunication consists of three layer, Local, Tandem and Trunck Exchange layer. Network development researches for IPCC architecture are focus on network overlay hierarchy, Internet and PSTN. With this design hierarchy the goal of Interworking PSTN, VoIP and IN calling card, become reality. Overlay design for IPCC is not on Trunck Exchange, this is the new architecture, these overlay on Tandem and Local Exchange, to make the faster call processing. The nodes added: Gateway (GW) and Card Management Center (CMC) The GW do interfacing between PSTN and Internet Network used ISDN-PRA and Ethernet. The other functions are making bridge on circuit (PSTN) with packet (VoIP) based and real time billing process. The CMC used for data storage, pin validation, report activation, tariff system, directory number and all the administration transaction. With two nodes added the IPCC service offered to the market.

Design of real-time voice over internet protocol system under bandwidth network

NASA Astrophysics Data System (ADS)

Zhang, Li; Gong, Lina

2017-04-01

With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

An object-oriented design for automated navigation of semantic networks inside a medical data dictionary.

PubMed

Ruan, W; Bürkle, T; Dudeck, J

2000-01-01

In this paper we present a data dictionary server for the automated navigation of information sources. The underlying knowledge is represented within a medical data dictionary. The mapping between medical terms and information sources is based on a semantic network. The key aspect of implementing the dictionary server is how to represent the semantic network in a way that is easier to navigate and to operate, i.e. how to abstract the semantic network and to represent it in memory for various operations. This paper describes an object-oriented design based on Java that represents the semantic network in terms of a group of objects. A node and its relationships to its neighbors are encapsulated in one object. Based on such a representation model, several operations have been implemented. They comprise the extraction of parts of the semantic network which can be reached from a given node as well as finding all paths between a start node and a predefined destination node. This solution is independent of any given layout of the semantic structure. Therefore the module, called Giessen Data Dictionary Server can act independent of a specific clinical information system. The dictionary server will be used to present clinical information, e.g. treatment guidelines or drug information sources to the clinician in an appropriate working context. The server is invoked from clinical documentation applications which contain an infobutton. Automated navigation will guide the user to all the information relevant to her/his topic, which is currently available inside our closed clinical network.

Detailed temporal structure of communication networks in groups of songbirds.

PubMed

Stowell, Dan; Gill, Lisa; Clayton, David

2016-06-01

Animals in groups often exchange calls, in patterns whose temporal structure may be influenced by contextual factors such as physical location and the social network structure of the group. We introduce a model-based analysis for temporal patterns of animal call timing, originally developed for networks of firing neurons. This has advantages over cross-correlation analysis in that it can correctly handle common-cause confounds and provides a generative model of call patterns with explicit parameters for the influences between individuals. It also has advantages over standard Markovian analysis in that it incorporates detailed temporal interactions which affect timing as well as sequencing of calls. Further, a fitted model can be used to generate novel synthetic call sequences. We apply the method to calls recorded from groups of domesticated zebra finch (Taeniopygia guttata) individuals. We find that the communication network in these groups has stable structure that persists from one day to the next, and that 'kernels' reflecting the temporal range of influence have a characteristic structure for a calling individual's effect on itself, its partner and on others in the group. We further find characteristic patterns of influences by call type as well as by individual. © 2016 The Authors.

Abstract Algebra for Teachers: An Evaluative Case Study

ERIC Educational Resources Information Center

Hoffman, Andrew Joseph

2017-01-01

This manuscript describes the study of an abstract algebra course for preservice secondary mathematics teachers (PSMTs). Often, courses in abstract algebra have not been viewed as productive, beneficial learning experiences for future teachers, both by researchers and PSMTs themselves. This despite calls for increased content knowledge for…

Benefits of an Object-oriented Database Representation for Controlled Medical Terminologies

PubMed Central

Gu, Huanying; Halper, Michael; Geller, James; Perl, Yehoshua

1999-01-01

Objective: Controlled medical terminologies (CMTs) have been recognized as important tools in a variety of medical informatics applications, ranging from patient-record systems to decision-support systems. Controlled medical terminologies are typically organized in semantic network structures consisting of tens to hundreds of thousands of concepts. This overwhelming size and complexity can be a serious barrier to their maintenance and widespread utilization. The authors propose the use of object-oriented databases to address the problems posed by the extensive scope and high complexity of most CMTs for maintenance personnel and general users alike. Design: The authors present a methodology that allows an existing CMT, modeled as a semantic network, to be represented as an equivalent object-oriented database. Such a representation is called an object-oriented health care terminology repository (OOHTR). Results: The major benefit of an OOHTR is its schema, which provides an important layer of structural abstraction. Using the high-level view of a CMT afforded by the schema, one can gain insight into the CMT's overarching organization and begin to better comprehend it. The authors' methodology is applied to the Medical Entities Dictionary (MED), a large CMT developed at Columbia-Presbyterian Medical Center. Examples of how the OOHTR schema facilitated updating, correcting, and improving the design of the MED are presented. Conclusion: The OOHTR schema can serve as an important abstraction mechanism for enhancing comprehension of a large CMT, and thus promotes its usability. PMID:10428002

Using Virtual Social Networks for Case Finding in Clinical Studies: An Experiment from Adolescence, Brain, Cognition, and Diabetes Study.

PubMed

Pourabbasi, Ata; Farzami, Jalal; Shirvani, Mahbubeh-Sadat Ebrahimnegad; Shams, Amir Hossein; Larijani, Bagher

2017-01-01

One of the main usages of social networks in clinical studies is facilitating the process of sampling and case finding for scientists. The main focus of this study is on comparing two different methods of sampling through phone calls and using social network, for study purposes. One of the researchers started calling 214 families of children with diabetes during 90 days. After this period, phone calls stopped, and the team started communicating with families through telegram, a virtual social network for 30 days. The number of children who participated in the study was evaluated. Although the telegram method was 60 days shorter than the phone call method, researchers found that the number of participants from telegram (17.6%) did not have any significant differences compared with the ones being phone called (12.9%). Using social networks can be suggested as a beneficial method for local researchers who look for easier sampling methods, winning their samples' trust, following up with the procedure, and an easy-access database.

Abstraction in Mathematics and Mathematics Learning

ERIC Educational Resources Information Center

Mitchelmore, Michael; White, Paul

2004-01-01

It is claimed that, since mathematics is essentially a self-contained system, mathematical objects may best be described as "abstract-apart." On the other hand, fundamental mathematical ideas are closely related to the real world and their learning involves empirical concepts. These concepts may be called "abstract-general" because they embody…

High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Voice Call Analysis

DTIC Science & Technology

2015-09-01

Gateway 2 4. Voice Packet Flow: SIP , Session Description Protocol (SDP), and RTP 3 5. Voice Data Analysis 5 6. Call Analysis 6 7. Call Metrics 6...analysis processing is designed for a general VoIP system architecture based on Session Initiation Protocol ( SIP ) for negotiating call sessions and...employs Skinny Client Control Protocol for network communication between the phone and the local CallManager (e.g., for each dialed digit), SIP

Assessing the Effects of Multi-Node Sensor Network Configurations on the Operational Tempo

DTIC Science & Technology

2014-09-01

receiver, nP is the noise power of the receiver, and iL is the implementation loss of the receiver due to hardware manufacturing. The received...13. ABSTRACT (maximum 200 words) The LPISimNet software tool provides the capability to quantify the performance of sensor network configurations by...INTENTIONALLY LEFT BLANK v ABSTRACT The LPISimNet software tool provides the capability to quantify the performance of sensor network configurations

Biomedical hypothesis generation by text mining and gene prioritization.

PubMed

Petric, Ingrid; Ligeti, Balazs; Gyorffy, Balazs; Pongor, Sandor

2014-01-01

Text mining methods can facilitate the generation of biomedical hypotheses by suggesting novel associations between diseases and genes. Previously, we developed a rare-term model called RaJoLink (Petric et al, J. Biomed. Inform. 42(2): 219-227, 2009) in which hypotheses are formulated on the basis of terms rarely associated with a target domain. Since many current medical hypotheses are formulated in terms of molecular entities and molecular mechanisms, here we extend the methodology to proteins and genes, using a standardized vocabulary as well as a gene/protein network model. The proposed enhanced RaJoLink rare-term model combines text mining and gene prioritization approaches. Its utility is illustrated by finding known as well as potential gene-disease associations in ovarian cancer using MEDLINE abstracts and the STRING database.

Network Visualization Project (NVP)

DTIC Science & Technology

2016-07-01

network visualization, network traffic analysis, network forensics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF...shell, is a command-line framework used for network forensic analysis. Dshell processes existing pcap files and filters output information based on

Analysis of competition between transformation pathways in the functioning of biotic abstract dual automata.

PubMed

Popa, Radu; Cimpoiasu, Vily M

2013-05-01

Properties of avenues of transformation and their mutualism with forms of organization in dynamic systems are essential for understanding the evolution of prebiotic order. We have analyzed competition between two avenues of transformation in an A↔B system, using the simulation approach called BiADA (Biotic Abstract Dual Automata). We discuss means of avoiding common pitfalls of abstract system modeling and benefits of BiADA-based simulations. We describe the effect of the availability of free energy, energy sink magnitude, and autocatalysis on the evolution of energy flux and order in the system. Results indicate that prebiotic competition between avenues of transformation was more stringent in energy-limited environments. We predict that in such conditions the efficiency of autocatalysis during competition between alternative system states will increase for systems with forms of organization having short half-lives and thus information that is time-sensitive to energy starvation. Our results also offer a potential solution to Manfred Eigen's error catastrophe dilemma. In the conditions discussed above, the exponential growth of quasi species is curbed through the removal of less competitive "genetic" variants via energy starvation. We propose that one of the most important achievements (and selective edges) of a dynamic network during competition in energy-limited or energy-variable environments was the capacity to correlate the internal energy flux and the need for free energy with the availability of free energy in the environment.

GUIdock-VNC: using a graphical desktop sharing system to provide a browser-based interface for containerized software

PubMed Central

Mittal, Varun; Hung, Ling-Hong; Keswani, Jayant; Kristiyanto, Daniel; Lee, Sung Bong

2017-01-01

Abstract Background: Software container technology such as Docker can be used to package and distribute bioinformatics workflows consisting of multiple software implementations and dependencies. However, Docker is a command line–based tool, and many bioinformatics pipelines consist of components that require a graphical user interface. Results: We present a container tool called GUIdock-VNC that uses a graphical desktop sharing system to provide a browser-based interface for containerized software. GUIdock-VNC uses the Virtual Network Computing protocol to render the graphics within most commonly used browsers. We also present a minimal image builder that can add our proposed graphical desktop sharing system to any Docker packages, with the end result that any Docker packages can be run using a graphical desktop within a browser. In addition, GUIdock-VNC uses the Oauth2 authentication protocols when deployed on the cloud. Conclusions: As a proof-of-concept, we demonstrated the utility of GUIdock-noVNC in gene network inference. We benchmarked our container implementation on various operating systems and showed that our solution creates minimal overhead. PMID:28327936

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

NASA Astrophysics Data System (ADS)

Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

PubMed

Sadeghi, Zahra

2016-09-01

In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

Announcements

NASA Astrophysics Data System (ADS)

1997-10-01

NSF-Course and Curriculum Development Program Call for Award Nominations Gordon Conference- Innocations in College Chemistry Teaching Summer Opportunity for Students High School Chemistry Day ACS Satellite TV Seminars Wanted - Newletter Editor ACS Abstract Deadline Call for Award Nominations

Practice‐based Research Network Research Good Practices (PRGPs): Summary of Recommendations

PubMed Central

Campbell‐Voytal, Kimberly; Daly, Jeanette; Nagykaldi, Zsolt J.; O'Beirne, Maeve; Sterling, Pamela; Fagnan, Lyle J.; Levy, Barcey; Michaels, LeAnn; Louks, Hannah A.; Smith, Paul; Aspy, Cheryl B.; Patterson, V. Beth; Kano, Miria; Sussman, Andrew L.; Williams, Robert; Neale, Anne Victoria

2015-01-01

Abstract Introduction Practice‐based research networks (PBRNs) conduct research in community settings, which poses quality control challenges to the integrity of research, such as study implementation and data collection. A foundation for improving research processes within PBRNs is needed to ensure research integrity. Methods Network directors and coordinators from seven U.S.‐based PBRNs worked with a professional team facilitator during semiannual in‐person meetings and monthly conference calls to produce content for a compendium of recommended research practices specific to the context of PBRNs. Participants were assigned to contribute content congruent with their expertise. Feedback on the draft document was obtained from attendees at the preconference workshop at the annual PBRN meeting in 2013. A revised document was circulated to additional PBRN peers prior to finalization. Results The PBRN Research Good Practices (PRGPs) document is organized into four chapters: (1) Building PBRN Infrastructure; (2) Study Development and Implementation; (3) Data Management, and (4) Dissemination Policies. Each chapter contains an introduction, detailed procedures for each section, and example resources with information links. Conclusion The PRGPs is a PBRN‐specific resource to facilitate PBRN management and staff training, to promote adherence to study protocols, and to increase validity and generalizability of study findings. PMID:26296309

Fin whale tracks recorded by a seismic network on the Juan de Fuca Ridge, Northeast Pacific Ocean.

PubMed

Soule, Dax C; Wilcock, William S D

2013-03-01

Fin whale calls recorded from 2003 to 2004 by a seafloor seismic network on the Endeavour segment of the Juan de Fuca Ridge were analyzed to determine tracks and calling patterns. Over 150 tracks were obtained with a total duration of ~800 h and swimming speeds from 1 to 12 km/h. The dominant inter-pulse interval (IPI) is 24 s and the IPI patterns define 4 categories: a 25 s single IPI and 24/30 s dual IPI produced by single calling whales, a 24/13 s dual IPI interpreted as two calling whales, and an irregular IPI interpreted as groups of calling whales. There are also tracks in which the IPI switches between categories. Call rates vary seasonally with all the tracks between August and April. From August to October tracks are dominated by the irregular IPI and are predominantly headed to the northwest, suggesting that a portion of the fin whale population does not migrate south in the fall. The other IPI categories occur primarily from November to March. These tracks have slower swimming speeds, tend to meander, and are predominantly to the south. The distribution of fin whales around the network is non-random with more calls near the network and to the east and north.

Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task

ERIC Educational Resources Information Center

Tabor, Whitney; Cho, Pyeong W.; Dankowicz, Harry

2013-01-01

Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the…

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Impact of a Regional Pharmacy Call Center on Telephone Access Metrics Within the Veterans Health Administration.

PubMed

White, Christina A; Jones, Marshall R; Kuester, Melanie K; Myers, Kelly L; Schnarr, Barbara A

2015-05-01

To establish a cost-effective centralized pharmacy call center to serve the patients of Veterans Integrated Service Network (VISN) 11 that would meet established performance metrics. A pilot project began in August 2011 with the Indianapolis VA Medical Center (VAMC) and the Health Resource Center (HRC) in Topeka, Kansas. The Indianapolis VAMC used a first-call resolution business model consisting of pharmacy technicians receiving tier 1 phone calls that could be escalated to a tier 2 line that consisted of lead technicians and pharmacists, while the HRC utilized general telephone agents that would transfer unresolved calls to the primary facility. Pre- and post-VISN 11 Pharmacy Call Center performance metrics were compared for each of the 7 facilities in the network with the goals being monthly average abandoned call rate less than 5% and average speed to answer less than 30 seconds. Cost per call was also compared. The average abandoned call rate for the network during the year prior to VISN 11 Pharmacy Call Center implementation (August 2010-July 2011) was 15.66% and decreased to 3% in July 2014. The average abandoned call rate decreased for each individual facility. In fiscal year 2014, the VISN 11 Pharmacy Call Center was operating at a cost of $4.35 per call while providing more services than the HRC, resulting in less workload being transferred back to the individual facilities. A centralized VISN pharmacy call center is a reasonable alternative to individual facility call centers or the HRC.

Neural-tree call admission controller for ATM networks

NASA Astrophysics Data System (ADS)

Rughooputh, Harry C. S.

1999-03-01

Asynchronous Transfer Mode (ATM) has been recommended by ITU-T as the transport method for broadband integrated services digital networks. In high-speed ATM networks different types of multimedia traffic streams with widely varying traffic characteristics and Quality of Service (QoS) are asynchronously multiplexed on transmission links and switched without window flow control as found in X.25. In such an environment, a traffic control scheme is required to manage the required QoS of each class individually. To meet the QoS requirements, Bandwidth Allocation and Call Admission Control (CAC) in ATM networks must be able to adapt gracefully to the dynamic behavior of traffic and the time-varying nature of the network condition. In this paper, a Neural Network approach for CAC is proposed. The call admission problem is addressed by designing controllers based on Neural Tree Networks. Simulations reveal that the proposed scheme is not only simple but it also offers faster response than conventional neural/neuro-fuzzy controllers.

A fuzzy call admission control scheme in wireless networks

NASA Astrophysics Data System (ADS)

Ma, Yufeng; Gong, Shenguang; Hu, Xiulin; Zhang, Yunyu

2007-11-01

Scarcity of the spectrum resource and mobility of users make quality of service (QoS) provision a critical issue in wireless networks. This paper presents a fuzzy call admission control scheme to meet the requirement of the QoS. A performance measure is formed as a weighted linear function of new call and handoff call blocking probabilities. Simulation compares the proposed fuzzy scheme with an adaptive channel reservation scheme. Simulation results show that fuzzy scheme has a better robust performance in terms of average blocking criterion.

Output power distributions of terminals in a 3G mobile communication network.

PubMed

Persson, Tomas; Törnevik, Christer; Larsson, Lars-Eric; Lovén, Jan

2012-05-01

The objective of this study was to examine the distribution of the output power of mobile phones and other terminals connected to a 3G network in Sweden. It is well known that 3G terminals can operate with very low output power, particularly for voice calls. Measurements of terminal output power were conducted in the Swedish TeliaSonera 3G network in November 2008 by recording network statistics. In the analysis, discrimination was made between rural, suburban, urban, and dedicated indoor networks. In addition, information about terminal output power was possible to collect separately for voice and data traffic. Information from six different Radio Network Controllers (RNCs) was collected during at least 1 week. In total, more than 800000 h of voice calls were collected and in addition to that a substantial amount of data traffic. The average terminal output power for 3G voice calls was below 1 mW for any environment including rural, urban, and dedicated indoor networks. This is <1% of the maximum available output power. For data applications the average output power was about 6-8 dB higher than for voice calls. For rural areas the output power was about 2 dB higher, on average, than in urban areas. Copyright © 2011 Wiley Periodicals, Inc.

Automated detection and localization of bowhead whale sounds in the presence of seismic airgun surveys.

PubMed

Thode, Aaron M; Kim, Katherine H; Blackwell, Susanna B; Greene, Charles R; Nations, Christopher S; McDonald, Trent L; Macrander, A Michael

2012-05-01

An automated procedure has been developed for detecting and localizing frequency-modulated bowhead whale sounds in the presence of seismic airgun surveys. The procedure was applied to four years of data, collected from over 30 directional autonomous recording packages deployed over a 280 km span of continental shelf in the Alaskan Beaufort Sea. The procedure has six sequential stages that begin by extracting 25-element feature vectors from spectrograms of potential call candidates. Two cascaded neural networks then classify some feature vectors as bowhead calls, and the procedure then matches calls between recorders to triangulate locations. To train the networks, manual analysts flagged 219 471 bowhead call examples from 2008 and 2009. Manual analyses were also used to identify 1.17 million transient signals that were not whale calls. The network output thresholds were adjusted to reject 20% of whale calls in the training data. Validation runs using 2007 and 2010 data found that the procedure missed 30%-40% of manually detected calls. Furthermore, 20%-40% of the sounds flagged as calls are not present in the manual analyses; however, these extra detections incorporate legitimate whale calls overlooked by human analysts. Both manual and automated methods produce similar spatial and temporal call distributions.

Packet Traffic Dynamics Near Onset of Congestion in Data Communication Network Model

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-05-01

The dominant technology of data communication networks is the Packet Switching Network (PSN). It is a complex technology organized as various hierarchical layers according to the International Standard Organization (ISO) Open Systems Interconnect (OSI) Reference Model. The Network Layer of the ISO OSI Reference Model is responsible for delivering packets from their sources to their destinations and for dealing with congestion if it arises in a network. Thus, we focus on this layer and present an abstraction of the Network Layer of the ISO OSI Reference Model. Using this abstraction we investigate how onset of traffic congestion is affected for various routing algorithms by changes in network connection topology. We study how aggregate measures of network performance depend on network connection topology and routing. We explore packets traffic spatio-temporal dynamics near the phase transition point from free flow to congestion for various network connection topologies and routing algorithms. We consider static and adaptive routings. We present selected simulation results.

Dynamic Multiple-Threshold Call Admission Control Based on Optimized Genetic Algorithm in Wireless/Mobile Networks

NASA Astrophysics Data System (ADS)

Wang, Shengling; Cui, Yong; Koodli, Rajeev; Hou, Yibin; Huang, Zhangqin

Due to the dynamics of topology and resources, Call Admission Control (CAC) plays a significant role for increasing resource utilization ratio and guaranteeing users' QoS requirements in wireless/mobile networks. In this paper, a dynamic multi-threshold CAC scheme is proposed to serve multi-class service in a wireless/mobile network. The thresholds are renewed at the beginning of each time interval to react to the changing mobility rate and network load. To find suitable thresholds, a reward-penalty model is designed, which provides different priorities between different service classes and call types through different reward/penalty policies according to network load and average call arrival rate. To speed up the running time of CAC, an Optimized Genetic Algorithm (OGA) is presented, whose components such as encoding, population initialization, fitness function and mutation etc., are all optimized in terms of the traits of the CAC problem. The simulation demonstrates that the proposed CAC scheme outperforms the similar schemes, which means the optimization is realized. Finally, the simulation shows the efficiency of OGA.

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.

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.

Auditing Complex Concepts in Overlapping Subsets of SNOMED

PubMed Central

Wang, Yue; Wei, Duo; Xu, Junchuan; Elhanan, Gai; Perl, Yehoshua; Halper, Michael; Chen, Yan; Spackman, Kent A.; Hripcsak, George

2008-01-01

Limited resources and the sheer volume of concepts make auditing a large terminology, such as SNOMED CT, a daunting task. It is essential to devise techniques that can aid an auditor by automatically identifying concepts that deserve attention. A methodology for this purpose based on a previously introduced abstraction network (called the p-area taxonomy) for a SNOMED CT hierarchy is presented. The methodology algorithmically gathers concepts appearing in certain overlapping subsets, defined exclusively with respect to the p-area taxonomy, for review. The results of applying the methodology to SNOMED’s Specimen hierarchy are presented. These results are compared against a control sample composed of concepts residing in subsets without the overlaps. With the use of the double bootstrap, the concept group produced by our methodology is shown to yield a statistically significant higher proportion of error discoveries. PMID:18998838

Auditing complex concepts in overlapping subsets of SNOMED.

PubMed

Wang, Yue; Wei, Duo; Xu, Junchuan; Elhanan, Gai; Perl, Yehoshua; Halper, Michael; Chen, Yan; Spackman, Kent A; Hripcsak, George

2008-11-06

Limited resources and the sheer volume of concepts make auditing a large terminology, such as SNOMED CT, a daunting task. It is essential to devise techniques that can aid an auditor by automatically identifying concepts that deserve attention. A methodology for this purpose based on a previously introduced abstraction network (called the p-area taxonomy) for a SNOMED CT hierarchy is presented. The methodology algorithmically gathers concepts appearing in certain overlapping subsets, defined exclusively with respect to the p-area taxonomy, for review. The results of applying the methodology to SNOMED's Specimen hierarchy are presented. These results are compared against a control sample composed of concepts residing in subsets without the overlaps. With the use of the double bootstrap, the concept group produced by our methodology is shown to yield a statistically significant higher proportion of error discoveries.

Structural methodologies for auditing SNOMED.

PubMed

Wang, Yue; Halper, Michael; Min, Hua; Perl, Yehoshua; Chen, Yan; Spackman, Kent A

2007-10-01

SNOMED is one of the leading health care terminologies being used worldwide. As such, quality assurance is an important part of its maintenance cycle. Methodologies for auditing SNOMED based on structural aspects of its organization are presented. In particular, automated techniques for partitioning SNOMED into smaller groups of concepts based primarily on relationships patterns are defined. Two abstraction networks, the area taxonomy and p-area taxonomy, are derived from the partitions. The high-level views afforded by these abstraction networks form the basis for systematic auditing. The networks tend to highlight errors that manifest themselves as irregularities at the abstract level. They also support group-based auditing, where sets of purportedly similar concepts are focused on for review. The auditing methodologies are demonstrated on one of SNOMED's top-level hierarchies. Errors discovered during the auditing process are reported.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

PubMed

Burbank, Kendra S

2015-12-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

PubMed Central

Burbank, Kendra S.

2015-01-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645

The integration of citizens into a science/policy network in genetics: governance arrangements and asymmetry in expertise

PubMed Central

Daudelin, Geneviève; Lehoux, Pascale; Abelson, Julia; Denis, Jean L.

2010-01-01

Abstract Objectives  While there are increasing calls for public input into health research and policy, the actual obtaining of such input faces many challenges in practice. This article examines how a Canadian science/policy network in the field of genetics integrated citizens into its structure and then managed their participation. Methods  Our ethnographic case study covers a 5‐year period (2003–08) and combines four data sources: observations of the network’s meetings and informal activities, debriefing sessions with the network’s leaders, semi‐structured interviews with network members (n = 20) and document analysis. Results  When setting up the network, the leaders wanted to include a range of perspectives (research, clinical and policy) to increase the relevance of their research production and knowledge‐transfer activities. After 2 years of operation, the network’s members agreed to also include citizens who were not knowledgeable in genetics and policy issues. As neither the structure nor the dynamics of the network were modified, the citizens very soon started to feel uncomfortable with their role. They doubted the relevance of their contribution, pointing to an asymmetry in knowledge between them and the expert members. There were significant tensions in the network’s governance and the citizens’ concerns during the process were not fully addressed. Conclusion  The integration of citizens into transdisciplinary networks requires recognizing and addressing the asymmetry of expertise that underpins such a collaborative endeavour. It also requires understanding that citizens may feel uncomfortable adopting the pre‐defined role ascribed to them, may need a space of their own or may even withdraw if they feel being used. PMID:21029284

Using Networks To Understand Medical Data: The Case of Class III Malocclusions

PubMed Central

Scala, Antonio; Auconi, Pietro; Scazzocchio, Marco; Caldarelli, Guido; McNamara, James A.; Franchi, Lorenzo

2012-01-01

A system of elements that interact or regulate each other can be represented by a mathematical object called a network. While network analysis has been successfully applied to high-throughput biological systems, less has been done regarding their application in more applied fields of medicine; here we show an application based on standard medical diagnostic data. We apply network analysis to Class III malocclusion, one of the most difficult to understand and treat orofacial anomaly. We hypothesize that different interactions of the skeletal components can contribute to pathological disequilibrium; in order to test this hypothesis, we apply network analysis to 532 Class III young female patients. The topology of the Class III malocclusion obtained by network analysis shows a strong co-occurrence of abnormal skeletal features. The pattern of these occurrences influences the vertical and horizontal balance of disharmony in skeletal form and position. Patients with more unbalanced orthodontic phenotypes show preponderance of the pathological skeletal nodes and minor relevance of adaptive dentoalveolar equilibrating nodes. Furthermore, by applying Power Graphs analysis we identify some functional modules among orthodontic nodes. These modules correspond to groups of tightly inter-related features and presumably constitute the key regulators of plasticity and the sites of unbalance of the growing dentofacial Class III system. The data of the present study show that, in their most basic abstraction level, the orofacial characteristics can be represented as graphs using nodes to represent orthodontic characteristics, and edges to represent their various types of interactions. The applications of this mathematical model could improve the interpretation of the quantitative, patient-specific information, and help to better targeting therapy. Last but not least, the methodology we have applied in analyzing orthodontic features can be applied easily to other fields of the medical science. PMID:23028552

Impact of a Regional Pharmacy Call Center on Telephone Access Metrics Within the Veterans Health Administration

PubMed Central

Jones, Marshall R.; Kuester, Melanie K.; Myers, Kelly L.; Schnarr, Barbara A.

2015-01-01

Purpose: To establish a cost-effective centralized pharmacy call center to serve the patients of Veterans Integrated Service Network (VISN) 11 that would meet established performance metrics. Methods: A pilot project began in August 2011 with the Indianapolis VA Medical Center (VAMC) and the Health Resource Center (HRC) in Topeka, Kansas. The Indianapolis VAMC used a first-call resolution business model consisting of pharmacy technicians receiving tier 1 phone calls that could be escalated to a tier 2 line that consisted of lead technicians and pharmacists, while the HRC utilized general telephone agents that would transfer unresolved calls to the primary facility. Pre- and post-VISN 11 Pharmacy Call Center performance metrics were compared for each of the 7 facilities in the network with the goals being monthly average abandoned call rate less than 5% and average speed to answer less than 30 seconds. Cost per call was also compared. Results: The average abandoned call rate for the network during the year prior to VISN 11 Pharmacy Call Center implementation (August 2010-July 2011) was 15.66% and decreased to 3% in July 2014. The average abandoned call rate decreased for each individual facility. In fiscal year 2014, the VISN 11 Pharmacy Call Center was operating at a cost of $4.35 per call while providing more services than the HRC, resulting in less workload being transferred back to the individual facilities. Conclusion: A centralized VISN pharmacy call center is a reasonable alternative to individual facility call centers or the HRC. PMID:26405322

Developing brain networks of attention.

PubMed

Posner, Michael I; Rothbart, Mary K; Voelker, Pascale

2016-12-01

Attention is a primary cognitive function critical for perception, language, and memory. We provide an update on brain networks related to attention, their development, training, and pathologies. An executive attention network, also called the cingulo-opercular network, allows voluntary control of behavior in accordance with goals. Individual differences among children in self-regulation have been measured by a higher order factor called effortful control, which is related to the executive network and to the size of the anterior cingulate cortex. Brain networks of attention arise in infancy and are related to individual differences, including pathology during childhood. Methods of training attention may improve performance and ameliorate pathology.

Neural network for control of rearrangeable Clos networks.

PubMed

Park, Y K; Cherkassky, V

1994-09-01

Rapid evolution in the field of communication networks requires high speed switching technologies. This involves a high degree of parallelism in switching control and routing performed at the hardware level. The multistage crossbar networks have always been attractive to switch designers. In this paper a neural network approach to controlling a three-stage Clos network in real time is proposed. This controller provides optimal routing of communication traffic requests on a call-by-call basis by rearranging existing connections, with a minimum length of rearrangement sequence so that a new blocked call request can be accommodated. The proposed neural network controller uses Paull's rearrangement algorithm, along with the special (least used) switch selection rule in order to minimize the length of rearrangement sequences. The functional behavior of our model is verified by simulations and it is shown that the convergence time required for finding an optimal solution is constant, regardless of the switching network size. The performance is evaluated for random traffic with various traffic loads. Simulation results show that applying the least used switch selection rule increases the efficiency in switch rearrangements, reducing the network convergence time. The implementation aspects are also discussed to show the feasibility of the proposed approach.

Precisely Tracking Childhood Death

PubMed Central

Farag, Tamer H.; Koplan, Jeffrey P.; Breiman, Robert F.; Madhi, Shabir A.; Heaton, Penny M.; Mundel, Trevor; Ordi, Jaume; Bassat, Quique; Menendez, Clara; Dowell, Scott F.

2017-01-01

Abstract. Little is known about the specific causes of neonatal and under-five childhood death in high-mortality geographic regions due to a lack of primary data and dependence on inaccurate tools, such as verbal autopsy. To meet the ambitious new Sustainable Development Goal 3.2 to eliminate preventable child mortality in every country, better approaches are needed to precisely determine specific causes of death so that prevention and treatment interventions can be strengthened and focused. Minimally invasive tissue sampling (MITS) is a technique that uses needle-based postmortem sampling, followed by advanced histopathology and microbiology to definitely determine cause of death. The Bill & Melinda Gates Foundation is supporting a new surveillance system called the Child Health and Mortality Prevention Surveillance network, which will determine cause of death using MITS in combination with other information, and yield cause-specific population-based mortality rates, eventually in up to 12–15 sites in sub-Saharan Africa and south Asia. However, the Gates Foundation funding alone is not enough. We call on governments, other funders, and international stakeholders to expand the use of pathology-based cause of death determination to provide the information needed to end preventable childhood mortality. PMID:28719334

Defeating Adversary Network Intelligence Efforts with Active Cyber Defense Techniques

DTIC Science & Technology

2008-06-01

Hide Things from Hackers: Processes, Principles, and Techniques,” Journal of Information Warfare , 5 (3): 26-40 (2006). 20. Rosenau, William ...54 Additional Sources Apel , Thomas. Generating Fingerprints of Network Servers and their Use in Honeypots. Thesis. Aachen University, Aachen...Paul Williams , PhD (ENG) REPORT U ABSTRACT U c. THIS PAGE U 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 55

Integrating Network Management for Cloud Computing Services

DTIC Science & Technology

2015-06-01

abstraction and system design. In this dissertation, we make three major contributions. We rst propose to consolidate the tra c and infrastructure management...abstraction and system design. In this dissertation, we make three major contributions. We first propose to consolidate the traffic and infrastructure ...1.3.1 Safe Datacenter Traffic/ Infrastructure Management . . . . . . 9 1.3.2 End-host/Network Cooperative Traffic Management . . . . . . 10 1.3.3 Direct

Persistence of social signatures in human communication.

PubMed

Saramäki, Jari; Leicht, E A; López, Eduardo; Roberts, Sam G B; Reed-Tsochas, Felix; Dunbar, Robin I M

2014-01-21

The social network maintained by a focal individual, or ego, is intrinsically dynamic and typically exhibits some turnover in membership over time as personal circumstances change. However, the consequences of such changes on the distribution of an ego's network ties are not well understood. Here we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in the ego networks and communication patterns of students making the transition from school to university or work. Our analysis reveals that individuals display a distinctive and robust social signature, captured by how interactions are distributed across different alters. Notably, for a given ego, these social signatures tend to persist over time, despite considerable turnover in the identity of alters in the ego network. Thus, as new network members are added, some old network members either are replaced or receive fewer calls, preserving the overall distribution of calls across network members. This is likely to reflect the consequences of finite resources such as the time available for communication, the cognitive and emotional effort required to sustain close relationships, and the ability to make emotional investments.

Persistence of social signatures in human communication

PubMed Central

Saramäki, Jari; Leicht, E. A.; López, Eduardo; Roberts, Sam G. B.; Reed-Tsochas, Felix; Dunbar, Robin I. M.

2014-01-01

The social network maintained by a focal individual, or ego, is intrinsically dynamic and typically exhibits some turnover in membership over time as personal circumstances change. However, the consequences of such changes on the distribution of an ego’s network ties are not well understood. Here we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in the ego networks and communication patterns of students making the transition from school to university or work. Our analysis reveals that individuals display a distinctive and robust social signature, captured by how interactions are distributed across different alters. Notably, for a given ego, these social signatures tend to persist over time, despite considerable turnover in the identity of alters in the ego network. Thus, as new network members are added, some old network members either are replaced or receive fewer calls, preserving the overall distribution of calls across network members. This is likely to reflect the consequences of finite resources such as the time available for communication, the cognitive and emotional effort required to sustain close relationships, and the ability to make emotional investments. PMID:24395777

Abstracts of Research, July 1973 through June 1974.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Computer and Information Science Research Center.

Abstracts of research papers in the fields of computer and information science are given; 72 papers are abstracted in the areas of information storage and retrieval, information processing, linguistic analysis, artificial intelligence, mathematical techniques, systems programing, and computer networks. In addition, the Ohio State University…

Investigating the functional neuroanatomy of concrete and abstract word processing through direct electric stimulation (DES) during awake surgery.

PubMed

Orena, E F; Caldiroli, D; Acerbi, F; Barazzetta, I; Papagno, C

2018-06-05

Neuropsychological, neuroimaging and electrophysiological studies demonstrate that abstract and concrete word processing relies not only on the activity of a common bilateral network but also on dedicated networks. The neuropsychological literature has shown that a selective sparing of abstract relative to concrete words can be documented in lesions of the left anterior temporal regions. We investigated concrete and abstract word processing in 10 patients undergoing direct electrical stimulation (DES) for brain mapping during awake surgery in the left hemisphere. A lexical decision and a concreteness judgment task were added to the neuropsychological assessment during intra-operative monitoring. On the concreteness judgment, DES delivered over the inferior frontal gyrus significantly decreased abstract word accuracy while accuracy for concrete words decreased when the anterior temporal cortex was stimulated. These results are consistent with a lexical-semantic model that distinguishes between concrete and abstract words related to different neural substrates in the left hemisphere.

On the efficacy of using the transfer-controlled procedure during periods of STP processor overloads in SS7 networks

NASA Astrophysics Data System (ADS)

Rumsewicz, Michael

1994-04-01

In this paper, we examine call completion performance, rather than message throughput, in a Common Channel Signaling network in which the processing resources, and not transmission resources, of a Signaling Transfer Point (STP) are overloaded. Specifically, we perform a transient analysis, via simulation, of a network consisting of a single Central Processor-based STP connecting many local exchanges. We consider the efficacy of using the Transfer Controlled (TFC) procedure when the network call attempt rate exceeds the processing capability of the STP. We find the following: (1) the success of the control depends critically on the rate at which TFC's are sent; (2) use of the TFC procedure in theevent of processor overload can provide reasonable call completion rates.

Video movie making using remote procedure calls and 4BSD Unix sockets on Unix, UNICOS, and MS-DOS systems

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

Robertson, D.W.; Johnston, W.E.; Hall, D.E.

1990-03-01

We describe the use of the Sun Remote Procedure Call and Unix socket interprocess communication mechanisms to provide the network transport for a distributed, client-server based, image handling system. Clients run under Unix or UNICOS and servers run under Unix or MS-DOS. The use of remote procedure calls across local or wide-area networks to make video movies is addressed.

Coding the Eggen Cards (Poster abstract)

NASA Astrophysics Data System (ADS)

Silvis, G.

2014-06-01

(Abstract only) A look at the Eggen Portal for accessing the Eggen cards. And a call for volunteers to help code the cards: 100,000 cards must be looked at and their star references identified and coded into the database for this to be a valuable resource.

Integration of Heterogeneous Bibliographic Information through Data Abstractions.

ERIC Educational Resources Information Center

Breazeal, Juliette Ow

This study examines the integration of heterogeneous bibliographic information resources from geographically distributed locations in an automated, unified, and controlled way using abstract data types called "classes" through the Message-Object Model defined in Smalltalk-80 software. The concept of achieving data consistency by…

47 CFR 64.1600 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) Aggregate information. The term “aggregate information” means collective data that relate to a group or... Signaling System 7 network. (d) Charge number. The term “charge number” refers to the delivery of the... Signaling System 7 network, that indicates whether the calling party authorizes presentation of the calling...

Inclusion of tank configurations as a variable in the cost optimization of branched piped-water networks

NASA Astrophysics Data System (ADS)

Hooda, Nikhil; Damani, Om

2017-06-01

The classic problem of the capital cost optimization of branched piped networks consists of choosing pipe diameters for each pipe in the network from a discrete set of commercially available pipe diameters. Each pipe in the network can consist of multiple segments of differing diameters. Water networks also consist of intermediate tanks that act as buffers between incoming flow from the primary source and the outgoing flow to the demand nodes. The network from the primary source to the tanks is called the primary network, and the network from the tanks to the demand nodes is called the secondary network. During the design stage, the primary and secondary networks are optimized separately, with the tanks acting as demand nodes for the primary network. Typically the choice of tank locations, their elevations, and the set of demand nodes to be served by different tanks is manually made in an ad hoc fashion before any optimization is done. It is desirable therefore to include this tank configuration choice in the cost optimization process itself. In this work, we explain why the choice of tank configuration is important to the design of a network and describe an integer linear program model that integrates the tank configuration to the standard pipe diameter selection problem. In order to aid the designers of piped-water networks, the improved cost optimization formulation is incorporated into our existing network design system called JalTantra.

Change Detection Algorithms for Information Assurance of Computer Networks

DTIC Science & Technology

2002-01-01

original document contains color images. 14. ABSTRACT see report 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18...number of computer attacks increases steadily per year. At the time of this writing the Internet Security Systems’ baseline assessment is that a new...across a network by exploiting security flaws in widely-used services offered by vulnerable computers. In order to locate the vulnerable computers, the

An Overview of MSHN: The Management System for Heterogeneous Networks

DTIC Science & Technology

1999-04-01

An Overview of MSHN: The Management System for Heterogeneous Networks Debra A. Hensgen†, Taylor Kidd†, David St. John§, Matthew C . Schnaidt†, Howard...ABSTRACT UU 18. NUMBER OF PAGES 15 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT unclassified c . THIS PAGE...Alhusaini, V. K. Prasanna, and C . S. Raghavendra, “A unified resource scheduling framework for heterogeneous computing environments,” Proc. 8th IEEE

A Sensemaking Approach to Visual Analytics of Attribute-Rich Social Networks

ERIC Educational Resources Information Center

Gou, Liang

2012-01-01

Social networks have become more complex, in particular considering the fact that elements in social networks are not only abstract topological nodes and links, but contain rich social attributes and reflecting diverse social relationships. For example, in a co-authorship social network in a scientific community, nodes in the social network, which…

Assuring SS7 dependability: A robustness characterization of signaling network elements

NASA Astrophysics Data System (ADS)

Karmarkar, Vikram V.

1994-04-01

Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.

NOW: A Workflow Language for Orchestration in Nomadic Networks

NASA Astrophysics Data System (ADS)

Philips, Eline; van der Straeten, Ragnhild; Jonckers, Viviane

Existing workflow languages for nomadic or mobile ad hoc networks do not offer adequate support for dealing with the volatile connections inherent to these environments. Services residing on mobile devices are exposed to (temporary) network failures, which should be considered the rule rather than the exception. This paper proposes a nomadic workflow language built on top of an ambient-oriented programming language which supports dynamic service discovery and communication primitives resilient to network failures. Our proposed language provides high level workflow abstractions for control flow and supports rich network and service failure detection and handling through compensating actions. Moreover, we introduce a powerful variable binding mechanism which enables dynamic data flow between services in a nomadic environment. By adding this extra layer of abstraction on top of an ambient-oriented programming language, the application programmer is offered a flexible way to develop applications for nomadic networks.

Dynamic Visualization of Co-expression in Systems Genetics Data

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

New, Joshua Ryan; Huang, Jian; Chesler, Elissa J

2008-01-01

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biologicalmore » networks and discover genes which reside in critical positions in networks and pathways. By using a graph as a universal data representation of correlation in gene expression data, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.« less

1987 Robert E. Horton Award to Thomas Dunne

NASA Astrophysics Data System (ADS)

Dunne, Thomas

Robert Horton demonstrated in his seminal 1945 paper that physically based quantitative models for landscape evolution can be constructed by using predicted overland flow in a sediment transport equation for sheetwash. He envisioned drainage network evolution by infiltration-limited overland flow as a process of channel incision, network growth, and then abstraction to a stable channel network fed by hillslopes too short for channel initiation. Not until the work of Tom Dunne in the late 1960s in the Sleepers River watershed, Vermont, was it realized that overland flow, and consequently hillslope evolution, could occur by an entirely different mechanism than that proposed by Horton. Dunne showed that in certain predictable zones of the landscape, exfiltration from saturated grounds adds to precipitation on the soil surface to form what he later called saturation overland flow. Many researchers have since found that this form of overland flow occurs in humid and semiarid landscapes throughout the world. So clear is Dunne's contribution to defining this process that some refer to it as the “Dunne mechanism” to distinguish it from “Horton overland flow.” His work also documented unquestionably the applicability of the partial area concept in explaining runoff generation. Because of this work, his research in snowmelt runoff, and his subsequent authorship with Luna Leopold of the widely used book entitled Water in Environmental Planning, Dunne has established himself as a leader of process hydrology.

Birth of an abstraction: a dynamical systems account of the discovery of an elsewhere principle in a category learning task.

PubMed

Tabor, Whitney; Cho, Pyeong W; Dankowicz, Harry

2013-01-01

Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the Elsewhere Condition (Kiparsky, 1973). Previous connectionist accounts of related phenomena have often been vague about the nature of the networks' encoding systems. We analyzed our network using dynamical systems theory, revealing topological and geometric properties that can be directly compared with the mechanisms of non-connectionist, rule-based accounts. The results reveal that the networks "contain" structures related to mechanisms posited by rule-based models, partly vindicating the insights of these models. On the other hand, they support the one mechanism (OM), as opposed to the more than one mechanism (MOM), view of symbolic abstraction by showing how the appearance of MOM behavior can arise emergently from one underlying set of principles. The key new contribution of this study is to show that dynamical systems theory can allow us to explicitly characterize the relationship between the two perspectives in implemented models. © 2013 Cognitive Science Society, Inc.

The performance evaluation of a new neural network based traffic management scheme for a satellite communication network

NASA Technical Reports Server (NTRS)

Ansari, Nirwan; Liu, Dequan

1991-01-01

A neural-network-based traffic management scheme for a satellite communication network is described. The scheme consists of two levels of management. The front end of the scheme is a derivation of Kohonen's self-organization model to configure maps for the satellite communication network dynamically. The model consists of three stages. The first stage is the pattern recognition task, in which an exemplar map that best meets the current network requirements is selected. The second stage is the analysis of the discrepancy between the chosen exemplar map and the state of the network, and the adaptive modification of the chosen exemplar map to conform closely to the network requirement (input data pattern) by means of Kohonen's self-organization. On the basis of certain performance criteria, whether a new map is generated to replace the original chosen map is decided in the third stage. A state-dependent routing algorithm, which arranges the incoming call to some proper path, is used to make the network more efficient and to lower the call block rate. Simulation results demonstrate that the scheme, which combines self-organization and the state-dependent routing mechanism, provides better performance in terms of call block rate than schemes that only have either the self-organization mechanism or the routing mechanism.

Enabling Tussle-Agile Inter-networking Architectures by Underlay Virtualisation

NASA Astrophysics Data System (ADS)

Dianati, Mehrdad; Tafazolli, Rahim; Moessner, Klaus

In this paper, we propose an underlay inter-network virtualisation framework in order to enable tussle-agile flexible networking over the existing inter-network infrastructures. The functionalities that inter-networking elements (transit nodes, access networks, etc.) need to support in order to enable virtualisation are discussed. We propose the base architectures of each the abstract elements to support the required inter-network virtualisation functionalities.

Intelligent call admission control for multi-class services in mobile cellular networks

NASA Astrophysics Data System (ADS)

Ma, Yufeng; Hu, Xiulin; Zhang, Yunyu

2005-11-01

Scarcity of the spectrum resource and mobility of users make quality of service (QoS) provision a critical issue in mobile cellular networks. This paper presents a fuzzy call admission control scheme to meet the requirement of the QoS. A performance measure is formed as a weighted linear function of new call and handoff call blocking probabilities of each service class. Simulation compares the proposed fuzzy scheme with complete sharing and guard channel policies. Simulation results show that fuzzy scheme has a better robust performance in terms of average blocking criterion.

Fault recovery in the reliable multicast protocol

NASA Technical Reports Server (NTRS)

Callahan, John R.; Montgomery, Todd L.; Whetten, Brian

1995-01-01

The Reliable Multicast Protocol (RMP) provides a unique, group-based model for distributed programs that need to handle reconfiguration events at the application layer. This model, called membership views, provides an abstraction in which events such as site failures, network partitions, and normal join-leave events are viewed as group reformations. RMP provides access to this model through an application programming interface (API) that notifies an application when a group is reformed as the result of a some event. RMP provides applications with reliable delivery of messages using an underlying IP Multicast (12, 5) media to other group members in a distributed environment even in the case of reformations. A distributed application can use various Quality of Service (QoS) levels provided by RMP to tolerate group reformations. This paper explores the implementation details of the mechanisms in RMP that provide distributed applications with membership view information and fault recovery capabilities.

Specification and Design of a Fault Recovery Model for the Reliable Multicast Protocol

NASA Technical Reports Server (NTRS)

Montgomery, Todd; Callahan, John R.; Whetten, Brian

1996-01-01

The Reliable Multicast Protocol (RMP) provides a unique, group-based model for distributed programs that need to handle reconfiguration events at the application layer. This model, called membership views, provides an abstraction in which events such as site failures, network partitions, and normal join-leave events are viewed as group reformations. RMP provides access to this model through an application programming interface (API) that notifies an application when a group is reformed as the result of a some event. RMP provides applications with reliable delivery of messages using an underlying IP Multicast media to other group members in a distributed environment even in the case of reformations. A distributed application can use various Quality of Service (QoS) levels provided by RMP to tolerate group reformations. This paper explores the implementation details of the mechanisms in RMP that provide distributed applications with membership view information and fault recovery capabilities.

Quorum Sensing Gene Regulation by LuxR/HapR Master Regulators in Vibrios

PubMed Central

Ball, Alyssa S.; Chaparian, Ryan R.

2017-01-01

ABSTRACT The coordination of group behaviors in bacteria is accomplished via the cell-cell signaling process called quorum sensing. Vibrios have historically been models for studying bacterial communication due to the diverse and remarkable behaviors controlled by quorum sensing in these bacteria, including bioluminescence, type III and type VI secretion, biofilm formation, and motility. Here, we discuss the Vibrio LuxR/HapR family of proteins, the master global transcription factors that direct downstream gene expression in response to changes in cell density. These proteins are structurally similar to TetR transcription factors but exhibit distinct biochemical and genetic features from TetR that determine their regulatory influence on the quorum sensing gene network. We review here the gene groups regulated by LuxR/HapR and quorum sensing and explore the targets that are common and unique among Vibrio species. PMID:28484045

CoPub: a literature-based keyword enrichment tool for microarray data analysis.

PubMed

Frijters, Raoul; Heupers, Bart; van Beek, Pieter; Bouwhuis, Maurice; van Schaik, René; de Vlieg, Jacob; Polman, Jan; Alkema, Wynand

2008-07-01

Medline is a rich information source, from which links between genes and keywords describing biological processes, pathways, drugs, pathologies and diseases can be extracted. We developed a publicly available tool called CoPub that uses the information in the Medline database for the biological interpretation of microarray data. CoPub allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs. CoPub is freely accessible at http://services.nbic.nl/cgi-bin/copub/CoPub.pl.

Organic Techniques for Protecting Virtual Private Network (VPN) Services from Access Link Flooding Attacks

DTIC Science & Technology

2002-01-01

Submitted to ICN 2002 Organic Techniques for Protecting Virtual Private Network (VPN) Services from Access Link Flooding Attacks1 Ranga S. Ramanujan ...using these techniques is also described. Contact author: Dr. Ranga S. Ramanujan Architecture Technology Corporation 9971 Valley View Road Eden Prairie...OF ABSTRACT 18. NUMBER OF PAGES 15 19a. NAME OF RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT unclassified c . THIS PAGE unclassified

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

Labyrinth, An Abstract Model for Hypermedia Applications. Description of its Static Components.

ERIC Educational Resources Information Center

Diaz, Paloma; Aedo, Ignacio; Panetsos, Fivos

1997-01-01

The model for hypermedia applications called Labyrinth allows: (1) the design of platform-independent hypermedia applications; (2) the categorization, generalization and abstraction of sparse unstructured heterogeneous information in multiple and interconnected levels; (3) the creation of personal views in multiuser hyperdocuments for both groups…

Abstracts for the symposium on the Application of neural networks to the earth sciences

USGS Publications Warehouse

Singer, Donald A.

2002-01-01

Artificial neural networks are a group of mathematical methods that attempt to mimic some of the processes in the human mind. Although the foundations for these ideas were laid as early as 1943 (McCulloch and Pitts, 1943), it wasn't until 1986 (Rumelhart and McClelland, 1986; Masters, 1995) that applications to practical problems became possible. It is the acknowledged superiority of the human mind at recognizing patterns that the artificial neural networks are trying to imitate with their interconnected neurons. Interconnections used in the methods that have been developed allow robust learning. Capabilities of neural networks fall into three kinds of applications: (1) function fitting or prediction, (2) noise reduction or pattern recognition, and (3) classification or placing into types. Because of these capabilities and the powerful abilities of artificial neural networks, there have been increasing applications of these methods in the earth sciences. The abstracts in this document represent excellent samples of the range of applications. Talks associated with the abstracts were presented at the Symposium on the Application of Neural Networks to the Earth Sciences: Seventh International Symposium on Mineral Exploration (ISME–02), held August 20–21, 2002, at NASA Moffett Field, Mountain View, California. This symposium was sponsored by the Mining and Materials Processing Institute of Japan (MMIJ), the U.S. Geological Survey, the Circum-Pacific Council, and NASA. The ISME symposia have been held every two years in order to bring together scientists actively working on diverse quantitative methods applied to the earth sciences. Although the title, International Symposium on Mineral Exploration, suggests exclusive focus on mineral exploration, interests and presentations have always been wide-ranging—abstracts presented here are no exception.

Autonomous perception and decision making in cyber-physical systems

NASA Astrophysics Data System (ADS)

Sarkar, Soumik

2011-07-01

The cyber-physical system (CPS) is a relatively new interdisciplinary technology area that includes the general class of embedded and hybrid systems. CPSs require integration of computation and physical processes that involves the aspects of physical quantities such as time, energy and space during information processing and control. The physical space is the source of information and the cyber space makes use of the generated information to make decisions. This dissertation proposes an overall architecture of autonomous perception-based decision & control of complex cyber-physical systems. Perception involves the recently developed framework of Symbolic Dynamic Filtering for abstraction of physical world in the cyber space. For example, under this framework, sensor observations from a physical entity are discretized temporally and spatially to generate blocks of symbols, also called words that form a language. A grammar of a language is the set of rules that determine the relationships among words to build sentences. Subsequently, a physical system is conjectured to be a linguistic source that is capable of generating a specific language. The proposed technology is validated on various (experimental and simulated) case studies that include health monitoring of aircraft gas turbine engines, detection and estimation of fatigue damage in polycrystalline alloys, and parameter identification. Control of complex cyber-physical systems involve distributed sensing, computation, control as well as complexity analysis. A novel statistical mechanics-inspired complexity analysis approach is proposed in this dissertation. In such a scenario of networked physical systems, the distribution of physical entities determines the underlying network topology and the interaction among the entities forms the abstract cyber space. It is envisioned that the general contributions, made in this dissertation, will be useful for potential application areas such as smart power grids and buildings, distributed energy systems, advanced health care procedures and future ground and air transportation systems.

Network structure exploration in networks with node attributes

NASA Astrophysics Data System (ADS)

Chen, Yi; Wang, Xiaolong; Bu, Junzhao; Tang, Buzhou; Xiang, Xin

2016-05-01

Complex networks provide a powerful way to represent complex systems and have been widely studied during the past several years. One of the most important tasks of network analysis is to detect structures (also called structural regularities) embedded in networks by determining group number and group partition. Most of network structure exploration models only consider network links. However, in real world networks, nodes may have attributes that are useful for network structure exploration. In this paper, we propose a novel Bayesian nonparametric (BNP) model to explore structural regularities in networks with node attributes, called Bayesian nonparametric attribute (BNPA) model. This model does not only take full advantage of both links between nodes and node attributes for group partition via shared hidden variables, but also determine group number automatically via the Bayesian nonparametric theory. Experiments conducted on a number of real and synthetic networks show that our BNPA model is able to automatically explore structural regularities in networks with node attributes and is competitive with other state-of-the-art models.

Enhanced polychronization in a spiking network with metaplasticity.

PubMed

Guise, Mira; Knott, Alistair; Benuskova, Lubica

2015-01-01

Computational models of metaplasticity have usually focused on the modeling of single synapses (Shouval et al., 2002). In this paper we study the effect of metaplasticity on network behavior. Our guiding assumption is that the primary purpose of metaplasticity is to regulate synaptic plasticity, by increasing it when input is low and decreasing it when input is high. For our experiments we adopt a model of metaplasticity that demonstrably has this effect for a single synapse; our primary interest is in how metaplasticity thus defined affects network-level phenomena. We focus on a network-level phenomenon called polychronicity, that has a potential role in representation and memory. A network with polychronicity has the ability to produce non-synchronous but precisely timed sequences of neural firing events that can arise from strongly connected groups of neurons called polychronous neural groups (Izhikevich et al., 2004). Polychronous groups (PNGs) develop readily when spiking networks are exposed to repeated spatio-temporal stimuli under the influence of spike-timing-dependent plasticity (STDP), but are sensitive to changes in synaptic weight distribution. We use a technique we have recently developed called Response Fingerprinting to show that PNGs formed in the presence of metaplasticity are significantly larger than those with no metaplasticity. A potential mechanism for this enhancement is proposed that links an inherent property of integrator type neurons called spike latency to an increase in the tolerance of PNG neurons to jitter in their inputs.

Nonbinary Tree-Based Phylogenetic Networks.

PubMed

Jetten, Laura; van Iersel, Leo

2018-01-01

Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can, for example, represent gene transfer events. Such phylogenetic networks are called tree-based. Here, we consider two possible generalizations of this concept to nonbinary networks, which we call tree-based and strictly-tree-based nonbinary phylogenetic networks. We give simple graph-theoretic characterizations of tree-based and strictly-tree-based nonbinary phylogenetic networks. Moreover, we show for each of these two classes that it can be decided in polynomial time whether a given network is contained in the class. Our approach also provides a new view on tree-based binary phylogenetic networks. Finally, we discuss two examples of nonbinary phylogenetic networks in biology and show how our results can be applied to them.

A Network Optimization Approach for Improving Organizational Design

DTIC Science & Technology

2004-01-01

functions, Dynamic Network Analysis, Social Network Analysis Abstract Organizations are frequently designed and redesigned, often in...links between sites on the web. Hence a change in any one of the four networks in which people are involved can potentially result in a cascade of...in terms of a set of networks that open the possibility of using all networks (both social and dynamic network measures) as indicators of potential

Effect of direct reciprocity and network structure on continuing prosperity of social networking services.

PubMed

Osaka, Kengo; Toriumi, Fujio; Sugawara, Toshihauru

2017-01-01

Social networking services (SNSs) are widely used as communicative tools for a variety of purposes. SNSs rely on the users' individual activities associated with some cost and effort, and thus it is not known why users voluntarily continue to participate in SNSs. Because the structures of SNSs are similar to that of the public goods (PG) game, some studies have focused on why voluntary activities emerge as an optimal strategy by modifying the PG game. However, their models do not include direct reciprocity between users, even though reciprocity is a key mechanism that evolves and sustains cooperation in human society. We developed an abstract SNS model called the reciprocity rewards and meta-rewards games that include direct reciprocity by extending the existing models. Then, we investigated how direct reciprocity in an SNS facilitates cooperation that corresponds to participation in SNS by posting articles and comments and how the structure of the networks of users exerts an influence on the strategies of users using the reciprocity rewards game. We run reciprocity rewards games on various complex networks and an instance network of Facebook and found that two types of stable cooperation emerged. First, reciprocity slightly improves the rate of cooperation in complete graphs but the improvement is insignificant because of the instability of cooperation. However, this instability can be avoided by making two assumptions: high degree of fun, i.e. articles are read with high probability, and different attitudes to reciprocal and non-reciprocal agents. We then propose the concept of half free riders to explain what strategy sustains cooperation-dominant situations. Second, we indicate that a certain WS network structure affects users' optimal strategy and facilitates stable cooperation without any extra assumptions. We give a detailed analysis of the different characteristics of the two types of cooperation-dominant situations and the effect of the memory of reciprocal agents on cooperation.

An automatic method to generate domain-specific investigator networks using PubMed abstracts.

PubMed

Yu, Wei; Yesupriya, Ajay; Wulf, Anja; Qu, Junfeng; Gwinn, Marta; Khoury, Muin J

2007-06-20

Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70-90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network. We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks.

An automatic method to generate domain-specific investigator networks using PubMed abstracts

PubMed Central

Yu, Wei; Yesupriya, Ajay; Wulf, Anja; Qu, Junfeng; Gwinn, Marta; Khoury, Muin J

2007-01-01

Background Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. Results We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70–90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network. Conclusion We successfully created a web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks. PMID:17584920

A Thesaurus for Use in a Computer-Aided Abstracting Tool Kit.

ERIC Educational Resources Information Center

Craven, Timothy C.

1993-01-01

Discusses the use of thesauri in automatic indexing and describes the development of a prototype computerized abstractor's assistant. Topics addressed include TEXNET, a text network management system; the use of TEXNET for abstracting; the structure and use of a thesaurus for abstracting in TEXNET; and weighted terms. (Contains 26 references.)…

Abstracts of SIG Sessions.

ERIC Educational Resources Information Center

Proceedings of the ASIS Annual Meeting, 1997

1997-01-01

Presents abstracts of SIG Sessions. Highlights include digital collections; information retrieval methods; public interest/fair use; classification and indexing; electronic publication; funding; globalization; information technology projects; interface design; networking in developing countries; metadata; multilingual databases; networked…

Detecting Role Errors in the Gene Hierarchy of the NCI Thesaurus

PubMed Central

Min, Hua; Cohen, Barry; Halper, Michael; Oren, Marc; Perl, Yehoshua

2008-01-01

Gene terminologies are playing an increasingly important role in the ever-growing field of genomic research. While errors in large, complex terminologies are inevitable, gene terminologies are even more susceptible to them due to the rapid growth of genomic knowledge and the nature of its discovery. It is therefore very important to establish quality-assurance protocols for such genomic-knowledge repositories. Different kinds of terminologies oftentimes require auditing methodologies adapted to their particular structures. In light of this, an auditing methodology tailored to the characteristics of the NCI Thesaurus’s (NCIT’s) Gene hierarchy is presented. The Gene hierarchy is of particular interest to the NCIT’s designers due to the primary role of genomics in current cancer research. This multiphase methodology focuses on detecting role-errors, such as missing roles or roles with incorrect or incomplete target structures, occurring within that hierarchy. The methodology is based on two kinds of abstraction networks, called taxonomies, that highlight the role distribution among concepts within the IS-A (subsumption) hierarchy. These abstract views tend to highlight portions of the hierarchy having a higher concentration of errors. The errors found during an application of the methodology are reported. Hypotheses pertaining to the efficacy of our methodology are investigated. PMID:19221606

The association of drinking water treatment and distribution network disturbances with Health Call Centre contacts for gastrointestinal illness symptoms.

PubMed

Malm, Annika; Axelsson, Gösta; Barregard, Lars; Ljungqvist, Jakob; Forsberg, Bertil; Bergstedt, Olof; Pettersson, Thomas J R

2013-09-01

There are relatively few studies on the association between disturbances in drinking water services and symptoms of gastrointestinal (GI) illness. Health Call Centres data concerning GI illness may be a useful source of information. This study investigates if there is an increased frequency of contacts with the Health Call Centre (HCC) concerning gastrointestinal symptoms at times when there is a risk of impaired water quality due to disturbances at water works or the distribution network. The study was conducted in Gothenburg, a Swedish city with 0.5 million inhabitants with a surface water source of drinking water and two water works. All HCC contacts due to GI symptoms (diarrhoea, vomiting or abdominal pain) were recorded for a three-year period, including also sex, age, and geocoded location of residence. The number of contacts with the HCC in the affected geographical areas were recorded during eight periods of disturbances in the water works (e.g. short stops of chlorine dosing), six periods of large disturbances in the distribution network (e.g. pumping station failure or pipe breaks with major consequences), and 818 pipe break and leak repairs over a three-year period. For each period of disturbance the observed number of calls was compared with the number of calls during a control period without disturbances in the same geographical area. In total about 55, 000 calls to the HCC due to GI symptoms were recorded over the three-year period, 35 per 1000 inhabitants and year, but much higher (>200) for children <3 yrs of age. There was no statistically significant increase in calls due to GI illness during or after disturbances at the water works or in the distribution network. Our results indicate that GI symptoms due to disturbances in water works or the distribution network are rare. The number of serious failures was, however limited, and further studies are needed to be able to assess the risk of GI illness in such cases. The technique of using geocoded HCC data together with geocoded records of disturbances in the drinking water network was feasible. Copyright © 2013 Elsevier Ltd. All rights reserved.

An Enriched Unified Medical Language System Semantic Network with a Multiple Subsumption Hierarchy

PubMed Central

Zhang, Li; Perl, Yehoshua; Halper, Michael; Geller, James; Cimino, James J.

2004-01-01

Objective: The Unified Medical Language System's (UMLS's) Semantic Network's (SN's) two-tree structure is restrictive because it does not allow a semantic type to be a specialization of several other semantic types. In this article, the SN is expanded into a multiple subsumption structure with a directed acyclic graph (DAG) IS-A hierarchy, allowing a semantic type to have multiple parents. New viable IS-A links are added as warranted. Design: Two methodologies are presented to identify and add new viable IS-A links. The first methodology is based on imposing the characteristic of connectivity on a previously presented partition of the SN. Four transformations are provided to find viable IS-A links in the process of converting the partition's disconnected groups into connected ones. The second methodology identifies new IS-A links through a string matching process involving names and definitions of various semantic types in the SN. A domain expert is needed to review all the results to determine the validity of the new IS-A links. Results: Nineteen new IS-A links are added to the SN, and four new semantic types are also created to support the multiple subsumption framework. The resulting network, called the Enriched Semantic Network (ESN), exhibits a DAG-structured hierarchy. A partition of the ESN containing 19 connected groups is also derived. Conclusion: The ESN is an expanded abstraction of the UMLS compared with the original SN. Its multiple subsumption hierarchy can accommodate semantic types with multiple parents. Its representation thus provides direct access to a broader range of subsumption knowledge. PMID:14764611

Optical network democratization.

PubMed

Nejabati, Reza; Peng, Shuping; Simeonidou, Dimitra

2016-03-06

The current Internet infrastructure is not able to support independent evolution and innovation at physical and network layer functionalities, protocols and services, while at same time supporting the increasing bandwidth demands of evolving and heterogeneous applications. This paper addresses this problem by proposing a completely democratized optical network infrastructure. It introduces the novel concepts of the optical white box and bare metal optical switch as key technology enablers for democratizing optical networks. These are programmable optical switches whose hardware is loosely connected internally and is completely separated from their control software. To alleviate their complexity, a multi-dimensional abstraction mechanism using software-defined network technology is proposed. It creates a universal model of the proposed switches without exposing their technological details. It also enables a conventional network programmer to develop network applications for control of the optical network without specific technical knowledge of the physical layer. Furthermore, a novel optical network virtualization mechanism is proposed, enabling the composition and operation of multiple coexisting and application-specific virtual optical networks sharing the same physical infrastructure. Finally, the optical white box and the abstraction mechanism are experimentally evaluated, while the virtualization mechanism is evaluated with simulation. © 2016 The Author(s).

Improving publication rates in a collaborative clinical trials research network.

PubMed

Archer, Stephanie Wilson; Carlo, Waldemar A; Truog, William E; Stevenson, David K; Van Meurs, Krisa P; Sánchez, Pablo J; Das, Abhik; Devaskar, Uday; Nelin, Leif D; Petrie Huitema, Carolyn M; Crawford, Margaret M; Higgins, Rosemary D

2016-10-01

Unpublished results can bias biomedical literature, favoring positive over negative findings, primary over secondary analyses, and can lead to duplicate studies that unnecessarily endanger subjects and waste resources. The Neonatal Research Network's (NRN) publication policies for approving, reviewing, and tracking abstracts and papers work to combat these problems. In 2003, the NRN restricted investigators with unfinished manuscripts from proposing new ones and in 2010, urged authors to complete long-outstanding manuscripts. Data from 1991 to 2015 were analyzed to determine effectiveness of these policy changes. The NRN has achieved an overall publication rate of 78% for abstracts. For 1990-2002, of 137 abstracts presented, 43 (31%) were published within 2 years; for 2003-2009, after the manuscript completion policy was instituted, of 140 abstracts presented, 68 (49%) were published within 2 years. Following the effort in 2010, the rate increased to 64%. The NRN surpassed reported rates by developing a comprehensive process, holding investigators accountable and tracking abstracts from presentation to publication. Copyright © 2016. Published by Elsevier Inc.

Software Certification for Temporal Properties With Affordable Tool Qualification

NASA Technical Reports Server (NTRS)

Xia, Songtao; DiVito, Benedetto L.

2005-01-01

It has been recognized that a framework based on proof-carrying code (also called semantic-based software certification in its community) could be used as a candidate software certification process for the avionics industry. To meet this goal, tools in the "trust base" of a proof-carrying code system must be qualified by regulatory authorities. A family of semantic-based software certification approaches is described, each different in expressive power, level of automation and trust base. Of particular interest is the so-called abstraction-carrying code, which can certify temporal properties. When a pure abstraction-carrying code method is used in the context of industrial software certification, the fact that the trust base includes a model checker would incur a high qualification cost. This position paper proposes a hybrid of abstraction-based and proof-based certification methods so that the model checker used by a client can be significantly simplified, thereby leading to lower cost in tool qualification.

Developing Computer Programming Concepts and Skills via Technology-Enriched Language-Art Projects: A Case Study

ERIC Educational Resources Information Center

Lee, Young-Jin

2010-01-01

Teaching computer programming to young children has been considered difficult because of its abstract and complex nature. The objectives of this study are (1) to investigate whether an innovative educational technology tool called Scratch could enable young children to learn abstract knowledge of computer programming while creating multimedia…

A Computer-Assisted Instruction in Teaching Abstract Statistics to Public Affairs Undergraduates

ERIC Educational Resources Information Center

Ozturk, Ali Osman

2012-01-01

This article attempts to demonstrate the applicability of a computer-assisted instruction supported with simulated data in teaching abstract statistical concepts to political science and public affairs students in an introductory research methods course. The software is called the Elaboration Model Computer Exercise (EMCE) in that it takes a great…

Aging-related changes in the default mode network and its anti-correlated networks: a resting-state fMRI study.

PubMed

Wu, Jing-Tao; Wu, Hui-Zhen; Yan, Chao-Gan; Chen, Wen-Xin; Zhang, Hong-Ying; He, Yong; Yang, Hai-Shan

2011-10-17

Intrinsic brain activity in a resting state incorporates components of the task negative network called default mode network (DMN) and task-positive networks called attentional networks. In the present study, the reciprocal neuronal networks in the elder group were compared with the young group to investigate the differences of the intrinsic brain activity using a method of temporal correlation analysis based on seed regions of posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC). We found significant decreased positive correlations and negative correlations with the seeds of PCC and vmPFC in the old group. The decreased coactivations in the DMN network components and their negative networks in the old group may reflect age-related alterations in various brain functions such as attention, motor control and inhibition modulation in cognitive processing. These alterations in the resting state anti-correlative networks could provide neuronal substrates for the aging brain. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Indiva: a middleware for managing distributed media environment

NASA Astrophysics Data System (ADS)

Ooi, Wei-Tsang; Pletcher, Peter; Rowe, Lawrence A.

2003-12-01

This paper presents a unified set of abstractions and operations for hardware devices, software processes, and media data in a distributed audio and video environment. These abstractions, which are provided through a middleware layer called Indiva, use a file system metaphor to access resources and high-level commands to simplify the development of Internet webcast and distributed collaboration control applications. The design and implementation of Indiva are described and examples are presented to illustrate the usefulness of the abstractions.

Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior

PubMed Central

Kochemazov, Stepan; Semenov, Alexander

2014-01-01

In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if the opinion of this agent at current time moment conforms to the opinion of some other agents at the previous time moment. We presume that at each moment of time every agent makes a decision by choosing from the set (where 1-decision corresponds to action and 0-decision corresponds to inaction). In our approach we model collective behavior with synchronous Boolean networks. We presume that in a network there can be agents that act at every moment of time. Such agents are called instigators. Also there can be agents that never act. Such agents are called loyalists. Agents that are neither instigators nor loyalists are called simple agents. We study two combinatorial problems. The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where the majority of simple agents are inactive to a state with the majority of active agents. The second problem is to find a disposition of loyalists that returns the network to a state with the majority of inactive agents. Similar problems are studied for networks in which simple agents demonstrate the contrary to conforming behavior that we call anticonforming. We obtained several theoretical results regarding the behavior of collectives of agents with conforming or anticonforming behavior. In computational experiments we solved the described problems for randomly generated networks with several hundred vertices. We reduced corresponding combinatorial problems to the Boolean satisfiability problem (SAT) and used modern SAT solvers to solve the instances obtained. PMID:25526612

Methods for solving reasoning problems in abstract argumentation – A survey

PubMed Central

Charwat, Günther; Dvořák, Wolfgang; Gaggl, Sarah A.; Wallner, Johannes P.; Woltran, Stefan

2015-01-01

Within the last decade, abstract argumentation has emerged as a central field in Artificial Intelligence. Besides providing a core formalism for many advanced argumentation systems, abstract argumentation has also served to capture several non-monotonic logics and other AI related principles. Although the idea of abstract argumentation is appealingly simple, several reasoning problems in this formalism exhibit high computational complexity. This calls for advanced techniques when it comes to implementation issues, a challenge which has been recently faced from different angles. In this survey, we give an overview on different methods for solving reasoning problems in abstract argumentation and compare their particular features. Moreover, we highlight available state-of-the-art systems for abstract argumentation, which put these methods to practice. PMID:25737590

Airborne Network Optimization with Dynamic Network Update

DTIC Science & Technology

2015-03-26

Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University...Member Dr. Barry E. Mullins Member AFIT-ENG-MS-15-M-030 Abstract Modern networks employ congestion and routing management algorithms that can perform...airborne networks. Intelligent agents can make use of Kalman filter predictions to make informed decisions to manage communication in airborne networks. The

Wireless Sensor Networks for Detection of IED Emplacement

DTIC Science & Technology

2009-06-01

unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Abstract We are investigating the use of wireless nonimaging -sensor...networks for the difficult problem of detection of suspicious behavior related to IED emplacement. Hardware for surveillance by nonimaging -sensor networks...with people crossing a live sensor network. We conclude that nonimaging -sensor networks can detect a variety of suspicious behavior, but

A social network approach to understanding science communication among fire professionals (Abstract)

Treesearch

Vita Wright; Andrea Thode; Anne Mottek-Lucas; Jacklynn Fallon; Megan Matonis

2012-01-01

Studies of science communication and use in the fire management community suggest manager's access research via informal information networks and that these networks vary by both agency and position. We used a phone survey followed by traditional statistical analyses to understand the informal social networks of fire professionals in two western regions of the...

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

NASA Astrophysics Data System (ADS)

Tiwari, Shivendra N.; Padhi, Radhakant

2018-01-01

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

Exploring Normalization and Network Reconstruction Methods using In Silico and In Vivo Models

EPA Science Inventory

Abstract: Lessons learned from the recent DREAM competitions include: The search for the best network reconstruction method continues, and we need more complete datasets with ground truth from more complex organisms. It has become obvious that the network reconstruction methods t...

Towards an Analytic Foundation for Network Architecture

DTIC Science & Technology

2010-12-31

SUPPLEMENTARY NOTES N/A 14. ABSTRACT In this project, we develop the analytic tools of stochastic optimization for wireless network design and apply them...and Mung Chiang, “ DaVinci : Dynamically Adaptive Virtual Networks for a Customized Internet,” in Proc. ACM SIGCOMM CoNext Conference, December 2008

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.

Deformable complex network for refining low-resolution X-ray structures

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

Zhang, Chong; Wang, Qinghua; Ma, Jianpeng, E-mail: jpma@bcm.edu

2015-10-27

A new refinement algorithm called the deformable complex network that combines a novel angular network-based restraint with a deformable elastic network model in the target function has been developed to aid in structural refinement in macromolecular X-ray crystallography. In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint withmore » the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.« less

Educational Imperatives of the Evolution of Consciousness: The Integral Visions of Rudolf Steiner and Ken Wilber

ERIC Educational Resources Information Center

Gidley, Jennifer M.

2007-01-01

Rudolf Steiner and Ken Wilber claim that human consciousness is evolving beyond the "formal", abstract, intellectual mode toward a "post-formal", integral mode. Wilber calls this "vision-logic" and Steiner calls it "consciousness/spiritual soul". Both point to the emergence of more complex, dialectical,…

Biotechnology worldwide and the 'European Biotechnology Thematic Network' Association (EBTNA).

PubMed

Bruschi, F; Dundar, M; Gahan, P B; Gartland, K; Szente, M; Viola-Magni, M P; Akbarova, Y

2011-09-01

The European Biotechnology Congress 2011 held under the auspices of the European Biotechnology Thematic Network Association (EBTNA) in conjunction with the Turkish Medical Genetics Association brings together a broad spectrum of biotechnologists from around the world. The subsequent abstracts indicate the manner in which biotechnology has permeated all aspects of research from the basic sciences through to small and medium enterprises and major industries. The brief statements before the presentation of the abstracts aim to introduce not only Biotechnology in general and its importance around the world, but also the European Biotechnology Thematic Network Association and its aims especially within the framework of education and ethics in biotechnology. Copyright © 2011 Elsevier Ltd. All rights reserved.

Hologram representation of design data in an expert system knowledge base

NASA Technical Reports Server (NTRS)

Shiva, S. G.; Klon, Peter F.

1988-01-01

A novel representational scheme for design object descriptions is presented. An abstract notion of modules and signals is developed as a conceptual foundation for the scheme. This abstraction relates the objects to the meaning of system descriptions. Anchored on this abstraction, a representational model which incorporates dynamic semantics for these objects is presented. This representational model is called a hologram scheme since it represents dual level information, namely, structural and semantic. The benefits of this scheme are presented.

Applying model abstraction techniques to optimize monitoring networks for detecting subsurface contaminant transport

USDA-ARS?s Scientific Manuscript database

Improving strategies for monitoring subsurface contaminant transport includes performance comparison of competing models, developed independently or obtained via model abstraction. Model comparison and parameter discrimination involve specific performance indicators selected to better understand s...

Computer Code for Transportation Network Design and Analysis

DOT National Transportation Integrated Search

1977-01-01

This document describes the results of research into the application of the mathematical programming technique of decomposition to practical transportation network problems. A computer code called Catnap (for Control Analysis Transportation Network A...

Graph Design via Convex Optimization: Online and Distributed Perspectives

NASA Astrophysics Data System (ADS)

Meng, De

Network and graph have long been natural abstraction of relations in a variety of applications, e.g. transportation, power system, social network, communication, electrical circuit, etc. As a large number of computation and optimization problems are naturally defined on graphs, graph structures not only enable important properties of these problems, but also leads to highly efficient distributed and online algorithms. For example, graph separability enables the parallelism for computation and operation as well as limits the size of local problems. More interestingly, graphs can be defined and constructed in order to take best advantage of those problem properties. This dissertation focuses on graph structure and design in newly proposed optimization problems, which establish a bridge between graph properties and optimization problem properties. We first study a new optimization problem called Geodesic Distance Maximization Problem (GDMP). Given a graph with fixed edge weights, finding the shortest path, also known as the geodesic, between two nodes is a well-studied network flow problem. We introduce the Geodesic Distance Maximization Problem (GDMP): the problem of finding the edge weights that maximize the length of the geodesic subject to convex constraints on the weights. We show that GDMP is a convex optimization problem for a wide class of flow costs, and provide a physical interpretation using the dual. We present applications of the GDMP in various fields, including optical lens design, network interdiction, and resource allocation in the control of forest fires. We develop an Alternating Direction Method of Multipliers (ADMM) by exploiting specific problem structures to solve large-scale GDMP, and demonstrate its effectiveness in numerical examples. We then turn our attention to distributed optimization on graph with only local communication. Distributed optimization arises in a variety of applications, e.g. distributed tracking and localization, estimation problems in sensor networks, multi-agent coordination. Distributed optimization aims to optimize a global objective function formed by summation of coupled local functions over a graph via only local communication and computation. We developed a weighted proximal ADMM for distributed optimization using graph structure. This fully distributed, single-loop algorithm allows simultaneous updates and can be viewed as a generalization of existing algorithms. More importantly, we achieve faster convergence by jointly designing graph weights and algorithm parameters. Finally, we propose a new problem on networks called Online Network Formation Problem: starting with a base graph and a set of candidate edges, at each round of the game, player one first chooses a candidate edge and reveals it to player two, then player two decides whether to accept it; player two can only accept limited number of edges and make online decisions with the goal to achieve the best properties of the synthesized network. The network properties considered include the number of spanning trees, algebraic connectivity and total effective resistance. These network formation games arise in a variety of cooperative multiagent systems. We propose a primal-dual algorithm framework for the general online network formation game, and analyze the algorithm performance by the competitive ratio and regret.

LGscore: A method to identify disease-related genes using biological literature and Google data.

PubMed

Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun

2015-04-01

Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessing the Impact of Homophobic Name Calling on Early Adolescent Mental Health: A Longitudinal Social Network Analysis of Competing Peer Influence Effects.

PubMed

DeLay, Dawn; Hanish, Laura D; Zhang, Linlin; Martin, Carol Lynn

2017-05-01

The goal of the current study was to improve our understanding of why adolescence is a critical period for the consideration of declining mental health. We did this by focusing on the impact of homophobic name calling on early adolescent mental health after the transition to middle school. Because we know that homophobic name calling emerges within a dynamic peer group structure, we used longitudinal social network analysis to assess the relation between homophobic name calling, depressive symptoms, and self-esteem while simultaneously limiting bias from alternative peer socialization mechanisms. A sample of adolescents who recently transitioned to a large public middle school (N = 299; 53 % girls; M age  = 11.13 years, SD = 0.48) were assessed. Longitudinal assessments of peer relationship networks, depressive symptoms, and self-esteem were collected during the fall and spring of the academic year. The results suggest that, after accounting for the simultaneous effect of alternative peer socialization processes, adolescent experiences of homophobic name calling in the fall predict higher levels of depressive symptoms and lower levels of self-esteem over the course of the academic year. These findings provide evidence of a significant influence of homophobic name calling on adolescent mental health.

Artificial intelligence: Deep neural reasoning

NASA Astrophysics Data System (ADS)

Jaeger, Herbert

2016-10-01

The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471

Business and Organizational Communication: Abstracts of Doctoral Dissertations Published in "Dissertation Abstracts International," October 1978 through June 1979 (Vol. 39 Nos. 4 through 12).

ERIC Educational Resources Information Center

ERIC Clearinghouse on Reading and Communication Skills, Urbana, IL.

This collection of abstracts is part of a continuing series providing information on recent doctoral dissertations. The 20 titles deal with the following topics: written communication competencies necessary in the accounting profession; the cooperative school approach to developing a communication network; organizational communication and faculty…

Journalism and Journalism Education: Abstracts of Doctoral Dissertations Published in "Dissertation Abstracts International," January through June 1978 (Vol. 38 Nos. 7 through 12).

ERIC Educational Resources Information Center

ERIC Clearinghouse on Reading and Communication Skills, Urbana, IL.

This collection of abstracts is part of a continuing series providing information on recent doctoral dissertations. The 11 titles deal with the following topics: the role and function of the California Journalism Articulation Committee; international communication as an academic career for journalism professors; network television news discourse;…

Quality assurance of chemical ingredient classification for the National Drug File - Reference Terminology.

PubMed

Zheng, Ling; Yumak, Hasan; Chen, Ling; Ochs, Christopher; Geller, James; Kapusnik-Uner, Joan; Perl, Yehoshua

2017-09-01

The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology consisting of several classification hierarchies on top of an extensive collection of drug concepts. These hierarchies provide important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects. Within NDF-RT such information is represented using tens of thousands of roles connecting drugs to classifications. In previous studies, we have introduced various kinds of Abstraction Networks to summarize the content and structure of terminologies in order to facilitate their visual comprehension, and support quality assurance of terminologies. However, these previous kinds of Abstraction Networks are not appropriate for summarizing the NDF-RT classification hierarchies, due to its unique structure. In this paper, we present the novel Ingredient Abstraction Network (IAbN) to summarize, visualize and support the audit of NDF-RT's Chemical Ingredients hierarchy and its associated drugs. A common theme in our quality assurance framework is to use characterizations of sets of concepts, revealed by the Abstraction Network structure, to capture concepts, the modeling of which is more complex than for other concepts. For the IAbN, we characterize drug ingredient concepts as more complex if they belong to IAbN groups with multiple parent groups. We show that such concepts have a statistically significantly higher rate of errors than a control sample and identify two especially common patterns of errors. Copyright © 2017 Elsevier Inc. All rights reserved.

Wireless Sensor Network Radio Power Management and Simulation Models

DTIC Science & Technology

2010-01-01

The Open Electrical & Electronic Engineering Journal, 2010, 4, 21-31 21 1874-1290/10 2010 Bentham Open Open Access Wireless Sensor Network Radio...Air Force Institute of Technology, Wright-Patterson AFB, OH, USA Abstract: Wireless sensor networks (WSNs) create a new frontier in collecting and...consumption. Keywords: Wireless sensor network , power management, energy-efficiency, medium access control (MAC), simulation pa- rameters. 1

From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

NASA Astrophysics Data System (ADS)

Saramäki, Jari; Moro, Esteban

2015-06-01

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

An Exploration of Autonetnography as an eResearch Methodology to Examine Learning and Teaching Scholarship in Networked Learning

ERIC Educational Resources Information Center

Howard, Lyz

2016-01-01

As an experienced face-to-face teacher, working in a small Crown Dependency with no Higher Education Institute (HEI) to call its own, the subsequent geographical and professional isolation in the context of Networked Learning (NL), as a sub-set of eLearning, calls for innovative ways in which to develop self-reliant methods of professional…

GEOMORPHOLOGY OF INTERTIDAL CREEK NETWORKS. (R828677C003)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Facing the IT Talent Squeeze in a Networked Economy

ERIC Educational Resources Information Center

Joyce, Peter J.

2008-01-01

Ten years ago, Cisco began working with schools on a pilot initiative called the Cisco Networking Academy. Today, the Networking Academy program operates in more than 160 countries, comprising a network of more than 7,600 schools that teach the information technology skills essential in a global economy. Cisco Networking Academy has partnered with…

Behavioral networks as a model for intelligent agents

NASA Technical Reports Server (NTRS)

Sliwa, Nancy E.

1990-01-01

On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs.

Improving life sciences information retrieval using semantic web technology.

PubMed

Quan, Dennis

2007-05-01

The ability to retrieve relevant information is at the heart of every aspect of research and development in the life sciences industry. Information is often distributed across multiple systems and recorded in a way that makes it difficult to piece together the complete picture. Differences in data formats, naming schemes and network protocols amongst information sources, both public and private, must be overcome, and user interfaces not only need to be able to tap into these diverse information sources but must also assist users in filtering out extraneous information and highlighting the key relationships hidden within an aggregated set of information. The Semantic Web community has made great strides in proposing solutions to these problems, and many efforts are underway to apply Semantic Web techniques to the problem of information retrieval in the life sciences space. This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.

Detection of whale calls in noise: performance comparison between a beluga whale, human listeners, and a neural network.

PubMed

Erbe, C

2000-07-01

This article examines the masking by anthropogenic noise of beluga whale calls. Results from human masking experiments and a software backpropagation neural network are compared to the performance of a trained beluga whale. The goal was to find an accurate, reliable, and fast model to replace lengthy and expensive animal experiments. A beluga call was masked by three types of noise, an icebreaker's bubbler system and propeller noise, and ambient arctic ice-cracking noise. Both the human experiment and the neural network successfully modeled the beluga data in the sense that they classified the noises in the same order from strongest to weakest masking as the whale and with similar call-detection thresholds. The neural network slightly outperformed the humans. Both models were then used to predict the masking of a fourth type of noise, Gaussian white noise. Their prediction ability was judged by returning to the aquarium to measure masked-hearing thresholds of a beluga in white noise. Both models and the whale identified bubbler noise as the strongest masker, followed by ramming, then white noise. Natural ice-cracking noise masked the least. However, the humans and the neural network slightly overpredicted the amount of masking for white noise. This is neglecting individual variation in belugas, because only one animal could be trained. Comparing the human model to the neural network model, the latter has the advantage of objectivity, reproducibility of results, and efficiency, particularly if the interference of a large number of signals and noise is to be examined.

The Feedback-related Negativity Codes Components of Abstract Inference during Reward-based Decision-making.

PubMed

Reiter, Andrea M F; Koch, Stefan P; Schröger, Erich; Hinrichs, Hermann; Heinze, Hans-Jochen; Deserno, Lorenz; Schlagenhauf, Florian

2016-08-01

Behavioral control is influenced not only by learning from the choices made and the rewards obtained but also by "what might have happened," that is, inference about unchosen options and their fictive outcomes. Substantial progress has been made in understanding the neural signatures of direct learning from choices that are actually made and their associated rewards via reward prediction errors (RPEs). However, electrophysiological correlates of abstract inference in decision-making are less clear. One seminal theory suggests that the so-called feedback-related negativity (FRN), an ERP peaking 200-300 msec after a feedback stimulus at frontocentral sites of the scalp, codes RPEs. Hitherto, the FRN has been predominantly related to a so-called "model-free" RPE: The difference between the observed outcome and what had been expected. Here, by means of computational modeling of choice behavior, we show that individuals employ abstract, "double-update" inference on the task structure by concurrently tracking values of chosen stimuli (associated with observed outcomes) and unchosen stimuli (linked to fictive outcomes). In a parametric analysis, model-free RPEs as well as their modification because of abstract inference were regressed against single-trial FRN amplitudes. We demonstrate that components related to abstract inference uniquely explain variance in the FRN beyond model-free RPEs. These findings advance our understanding of the FRN and its role in behavioral adaptation. This might further the investigation of disturbed abstract inference, as proposed, for example, for psychiatric disorders, and its underlying neural correlates.

Talking and learning physics: Predicting future grades from network measures and Force Concept Inventory pretest scores

NASA Astrophysics Data System (ADS)

Bruun, Jesper; Brewe, Eric

2013-12-01

The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the position in a network, called centrality measures, can be understood in terms of interactions that happen in the context of a university physics course. We apply this discussion to an empirical data set of self-reported student interactions. In a weekly administered survey, first year university students enrolled in an introductory physics course at a Danish university indicated with whom they remembered having communicated within different interaction categories. For three categories pertaining to (1) communication about how to solve physics problems in the course (called the PS category), (2) communications about the nature of physics concepts (called the CD category), and (3) social interactions that are not strictly related to the content of the physics classes (called the ICS category) in the introductory mechanics course, we use the survey data to create networks of student interaction. For each of these networks, we calculate centrality measures for each student and correlate these measures with grades from the introductory course, grades from two subsequent courses, and the pretest Force Concept Inventory (FCI) scores. We find highly significant correlations (p<0.001) between network centrality measures and grades in all networks. We find the highest correlations between network centrality measures and future grades. In the network composed of interactions regarding problem solving (the PS network), the centrality measures hide and PageRank show the highest correlations (r=-0.32 and r=0.33, respectively) with future grades. In the CD network, the network measure target entropy shows the highest correlation (r=0.45) with future grades. In the network composed solely of noncontent related social interactions, these patterns of correlation are maintained in the sense that these network measures show the highest correlations and maintain their internal ranking. Using hierarchical linear regression, we find that a linear model that adds the network measures hide and target entropy, calculated on the ICS network, significantly improves a base model that uses only the FCI pretest scores from the beginning of the semester. Though one should not infer causality from these results, they do point to how social interactions in class are intertwined with academic interactions. We interpret this as an integral part of learning, and suggest that physics is a robust example.

Enhancing Teaching and Learning Wi-Fi Networking Using Limited Resources to Undergraduates

ERIC Educational Resources Information Center

Sarkar, Nurul I.

2013-01-01

Motivating students to learn Wi-Fi (wireless fidelity) wireless networking to undergraduate students is often difficult because many students find the subject rather technical and abstract when presented in traditional lecture format. This paper focuses on the teaching and learning aspects of Wi-Fi networking using limited hardware resources. It…

DReAM: Demand Response Architecture for Multi-level District Heating and Cooling Networks

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

Bhattacharya, Saptarshi; Chandan, Vikas; Arya, Vijay

In this paper, we exploit the inherent hierarchy of heat exchangers in District Heating and Cooling (DHC) networks and propose DReAM, a novel Demand Response (DR) architecture for Multi-level DHC networks. DReAM serves to economize system operation while still respecting comfort requirements of individual consumers. Contrary to many present day DR schemes that work on a consumer level granularity, DReAM works at a level of hierarchy above buildings, i.e. substations that supply heat to a group of buildings. This improves the overall DR scalability and reduce the computational complexity. In the first step of the proposed approach, mathematical models ofmore » individual substations and their downstream networks are abstracted into appropriately constructed low-complexity structural forms. In the second step, this abstracted information is employed by the utility to perform DR optimization that determines the optimal heat inflow to individual substations rather than buildings, in order to achieve the targeted objectives across the network. We validate the proposed DReAM framework through experimental results under different scenarios on a test network.« less

Artificial Neural Network Metamodels of Stochastic Computer Simulations

DTIC Science & Technology

1994-08-10

SUBTITLE r 5. FUNDING NUMBERS Artificial Neural Network Metamodels of Stochastic I () Computer Simulations 6. AUTHOR(S) AD- A285 951 Robert Allen...8217!298*1C2 ARTIFICIAL NEURAL NETWORK METAMODELS OF STOCHASTIC COMPUTER SIMULATIONS by Robert Allen Kilmer B.S. in Education Mathematics, Indiana...dedicate this document to the memory of my father, William Ralph Kilmer. mi ABSTRACT Signature ARTIFICIAL NEURAL NETWORK METAMODELS OF STOCHASTIC

Monitor Network Traffic with Packet Capture (pcap) on an Android Device

DTIC Science & Technology

2015-09-01

administrative privileges . Under the current design Android development requirement, an Android Graphical User Interface (GUI) application cannot directly...build an Android application to monitor network traffic using open source packet capture (pcap) libraries. 15. SUBJECT TERMS ELIDe, Android , pcap 16...Building Application with Native Codes 5 8.1 Calling Native Codes Using JNI 5 8.2 Calling Native Codes from an Android Application 8 9. Retrieve Live

Analysis of a large-scale weighted network of one-to-one human communication

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Saramäki, Jari; Hyvönen, Jörkki; Szabó, Gábor; Argollo de Menezes, M.; Kaski, Kimmo; Barabási, Albert-László; Kertész, János

2007-06-01

We construct a connected network of 3.9 million nodes from mobile phone call records, which can be regarded as a proxy for the underlying human communication network at the societal level. We assign two weights on each edge to reflect the strength of social interaction, which are the aggregate call duration and the cumulative number of calls placed between the individuals over a period of 18 weeks. We present a detailed analysis of this weighted network by examining its degree, strength, and weight distributions, as well as its topological assortativity and weighted assortativity, clustering and weighted clustering, together with correlations between these quantities. We give an account of motif intensity and coherence distributions and compare them to a randomized reference system. We also use the concept of link overlap to measure the number of common neighbours any two adjacent nodes have, which serves as a useful local measure for identifying the interconnectedness of communities. We report a positive correlation between the overlap and weight of a link, thus providing strong quantitative evidence for the weak ties hypothesis, a central concept in social network analysis. The percolation properties of the network are found to depend on the type and order of removed links, and they can help understand how the local structure of the network manifests itself at the global level. We hope that our results will contribute to modelling weighted large-scale social networks, and believe that the systematic approach followed here can be adopted to study other weighted networks.

"Master-Slave" Biological Network Alignment

NASA Astrophysics Data System (ADS)

Ferraro, Nicola; Palopoli, Luigi; Panni, Simona; Rombo, Simona E.

Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. Here the new idea is developed to devise a method for global alignment of PPI networks that in fact exploit differences in the characterization of organisms at hand. We assume that the PPI network (called Master) of the best characterized is used as a fingerprint to guide the alignment process to the second input network (called Slave), so that generated results preferably retain the structural characteristics of the Master (and using the Slave) network. We tested our method showing that the results it returns are biologically relevant.

77 FR 60680 - Development of the Nationwide Interoperable Public Safety Broadband Network

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-04

... public comment on the conceptual network architecture presentation made at the FirstNet Board of... business plan considerations. NTIA also seeks comment on the general concept of how to develop applications... network based on a single, nationwide network architecture called for under the Middle Class Tax Relief...

A Study of the Effects of Fieldbus Network Induced Delays on Control Systems

ERIC Educational Resources Information Center

Mainoo, Joseph

2012-01-01

Fieldbus networks are all-digital, two-way, multi-drop communication systems that are used to connect field devices such as sensors and actuators, and controllers. These fieldbus network systems are also called networked control systems (NCS). Although, there are different varieties of fieldbus networks such as Foundation Field Bus, DeviceNet, and…

Network traffic behaviour near phase transition point

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-03-01

We explore packet traffic dynamics in a data network model near phase transition point from free flow to congestion. The model of data network is an abstraction of the Network Layer of the OSI (Open Systems Interconnect) Reference Model of packet switching networks. The Network Layer is responsible for routing packets across the network from their sources to their destinations and for control of congestion in data networks. Using the model we investigate spatio-temporal packets traffic dynamics near the phase transition point for various network connection topologies, and static and adaptive routing algorithms. We present selected simulation results and analyze them.

Vocalization frequency and duration are coded in separate hindbrain nuclei.

PubMed

Chagnaud, Boris P; Baker, Robert; Bass, Andrew H

2011-06-14

Temporal patterning is an essential feature of neural networks producing precisely timed behaviours such as vocalizations that are widely used in vertebrate social communication. Here we show that intrinsic and network properties of separate hindbrain neuronal populations encode the natural call attributes of frequency and duration in vocal fish. Intracellular structure/function analyses indicate that call duration is encoded by a sustained membrane depolarization in vocal prepacemaker neurons that innervate downstream pacemaker neurons. Pacemaker neurons, in turn, encode call frequency by rhythmic, ultrafast oscillations in their membrane potential. Pharmacological manipulations show prepacemaker activity to be independent of pacemaker function, thus accounting for natural variation in duration which is the predominant feature distinguishing call types. Prepacemaker neurons also innervate key hindbrain auditory nuclei thereby effectively serving as a call-duration corollary discharge. We propose that premotor compartmentalization of neurons coding distinct acoustic attributes is a fundamental trait of hindbrain vocal pattern generators among vertebrates.

Vocalization frequency and duration are coded in separate hindbrain nuclei

PubMed Central

Chagnaud, Boris P.; Baker, Robert; Bass, Andrew H.

2011-01-01

Temporal patterning is an essential feature of neural networks producing precisely timed behaviours such as vocalizations that are widely used in vertebrate social communication. Here we show that intrinsic and network properties of separate hindbrain neuronal populations encode the natural call attributes of frequency and duration in vocal fish. Intracellular structure/function analyses indicate that call duration is encoded by a sustained membrane depolarization in vocal prepacemaker neurons that innervate downstream pacemaker neurons. Pacemaker neurons, in turn, encode call frequency by rhythmic, ultrafast oscillations in their membrane potential. Pharmacological manipulations show prepacemaker activity to be independent of pacemaker function, thus accounting for natural variation in duration which is the predominant feature distinguishing call types. Prepacemaker neurons also innervate key hindbrain auditory nuclei thereby effectively serving as a call-duration corollary discharge. We propose that premotor compartmentalization of neurons coding distinct acoustic attributes is a fundamental trait of hindbrain vocal pattern generators among vertebrates. PMID:21673667

Significant wave heights from Sentinel-1 SAR: Validation and applications

NASA Astrophysics Data System (ADS)

Stopa, J. E.; Mouche, A.

2017-03-01

Two empirical algorithms are developed for wave mode images measured from the synthetic aperture radar aboard Sentinel-1 A. The first method, called CWAVE_S1A, is an extension of previous efforts developed for ERS2 and the second method, called Fnn, uses the azimuth cutoff among other parameters to estimate significant wave heights (Hs) and average wave periods without using a modulation transfer function. Neural networks are trained using colocated data generated from WAVEWATCH III and independently verified with data from altimeters and in situ buoys. We use neural networks to relate the nonlinear relationships between the input SAR image parameters and output geophysical wave parameters. CWAVE_S1A performs well and has reduced precision compared to Fnn with Hs root mean square errors within 0.5 and 0.6 m, respectively. The developed neural networks extend the SAR's ability to retrieve useful wave information under a large range of environmental conditions including extratropical and tropical cyclones in which Hs estimation is traditionally challenging.