Cone beam computed tomography study of apical root resorption induced by Herbst appliance

Science.gov (United States)

SCHWARTZ, João Paulo; RAVELI, Taísa Boamorte; ALMEIDA, Kélei Cristina de Mathias; SCHWARTZ-FILHO, Humberto Osvaldo; RAVELI, Dirceu Barnabé

2015-01-01

Objective This study evaluated the frequency of root resorption during the orthodontic treatment with Herbst appliance by Cone Beam Computed Tomography (CBCT). Material and Methods The sample comprised 23 patients (11 men, 12 women; mean ages 15.76±1.75 years) with Class II division 1 malocclusion, treated with Herbst appliance. CBCT was obtained before treatment (T0) and after Herbst treatment (T1). All the dental roots, except third molars, were evaluated, and apical root resorption was determined using the axial guided navigation method. Paired t-tests and Wilcoxon T Test were used to compare the dependent samples in parametric and nonparametric cases, respectively. Chi-Square Test with Yates’ correction was used to evaluate the relationship between apical root resorption and gender. Results were considered at a significance level of 5%. Results Apical resorption was detected by CBCT in 57.96% of 980 roots that underwent Herbst appliance treatment. All patients had minimal resorption and there was no statistical significance between the genders. Conclusion CBCT three-dimensional evaluation showed association between Herbst appliance and minimal apical root resorption, mostly in the anchoring teeth, without clinical significance. PMID:26537718

Cone beam computed tomography study of apical root resorption induced by Herbst appliance

Directory of Open Access Journals (Sweden)

João Paulo SCHWARTZ

2015-10-01

Full Text Available Objective This study evaluated the frequency of root resorption during the orthodontic treatment with Herbst appliance by Cone Beam Computed Tomography (CBCT.Material and Methods The sample comprised 23 patients (11 men, 12 women; mean ages 15.76±1.75 years with Class II division 1 malocclusion, treated with Herbst appliance. CBCT was obtained before treatment (T0 and after Herbst treatment (T1. All the dental roots, except third molars, were evaluated, and apical root resorption was determined using the axial guided navigation method. Paired t-tests and Wilcoxon T Test were used to compare the dependent samples in parametric and nonparametric cases, respectively. Chi-Square Test with Yates’ correction was used to evaluate the relationship between apical root resorption and gender. Results were considered at a significance level of 5%.Results Apical resorption was detected by CBCT in 57.96% of 980 roots that underwent Herbst appliance treatment. All patients had minimal resorption and there was no statistical significance between the genders.Conclusion CBCT three-dimensional evaluation showed association between Herbst appliance and minimal apical root resorption, mostly in the anchoring teeth, without clinical significance.

Equipment and appliances for underwater operations. Pt. 2

International Nuclear Information System (INIS)

Krueger, P.

1976-01-01

The 6/75 edition of 'mt' reported on the 'ARGE underwater appliances' and the study on 'design development of appliances and equipment for underwater use' in a brief summary. One of these designs, the 'unmanned DSWS underwater appliance' was described in detail. The present article describes three further design developments mentioned in the above study and which are based on unmanned appliances connected to the mother-ship. These designs were developed by Preussag-Meerestechnik. (orig.) [de

Embedded Systems for Smart Appliances and Energy Management

CERN Document Server

Neumann, Peter; Mahlknecht, Stefan

2013-01-01

This book provides a comprehensive introduction to embedded systems for smart appliances and energy management, bringing together for the first time a multidisciplinary blend of topics from embedded systems, information technology and power engineering.  Coverage includes challenges for future resource distribution grids, energy management in smart appliances, micro energy generation, demand response management, ultra-low power stand by, smart standby and communication networks in home and building automation.   Provides a comprehensive, multidisciplinary introduction to embedded systems for smart appliances and energy management; Equips researchers and engineers with information required to succeed in designing energy management for smart appliances; Includes coverage of resource distribution grids, energy management in smart appliances, micro energy generation, demand response management, ultra-low power stand by, smart standby and communication networks in home and building automation.  

Connecting to the Internet Securely; Protecting Home Networks CIAC-2324

Energy Technology Data Exchange (ETDEWEB)

Orvis, W J; Krystosek, P; Smith, J

2002-11-27

With more and more people working at home and connecting to company networks via the Internet, the risk to company networks to intrusion and theft of sensitive information is growing. Working from home has many positive advantages for both the home worker and the company they work for. However, as companies encourage people to work from home, they need to start considering the interaction of the employee's home network and the company network he connects to. This paper discusses problems and solutions related to protection of home computers from attacks on those computers via the network connection. It does not consider protection of those systems from people who have physical access to the computers nor does it consider company laptops taken on-the-road. Home networks are often targeted by intruders because they are plentiful and they are usually not well secured. While companies have departments of professionals to maintain and secure their networks, home networks are maintained by the employee who may be less knowledgeable about network security matters. The biggest problems with home networks are that: Home networks are not designed to be secure and may use technologies (wireless) that are not secure; The operating systems are not secured when they are installed; The operating systems and applications are not maintained (for security considerations) after they are installed; and The networks are often used for other activities that put them at risk for being compromised. Home networks that are going to be connected to company networks need to be cooperatively secured by the employee and the company so they do not open up the company network to intruders. Securing home networks involves many of the same operations as securing a company network: Patch and maintain systems; Securely configure systems; Eliminate unneeded services; Protect remote logins; Use good passwords; Use current antivirus software; and Moderate your Internet usage habits. Most of these

Computer Networks and Globalization

Directory of Open Access Journals (Sweden)

J. Magliaro

2007-07-01

Full Text Available Communication and information computer networks connect the world in ways that make globalization more natural and inequity more subtle. As educators, we look at these phenomena holistically analyzing them from the realist’s view, thus exploring tensions, (in equity and (injustice, and from the idealist’s view, thus embracing connectivity, convergence and development of a collective consciousness. In an increasingly market- driven world we find examples of openness and human generosity that are based on networks, specifically the Internet. After addressing open movements in publishing, software industry and education, we describe the possibility of a dialectic equilibrium between globalization and indigenousness in view of ecologically designed future smart networks

On Connectivity of Wireless Sensor Networks with Directional Antennas

Directory of Open Access Journals (Sweden)

Qiu Wang

2017-01-01

Full Text Available In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

Minimum cost connection networks

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Tvede, Mich

In the present paper we consider the allocation of cost in connection networks. Agents have connection demands in form of pairs of locations they want to be connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection demands...

Large Scale Computing for the Modelling of Whole Brain Connectivity

DEFF Research Database (Denmark)

Albers, Kristoffer Jon

organization of the brain in continuously increasing resolution. From these images, networks of structural and functional connectivity can be constructed. Bayesian stochastic block modelling provides a prominent data-driven approach for uncovering the latent organization, by clustering the networks into groups...... of neurons. Relying on Markov Chain Monte Carlo (MCMC) simulations as the workhorse in Bayesian inference however poses significant computational challenges, especially when modelling networks at the scale and complexity supported by high-resolution whole-brain MRI. In this thesis, we present how to overcome...... these computational limitations and apply Bayesian stochastic block models for un-supervised data-driven clustering of whole-brain connectivity in full image resolution. We implement high-performance software that allows us to efficiently apply stochastic blockmodelling with MCMC sampling on large complex networks...

Pacific Research Platform - Creation of a West Coast Big Data Freeway System Applied to the CONNected objECT (CONNECT) Data Mining Framework for Earth Science Knowledge Discovery

Science.gov (United States)

Sellars, S. L.; Nguyen, P.; Tatar, J.; Graham, J.; Kawsenuk, B.; DeFanti, T.; Smarr, L.; Sorooshian, S.; Ralph, M.

2017-12-01

A new era in computational earth sciences is within our grasps with the availability of ever-increasing earth observational data, enhanced computational capabilities, and innovative computation approaches that allow for the assimilation, analysis and ability to model the complex earth science phenomena. The Pacific Research Platform (PRP), CENIC and associated technologies such as the Flash I/O Network Appliance (FIONA) provide scientists a unique capability for advancing towards this new era. This presentation reports on the development of multi-institutional rapid data access capabilities and data pipeline for applying a novel image characterization and segmentation approach, CONNected objECT (CONNECT) algorithm to study Atmospheric River (AR) events impacting the Western United States. ARs are often associated with torrential rains, swollen rivers, flash flooding, and mudslides. CONNECT is computationally intensive, reliant on very large data transfers, storage and data mining techniques. The ability to apply the method to multiple variables and datasets located at different University of California campuses has previously been challenged by inadequate network bandwidth and computational constraints. The presentation will highlight how the inter-campus CONNECT data mining framework improved from our prior download speeds of 10MB/s to 500MB/s using the PRP and the FIONAs. We present a worked example using the NASA MERRA data to describe how the PRP and FIONA have provided researchers with the capability for advancing knowledge about ARs. Finally, we will discuss future efforts to expand the scope to additional variables in earth sciences.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

Science.gov (United States)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks.

Science.gov (United States)

Pyle, Ryan; Rosenbaum, Robert

2017-01-06

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

46 CFR 78.17-5 - Valves and closing appliances.

Science.gov (United States)

2010-10-01

... 46 Shipping 3 2010-10-01 2010-10-01 false Valves and closing appliances. 78.17-5 Section 78.17-5..., Drills, and Inspections § 78.17-5 Valves and closing appliances. (a) It shall be the duty of the master to see that all valves, including cross connecting valves where fitted, and other appliances such as...

Controlling networking multimedia appliances: with an open environment - a plan-based approach

OpenAIRE

Jantz, D.; Heider, T.

2000-01-01

The need for a better user assistance in technical environments led to the birth of a planning assistant. The principal problems in representing real world tasks in this environment of multimedia home devices are explained. A special issue is the developed EMBASSI Generic Architecture to integrate networked multimedia appliances. The planning assistant engages planning algorithms to fullfill user desires without handling traditional technical control interfaces.

Assessment of perceived orthodontic appliance attractiveness.

Science.gov (United States)

Ziuchkovski, James P; Fields, Henry W; Johnston, William M; Lindsey, Delwin T

2008-04-01

To date, no studies have been published in the literature evaluating the esthetics of orthodontic appliances. The purpose of this study was to assess appliance variables, including appliance type, brand, wire, and ligature tie, for their relative attractiveness. Demographic factors were also evaluated. Appliances were placed in an adult, and digital images were captured, standardized, and incorporated into a computer-based survey. Subjects (n = 200) rated each image for attractiveness on a visual analog scale. The attractiveness ratings were analyzed by using factorial analysis of variance with repeated measures. Post-hoc testing was done with the Tukey-Kramer test (overall a appliances), ceramic, and all self-ligating/stainless steel appliances. No differences between brands in each appliance type were found. Ratings of some ceramic appliances were significantly affected by archwire and ligature tie, depending on several demographic interactions. Orthodontic appliance attractiveness varies by the following hierarchy of appliance types: alternative > ceramic > all stainless steel/self-ligating. Wire and tie selection can affect the appearance of ceramic appliances but have no impact on stainless steel or self-ligating appliances. Certain demographic factors have variable effects on attractiveness ratings.

Documentation of Appliances & Interaction Devices

DEFF Research Database (Denmark)

2004-01-01

The interaction devices and appliances explored in the WorkSPACE project, address spatial computing in the context of work. We have developed and explored a range of appliances and interaction devices. The scope has been to develop tools for support of collaboration by mixing digital and physical...

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

Energy Technology Data Exchange (ETDEWEB)

Archer, Charles J.; Faraj, Daniel A.; Inglett, Todd A.; Ratterman, Joseph D.

2018-01-30

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selected link to the adjacent compute node connected to the compute node through the selected link.

Soft Computing Methods for Disulfide Connectivity Prediction.

Science.gov (United States)

Márquez-Chamorro, Alfonso E; Aguilar-Ruiz, Jesús S

2015-01-01

The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

Science.gov (United States)

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Switch-connected HyperX network

Science.gov (United States)

Chen, Dong; Heidelberger, Philip

2018-02-13

A network system includes a plurality of sub-network planes and global switches. The sub-network planes have a same network topology as each other. Each of the sub-network planes includes edge switches. Each of the edge switches has N ports. Each of the global switches is configured to connect a group of edge switches at a same location in the sub-network planes. In each of the sub-network planes, some of the N ports of each of the edge switches are connected to end nodes, and others of the N ports are connected to other edge switches in the same sub-network plane, other of the N ports are connected to at least one of the global switches.

Relay Protection Coordination for Photovoltaic Power Plant Connected on Distribution Network

OpenAIRE

Nikolovski, Srete; Papuga, Vanja; Knežević, Goran

2014-01-01

This paper presents a procedure and computation of relay protection coordination for a PV power plant connected to the distribution network. In recent years, the growing concern for environment preservation has caused expansion of photovoltaic PV power plants in distribution networks. Numerical computer simulation is an indispensable tool for studying photovoltaic (PV) systems protection coordination. In this paper, EasyPower computer program is used with the module Power Protector. Time-curr...

Handbook of networking & connectivity

CERN Document Server

McClain, Gary R

1994-01-01

Handbook of Networking & Connectivity focuses on connectivity standards in use, including hardware and software options. The book serves as a guide for solving specific problems that arise in designing and maintaining organizational networks.The selection first tackles open systems interconnection, guide to digital communications, and implementing TCP/IP in an SNA environment. Discussions focus on elimination of the SNA backbone, routing SNA over internets, connectionless versus connection-oriented networks, internet concepts, application program interfaces, basic principles of layering, proto

Hyperswitch Network For Hypercube Computer

Science.gov (United States)

Chow, Edward; Madan, Herbert; Peterson, John

1989-01-01

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Email networks and the spread of computer viruses

Science.gov (United States)

Newman, M. E.; Forrest, Stephanie; Balthrop, Justin

2002-09-01

Many computer viruses spread via electronic mail, making use of computer users' email address books as a source for email addresses of new victims. These address books form a directed social network of connections between individuals over which the virus spreads. Here we investigate empirically the structure of this network using data drawn from a large computer installation, and discuss the implications of this structure for the understanding and prevention of computer virus epidemics.

An improved algorithm for connectivity analysis of distribution networks

International Nuclear Information System (INIS)

Kansal, M.L.; Devi, Sunita

2007-01-01

In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks

Computer network for experimental research using ISDN

International Nuclear Information System (INIS)

Ida, Katsumi; Nakanishi, Hideya

1997-01-01

This report describes the development of a computer network that uses the Integrated Service Digital Network (ISDN) for real-time analysis of experimental plasma physics and nuclear fusion research. Communication speed, 64/128kbps (INS64) or 1.5Mbps (INS1500) per connection, is independent of how busy the network is. When INS-1500 is used, the communication speed, which is proportional to the public telephone connection fee, can be dynamically varied from 64kbps to 1472kbps (depending on how much data are being transferred using the Bandwidth-on-Demand (BOD) function in the ISDN Router. On-demand dial-up and time-out disconnection reduce the public telephone connection fee by 10%-97%. (author)

Computational Approach for Securing Radiology-Diagnostic Data in Connected Health Network using High-Performance GPU-Accelerated AES.

Science.gov (United States)

Adeshina, A M; Hashim, R

2017-03-01

Diagnostic radiology is a core and integral part of modern medicine, paving ways for the primary care physicians in the disease diagnoses, treatments and therapy managements. Obviously, all recent standard healthcare procedures have immensely benefitted from the contemporary information technology revolutions, apparently revolutionizing those approaches to acquiring, storing and sharing of diagnostic data for efficient and timely diagnosis of diseases. Connected health network was introduced as an alternative to the ageing traditional concept in healthcare system, improving hospital-physician connectivity and clinical collaborations. Undoubtedly, the modern medicinal approach has drastically improved healthcare but at the expense of high computational cost and possible breach of diagnosis privacy. Consequently, a number of cryptographical techniques are recently being applied to clinical applications, but the challenges of not being able to successfully encrypt both the image and the textual data persist. Furthermore, processing time of encryption-decryption of medical datasets, within a considerable lower computational cost without jeopardizing the required security strength of the encryption algorithm, still remains as an outstanding issue. This study proposes a secured radiology-diagnostic data framework for connected health network using high-performance GPU-accelerated Advanced Encryption Standard. The study was evaluated with radiology image datasets consisting of brain MR and CT datasets obtained from the department of Surgery, University of North Carolina, USA, and the Swedish National Infrastructure for Computing. Sample patients' notes from the University of North Carolina, School of medicine at Chapel Hill were also used to evaluate the framework for its strength in encrypting-decrypting textual data in the form of medical report. Significantly, the framework is not only able to accurately encrypt and decrypt medical image datasets, but it also

A generative modeling approach to connectivity-Electrical conduction in vascular networks

DEFF Research Database (Denmark)

Hald, Bjørn Olav

2016-01-01

The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel...... to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks...... of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub...

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

Science.gov (United States)

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems. PMID:29503613

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers.

Science.gov (United States)

Jordan, Jakob; Ippen, Tammo; Helias, Moritz; Kitayama, Itaru; Sato, Mitsuhisa; Igarashi, Jun; Diesmann, Markus; Kunkel, Susanne

2018-01-01

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

Directory of Open Access Journals (Sweden)

Jakob Jordan

2018-02-01

Full Text Available State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Choice Of Computer Networking Cables And Their Effect On Data ...

African Journals Online (AJOL)

Computer networking is the order of the day in this Information and Communication Technology (ICT) age. Although a network can be through a wireless device most local connections are done using cables. There are three main computer-networking cables namely coaxial cable, unshielded twisted pair cable and the optic ...

Development of new process network for gas chromatograph and analyzers connected with SCADA system and Digital Control Computers at Cernavoda NPP Unit 1

International Nuclear Information System (INIS)

Deneanu, Cornel; Popa Nemoiu, Dragos; Nica, Dana; Bucur, Cosmin

2007-01-01

The continuous monitoring of gas mixture concentrations (deuterium/ hydrogen/oxygen/nitrogen) accumulated in 'Moderator Cover Gas', 'Liquid Control Zone' and 'Heat Transport D 2 O Storage Tank Cover Gas', as well as the continuous monitoring of Heavy Water into Light Water concentration in 'Boilers Steam', 'Boilers Blown Down', 'Moderator heat exchangers', and 'Recirculated Water System', sensing any leaks of Cernavoda NPP U1 led to requirement of developing a new process network for gas chromatograph and analyzers connected to the SCADA system and Digital Control Computers of Cernavoda NPP Unit 1. In 2005 it was designed and implemented the process network for gas chromatograph which connected the gas chromatograph equipment to the SCADA system and Digital Control Computers of the Cernavoda NPP Unit 1. Later this process network for gas chromatograph has been extended to connect the AE13 and AE14 Fourier Transform Infrared (FTIR) analyzers with either. The Gas Chromatograph equipment measures with best accuracy the mixture gases (deuterium/ hydrogen/oxygen/nitrogen) concentration. The Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers measure the Heavy Water into Light Water concentration in Boilers Steam, Boilers BlownDown, Moderator heat exchangers, and Recirculated Water System, monitoring and signaling any leaks. The Gas Chromatograph equipment and Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers use the new OPC (Object Link Embedded for Process Control) technologies available in ABB's VistaNet network for interoperability with automation equipment. This new process network has interconnected the ABB chromatograph and Fourier Transform Infrared analyzers with plant Digital Control Computers using new technology. The result was an increased reliability and capability for inspection and improved system safety

Developments of the general computer network of NIPNE-HH

International Nuclear Information System (INIS)

Mirica, M.; Constantinescu, S.; Danet, A.

1997-01-01

Since 1991 the general computer network of NIPNE-HH was developed and connected to RNCN (Romanian National Computer Network) for research and development and it offers to the Romanian physics research community an efficient and cost-effective infrastructure to communicate and collaborate with fellow researchers abroad, and to collect and exchange the most up-to-date information in their research area. RNCN is targeted on the following main objectives: Setting up a technical and organizational infrastructure meant to provide national and international electronic services for the Romanian scientific research community; - Providing a rapid and competitive tool for the exchange of information in the framework of Research and Development (R-D) community; - Using the scientific and technical data bases available in the country and offered by the national networks from other countries through international networks; - Providing a support for information, scientific and technical co-operation. RNCN has two international links: to EBONE via ACONET (64kbps) and to EuropaNET via Hungarnet (64 kbps). The guiding principle in designing the project of general computer network of NIPNE-HH, as part of RNCN, was to implement an open system based on OSI standards taking into account the following criteria: - development of a flexible solution, according to OSI specifications; - solutions of reliable gateway with the existing network already in use,allowing the access to the worldwide networks; - using the TCP/IP transport protocol for each Local Area Network (LAN) and for the connection to RNCN; - ensuring the integration of different and heterogeneous software and hardware platforms (DOS, Windows, UNIX, VMS, Linux, etc) through some specific interfaces. The major objectives achieved in direction of developing the general computer network of NIPNE-HH are: - linking all the existing and newly installed computer equipment and providing an adequate connectivity. LANs from departments

Characteristics of the TRISTAN control computer network

International Nuclear Information System (INIS)

Kurokawa, Shinichi; Akiyama, Atsuyoshi; Katoh, Tadahiko; Kikutani, Eiji; Koiso, Haruyo; Oide, Katsunobu; Shinomoto, Manabu; Kurihara, Michio; Abe, Kenichi

1986-01-01

Twenty-four minicomputers forming an N-to-N token-ring network control the TRISTAN accelerator complex. The computers are linked by optical fiber cables with 10 Mbps transmission speed. The software system is based on NODAL, a multicomputer interpretive language developed at the CERN SPS. The high-level services offered to the users of the network are remote execution by the EXEC, EXEC-P and IMEX commands of NODAL and uniform file access throughout the system. The network software was designed to achieve the fast response of the EXEC command. The performance of the network is also reported. Tasks that overload the minicomputers are processed on the KEK central computers. One minicomputer in the network serves as a gateway to KEKNET, which connects the minicomputer network and the central computers. The communication with the central computers is managed within the framework of the KEK NODAL system. NODAL programs communicate with the central computers calling NODAL functions; functions for exchanging data between a data set on the central computers and a NODAL variable, submitting a batch job to the central computers, checking the status of the submitted job, etc. are prepared. (orig.)

Ubiquitous monitoring of electrical household appliances.

Science.gov (United States)

Lloret, Jaime; Macías, Elsa; Suárez, Alvaro; Lacuesta, Raquel

2012-11-07

The number of appliances at home is increasing continuously, mainly because they make our lives easier. Currently, technology is integrated in all objects of our daily life. TCP/IP let us monitor our home in real time and check ubiquitously if something is happening at home. Bearing in mind this idea, we have developed a low-cost system, which can be used in any type of electrical household appliance that takes information from the appliance and posts the information to the Twitter Social network. Several sensors placed in the household appliances gather the sensed data and send them wired or wirelessly, depending on the case, using small and cheap devices to a gateway located in the home. This gateway takes decisions, based on the received data, and sends notifications to Twitter. We have developed a software application that takes the values and decides when to issue an alarm to the registered users (Twitter friends of our smart home). The performance of our system has been measured taking into account the home network (using IEEE 802.3u and IEEE 802.11g) and the data publishing in Twitter. As a result, we have generated an original product and service for any electrical household appliance, regardless of the model and manufacturer, that helps home users improve their quality of life. The paper also shows that there is no system with the same innovative features like the ones presented in this paper.

Ubiquitous Monitoring of Electrical Household Appliances

Science.gov (United States)

Lloret, Jaime; Macías, Elsa; Suárez, Alvaro; Lacuesta, Raquel

2012-01-01

The number of appliances at home is increasing continuously, mainly because they make our lives easier. Currently, technology is integrated in all objects of our daily life. TCP/IP let us monitor our home in real time and check ubiquitously if something is happening at home. Bearing in mind this idea, we have developed a low-cost system, which can be used in any type of electrical household appliance that takes information from the appliance and posts the information to the Twitter Social network. Several sensors placed in the household appliances gather the sensed data and send them wired or wirelessly, depending on the case, using small and cheap devices to a gateway located in the home. This gateway takes decisions, based on the received data, and sends notifications to Twitter. We have developed a software application that takes the values and decides when to issue an alarm to the registered users (Twitter friends of our smart home). The performance of our system has been measured taking into account the home network (using IEEE 802.3u and IEEE 802.11g) and the data publishing in Twitter. As a result, we have generated an original product and service for any electrical household appliance, regardless of the model and manufacturer, that helps home users improve their quality of life. The paper also shows that there is no system with the same innovative features like the ones presented in this paper. PMID:23202205

Crew appliance study

Science.gov (United States)

Proctor, B. W.; Reysa, R. P.; Russell, D. J.

1975-01-01

Viable crew appliance concepts were identified by means of a thorough literature search. Studies were made of the food management, personal hygiene, housekeeping, and off-duty habitability functions to determine which concepts best satisfy the Space Shuttle Orbiter and Modular Space Station mission requirements. Models of selected appliance concepts not currently included in the generalized environmental-thermal control and life support systems computer program were developed and validated. Development plans of selected concepts were generated for future reference. A shuttle freezer conceptual design was developed and a test support activity was provided for regenerative environmental control life support subsystems.

A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems.

Science.gov (United States)

Khan, Murad; Silva, Bhagya Nathali; Han, Kijun

2017-02-09

The Web of Things (WoT) plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN), which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST) architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances.

A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems

Directory of Open Access Journals (Sweden)

Murad Khan

2017-02-01

Full Text Available The Web of Things (WoT plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN, which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances.

Highly reliable computer network for real time system

International Nuclear Information System (INIS)

Mohammed, F.A.; Omar, A.A.; Ayad, N.M.A.; Madkour, M.A.I.; Ibrahim, M.K.

1988-01-01

Many of computer networks have been studied different trends regarding the network architecture and the various protocols that govern data transfers and guarantee a reliable communication among all a hierarchical network structure has been proposed to provide a simple and inexpensive way for the realization of a reliable real-time computer network. In such architecture all computers in the same level are connected to a common serial channel through intelligent nodes that collectively control data transfers over the serial channel. This level of computer network can be considered as a local area computer network (LACN) that can be used in nuclear power plant control system since it has geographically dispersed subsystems. network expansion would be straight the common channel for each added computer (HOST). All the nodes are designed around a microprocessor chip to provide the required intelligence. The node can be divided into two sections namely a common section that interfaces with serial data channel and a private section to interface with the host computer. This part would naturally tend to have some variations in the hardware details to match the requirements of individual host computers. fig 7

Implementation of neural networks on 'Connection Machine'

International Nuclear Information System (INIS)

Belmonte, Ghislain

1990-12-01

This report is a first approach to the notion of neural networks and their possible applications within the framework of artificial intelligence activities of the Department of Applied Mathematics of the Limeil-Valenton Research Center. The first part is an introduction to the field of neural networks; the main neural network models are described in this section. The applications of neural networks in the field of classification have mainly been studied because they could more particularly help to solve some of the decision support problems dealt with by the C.E.A. As the neural networks perform a large number of parallel operations, it was therefore logical to use a parallel architecture computer: the Connection Machine (which uses 16384 processors and is located at E.T.C.A. Arcueil). The second part presents some generalities on the parallelism and the Connection Machine, and two implementations of neural networks on Connection Machine. The first of these implementations concerns one of the most used algorithms to realize the learning of neural networks: the Gradient Retro-propagation algorithm. The second one, less common, concerns a network of neurons destined mainly to the recognition of forms: the Fukushima Neocognitron. The latter is studied by the C.E.A. of Bruyeres-le-Chatel in order to realize an embedded system (including hardened circuits) for the fast recognition of forms [fr

CernVM - a virtual software appliance for LHC applications

International Nuclear Information System (INIS)

Buncic, P; Sanchez, C Aguado; Blomer, J; Franco, L; Mato, P; Harutyunian, A; Yao, Y

2010-01-01

CernVM is a Virtual Software Appliance capable of running physics applications from the LHC experiments at CERN. It aims to provide a complete and portable environment for developing and running LHC data analysis on any end-user computer (laptop, desktop) as well as on the Grid, independently of Operating System platforms (Linux, Windows, MacOS). The experiment application software and its specific dependencies are built independently from CernVM and delivered to the appliance just in time by means of a CernVM File System (CVMFS) specifically designed for efficient software distribution. The procedures for building, installing and validating software releases remains under the control and responsibility of each user community. We provide a mechanism to publish pre-built and configured experiment software releases to a central distribution point from where it finds its way to the running CernVM instances via the hierarchy of proxy servers or content delivery networks. In this paper, we present current state of CernVM project and compare performance of CVMFS to performance of traditional network file system like AFS and discuss possible scenarios that could further improve its performance and scalability.

Multimodal Hyper-connectivity Networks for MCI Classification.

Science.gov (United States)

Li, Yang; Gao, Xinqiang; Jie, Biao; Yap, Pew-Thian; Kim, Min-Jeong; Wee, Chong-Yaw; Shen, Dinggang

2017-09-01

Hyper-connectivity network is a network where every edge is connected to more than two nodes, and can be naturally denoted using a hyper-graph. Hyper-connectivity brain network, either based on structural or functional interactions among the brain regions, has been used for brain disease diagnosis. However, the conventional hyper-connectivity network is constructed solely based on single modality data, ignoring potential complementary information conveyed by other modalities. The integration of complementary information from multiple modalities has been shown to provide a more comprehensive representation about the brain disruptions. In this paper, a novel multimodal hyper-network modelling method was proposed for improving the diagnostic accuracy of mild cognitive impairment (MCI). Specifically, we first constructed a multimodal hyper-connectivity network by simultaneously considering information from diffusion tensor imaging and resting-state functional magnetic resonance imaging data. We then extracted different types of network features from the hyper-connectivity network, and further exploited a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Our proposed multimodal hyper-connectivity network demonstrated a better MCI classification performance than the conventional single modality based hyper-connectivity networks.

Open Problems in Network-aware Data Management in Exa-scale Computing and Terabit Networking Era

Energy Technology Data Exchange (ETDEWEB)

Balman, Mehmet; Byna, Surendra

2011-12-06

Accessing and managing large amounts of data is a great challenge in collaborative computing environments where resources and users are geographically distributed. Recent advances in network technology led to next-generation high-performance networks, allowing high-bandwidth connectivity. Efficient use of the network infrastructure is necessary in order to address the increasing data and compute requirements of large-scale applications. We discuss several open problems, evaluate emerging trends, and articulate our perspectives in network-aware data management.

Network and computing infrastructure for scientific applications in Georgia

Science.gov (United States)

Kvatadze, R.; Modebadze, Z.

2016-09-01

Status of network and computing infrastructure and available services for research and education community of Georgia are presented. Research and Educational Networking Association - GRENA provides the following network services: Internet connectivity, network services, cyber security, technical support, etc. Computing resources used by the research teams are located at GRENA and at major state universities. GE-01-GRENA site is included in European Grid infrastructure. Paper also contains information about programs of Learning Center and research and development projects in which GRENA is participating.

Connection Setup Signaling Scheme with Flooding-Based Path Searching for Diverse-Metric Network

Science.gov (United States)

Kikuta, Ko; Ishii, Daisuke; Okamoto, Satoru; Oki, Eiji; Yamanaka, Naoaki

Connection setup on various computer networks is now achieved by GMPLS. This technology is based on the source-routing approach, which requires the source node to store metric information of the entire network prior to computing a route. Thus all metric information must be distributed to all network nodes and kept up-to-date. However, as metric information become more diverse and generalized, it is hard to update all information due to the huge update overhead. Emerging network services and applications require the network to support diverse metrics for achieving various communication qualities. Increasing the number of metrics supported by the network causes excessive processing of metric update messages. To reduce the number of metric update messages, another scheme is required. This paper proposes a connection setup scheme that uses flooding-based signaling rather than the distribution of metric information. The proposed scheme requires only flooding of signaling messages with requested metric information, no routing protocol is required. Evaluations confirm that the proposed scheme achieves connection establishment without excessive overhead. Our analysis shows that the proposed scheme greatly reduces the number of control messages compared to the conventional scheme, while their blocking probabilities are comparable.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Science.gov (United States)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral

FY 2000 report on the results of the development of the stand-by consumption power reduction technology. Verification experiment on the technology to reduce stand-by power of household electric appliances; 2000 nendo taikiji shohi denryoku sakugen gijutsu kaihatsu seika hokokusho. Kaden seihin taikiji denryoku sakugen gijutsu no jissho jikken

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

Study was made of the energy conservation by reducing stand-by consumption power of household electric appliances. In the study, remote control, household electric appliance, and outlet box were developed, and a system was developed in which each of the three was connected by network and the commercial power source supply is cut off at the time of the stand-by state of household electric appliances. The outlet box collectively manages timer information and reservation information. User sends out control command toward the outlet box using the two-way remote control, and controls all the household electric appliances connected via network. The screen data of household electric appliances are sent to the two-way remote control via the outlet box and presented to user. When the time comes for automatic execution such as video recording during absence, the outlet box carries commercial power source to household electric appliances. Using these appliances, verification experiment was carried out in the model house which was built with the ordinary house as model. A reduction in stand-by consumption power, approximately 218kWh/year(center dot)household, was verified. (NEDO)

Computer network for electric power control systems. Chubu denryoku (kabu) denryoku keito seigyoyo computer network

Energy Technology Data Exchange (ETDEWEB)

Tsuneizumi, T. (Chubu Electric Power Co. Inc., Nagoya (Japan)); Shimomura, S.; Miyamura, N. (Fuji Electric Co. Ltd., Tokyo (Japan))

1992-06-03

A computer network for electric power control system was developed that is applied with the open systems interconnection (OSI), an international standard for communications protocol. In structuring the OSI network, a direct session layer was accessed from the operation functions when high-speed small-capacity information is transmitted. File transfer, access and control having a function of collectively transferring large-capacity data were applied when low-speed large-capacity information is transmitted. A verification test for the realtime computer network (RCN) mounting regulation was conducted according to a verification model using a mini-computer, and a result that can satisfy practical performance was obtained. For application interface, kernel, health check and two-route transmission functions were provided as a connection control function, so were transmission verification function and late arrival abolishing function. In system mounting pattern, dualized communication server (CS) structure was adopted. A hardware structure may include a system to have the CS function contained in a host computer and a separate installation system. 5 figs., 6 tabs.

FLOW-BASED NETWORK MEASURES OF BRAIN CONNECTIVITY IN ALZHEIMER'S DISEASE.

Science.gov (United States)

Prasad, Gautam; Joshi, Shantanu H; Nir, Talia M; Toga, Arthur W; Thompson, Paul M

2013-01-01

We present a new flow-based method for modeling brain structural connectivity. The method uses a modified maximum-flow algorithm that is robust to noise in the diffusion data and guided by biologically viable pathways and structure of the brain. A flow network is first created using a lattice graph by connecting all lattice points (voxel centers) to all their neighbors by edges. Edge weights are based on the orientation distribution function (ODF) value in the direction of the edge. The maximum-flow is computed based on this flow graph using the flow or the capacity between each region of interest (ROI) pair by following the connected tractography fibers projected onto the flow graph edges. Network measures such as global efficiency, transitivity, path length, mean degree, density, modularity, small world, and assortativity are computed from the flow connectivity matrix. We applied our method to diffusion-weighted images (DWIs) from 110 subjects (28 normal elderly, 56 with early and 11 with late mild cognitive impairment, and 15 with AD) and segmented co-registered anatomical MRIs into cortical regions. Experimental results showed better performance compared to the standard fiber-counting methods when distinguishing Alzheimer's disease from normal aging.

MDA-image: an environment of networked desktop computers for teleradiology/pathology.

Science.gov (United States)

Moffitt, M E; Richli, W R; Carrasco, C H; Wallace, S; Zimmerman, S O; Ayala, A G; Benjamin, R S; Chee, S; Wood, P; Daniels, P

1991-04-01

MDA-Image, a project of The University of Texas M. D. Anderson Cancer Center, is an environment of networked desktop computers for teleradiology/pathology. Radiographic film is digitized with a film scanner and histopathologic slides are digitized using a red, green, and blue (RGB) video camera connected to a microscope. Digitized images are stored on a data server connected to the institution's computer communication network (Ethernet) and can be displayed from authorized desktop computers connected to Ethernet. Images are digitized for cases presented at the Bone Tumor Management Conference, a multidisciplinary conference in which treatment options are discussed among clinicians, surgeons, radiologists, pathologists, radiotherapists, and medical oncologists. These radiographic and histologic images are shown on a large screen computer monitor during the conference. They are available for later review for follow-up or representation.

State of the Art of Network Security Perspectives in Cloud Computing

Science.gov (United States)

Oh, Tae Hwan; Lim, Shinyoung; Choi, Young B.; Park, Kwang-Roh; Lee, Heejo; Choi, Hyunsang

Cloud computing is now regarded as one of social phenomenon that satisfy customers' needs. It is possible that the customers' needs and the primary principle of economy - gain maximum benefits from minimum investment - reflects realization of cloud computing. We are living in the connected society with flood of information and without connected computers to the Internet, our activities and work of daily living will be impossible. Cloud computing is able to provide customers with custom-tailored features of application software and user's environment based on the customer's needs by adopting on-demand outsourcing of computing resources through the Internet. It also provides cloud computing users with high-end computing power and expensive application software package, and accordingly the users will access their data and the application software where they are located at the remote system. As the cloud computing system is connected to the Internet, network security issues of cloud computing are considered as mandatory prior to real world service. In this paper, survey and issues on the network security in cloud computing are discussed from the perspective of real world service environments.

Mobile network architecture of the long-range WindScanner system

OpenAIRE

Vasiljevic, Nikola; Lea, Guillaume; Hansen, Per; Jensen, Henrik M.

2016-01-01

In this report we have presented the network architecture of the long-range WindScanner system that allows utilization of mobile network connections without the use of static public IP addresses. The architecture mitigates the issues of additional fees and contractual obligations that are linked to the acquisition of the mobile network connections with static public IP addresses. The architecture consists of a hardware VPN solution based on the network appliances Z1 and MX60 from Cisco Meraki...

Smart Security System For Home Appliances Control Based On Internet Of Things

Directory of Open Access Journals (Sweden)

Su Zin Zin Win

2015-08-01

Full Text Available Technology is always evolves. Home security is essential for occupants convenience and protection. Security systems are being preferred over manual system. With the rapid increase in the number of users of internet over the past decade has made Internet a part and parcel of life and IoTs is the latest and emerging internet technology. Home Appliances Control of Smart Security System using IoTs uses computers or mobile devices to control basic home functions and features through internet from anywhere around the world. This security system differs from other system by allowing the user to operate the system from anywhere around the world through internet connection. With the implementation of Arduino Mega microcontroller as an Embedded device security system design was constructed with many sensors and web server database. The Arduino Ethernet shield is used to eliminate the use of a personal computer PC. The motion sensing circuit temperature and humidity sensing circuit smoke or gas sensing circuit door lock sensing circuit light onoff circuit were designed to be connected with Arduino Mega microcontroller and Ethernet shield. This system can monitor the temperature and humidity values and the state of some sensors for intruder detection. It can also control the electric appliances like lights and door at home. Real time result was displayed on web server page via the internet.

Ubiquitous Monitoring of Electrical Household Appliances 

Directory of Open Access Journals (Sweden)

Raquel Lacuesta

2012-11-01

Full Text Available The number of appliances at home is increasing continuously, mainly because they make our lives easier. Currently, technology is integrated in all objects of our daily life. TCP/IP let us monitor our home in real time and check ubiquitously if something is happening at home. Bearing in mind this idea, we have developed a low-cost system, which can be used in any type of electrical household appliance that takes information from the appliance and posts the information to the Twitter Social network. Several sensors placed in the household appliances gather the sensed data and send them wired or wirelessly, depending on the case, using small and cheap devices to a gateway located in the home. This gateway takes decisions, based on the received data, and sends notifications to Twitter. We have developed a software application that takes the values and decides when to issue an alarm to the registered users (Twitter friends of our smart home. The performance of our system has been measured taking into account the home network (using IEEE 802.3u and IEEE 802.11g and the data publishing in Twitter. As a result, we have generated an original product and service for any electrical household appliance, regardless of the model and manufacturer, that helps home users improve their quality of life. The paper also shows that there is no system with the same innovative features like the ones presented in this paper.

Research on the model of home networking

Science.gov (United States)

Yun, Xiang; Feng, Xiancheng

2007-11-01

It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network

Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

Directory of Open Access Journals (Sweden)

Lindsay eRutter

2013-07-01

Full Text Available Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.

Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

Science.gov (United States)

Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

2017-05-01

Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

CX: A Scalable, Robust Network for Parallel Computing

Directory of Open Access Journals (Sweden)

Peter Cappello

2002-01-01

Full Text Available CX, a network-based computational exchange, is presented. The system's design integrates variations of ideas from other researchers, such as work stealing, non-blocking tasks, eager scheduling, and space-based coordination. The object-oriented API is simple, compact, and cleanly separates application logic from the logic that supports interprocess communication and fault tolerance. Computations, of course, run to completion in the presence of computational hosts that join and leave the ongoing computation. Such hosts, or producers, use task caching and prefetching to overlap computation with interprocessor communication. To break a potential task server bottleneck, a network of task servers is presented. Even though task servers are envisioned as reliable, the self-organizing, scalable network of n- servers, described as a sibling-connected height-balanced fat tree, tolerates a sequence of n-1 server failures. Tasks are distributed throughout the server network via a simple "diffusion" process. CX is intended as a test bed for research on automated silent auctions, reputation services, authentication services, and bonding services. CX also provides a test bed for algorithm research into network-based parallel computation.

Synchronization from Second Order Network Connectivity Statistics

Science.gov (United States)

Zhao, Liqiong; Beverlin, Bryce; Netoff, Theoden; Nykamp, Duane Q.

2011-01-01

We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections, and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by their increasing the effective coupling strength. The decrease of synchrony with convergent connections is primarily due to the resulting heterogeneity in firing rates. PMID:21779239

Synchronization from second order network connectivity statistics

Directory of Open Access Journals (Sweden)

Liqiong eZhao

2011-07-01

Full Text Available We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks (SONETs, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by a pool and redistribute mechanism. The pooling of many inputs averages out independent fluctuations, amplifying weak correlations in the inputs. With increased chain connections, neurons with many inputs tend to have many outputs. Hence, chains ensure that the amplified correlations in the neurons with many inputs are redistributed throughout the network, enhancing the development of synchrony across the network.

Connectivity, flow and transport in network models of fractured media

International Nuclear Information System (INIS)

Robinson, P.C.

1984-10-01

In order to evaluate the safety of radioactive waste disposal underground it is important to understand the way in which radioactive material is transported through the rock to the surface. If the rock is fractured the usual models may not be applicable. In this work we look at three aspects of fracture networks: connectivity, flow and transport. These are studied numerically by generating fracture networks in a computer and modelling the processes which occur. Connectivity relates to percolation theory, and critical densities for fracture systems are found in two and three dimensions. The permeability of two-dimensional networks is studied. The way that permeability depends on fracture density, network size and spread of fracture length can be predicted using a cut lattice model. Transport through the fracture network by convection through the fractures and mixing at the intersections is studied. The Fickian dispersion equation does not describe the resulting hydrodynamic dispersion. Extensions to the techniques to three dimensions and to include other processes are discussed. (author)

Mobile network architecture of the long-range WindScanner system

DEFF Research Database (Denmark)

Vasiljevic, Nikola; Lea, Guillaume; Hansen, Per

to the acquisition of the mobile network connections with static public IP addresses. The architecture consists of a hardware VPN solution based on the network appliances Z1 and MX60 from Cisco Meraki with additional 3G or 4G dongles. With the presented network architecture and appropriate configuration, we fulfill...

Default network connectivity in medial temporal lobe amnesia.

Science.gov (United States)

Hayes, Scott M; Salat, David H; Verfaellie, Mieke

2012-10-17

There is substantial overlap between the brain regions supporting episodic memory and the default network. However, in humans, the impact of bilateral medial temporal lobe (MTL) damage on a large-scale neural network such as the default mode network is unknown. To examine this issue, resting fMRI was performed with amnesic patients and control participants. Seed-based functional connectivity analyses revealed robust default network connectivity in amnesia in cortical default network regions such as medial prefrontal cortex, posterior medial cortex, and lateral parietal cortex, as well as evidence of connectivity to residual MTL tissue. Relative to control participants, decreased posterior cingulate cortex connectivity to MTL and increased connectivity to cortical default network regions including lateral parietal and medial prefrontal cortex were observed in amnesic patients. In contrast, somatomotor network connectivity was intact in amnesic patients, indicating that bilateral MTL lesions may selectively impact the default network. Changes in default network connectivity in amnesia were largely restricted to the MTL subsystem, providing preliminary support from MTL amnesic patients that the default network can be fractionated into functionally and structurally distinct components. To our knowledge, this is the first examination of the default network in amnesia.

Nonrandom network connectivity comes in pairs

Directory of Open Access Journals (Sweden)

Felix Z. Hoffmann

2017-02-01

Full Text Available Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, Pij = Pji, the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric.

Optimal Scheduling of Domestic Appliances via MILP

Directory of Open Access Journals (Sweden)

Zdenek Bradac

2014-12-01

Full Text Available This paper analyzes a consumption scheduling mechanism for domestic appliances within a home area network. The aim of the proposed scheduling is to minimize the total energy price paid by the consumer and to reduce power peaks in order to achieve a balanced daily load schedule. An exact and computationally efficient mixed-integer linear programming (MILP formulation of the problem is presented. This model is verified by several problem instances. Realistic scenarios based on the real price tariffs commercially available in the Czech Republic are calculated. The results obtained by solving the optimization problem are compared with a simulation of the ripple control service currently used by many domestic consumers in the Czech Republic.

Modern Embedded Computing Designing Connected, Pervasive, Media-Rich Systems

CERN Document Server

Barry, Peter

2012-01-01

Modern embedded systems are used for connected, media-rich, and highly integrated handheld devices such as mobile phones, digital cameras, and MP3 players. All of these embedded systems require networking, graphic user interfaces, and integration with PCs, as opposed to traditional embedded processors that can perform only limited functions for industrial applications. While most books focus on these controllers, Modern Embedded Computing provides a thorough understanding of the platform architecture of modern embedded computing systems that drive mobile devices. The book offers a comprehen

Insecure Network, Unknown Connection: Understanding Wi-Fi Privacy Assumptions of Mobile Device Users

Directory of Open Access Journals (Sweden)

Bram Bonné

2017-07-01

Full Text Available Smartphones and other mobile devices have proliferated in the past five years. The expectation of mobile device users to always be online has led to Wi-Fi networks being offered by a variety of providers. Using these networks introduces multiple security risks. In this work, we assess to what extent the privacy stance of mobile device users corresponds with their actual behavior by conducting a study with 108 participants. Our methodology consists of monitoring Wi-Fi networks that the participants’ devices connect to and the connections made by apps on these devices, for a period of 30 days. Afterwards, participants are surveyed about their awareness and privacy sensitiveness. We show that while a higher expertise in computer networks corresponds to more awareness about the connections made by apps, neither this expertise nor the actual privacy stance of the participant translates to better security habits. Moreover, participants in general were unaware about a significant part of connections made by apps on their devices, a matter that is worsened by the fact that one third of Wi-Fi networks that participants connect to do not have any security enabled. Based on our results, we provide recommendations to network providers, developers and users on how to improve Wi-Fi security for mobile devices.

Symposium Connects Government Problems with State of the Art Network Science Research

Science.gov (United States)

2015-10-16

Symposium Connects Government Problems with State-of-the- Art Network Science Research By Rajmonda S. Caceres and Benjamin A. Miller Network...the US Gov- ernment, and match these with the state-of-the- art models and techniques developed in the network science research community. Since its... science has grown significantly in the last several years as a field at the intersec- tion of mathematics, computer science , social science , and engineering

The International Database of Efficient Appliances (IDEA): A new tool to support appliance energy-efficiency deployment

International Nuclear Information System (INIS)

Gerke, Brian F.; McNeil, Michael A.; Tu, Thomas

2017-01-01

Highlights: •IDEA collects, organizes, and stores data on appliance features and efficiency. •Data can be gathered for any appliance type on any international market. •IDEA enables new approaches to efficiency deployment and monitoring. •Techniques are developed for cross-market comparison of energy-savings potential. •We find significant cost-effective energy-savings potential from efficiency for Indian and Chinese refrigerators. -- Abstract: Appliance energy-efficiency programs are a central component of many countries’ energy-policy portfolios. A major barrier to optimal implementation of these programs is lack of data to determine market baselines, assess the potential for cost-effective energy savings, and track markets over time to evaluate and verify program impacts. To address this gap, we have developed the International Database of Efficient Appliances (IDEA), a suite of software tools that automatically gathers data that is currently dispersed across various online sources and compiles it into a unified repository of information on efficiency, price, and features for a diversity of appliances and devices in markets around the world. In this article we describe the framework and functionality of IDEA, and we demonstrate its power as a resource for research and policy development related to appliance energy efficiency. Using IDEA data for refrigerators in China and India, we assess the potential for cost-effective energy savings within each market by computing robust indicators that can also be easily compared across different appliances and markets. We find that significant cost-effective savings are available on both markets. We discuss implications for the development of future energy-efficiency deployment programs.

Efficient generation of connectivity in neuronal networks from simulator-independent descriptions

Directory of Open Access Journals (Sweden)

Mikael eDjurfeldt

2014-04-01

Full Text Available Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed.We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeller's needs. We have used the connection generator interface to connect C++ and Python implementations of the connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modelling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.

Line-plane broadcasting in a data communications network of a parallel computer

Science.gov (United States)

Archer, Charles J.; Berg, Jeremy E.; Blocksome, Michael A.; Smith, Brian E.

2010-06-08

Methods, apparatus, and products are disclosed for line-plane broadcasting in a data communications network of a parallel computer, the parallel computer comprising a plurality of compute nodes connected together through the network, the network optimized for point to point data communications and characterized by at least a first dimension, a second dimension, and a third dimension, that include: initiating, by a broadcasting compute node, a broadcast operation, including sending a message to all of the compute nodes along an axis of the first dimension for the network; sending, by each compute node along the axis of the first dimension, the message to all of the compute nodes along an axis of the second dimension for the network; and sending, by each compute node along the axis of the second dimension, the message to all of the compute nodes along an axis of the third dimension for the network.

An Iterative Load Disaggregation Approach Based on Appliance Consumption Pattern

Directory of Open Access Journals (Sweden)

Huijuan Wang

2018-04-01

Full Text Available Non-intrusive load monitoring (NILM, monitoring single-appliance consumption level by decomposing the aggregated energy consumption, is a novel and economic technology that is beneficial to energy utilities and energy demand management strategies development. Hardware costs of high-frequency sampling and algorithm’s computational complexity hampered NILM large-scale application. However, low sampling data shows poor performance in event detection when multiple appliances are simultaneously turned on. In this paper, we contribute an iterative disaggregation approach that is based on appliance consumption pattern (ILDACP. Our approach combined Fuzzy C-means clustering algorithm, which provide an initial appliance operating status, and sub-sequence searching Dynamic Time Warping, which retrieves single energy consumption based on the typical power consumption pattern. Results show that the proposed approach is effective to accurately disaggregate power consumption, and is suitable for the situation where different appliances are simultaneously operated. Also, the approach has lower computational complexity than Hidden Markov Model method and it is easy to implement in the household without installing special equipment.

Toward semantic interoperability of energy using and producing appliances in residential environments

NARCIS (Netherlands)

Hartog, F.T.H. den; Daniele, L.M.; Roes, J.B.M.

2015-01-01

About two thirds of the energy consumed in buildings originates household appliances. Nowadays, appliances are often intelligent and networked devices that form complete energy consuming, producing, and managing systems. Reducing energy is therefore a matter of managing and optimizing the energy

Are we connected? : Ports in Global Networks

NARCIS (Netherlands)

R.A. Zuidwijk (Rob)

2015-01-01

markdownabstractAbstract Global supply chains are built on organizational, information, and logistics networks. Ports are connected via these networks and also need to connect these networks. Synchromodality is an innovative concept for container transportation, and the port plays an important

Computational network design from functional specifications

KAUST Repository

Peng, Chi Han

2016-07-11

Connectivity and layout of underlying networks largely determine agent behavior and usage in many environments. For example, transportation networks determine the flow of traffic in a neighborhood, whereas building floorplans determine the flow of people in a workspace. Designing such networks from scratch is challenging as even local network changes can have large global effects. We investigate how to computationally create networks starting from only high-level functional specifications. Such specifications can be in the form of network density, travel time versus network length, traffic type, destination location, etc. We propose an integer programming-based approach that guarantees that the resultant networks are valid by fulfilling all the specified hard constraints and that they score favorably in terms of the objective function. We evaluate our algorithm in two different design settings, street layout and floorplans to demonstrate that diverse networks can emerge purely from high-level functional specifications.

Status Checking System of Home Appliances using machine learning

Directory of Open Access Journals (Sweden)

Yoon Chi-Yurl

2017-01-01

Full Text Available This paper describes status checking system of home appliances based on machine learning, which can be applied to existing household appliances without networking function. Designed status checking system consists of sensor modules, a wireless communication module, cloud server, android application and a machine learning algorithm. The developed system applied to washing machine analyses and judges the four-kinds of appliance’s status such as staying, washing, rinsing and spin-drying. The measurements of sensor and transmission of sensing data are operated on an Arduino board and the data are transmitted to cloud server in real time. The collected data are parsed by an Android application and injected into the machine learning algorithm for learning the status of the appliances. The machine learning algorithm compares the stored learning data with collected real-time data from the appliances. Our results are expected to contribute as a base technology to design an automatic control system based on machine learning technology for household appliances in real-time.

Analyzing Social Media Networks with NodeXL Insights from a Connected World

CERN Document Server

Hansen, Derek; Smith, Marc A

2010-01-01

Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

Science.gov (United States)

Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S.; Shen, Xilin; Constable, R. Todd; Li, Chiang-Shan R.; Chun, Marvin M.

2016-01-01

Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained attention task, and a low-attention network, comprising connections negatively correlated with performance. Validating the networks as generalizable biomarkers of attention, models based on network strength at rest predicted attention-deficit/hyperactivity disorder (ADHD) symptoms in an independent group of individuals (Rosenberg et al., 2016). To investigate whether these networks play a causal role in attention, here we examined their strength in healthy adults given methylphenidate (Ritalin), a common ADHD treatment, compared with unmedicated controls. As predicted, individuals given methylphenidate showed patterns of connectivity associated with better sustained attention: higher high-attention and lower low-attention network strength than controls. There was significant overlap between the high-attention network and a network with greater strength in the methylphenidate group, and between the low-attention network and a network with greater strength in the control group. Network strength also predicted behavior on a stop-signal task, such that participants with higher go response rates showed higher high-attention and lower low-attention network strength. These results suggest that methylphenidate acts by modulating functional brain networks related to sustained attention, and that changing whole-brain connectivity patterns may help improve attention. SIGNIFICANCE STATEMENT Recent work identified a promising neuromarker of sustained attention based on whole

Fast computation with spikes in a recurrent neural network

International Nuclear Information System (INIS)

Jin, Dezhe Z.; Seung, H. Sebastian

2002-01-01

Neural networks with recurrent connections are sometimes regarded as too slow at computation to serve as models of the brain. Here we analytically study a counterexample, a network consisting of N integrate-and-fire neurons with self excitation, all-to-all inhibition, instantaneous synaptic coupling, and constant external driving inputs. When the inhibition and/or excitation are large enough, the network performs a winner-take-all computation for all possible external inputs and initial states of the network. The computation is done very quickly: As soon as the winner spikes once, the computation is completed since no other neurons will spike. For some initial states, the winner is the first neuron to spike, and the computation is done at the first spike of the network. In general, there are M potential winners, corresponding to the top M external inputs. When the external inputs are close in magnitude, M tends to be larger. If M>1, the selection of the actual winner is strongly influenced by the initial states. If a special relation between the excitation and inhibition is satisfied, the network always selects the neuron with the maximum external input as the winner

Transforce lingual appliances pre-adjusted invisible appliances simplify treatment.

Science.gov (United States)

Clark, William John

2011-01-01

Transforce lingual appliances are designed to be used in conjunction with conventional fixed appliances. Lingual arch development is normally followed by bonded fixed appliances to detail the occlusion. Alternatively Transforce appliance treatment is an efficient method of preparing complex malocclusions prior to a finishing stage with invisible appliances. This approach is ideal for adult treatment, using light continuous forces for arch development with appliances that are comfortable to wear. Sagittal and Transverse appliances are designed for arch development in a range of sizes for contracted arches. They can be used to treat all classes of malocclusion and are pre-adjusted fixed/removable devices for non-compliance treatment. Force modules with nickel titanium coil springs enclosed in a tube deliver a gentle, biocompatible continuous force with a long range of action. They are excellent for mixed dentition and ideal for adult arch development. There are multiple sizes for upper and lower arch development and a sizing chart may be placed over a study model for correct selection, eliminating the need for laboratory work.

An Optimal Path Computation Architecture for the Cloud-Network on Software-Defined Networking

Directory of Open Access Journals (Sweden)

Hyunhun Cho

2015-05-01

Full Text Available Legacy networks do not open the precise information of the network domain because of scalability, management and commercial reasons, and it is very hard to compute an optimal path to the destination. According to today’s ICT environment change, in order to meet the new network requirements, the concept of software-defined networking (SDN has been developed as a technological alternative to overcome the limitations of the legacy network structure and to introduce innovative concepts. The purpose of this paper is to propose the application that calculates the optimal paths for general data transmission and real-time audio/video transmission, which consist of the major services of the National Research & Education Network (NREN in the SDN environment. The proposed SDN routing computation (SRC application is designed and applied in a multi-domain network for the efficient use of resources, selection of the optimal path between the multi-domains and optimal establishment of end-to-end connections.

Computer application for database management and networking of service radio physics

International Nuclear Information System (INIS)

Ferrando Sanchez, A.; Cabello Murillo, E.; Diaz Fuentes, R.; Castro Novais, J.; Clemente Gutierrez, F.; Casa de Juan, M. A. de la; Adaimi Hernandez, P.

2011-01-01

The databases in the quality control prove to be a powerful tool for recording, management and statistical process control. Developed in a Windows environment and under Access (Micros of Office) our service implements this philosophy on the canter's computer network. A computer that acts as the server provides the database to the treatment units to record quality control measures daily and incidents. To remove shortcuts stop working with data migration, possible use of duplicate and erroneous data loss because of errors in network connections, which are common problems, we proceeded to manage connections and access to databases ease of maintenance and use horn to all service personnel.

Default network connectivity during a working memory task.

Science.gov (United States)

Bluhm, Robyn L; Clark, C Richard; McFarlane, Alexander C; Moores, Kathryn A; Shaw, Marnie E; Lanius, Ruth A

2011-07-01

The default network exhibits correlated activity at rest and has shown decreased activation during performance of cognitive tasks. There has been little investigation of changes in connectivity of this network during task performance. In this study, we examined task-related modulation of connectivity between two seed regions from the default network posterior cingulated cortex (PCC) and medial prefrontal cortex (mPFC) and the rest of the brain in 12 healthy adults. The purpose was to determine (1) whether connectivity within the default network differs between a resting state and performance of a cognitive (working memory) task and (2) whether connectivity differs between these nodes of the default network and other brain regions, particularly those implicated in cognitive tasks. There was little change in connectivity with the other main areas of the default network for either seed region, but moderate task-related changes in connectivity occurred between seed regions and regions outside the default network. For example, connectivity of the mPFC with the right insula and the right superior frontal gyrus decreased during task performance. Increased connectivity during the working memory task occurred between the PCC and bilateral inferior frontal gyri, and between the mPFC and the left inferior frontal gyrus, cuneus, superior parietal lobule, middle temporal gyrus and cerebellum. Overall, the areas showing greater correlation with the default network seed regions during task than at rest have been previously implicated in working memory tasks. These changes may reflect a decrease in the negative correlations occurring between the default and task-positive networks at rest. Copyright © 2010 Wiley-Liss, Inc.

Effects of Neuromodulation on Excitatory-Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

Science.gov (United States)

Rich, Scott; Zochowski, Michal; Booth, Victoria

2018-01-01

Acetylcholine (ACh), one of the brain's most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E-I networks), which are ubiquitous in the brain. Utilizing biophysical models of E-I networks, we analyze how the network connectivity structure in terms of synaptic connectivity alters the influence of ACh on the generation of synchronous excitatory bursting. We investigate networks containing all combinations of excitatory and inhibitory cells with high (Type I properties) or low (Type II properties) modulatory tone. To vary network connectivity structure, we focus on the effects of the strengths of inter-connections between excitatory and inhibitory cells (E-I synapses and I-E synapses), and the strengths of intra-connections among excitatory cells (E-E synapses) and among inhibitory cells (I-I synapses). We show that the presence of ACh may or may not affect the generation of network synchrony depending on the network connectivity. Specifically, strong network inter-connectivity induces synchronous excitatory bursting regardless of the cellular propensity for synchronization, which aligns with predictions of the PING model. However, when a network's intra-connectivity dominates its inter-connectivity, the propensity for synchrony of either inhibitory or excitatory cells can determine the generation of network-wide bursting.

Low-power Appliance Recognition using Recurrent Neural Networks

NARCIS (Netherlands)

Rizky Pratama, Azkario; Simanjuntak, Frans Juanda; Lazovik, Aliaksandr; Aiello, Marco

2018-01-01

Indoor energy consumption can be understood by breaking overall power consumption down into individual components and appliance activations. The clas- sification of components of energy usage is known as load disaggregation or ap- pliance recognition. Most of the previous efforts address the

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

Directory of Open Access Journals (Sweden)

Recep Colak

2010-10-01

Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

Science.gov (United States)

Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

Connectivity strategies for higher-order neural networks applied to pattern recognition

Science.gov (United States)

Spirkovska, Lilly; Reid, Max B.

1990-01-01

Different strategies for non-fully connected HONNs (higher-order neural networks) are discussed, showing that by using such strategies an input field of 128 x 128 pixels can be attained while still achieving in-plane rotation and translation-invariant recognition. These techniques allow HONNs to be used with the larger input scenes required for practical pattern-recognition applications. The number of interconnections that must be stored has been reduced by a factor of approximately 200,000 in a T/C case and about 2000 in a Space Shuttle/F-18 case by using regional connectivity. Third-order networks have been simulated using several connection strategies. The method found to work best is regional connectivity. The main advantages of this strategy are the following: (1) it considers features of various scales within the image and thus gets a better sample of what the image looks like; (2) it is invariant to shape-preserving geometric transformations, such as translation and rotation; (3) the connections are predetermined so that no extra computations are necessary during run time; and (4) it does not require any extra storage for recording which connections were formed.

Altered network hub connectivity after acute LSD administration

Directory of Open Access Journals (Sweden)

Felix Müller

Full Text Available LSD is an ambiguous substance, said to mimic psychosis and to improve mental health in people suffering from anxiety and depression. Little is known about the neuronal correlates of altered states of consciousness induced by this substance. Limited previous studies indicated profound changes in functional connectivity of resting state networks after the administration of LSD. The current investigation attempts to replicate and extend those findings in an independent sample. In a double-blind, randomized, cross-over study, 100 μg LSD and placebo were orally administered to 20 healthy participants. Resting state brain activity was assessed by functional magnetic resonance imaging. Within-network and between-network connectivity measures of ten established resting state networks were compared between drug conditions. Complementary analysis were conducted using resting state networks as sources in seed-to-voxel analyses. Acute LSD administration significantly decreased functional connectivity within visual, sensorimotor and auditory networks and the default mode network. While between-network connectivity was widely increased and all investigated networks were affected to some extent, seed-to-voxel analyses consistently indicated increased connectivity between networks and subcortical (thalamus, striatum and cortical (precuneus, anterior cingulate cortex hub structures. These latter observations are consistent with findings on the importance of hubs in psychopathological states, especially in psychosis, and could underlay therapeutic effects of hallucinogens as proposed by a recent model. Keywords: LSD, fMRI, Functional connectivity, Networks, Hubs

Graph Analysis and Modularity of Brain Functional Connectivity Networks: Searching for the Optimal Threshold

Directory of Open Access Journals (Sweden)

Cécile Bordier

2017-08-01

Full Text Available Neuroimaging data can be represented as networks of nodes and edges that capture the topological organization of the brain connectivity. Graph theory provides a general and powerful framework to study these networks and their structure at various scales. By way of example, community detection methods have been widely applied to investigate the modular structure of many natural networks, including brain functional connectivity networks. Sparsification procedures are often applied to remove the weakest edges, which are the most affected by experimental noise, and to reduce the density of the graph, thus making it theoretically and computationally more tractable. However, weak links may also contain significant structural information, and procedures to identify the optimal tradeoff are the subject of active research. Here, we explore the use of percolation analysis, a method grounded in statistical physics, to identify the optimal sparsification threshold for community detection in brain connectivity networks. By using synthetic networks endowed with a ground-truth modular structure and realistic topological features typical of human brain functional connectivity networks, we show that percolation analysis can be applied to identify the optimal sparsification threshold that maximizes information on the networks' community structure. We validate this approach using three different community detection methods widely applied to the analysis of brain connectivity networks: Newman's modularity, InfoMap and Asymptotical Surprise. Importantly, we test the effects of noise and data variability, which are critical factors to determine the optimal threshold. This data-driven method should prove particularly useful in the analysis of the community structure of brain networks in populations characterized by different connectivity strengths, such as patients and controls.

Connecting Network Properties of Rapidly Disseminating Epizoonotics

Science.gov (United States)

Rivas, Ariel L.; Fasina, Folorunso O.; Hoogesteyn, Almira L.; Konah, Steven N.; Febles, José L.; Perkins, Douglas J.; Hyman, James M.; Fair, Jeanne M.; Hittner, James B.; Smith, Steven D.

2012-01-01

Background To effectively control the geographical dissemination of infectious diseases, their properties need to be determined. To test that rapid microbial dispersal requires not only susceptible hosts but also a pre-existing, connecting network, we explored constructs meant to reveal the network properties associated with disease spread, which included the road structure. Methods Using geo-temporal data collected from epizoonotics in which all hosts were susceptible (mammals infected by Foot-and-mouth disease virus, Uruguay, 2001; birds infected by Avian Influenza virus H5N1, Nigeria, 2006), two models were compared: 1) ‘connectivity’, a model that integrated bio-physical concepts (the agent’s transmission cycle, road topology) into indicators designed to measure networks (‘nodes’ or infected sites with short- and long-range links), and 2) ‘contacts’, which focused on infected individuals but did not assess connectivity. Results The connectivity model showed five network properties: 1) spatial aggregation of cases (disease clusters), 2) links among similar ‘nodes’ (assortativity), 3) simultaneous activation of similar nodes (synchronicity), 4) disease flows moving from highly to poorly connected nodes (directionality), and 5) a few nodes accounting for most cases (a “20∶80″ pattern). In both epizoonotics, 1) not all primary cases were connected but at least one primary case was connected, 2) highly connected, small areas (nodes) accounted for most cases, 3) several classes of nodes were distinguished, and 4) the contact model, which assumed all primary cases were identical, captured half the number of cases identified by the connectivity model. When assessed together, the synchronicity and directionality properties explained when and where an infectious disease spreads. Conclusions Geo-temporal constructs of Network Theory’s nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished

An Improved Computing Method for 3D Mechanical Connectivity Rates Based on a Polyhedral Simulation Model of Discrete Fracture Network in Rock Masses

Science.gov (United States)

Li, Mingchao; Han, Shuai; Zhou, Sibao; Zhang, Ye

2018-06-01

Based on a 3D model of a discrete fracture network (DFN) in a rock mass, an improved projective method for computing the 3D mechanical connectivity rate was proposed. The Monte Carlo simulation method, 2D Poisson process and 3D geological modeling technique were integrated into a polyhedral DFN modeling approach, and the simulation results were verified by numerical tests and graphical inspection. Next, the traditional projective approach for calculating the rock mass connectivity rate was improved using the 3D DFN models by (1) using the polyhedral model to replace the Baecher disk model; (2) taking the real cross section of the rock mass, rather than a part of the cross section, as the test plane; and (3) dynamically searching the joint connectivity rates using different dip directions and dip angles at different elevations to calculate the maximum, minimum and average values of the joint connectivity at each elevation. In a case study, the improved method and traditional method were used to compute the mechanical connectivity rate of the slope of a dam abutment. The results of the two methods were further used to compute the cohesive force of the rock masses. Finally, a comparison showed that the cohesive force derived from the traditional method had a higher error, whereas the cohesive force derived from the improved method was consistent with the suggested values. According to the comparison, the effectivity and validity of the improved method were verified indirectly.

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

Directory of Open Access Journals (Sweden)

Bego Blanco

2017-01-01

Full Text Available In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.

Electronic Control System Of Home Appliances Using Speech Command Words

Directory of Open Access Journals (Sweden)

Aye Min Soe

2015-06-01

Full Text Available Abstract The main idea of this paper is to develop a speech recognition system. By using this system smart home appliances are controlled by spoken words. The spoken words chosen for recognition are Fan On Fan Off Light On Light Off TV On and TV Off. The input of the system takes speech signals to control home appliances. The proposed system has two main parts speech recognition and smart home appliances electronic control system. Speech recognition is implemented in MATLAB environment. In this process it contains two main modules feature extraction and feature matching. Mel Frequency Cepstral Coefficients MFCC is used for feature extraction. Vector Quantization VQ approach using clustering algorithm is applied for feature matching. In electrical home appliances control system RF module is used to carry command signal from PC to microcontroller wirelessly. Microcontroller is connected to driver circuit for relay and motor. The input commands are recognized very well. The system is a good performance to control home appliances by spoken words.

Computerized management of radiology department: Installation and use of local area network(LAN) by personal computers

International Nuclear Information System (INIS)

Lee, Young Joon; Han, Kook Sang; Geon, Do Ig; Sol, Chang Hyo; Kim, Byung Soo

1993-01-01

There is increasing need for network connecting personal computers(PC) together. Thus local area network(LAN) emerged, which was designed to allow multiple computers to access and share multiple files and programs and expensive peripheral devices and to communicate with each user. We build PC-LAN in our department that consisted of 1) hardware-9 sets of personal computers(IBM compatible 80386 DX, 1 set; 80286 AT, 8 sets) and cables and network interface cards (Ethernet compatible, 16 bits) that connected PC and peripheral devices 2) software - network operating system and database management system. We managed this network for 6 months. The benefits of PC-LAN were 1) multiuser (share multiple files and programs, peripheral devices) 2) real data processing 3) excellent expandability and flexibility, compatibility, easy connectivity 4) single cable for networking) rapid data transmission 5) simple and easy installation and management 6) using conventional PC's software running under DOS(Disk Operating System) without transformation 7) low networking cost. In conclusion, PC-lan provides an easier and more effective way to manage multiuser database system needed at hospital departments instead of more expensive and complex network of minicomputer or mainframe

Stability of a neural network model with small-world connections

International Nuclear Information System (INIS)

Li Chunguang; Chen Guanrong

2003-01-01

Small-world networks are highly clustered networks with small distances among the nodes. There are many biological neural networks that present this kind of connection. There are no special weightings in the connections of most existing small-world network models. However, this kind of simply connected model cannot characterize biological neural networks, in which there are different weights in synaptic connections. In this paper, we present a neural network model with weighted small-world connections and further investigate the stability of this model

The status of computing and means of local and external networking at JINR

Energy Technology Data Exchange (ETDEWEB)

Dorokhin, A T; Shirikov, V P

1996-12-31

The goal of this report is to represent a view of the current state of computer support at JINR different physical researches. JINR network and its applications are considered. Trends of local networks and the connectivity with global networks are discussed. 3 refs.

Created in Close Interaction with the Industry: The Smart Appliances REFerence (SAREF) Ontology

NARCIS (Netherlands)

Daniele, L.M.; Hartog, F.T.H. den; Roes, J.B.M.

2015-01-01

Around two thirds of the energy consumed by buildings can be traced back to the residential sectors and thus household appliances. Today, most appliances are highly intelligent and networked devices, in principle being able to form complete energy consuming, producing, and managing systems. Reducing

Ecological connectivity networks in rapidly expanding cities.

Science.gov (United States)

Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

2017-06-01

Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for

Ecological connectivity networks in rapidly expanding cities

Directory of Open Access Journals (Sweden)

Amal Najihah M. Nor

2017-06-01

Full Text Available Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow (Passer montanus and Yellow-vented bulbul (Pycnonotus goiavier in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines. The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such

Correlation Networks for Identifying Changes in Brain Connectivity during Epileptiform Discharges and Transcranial Magnetic Stimulation

Directory of Open Access Journals (Sweden)

Elsa Siggiridou

2014-07-01

Full Text Available The occurrence of epileptiform discharges (ED in electroencephalographic (EEG recordings of patients with epilepsy signifies a change in brain dynamics and particularly brain connectivity. Transcranial magnetic stimulation (TMS has been recently acknowledged as a non-invasive brain stimulation technique that can be used in focal epilepsy for therapeutic purposes. In this case study, it is investigated whether simple time-domain connectivity measures, namely cross-correlation and partial cross-correlation, can detect alterations in the connectivity structure estimated from selected EEG channels before and during ED, as well as how this changes with the application of TMS. The correlation for each channel pair is computed on non-overlapping windows of 1 s duration forming weighted networks. Further, binary networks are derived by thresholding or statistical significance tests (parametric and randomization tests. The information for the binary networks is summarized by statistical network measures, such as the average degree and the average path length. Alterations of brain connectivity before, during and after ED with or without TMS are identified by statistical analysis of the network measures at each state.

How has climate change altered network connectivity in a mountain stream network?

Science.gov (United States)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.; Johnson, S.

2017-12-01

Connectivity along river networks is broadly recognized as dynamic, with seasonal and event-based expansion and contraction of the network extent. Intermittently flowing streams are particularly important as they define a crucial threshold for continuously connected waters that enable migration by aquatic species. In the Pacific northwestern U.S., changes in atmospheric circulation have been found to alter rainfall patterns and result in decreased summer low-flows in the region. However, the impact of this climate dynamic on network connectivity is heretofore unstudied. Thus, we ask: How has connectivity in the riparian corridor changed in response to observed changes in climate? In this study we take the well-studied H.J. Andrews Experimental Forest as representative of mountain river networks in the Pacific northwestern U.S. First, we analyze 63 years of stream gauge information from a network of 11 gauges to document observed changes in timing and magnitude of stream discharge. We found declining magnitudes of seasonal low-flows and shifting seasonality of water export from the catchment, both of which we attribute to changes in precipitation timing and storage as snow vs. rainfall. Next, we use these discharge data to drive a reduced-complexity model of the river network to simulate network connectivity over 63 years. Model results show that network contraction (i.e., minimum network extent) has decreased over the past 63 years. Unexpectedly, the increasing winter peak flows did not correspond with increasing network expansion, suggesting a geologic control on maximum flowing network extent. We find dynamic expansion and contraction of the network primarily occurs during period of catchment discharge less than about 1 m3/s at the outlet, whereas the network extent is generally constant for discharges from 1 to 300 m3/s. Results of our study are of interest to scientists focused on connectivity as a control on ecological processes both directly (e.g., fish

Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity.

Science.gov (United States)

Diaz-Pier, Sandra; Naveau, Mikaël; Butz-Ostendorf, Markus; Morrison, Abigail

2016-01-01

With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework.

Quantifying the digital divide: a scientific overview of network connectivity and grid infrastructure in South Asian countries

International Nuclear Information System (INIS)

Khan, S M; Cottrell, R L; Kalim, U; Ali, A

2008-01-01

The future of Computing in High Energy Physics (HEP) applications depends on both the Network and Grid infrastructure. South Asian countries such as India and Pakistan are making significant progress by building clusters as well as improving their network infrastructure However to facilitate the use of these resources, they need to manage the issues of network connectivity to be among the leading participants in Computing for HEP experiments. In this paper we classify the connectivity for academic and research institutions of South Asia. The quantitative measurements are carried out using the PingER methodology; an approach that induces minimal ICMP traffic to gather active end-to-end network statistics. The PingER project has been measuring the Internet performance for the last decade. Currently the measurement infrastructure comprises of over 700 hosts in more than 130 countries which collectively represents approximately 99% of the world's Internet-connected population. Thus, we are well positioned to characterize the world's connectivity. Here we present the current state of the National Research and Educational Networks (NRENs) and Grid Infrastructure in the South Asian countries and identify the areas of concern. We also present comparisons between South Asia and other developing as well as developed regions. We show that there is a strong correlation between the Network performance and several Human Development indices

Quantifying the Digital Divide: A Scientific Overview of Network Connectivity and Grid Infrastructure in South Asian Countries

International Nuclear Information System (INIS)

Khan, Shahryar Muhammad; Cottrell, R. Les; Kalim, Umar; Ali, Arshad

2007-01-01

The future of Computing in High Energy Physics (HEP) applications depends on both the Network and Grid infrastructure. South Asian countries such as India and Pakistan are making significant progress by building clusters as well as improving their network infrastructure However to facilitate the use of these resources, they need to manage the issues of network connectivity to be among the leading participants in Computing for HEP experiments. In this paper we classify the connectivity for academic and research institutions of South Asia. The quantitative measurements are carried out using the PingER methodology; an approach that induces minimal ICMP traffic to gather active end-to-end network statistics. The PingER project has been measuring the Internet performance for the last decade. Currently the measurement infrastructure comprises of over 700 hosts in more than 130 countries which collectively represents approximately 99% of the world's Internet-connected population. Thus, we are well positioned to characterize the world's connectivity. Here we present the current state of the National Research and Educational Networks (NRENs) and Grid Infrastructure in the South Asian countries and identify the areas of concern. We also present comparisons between South Asia and other developing as well as developed regions. We show that there is a strong correlation between the Network performance and several Human Development indices

Social network models predict movement and connectivity in ecological landscapes

Science.gov (United States)

Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

2011-01-01

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Social network models predict movement and connectivity in ecological landscapes.

Science.gov (United States)

Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M

2011-11-29

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

SEADE: Countering the Futility of Network Security

Science.gov (United States)

2015-10-01

guards, and computer cages) and logical security measures (network firewall and intrusion detection). However, no matter how many layers of network...security built-in and with minimal security dependence on network security appliances (e.g., firewalls ). As Secretary of Defense Ashton Carter...based analysis that assumes nothing bad will happen to applications/data if those defenses prevent malware transactions at the entrance. The

Pramipexole Modulates Interregional Connectivity Within the Sensorimotor Network.

Science.gov (United States)

Ye, Zheng; Hammer, Anke; Münte, Thomas F

2017-05-01

Pramipexole is widely prescribed to treat Parkinson's disease but has been reported to cause impulse control disorders such as pathological gambling. Recent neurocomputational models suggested that D2 agonists may distort functional connections between the striatum and the motor cortex, resulting in impaired reinforcement learning and pathological gambling. To examine how D2 agonists modulate the striatal-motor connectivity, we carried out a pharmacological resting-state functional magnetic resonance imaging study with a double-blind randomized within-subject crossover design. We analyzed the medication-induced changes of network connectivity and topology with two approaches, an independent component analysis (ICA) and a graph theoretical analysis (GTA). The ICA identified the sensorimotor network (SMN) as well as other classical resting-state networks. Within the SMN, the connectivity between the right caudate nucleus and other cortical regions was weaker under pramipexole than under placebo. The GTA measured the topological properties of the whole-brain network at global and regional levels. Both the whole-brain network under placebo and that under pramipexole were identified as small-world networks. The two whole-brain networks were similar in global efficiency, clustering coefficient, small-world index, and modularity. However, the degree of the right caudate nucleus decreased under pramipexole mainly due to the loss of the connectivity with the supplementary motor area, paracentral lobule, and precentral and postcentral gyrus of the SMN. The two network analyses consistently revealed that pramipexole weakened the functional connectivity between the caudate nucleus and the SMN regions.

Selectivity and sparseness in randomly connected balanced networks.

Directory of Open Access Journals (Sweden)

Cengiz Pehlevan

Full Text Available Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the "paradoxical" effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.

Dual connectivity for LTE-advanced heterogeneous networks

DEFF Research Database (Denmark)

Wang, Hua; Rosa, Claudio; Pedersen, Klaus I.

2016-01-01

Dual connectivity (DC) allows user equipments (UEs) to receive data simultaneously from different eNodeBs (eNBs) in order to boost the performance in a heterogeneous network with dedicated carrier deployment. Yet, how to efficiently operate with DC opens a number of research questions. In this pa......Dual connectivity (DC) allows user equipments (UEs) to receive data simultaneously from different eNodeBs (eNBs) in order to boost the performance in a heterogeneous network with dedicated carrier deployment. Yet, how to efficiently operate with DC opens a number of research questions...... aggregation (CA) and virtually zerolatency fronthaul connections, and in any case it is significantly higher compared to the case without DC. Keywords: Dual connectivity Heterogeneous network LTE-advanced Radio resource management Performance evaluation...

Attractor neural networks with resource-efficient synaptic connectivity

Science.gov (United States)

Pehlevan, Cengiz; Sengupta, Anirvan

Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

Default Mode Network Connectivity in Stroke Patients.

Science.gov (United States)

Tuladhar, Anil Man; Snaphaan, Liselore; Shumskaya, Elena; Rijpkema, Mark; Fernandez, Guillén; Norris, David G; de Leeuw, Frank-Erik

2013-01-01

The pathophysiology of episodic memory dysfunction after infarction is not completely understood. It has been suggested that infarctions located anywhere in the brain can induce widespread effects causing disruption of functional networks of the cortical regions. The default mode network, which includes the medial temporal lobe, is a functional network that is associated with episodic memory processing. We investigated whether the default mode network activity is reduced in stroke patients compared to healthy control subjects in the resting state condition. We assessed the whole brain network properties during resting state functional MRI in 21 control subjects and 20 'first-ever' stroke patients. Patients were scanned 9-12 weeks after stroke onset. Stroke lesions were located in various parts of the brain. Independent component analyses were conducted to identify the default mode network and to compare the group differences of the default mode network. Furthermore, region-of-interest based analysis was performed to explore the functional connectivity between the regions of the default mode network. Stroke patients performed significantly worse than control subjects on the delayed recall score on California verbal learning test. We found decreased functional connectivity in the left medial temporal lobe, posterior cingulate and medial prefrontal cortical areas within the default mode network and reduced functional connectivity between these regions in stroke patients compared with controls. There were no significant volumetric differences between the groups. These results demonstrate that connectivity within the default mode network is reduced in 'first-ever' stroke patients compared to control subjects. This phenomenon might explain the occurrence of post-stroke cognitive dysfunction in stroke patients.

Connectivity analysis of one-dimensional ad-hoc networks

DEFF Research Database (Denmark)

Hansen, Martin Bøgsted; Rasmussen, Jakob Gulddahl; Schwefel, Hans-Peter

hop-count; (3) the connectivity distance, expressing the geographic distance that a message can be propagated in the network on multi-hop paths; (4) the connectivity hops, which corresponds to the number of hops that are necessary to reach all nodes in the connected network. The paper develops...

Designing Green Networks and Network Operations Saving Run-the-Engine Costs

CERN Document Server

Minoli, Daniel

2011-01-01

In recent years the confluence of socio-political trends toward environmental responsibility and the pressing need to reduce Run-the-Engine (RTE) costs has given birth to a nascent discipline of Green IT. A clear and concise introduction to green networks and green network operations, this book examines analytical measures and discusses virtualization, network computing, and web services as approaches for green data centers and networks. It identifies some strategies for green appliance and end devices and examines the methodical steps that can be taken over time to achieve a seamless migratio

Paralelno umrežavanje računara / Parallel networking of the computers

Directory of Open Access Journals (Sweden)

Milojko Jevtović

2007-04-01

Full Text Available U radu je izložena originalna koncepcija tehničkog rešenja paralelnog umrežavanja računara, kao i lokalnih računarskih mreža (LAN - Local Area Network, odnosno povezivanje i istovremena komunikacija preko više različitih transportnih telekomunikacionih mreža. Opisano je jedno rešenje paralelnog umrežavanja, kojim je omogućen pouzdani prenos multimedijalnog saobraćaja i prenos podataka u realnom vremenu između računara ili LAN istovremeno preko N (N = 1, 2, 3, 4,.. različitih, međusobno nezavisnih mreža širokog prostranstva (WAN - Wide Area Network. Paralelno umrežavanje zasnovano je na korišćenju univerzalnog modema, čije je rešenje, takođe ukratko predstavljeno. / In this paper, new concept for parallel networking of the computers or LANs over different WAN telecommunications networks, is presented. One solution of the parallel networks, which enables reliable transfer of multimedia traffic and data transmission in real time between a computer of LAN via N (N = 1, 2 3, 4,… different inter-connected Wide Area Network. Connections between computers or LANs and wide area networks are realized using universal modems whose solution has also been presented.

Default network connectivity as a vulnerability marker for obsessive compulsive disorder.

Science.gov (United States)

Peng, Z W; Xu, T; He, Q H; Shi, C Z; Wei, Z; Miao, G D; Jing, J; Lim, K O; Zuo, X N; Chan, R C K

2014-05-01

Aberrant functional connectivity within the default network is generally assumed to be involved in the pathophysiology of obsessive compulsive disorder (OCD); however, the genetic risk of default network connectivity in OCD remains largely unknown. Here, we systematically investigated default network connectivity in 15 OCD patients, 15 paired unaffected siblings and 28 healthy controls. We sought to examine the profiles of default network connectivity in OCD patients and their siblings, exploring the correlation between abnormal default network connectivity and genetic risk for this population. Compared with healthy controls, OCD patients exhibited reduced strength of default network functional connectivity with the posterior cingulate cortex (PCC), and increased functional connectivity in the right inferior frontal lobe, insula, superior parietal cortex and superior temporal cortex, while their unaffected first-degree siblings only showed reduced local connectivity in the PCC. These findings suggest that the disruptions of default network functional connectivity might be associated with family history of OCD. The decreased default network connectivity in both OCD patients and their unaffected siblings may serve as a potential marker of OCD.

Smart meter deployment optimisation and its analysis for appliance load monitoring

Directory of Open Access Journals (Sweden)

Ahmed Shaharyar Khwaja

2015-04-01

Full Text Available In this study, the authors study the problem of smart meter deployment optimisation for appliance load monitoring, that is, to monitor a number of devices without any ambiguity using the minimum number of low-cost smart meters. The importance of this problem is due to the fact that the number of meters should be reduced to decrease the deployment cost, improve reliability and decrease congestion. In this way, in future, smart meters can provide additional information about the type and number of distinct devices connected, besides their normal functionalities concerned with providing overall energy measurements and their communication. The authors present two exact smart meter deployment optimisation algorithms, one based on exhaustive search and the other based on efficient implementation of the exhaustive search. They formulate the problem mathematically and present computational complexity analysis of their algorithms. Simulation scenarios show that for a typical number of home appliances, the efficient search method is significantly faster compared to the exhaustive search and can provide the same optimal solution. The authors also show the dependency of their method on the distribution of the load pattern that can potentially be in a typical household.

Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks

Science.gov (United States)

Amin, Hayder; Maccione, Alessandro; Nieus, Thierry

2017-01-01

Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs), interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities) that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity. PMID:28749937

Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.

Directory of Open Access Journals (Sweden)

Davide Lonardoni

2017-07-01

Full Text Available Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons. In vivo, waves of spikes transiently characterize the activity of developing brain circuits and are fundamental for activity-dependent circuit formation. In vitro, coordinated spontaneous spiking activity, or network bursts (NBs, interleaved within periods of asynchronous spikes emerge during the development of 2D and 3D neuronal cultures. Several studies have investigated this type of activity and its dynamics, but how a neuronal system generates these coordinated events remains unclear. Here, we investigate at a cellular level the generation of network bursts in spontaneously active neuronal cultures by exploiting high-resolution multielectrode array recordings and computational network modelling. Our analysis reveals that NBs are generated in specialized regions of the network (functional neuronal communities that feature neuronal links with high cross-correlation peak values, sub-millisecond lags and that share very similar structural connectivity motifs providing recurrent interactions. We show that the particular properties of these local structures enable locally amplifying spontaneous asynchronous spikes and that this mechanism can lead to the initiation of NBs. Through the analysis of simulated and experimental data, we also show that AMPA currents drive the coordinated activity, while NMDA and GABA currents are only involved in shaping the dynamics of NBs. Overall, our results suggest that the presence of functional neuronal communities with recurrent local connections allows a neuronal system to generate spontaneous coordinated spiking activity events. As suggested by the rules used for implementing our computational model, such functional communities might naturally emerge during network development by following simple constraints on distance-based connectivity.

Streaming Multimedia via Overlay Networks using Wi-Fi Peer-to-Peer Connections

DEFF Research Database (Denmark)

Poderys, Justas; Soler, José

2017-01-01

Short range ad-hoc wireless networks can be used to deliver streaming multimedia for information, entertainment and advertisement purposes. To enable short-range communication between various devices, the Wi-Fi Alliance proposed an extension to the IEEE802.11 Wi-Fi standard called Wi-Fi Peer......-to-Peer (P2P). It allows compliant devices to form ad-hoc communication groups without interrupting conventional access point-based Wi-Fi communication. This paper proposes to use Wi-Fi P2P connectivity to distribute streaming multimedia in ah-hoc formed user groups. The exchange of multimedia data...... is performed by forming an overlay network using Peer-to-Peer Streaming Peer Protocol (PPSPP). In order to make PPSPP function over WiFi P2P connections, this paper proposes a number of changes to the protocol. The performance of the proposed system is evaluated using a computer networks emulator...

Orthodontic appliance preferences of children and adolescents.

Science.gov (United States)

Walton, Daniel K; Fields, Henry W; Johnston, William M; Rosenstiel, Stephen F; Firestone, Allen R; Christensen, James C

2010-12-01

Although attractiveness and acceptability of orthodontic appliances have been rated by adults for themselves and for adolescents, children and adolescents have not provided any substantial data. The objective of this study was to evaluate preferences and acceptability of orthodontic appliances in children and adolescents. Images of orthodontic appliances previously captured and standardized were selected and incorporated into a computer-based survey. Additional images of shaped brackets and colored elastomeric ties, as well as discolored clear elastomeric ties, were captured and incorporated onto existing survey images with Photoshop (Adobe, San Jose, Calif). The survey displayed 12 orthodontic appliance variations to 139 children in 3 age groups: 9 to 11 years (n = 45), 12 to 14 years (n = 49), and 15 to 17 years (n = 45). The subjects rated each image for attractiveness and acceptability. All images were displayed and rated twice to assess rater reliability. Overall reliability ratings were r = 0.74 for attractiveness and k = 0.66 for acceptability. There were significant differences in bracket attractiveness and acceptability in each age group. The highest-rated appliances were clear aligners, twin brackets with colored ties, and shaped brackets with and without colored ties. Colored elastomeric ties improved attractiveness significantly over brackets without colored ties for children in the 12-to-14 year group. There was a tendency for older subjects to rate clear orthodontic appliances higher than did younger subjects. Ceramic brackets with discolored ties tended to be rated lower than ceramic brackets with new ties and scored lowest in acceptability and attractiveness in all age groups. Girls rated shaped brackets significantly higher than did boys. Children's preferences for orthodontic appliances differ by age and sex. Child and adolescent preferences differ from adult preferences. Copyright © 2010 American Association of Orthodontists. Published by Mosby

New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

Science.gov (United States)

Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

2012-01-21

Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

Hyper-connectivity of functional networks for brain disease diagnosis.

Science.gov (United States)

Jie, Biao; Wee, Chong-Yaw; Shen, Dinggang; Zhang, Daoqiang

2016-08-01

Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help

High-speed packet switching network to link computers

CERN Document Server

Gerard, F M

1980-01-01

Virtually all of the experiments conducted at CERN use minicomputers today; some simply acquire data and store results on magnetic tape while others actually control experiments and help to process the resulting data. Currently there are more than two hundred minicomputers being used in the laboratory. In order to provide the minicomputer users with access to facilities available on mainframes and also to provide intercommunication between various experimental minicomputers, CERN opted for a packet switching network back in 1975. It was decided to use Modcomp II computers as switching nodes. The only software to be taken was a communications-oriented operating system called Maxcom. Today eight Modcomp II 16-bit computers plus six newer Classic minicomputers from Modular Computer Services have been purchased for the CERNET data communications networks. The current configuration comprises 11 nodes connecting more than 40 user machines to one another and to the laboratory's central computing facility. (0 refs).

Population coding in sparsely connected networks of noisy neurons.

Science.gov (United States)

Tripp, Bryan P; Orchard, Jeff

2012-01-01

This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

Introduction to computer networking

CERN Document Server

Robertazzi, Thomas G

2017-01-01

This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional. • Features a concise, accessible treatment of computer networking, focusing on new technological topics; • Provides non-mathematical introduction to networks in their most common forms today;< • Includes new developments in switching, optical networks, WiFi, Bluetooth, LTE, 5G, and quantum cryptography.

Choosing Wood Burning Appliances

Science.gov (United States)

Information to assist consumers in choosing a wood burning appliance, including types of appliances, the differences between certified and non-certified appliances, and alternative wood heating options.

Services Recommendation System based on Heterogeneous Network Analysis in Cloud Computing

OpenAIRE

Junping Dong; Qingyu Xiong; Junhao Wen; Peng Li

2014-01-01

Resources are provided mainly in the form of services in cloud computing. In the distribute environment of cloud computing, how to find the needed services efficiently and accurately is the most urgent problem in cloud computing. In cloud computing, services are the intermediary of cloud platform, services are connected by lots of service providers and requesters and construct the complex heterogeneous network. The traditional recommendation systems only consider the functional and non-functi...

Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

International Nuclear Information System (INIS)

Wang, Xun-Heng; Li, Lihua

2015-01-01

Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

Energy Technology Data Exchange (ETDEWEB)

Wang, Xun-Heng, E-mail: xhwang@hdu.edu.cn [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China); School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096 (China); Li, Lihua [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China)

2015-05-15

Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

International Nuclear Information System (INIS)

Stern, R.E.; Song, J.; Work, D.B.

2017-01-01

The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

Towards Designing PLC Networks for Ubiquitous Connectivity in Enterprises

OpenAIRE

Ali, Kamran; Pefkianakis, Ioannis; Liu, Alex X.; Kim, Kyu-Han

2016-01-01

Powerline communication (PLC) provides inexpensive, secure and high speed network connectivity, by leveraging the existing power distribution networks inside the buildings. While PLC technology has the potential to improve connectivity and is considered a key enabler for sensing, control, and automation applications in enterprises, it has been mainly deployed for improving connectivity in homes. Deploying PLCs in enterprises is more challenging since the power distribution network is more com...

Analysis of stationary availability factor of two-level backbone computer networks with arbitrary topology

Science.gov (United States)

Rahman, P. A.

2018-05-01

This scientific paper deals with the two-level backbone computer networks with arbitrary topology. A specialized method, offered by the author for calculation of the stationary availability factor of the two-level backbone computer networks, based on the Markov reliability models for the set of the independent repairable elements with the given failure and repair rates and the methods of the discrete mathematics, is also discussed. A specialized algorithm, offered by the author for analysis of the network connectivity, taking into account different kinds of the network equipment failures, is also observed. Finally, this paper presents an example of calculation of the stationary availability factor for the backbone computer network with the given topology.

Renewable energy resources and management appliances-use of smart technologies in the energy

International Nuclear Information System (INIS)

Kultan, J.

2012-01-01

The contribution is aimed at analyzing the impact of renewable energy resources to power system steady modes and the possibility of using smart technology to reduce the impact of inequalities and the variance of the energies and the quality of energy supplied. The use of smart technologies in the form of active dynamic appliances in response to network conditions to reduce effects of stochastic renewable resources dynamic impacts / wind blasts, quickly changing sunlight emissions on solar panels, increasing the amount of water in flow-based water power plants /or a change in network status. Active response appliances, depending on network conditions, improves parameters of economic power generation, transmission, distribution and consumption. (Authors)

Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity

Science.gov (United States)

Liu, Sijia; Chen, Pin-Yu; Hero, Alfred O.

2018-04-01

We consider the problem of accelerating distributed optimization in multi-agent networks by sequentially adding edges. Specifically, we extend the distributed dual averaging (DDA) subgradient algorithm to evolving networks of growing connectivity and analyze the corresponding improvement in convergence rate. It is known that the convergence rate of DDA is influenced by the algebraic connectivity of the underlying network, where better connectivity leads to faster convergence. However, the impact of network topology design on the convergence rate of DDA has not been fully understood. In this paper, we begin by designing network topologies via edge selection and scheduling. For edge selection, we determine the best set of candidate edges that achieves the optimal tradeoff between the growth of network connectivity and the usage of network resources. The dynamics of network evolution is then incurred by edge scheduling. Further, we provide a tractable approach to analyze the improvement in the convergence rate of DDA induced by the growth of network connectivity. Our analysis reveals the connection between network topology design and the convergence rate of DDA, and provides quantitative evaluation of DDA acceleration for distributed optimization that is absent in the existing analysis. Lastly, numerical experiments show that DDA can be significantly accelerated using a sequence of well-designed networks, and our theoretical predictions are well matched to its empirical convergence behavior.

Distributed computing methodology for training neural networks in an image-guided diagnostic application.

Science.gov (United States)

Plagianakos, V P; Magoulas, G D; Vrahatis, M N

2006-03-01

Distributed computing is a process through which a set of computers connected by a network is used collectively to solve a single problem. In this paper, we propose a distributed computing methodology for training neural networks for the detection of lesions in colonoscopy. Our approach is based on partitioning the training set across multiple processors using a parallel virtual machine. In this way, interconnected computers of varied architectures can be used for the distributed evaluation of the error function and gradient values, and, thus, training neural networks utilizing various learning methods. The proposed methodology has large granularity and low synchronization, and has been implemented and tested. Our results indicate that the parallel virtual machine implementation of the training algorithms developed leads to considerable speedup, especially when large network architectures and training sets are used.

Fast long-range connections in transportation networks

International Nuclear Information System (INIS)

Palhares Viana, Matheus; Fontoura Costa, Luciano da

2011-01-01

Multidimensional scaling is applied in order to visualize an analogue of the small-world effect implied by edges having different displacement velocities in transportation networks. Our findings are illustrated for two real-world systems, namely the London urban network (streets and underground) and the US highway network enhanced by some of the main US airlines routes. We also show that the travel time in these two networks is drastically changed by attacks targeting the edges with large displacement velocities. - Highlights: → Multidimensional scaling used to visualize the effects of fast long-range connections. → Fast long-range connections are important to decrease the average travel time. → The average travel time diverges quickly when the network is under target attacks.

Micro-generation network connection (renewables)

Energy Technology Data Exchange (ETDEWEB)

Thornycroft, J.; Russell, T.; Curran, J.

2003-07-01

The drive to reduce emissions of carbon dioxide will result in an increase in the number of small generation units seeking connection to the electric power distribution network. The objectives of this study were to consider connection issues relating to micro-generation from renewables and their integration into the UK distribution network. The document is divided into two sections. The first section describes the present system which includes input from micro-generation, the technical impacts and the financial considerations. The second part discusses technical, financial and governance options for the future. A summary of preferred options and recommendations is given. The study was carried out by the Halcrow Group Ltd under contract to the DTI.

Measuring symmetry, asymmetry and randomness in neural network connectivity.

Directory of Open Access Journals (Sweden)

Umberto Esposito

Full Text Available Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

Measuring symmetry, asymmetry and randomness in neural network connectivity.

Science.gov (United States)

Esposito, Umberto; Giugliano, Michele; van Rossum, Mark; Vasilaki, Eleni

2014-01-01

Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

Science.gov (United States)

Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Locating hardware faults in a data communications network of a parallel computer

Science.gov (United States)

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-01-12

Hardware faults location in a data communications network of a parallel computer. Such a parallel computer includes a plurality of compute nodes and a data communications network that couples the compute nodes for data communications and organizes the compute node as a tree. Locating hardware faults includes identifying a next compute node as a parent node and a root of a parent test tree, identifying for each child compute node of the parent node a child test tree having the child compute node as root, running a same test suite on the parent test tree and each child test tree, and identifying the parent compute node as having a defective link connected from the parent compute node to a child compute node if the test suite fails on the parent test tree and succeeds on all the child test trees.

Connectivity analysis of one-dimensional ad-hoc networks

DEFF Research Database (Denmark)

Bøgsted, Martin; Rasmussen, Jakob Gulddahl; Schwefel, Hans Peter

2011-01-01

distance, expressing the geographic distance that a message can be propagated in the network on multi-hop paths; (4) the connectivity hops, which corresponds to the number of hops that are necessary to reach all nodes in the connected network. The paper develops analytic expressions for the distributions...

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

Science.gov (United States)

Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

2018-06-01

Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Intrinsic network connectivity and own body perception in gender dysphoria.

Science.gov (United States)

Feusner, Jamie D; Lidström, Andreas; Moody, Teena D; Dhejne, Cecilia; Bookheimer, Susan Y; Savic, Ivanka

2017-08-01

Gender dysphoria (GD) is characterized by incongruence between one's identity and gender assigned at birth. The biological mechanisms of GD are unclear. We investigated brain network connectivity patterns involved in own body perception in the context of self in GD. Twenty-seven female-to-male (FtM) individuals with GD, 27 male controls, and 27 female controls underwent resting state fMRI. We compared functional connections within intrinsic connectivity networks involved in self-referential processes and own body perception -default mode network (DMN) and salience network - and visual networks, using independent components analyses. Behavioral correlates of network connectivity were also tested using self-perception ratings while viewing own body images morphed to their sex assigned at birth, and to the sex of their gender identity. FtM exhibited decreased connectivity of anterior and posterior cingulate and precuneus within the DMN compared with controls. In FtM, higher "self" ratings for bodies morphed towards the sex of their gender identity were associated with greater connectivity of the anterior cingulate within the DMN, during long viewing times. In controls, higher ratings for bodies morphed towards their gender assigned at birth were associated with right insula connectivity within the salience network, during short viewing times. Within visual networks FtM showed weaker connectivity in occipital and temporal regions. Results suggest disconnectivity within networks involved in own body perception in the context of self in GD. Moreover, perception of bodies in relation to self may be reflective rather than reflexive, as a function of mesial prefrontal processes. These may represent neurobiological correlates to the subjective disconnection between perception of body and self-identification.

Advanced Scientific Computing Research Network Requirements: ASCR Network Requirements Review Final Report

Energy Technology Data Exchange (ETDEWEB)

Bacon, Charles [Argonne National Lab. (ANL), Argonne, IL (United States); Bell, Greg [ESnet, Berkeley, CA (United States); Canon, Shane [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dart, Eli [ESnet, Berkeley, CA (United States); Dattoria, Vince [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Goodwin, Dave [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Lee, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hicks, Susan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Holohan, Ed [Argonne National Lab. (ANL), Argonne, IL (United States); Klasky, Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lauzon, Carolyn [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Rogers, Jim [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Skinner, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tierney, Brian [ESnet, Berkeley, CA (United States)

2013-03-08

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.

Performance of the TRISTAN computer control network

International Nuclear Information System (INIS)

Koiso, H.; Abe, K.; Akiyama, A.; Katoh, T.; Kikutani, E.; Kurihara, N.; Kurokawa, S.; Oide, K.; Shinomoto, M.

1985-01-01

An N-to-N token ring network of twenty-four minicomputers controls the TRISTAN accelerator complex. The computers are linked by optical fiber cables with 10 Mbps transmission speed. The software system is based on the NODAL, a multi-computer interpreter language developed at CERN SPS. Typical messages exchanged between computers are NODAL programs and NODAL variables transmitted by the EXEC and the REMIT commands. These messages are exchanged as a cluster of packets whose maximum size is 512 bytes. At present, eleven minicomputers are connected to the network and the total length of the ring is 1.5 km. In this condition, the maximum attainable throughput is 980 kbytes/s. The response of a pair of an EXEC and a REMIT transactions which transmit a NODAL array A and one line of program 'REMIT A' and immediately remit the A is measured to be 95+0.039/chi/ ms, where /chi/ is the array size in byte. In ordinary accelerator operations, the maximum channel utilization is 2%, the average packet length is 96 bytes and the transmission rate is 10 kbytes/s

Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

Science.gov (United States)

Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

2017-08-01

Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

Topology and computational performance of attractor neural networks

International Nuclear Information System (INIS)

McGraw, Patrick N.; Menzinger, Michael

2003-01-01

To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world, and scale-free topologies. The random configuration is the most efficient for storage and retrieval of patterns by the network as a whole. However, in the scale-free case retrieval errors are not distributed uniformly among the nodes. The portion of a pattern encoded by the subset of highly connected nodes is more robust and efficiently recognized than the rest of the pattern. The scale-free network thus achieves a very strong partial recognition. The implications of these findings for brain function and social dynamics are suggestive

Sensitivity of marine protected area network connectivity to atmospheric variability.

Science.gov (United States)

Fox, Alan D; Henry, Lea-Anne; Corne, David W; Roberts, J Murray

2016-11-01

International efforts are underway to establish well-connected systems of marine protected areas (MPAs) covering at least 10% of the ocean by 2020. But the nature and dynamics of ocean ecosystem connectivity are poorly understood, with unresolved effects of climate variability. We used 40-year runs of a particle tracking model to examine the sensitivity of an MPA network for habitat-forming cold-water corals in the northeast Atlantic to changes in larval dispersal driven by atmospheric cycles and larval behaviour. Trajectories of Lophelia pertusa larvae were strongly correlated to the North Atlantic Oscillation (NAO), the dominant pattern of interannual atmospheric circulation variability over the northeast Atlantic. Variability in trajectories significantly altered network connectivity and source-sink dynamics, with positive phase NAO conditions producing a well-connected but asymmetrical network connected from west to east. Negative phase NAO produced reduced connectivity, but notably some larvae tracked westward-flowing currents towards coral populations on the mid-Atlantic ridge. Graph theoretical metrics demonstrate critical roles played by seamounts and offshore banks in larval supply and maintaining connectivity across the network. Larval longevity and behaviour mediated dispersal and connectivity, with shorter lived and passive larvae associated with reduced connectivity. We conclude that the existing MPA network is vulnerable to atmospheric-driven changes in ocean circulation.

Connecting and Networking for Schools

Science.gov (United States)

Resources for connecting and networking for schools through e-newsletters, finding school IAQ Champions and other EPA school programs such as Asthma, Energy Star, Clean School Bus USA, School Flag, etc.

Interoperability for smart appliances in the IoT world

NARCIS (Netherlands)

Daniele, L.; Solanki, M.; Hartog, F. den; Roes, J.

2016-01-01

Household appliances are set to become highly intelligent, smart and networked devices in the near future. Systematically deployed on the Internet of Things (IoT), they would be able to form complete energy consuming, producing, and managing ecosystems. Smart systems are technically very

Social Networking for the Older and Wiser Connect with Family, and Friends Old and New

CERN Document Server

McManus, Sean

2010-01-01

Social networks enable anyone with a computer and Internet connection to stay in touch with friends and family across the globe, and rediscover old acquaintances.  Social Networking for the Older and Wiser starts with the basics of social networks, before moving onto intermediate topics, all whilst highlighting ways to protect your privacy and keep your details secure. The book is packed with step-by-step instructions on how to use Facebook, Twitter, Friends Reunited, Saga Zone, and other social networks to:Create an account on your chosen social networkReconnect and stay-in-touch with old fr

Computer-communication networks

CERN Document Server

Meditch, James S

1983-01-01

Computer- Communication Networks presents a collection of articles the focus of which is on the field of modeling, analysis, design, and performance optimization. It discusses the problem of modeling the performance of local area networks under file transfer. It addresses the design of multi-hop, mobile-user radio networks. Some of the topics covered in the book are the distributed packet switching queuing network design, some investigations on communication switching techniques in computer networks and the minimum hop flow assignment and routing subject to an average message delay constraint

Computer simulation of randomly cross-linked polymer networks

International Nuclear Information System (INIS)

Williams, Timothy Philip

2002-01-01

In this work, Monte Carlo and Stochastic Dynamics computer simulations of mesoscale model randomly cross-linked networks were undertaken. Task parallel implementations of the lattice Monte Carlo Bond Fluctuation model and Kremer-Grest Stochastic Dynamics bead-spring continuum model were designed and used for this purpose. Lattice and continuum precursor melt systems were prepared and then cross-linked to varying degrees. The resultant networks were used to study structural changes during deformation and relaxation dynamics. The effects of a random network topology featuring a polydisperse distribution of strand lengths and an abundance of pendant chain ends, were qualitatively compared to recent published work. A preliminary investigation into the effects of temperature on the structural and dynamical properties was also undertaken. Structural changes during isotropic swelling and uniaxial deformation, revealed a pronounced non-affine deformation dependant on the degree of cross-linking. Fractal heterogeneities were observed in the swollen model networks and were analysed by considering constituent substructures of varying size. The network connectivity determined the length scales at which the majority of the substructure unfolding process occurred. Simulated stress-strain curves and diffraction patterns for uniaxially deformed swollen networks, were found to be consistent with experimental findings. Analysis of the relaxation dynamics of various network components revealed a dramatic slowdown due to the network connectivity. The cross-link junction spatial fluctuations for networks close to the sol-gel threshold, were observed to be at least comparable with the phantom network prediction. The dangling chain ends were found to display the largest characteristic relaxation time. (author)

Performance of highly connected photonic switching lossless metro-access optical networks

Science.gov (United States)

Martins, Indayara Bertoldi; Martins, Yara; Barbosa, Felipe Rudge

2018-03-01

The present work analyzes the performance of photonic switching networks, optical packet switching (OPS) and optical burst switching (OBS), in mesh topology of different sizes and configurations. The "lossless" photonic switching node is based on a semiconductor optical amplifier, demonstrated and validated with experimental results on optical power gain, noise figure, and spectral range. The network performance was evaluated through computer simulations based on parameters such as average number of hops, optical packet loss fraction, and optical transport delay (Am). The combination of these elements leads to a consistent account of performance, in terms of network traffic and packet delivery for OPS and OBS metropolitan networks. Results show that a combination of highly connected mesh topologies having an ingress e-buffer present high efficiency and throughput, with very low packet loss and low latency, ensuring fast data delivery to the final receiver.

How do household characteristics affect appliance usage? Application of conditional demand analysis to Japanese household data

International Nuclear Information System (INIS)

Matsumoto, Shigeru

2016-01-01

Although both appliance ownership and usage patterns determine residential electricity consumption, it is less known how households actually use their appliances. In this study, we conduct conditional demand analyses to break down total household electricity consumption into a set of demand functions for electricity usage, across 12 appliance categories. We then examine how the socioeconomic characteristics of the households explain their appliance usage. Analysis of micro-level data from the Nation Survey of Family and Expenditure in Japan reveals that the family and income structure of households affect appliance usage. Specifically, we find that the presence of teenagers increases both air conditioner and dishwasher use, labor income and nonlabor income affect microwave usage in different ways, air conditioner usage decreases as the wife's income increases, and microwave usage decreases as the husband's income increases. Furthermore, we find that households use more electricity with new personal computers than old ones; this implies that the replacement of old personal computers increases electricity consumption. - Highlights: •We conduct conditional demand analyses to study household appliance usage. •Micro-level data from the National Survey of Family and Expenditure in Japan are analyzed. •We show how household characteristics determine appliance usage. •High-income households use specific appliances less intensively than low-income households. •The replacement of old TVs and PCs lead to greater electricity consumption.

A segmented appliance for space closure followed by Invisalign and fixed appliances.

Science.gov (United States)

Uribe, Flavio; Cutrera, Alice; Nanda, Ravinda

2011-01-01

This case report describes the use of a segmented appliance for space closure prior to using Invisalign. The maxillary right canine was retracted into the extracted first premolar space with a sectional wire from the first molar to the canine with no visible brackets in the incisor region. The advantage of this technique is the ability to achieve better root and rotational control during space closure with a fixed appliance that also has limited visibility. A maxillary fixed appliance was used to refine the esthetics in the maxillary arch due to the limitations of the Invisalign appliance in achieving rotational and vertical movements.

Brookhaven Reactor Experiment Control Facility, a distributed function computer network

International Nuclear Information System (INIS)

Dimmler, D.G.; Greenlaw, N.; Kelley, M.A.; Potter, D.W.; Rankowitz, S.; Stubblefield, F.W.

1975-11-01

A computer network for real-time data acquisition, monitoring and control of a series of experiments at the Brookhaven High Flux Beam Reactor has been developed and has been set into routine operation. This reactor experiment control facility presently services nine neutron spectrometers and one x-ray diffractometer. Several additional experiment connections are in progress. The architecture of the facility is based on a distributed function network concept. A statement of implementation and results is presented

Change in brain network connectivity during PACAP38-induced migraine attacks

DEFF Research Database (Denmark)

Amin, Faisal Mohammad; Hougaard, Anders; Magon, Stefano

2016-01-01

OBJECTIVE: To investigate resting-state functional connectivity in the salience network (SN), the sensorimotor network (SMN), and the default mode network (DMN) during migraine attacks induced by pituitary adenylate cyclase-activating polypeptide-38 (PACAP38). METHODS: In a double-blind, randomized...... connectivity with the bilateral opercular part of the inferior frontal gyrus in the SN. In SMN, there was increased connectivity with the right premotor cortex and decreased connectivity with the left visual cortex. Several areas showed increased (left primary auditory, secondary somatosensory, premotor......, and visual cortices) and decreased (right cerebellum and left frontal lobe) connectivity with DMN. We found no resting-state network changes after VIP (n = 15). CONCLUSIONS: PACAP38-induced migraine attack is associated with altered connectivity of several large-scale functional networks of the brain....

Reducing electricity demand peaks by scheduling home appliances usage

Energy Technology Data Exchange (ETDEWEB)

Rossello-Busquet, A.; Kardaras, G.; Baek Iversen, V.; Soler, J.; Dittmann, L.

2011-05-15

Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users' appliances should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions. On the contrary, the low priority devices have to pause their operation, when the algorithm dictates it, and resume it in the future. This can become beneficial for both energy companies and users. The electricity suppliers companies will be capable of regulating power generation during demand peaks periods. Moreover, users can be granted lower electricity bill rates for accepting delaying the operation of some of their appliances. In order to analyze this scenario, teletraffic engineering theory, which is used in evaluating the performance of telecommunication networks, is used. A reversible fair scheduling (RFS) algorithm, which was originally developed for telecommunication networks, is applied. The purpose is to analyze how a power consumption limit and priorities for home appliances will affect the demand peak and the users' everyday life. Verification of the effectiveness of the RFS algorithm is done by means of simulation and by using real data for power consumption and operation hours. The defined maximum power limit of 750 and 1000 Watt was not exceeded during

Effects of local and global network connectivity on synergistic epidemics

Science.gov (United States)

Broder-Rodgers, David; Pérez-Reche, Francisco J.; Taraskin, Sergei N.

2015-12-01

Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.

Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

Science.gov (United States)

Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

2018-02-01

Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

BONFIRE: benchmarking computers and computer networks

OpenAIRE

Bouckaert, Stefan; Vanhie-Van Gerwen, Jono; Moerman, Ingrid; Phillips, Stephen; Wilander, Jerker

2011-01-01

The benchmarking concept is not new in the field of computing or computer networking. With “benchmarking tools”, one usually refers to a program or set of programs, used to evaluate the performance of a solution under certain reference conditions, relative to the performance of another solution. Since the 1970s, benchmarking techniques have been used to measure the performance of computers and computer networks. Benchmarking of applications and virtual machines in an Infrastructure-as-a-Servi...

The super-Turing computational power of plastic recurrent neural networks.

Science.gov (United States)

Cabessa, Jérémie; Siegelmann, Hava T

2014-12-01

We study the computational capabilities of a biologically inspired neural model where the synaptic weights, the connectivity pattern, and the number of neurons can evolve over time rather than stay static. Our study focuses on the mere concept of plasticity of the model so that the nature of the updates is assumed to be not constrained. In this context, we show that the so-called plastic recurrent neural networks (RNNs) are capable of the precise super-Turing computational power--as the static analog neural networks--irrespective of whether their synaptic weights are modeled by rational or real numbers, and moreover, irrespective of whether their patterns of plasticity are restricted to bi-valued updates or expressed by any other more general form of updating. Consequently, the incorporation of only bi-valued plastic capabilities in a basic model of RNNs suffices to break the Turing barrier and achieve the super-Turing level of computation. The consideration of more general mechanisms of architectural plasticity or of real synaptic weights does not further increase the capabilities of the networks. These results support the claim that the general mechanism of plasticity is crucially involved in the computational and dynamical capabilities of biological neural networks. They further show that the super-Turing level of computation reflects in a suitable way the capabilities of brain-like models of computation.

46 CFR 111.77-3 - Appliances.

Science.gov (United States)

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Appliances. 111.77-3 Section 111.77-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) ELECTRICAL ENGINEERING ELECTRIC SYSTEMS-GENERAL REQUIREMENTS Appliances and Appliance Circuits § 111.77-3 Appliances. All electrical appliances, including, but...

Network-Embedded Management and Applications Understanding Programmable Networking Infrastructure

CERN Document Server

Wolter, Ralf

2013-01-01

Despite the explosion of networking services and applications in the past decades, the basic technological underpinnings of the Internet have remained largely unchanged. At its heart are special-purpose appliances that connect us to the digital world, commonly known as switches and routers. Now, however, the traditional framework is being increasingly challenged by new methods that are jostling for a position in the next-generation Internet. The concept of a network that is becoming more programmable is one of the aspects that are taking center stage. This opens new possibilities to embed software applications inside the network itself and to manage networks and communications services with unprecedented ease and efficiency. In this edited volume, distinguished experts take the reader on a tour of different facets of programmable network infrastructure and application exploit it. Presenting the state of the art in network embedded management and applications and programmable network infrastructure, the book c...

Ubiquitous Network Society

Directory of Open Access Journals (Sweden)

Cristian USCATU

2006-01-01

Full Text Available Technology is evolving faster than ever in the ITC domain. Computing devices become smaller and more powerful by the day (and cheaper than ever. They have started to move away from the classical “computer” towards portable devices like personal digital assistants (PDAs and mobile phones. Even these devices are no longer what they used to be. A phone is no longer a simple voice communication device, but a minicomputer with lots of functions. The addition of wireless communication protocols, like WiFi and Bluetooth, leads to a web of interconnected devices with the final purpose of enabling us to access desired services anywhere, at any time. Adding less complicated devices, as sensors and detectors, located everywhere (clothes, cars, furniture, home appliances etc. but connected to the same global network, we have a technological world aware of itself and aware of us, ready to serve our needs without hindering our lives. “Ubiquitous computing names the third wave in computing, just now beginning. First were mainframes, each shared by lots of people. Now we are in the personal computing era, person and machine staring uneasily at each other across the desktop. Next comes ubiquitous computing, or the age of calm technology, when technology recedes into the background of our lives.” [Weiser, 1995

Light Manipulation in Metallic Nanowire Networks with Functional Connectivity

KAUST Repository

Galinski, Henning

2016-12-27

Guided by ideas from complex systems, a new class of network metamaterials is introduced for light manipulation, which are based on the functional connectivity among heterogeneous subwavelength components arranged in complex networks. The model system is a nanonetwork formed by dealloying a metallic thin film. The connectivity of the network is deterministically controlled, enabling the formation of tunable absorbing states.

Population Coding in Sparsely Connected Networks of Noisy Neurons

Directory of Open Access Journals (Sweden)

Bryan Patrick Tripp

2012-05-01

Full Text Available This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behaviour. However, population coding theory has often ignored network structure, or assumed discrete, fully-connected populations (in contrast with the sparsely connected, continuous sheet of the cortex. In this study, we model a sheet of cortical neurons with sparse, primarily local connections, and find that a network with this structure can encode multiple internal state variables with high signal-to-noise ratio. However, in our model, although connection probability varies with the distance between neurons, we find that the connections cannot be instantiated at random according to these probabilities, but must have additional structure if information is to be encoded with high fidelity.

Prioritizing connection requests in GMPLS-controlled optical networks

DEFF Research Database (Denmark)

Ruepp, Sarah Renée; Koster, A.; Andriolli, N.

2009-01-01

We prioritize bidirectional connection requests by combining dynamic connection provisioning with off-line optimization. Results show that the proposed approach decreases wavelength-converter usage, thereby allowing operators to reduce blocking-probably under bulk connection assignment or network...

Scholastic performance and functional connectivity of brain networks in children.

Directory of Open Access Journals (Sweden)

Laura Chaddock-Heyman

Full Text Available One of the keys to understanding scholastic success is to determine the neural processes involved in school performance. The present study is the first to use a whole-brain connectivity approach to explore whether functional connectivity of resting state brain networks is associated with scholastic performance in seventy-four 7- to 9-year-old children. We demonstrate that children with higher scholastic performance across reading, math and language have more integrated and interconnected resting state networks, specifically the default mode network, salience network, and frontoparietal network. To add specificity, core regions of the dorsal attention and visual networks did not relate to scholastic performance. The results extend the cognitive role of brain networks in children as well as suggest the importance of network connectivity in scholastic success.

Mini-screws, a viable adjunct along with Incognito lingual appliance: A case series

Directory of Open Access Journals (Sweden)

Wei Lin

2015-01-01

Full Text Available Invisible orthodontics have been around for too long, and with the advent of computer-aided design/computer-aided manufacturing technology appliances such as Incognito TM has made the whole treatment experience more pleasant and aesthetic. However, even in lingual orthodontics, biomechanics play the most important role, and the use of temporary anchorage devices (TADs has made the whole treatment more effective and efficient. This article focuses on cases where TADs in lingual appliances play a critical role in the treatment of various malocclusions.

Stability of a giant connected component in a complex network

Science.gov (United States)

Kitsak, Maksim; Ganin, Alexander A.; Eisenberg, Daniel A.; Krapivsky, Pavel L.; Krioukov, Dmitri; Alderson, David L.; Linkov, Igor

2018-01-01

We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

Functional organization of intrinsic connectivity networks in Chinese-chess experts.

Science.gov (United States)

Duan, Xujun; Long, Zhiliang; Chen, Huafu; Liang, Dongmei; Qiu, Lihua; Huang, Xiaoqi; Liu, Timon Cheng-Yi; Gong, Qiyong

2014-04-16

The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

Cloud Computing Services for Seismic Networks

Science.gov (United States)

Olson, Michael

This thesis describes a compositional framework for developing situation awareness applications: applications that provide ongoing information about a user's changing environment. The thesis describes how the framework is used to develop a situation awareness application for earthquakes. The applications are implemented as Cloud computing services connected to sensors and actuators. The architecture and design of the Cloud services are described and measurements of performance metrics are provided. The thesis includes results of experiments on earthquake monitoring conducted over a year. The applications developed by the framework are (1) the CSN---the Community Seismic Network---which uses relatively low-cost sensors deployed by members of the community, and (2) SAF---the Situation Awareness Framework---which integrates data from multiple sources, including the CSN, CISN---the California Integrated Seismic Network, a network consisting of high-quality seismometers deployed carefully by professionals in the CISN organization and spread across Southern California---and prototypes of multi-sensor platforms that include carbon monoxide, methane, dust and radiation sensors.

Latest developments for a computer aided thermohydraulic network

International Nuclear Information System (INIS)

Alemberti, A.; Graziosi, G.; Mini, G.; Susco, M.

1999-01-01

Thermohydraulic networks are I-D systems characterized by a small number of basic components (pumps, valves, heat exchangers, etc) connected by pipes and limited spatially by a defined number of boundary conditions (tanks, atmosphere, etc). The network system is simulated by the well known computer program RELAPS/mod3. Information concerning the network geometry component behaviour, initial and boundary conditions are usually supplied to the RELAPS code using an ASCII input file by means of 'input cards'. CATNET (Computer Aided Thermalhydraulic NETwork) is a graphically user interface that, under specific user guidelines which completely define its range of applicability, permits a very high level of standardization and simplification of the RELAPS/mod3 input deck development process as well as of the output processing. The characteristics of the components (pipes, valves, pumps etc), defining the network system can be entered through CATNET. The CATNET interface is provided by special functions to compute form losses in the most typical bending and branching configurations. When the input of all system components is ready, CATNET is able to generate the RELAPS/mod3 input file. Finally, by means of CATNET, the RELAPS/mod3 code can be run and its output results can be transformed to an intuitive display form. The paper presents an example of application of the CATNET interface as well as the latest developments which greatly simplified the work of the users and allowed to reduce the possibility of input errors. (authors)

Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback.

Science.gov (United States)

Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank

2017-02-01

Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Non-intrusive appliance load monitoring system based on a modern kWh-meter

Energy Technology Data Exchange (ETDEWEB)

Pihala, H. [VTT Energy, Espoo (Finland). Energy Systems

1998-12-01

Non-intrusive appliance load monitoring (NIALM) is a fairly new method to estimate load profiles of individual electric appliances in a small building, like a household, by monitoring the whole load at a single point with one recording device without sub-meters. Appliances have special electrical characteristics, the positive and negative active and reactive power changes during the time they are switched on or off. These changes are called events and are detected with a monitoring device called an event recorder. Different NIALM-concepts developed in Europe and in the United States are generally discussed. The NIALM-concept developed in this study is based on a 3-phase, power quality monitoring kWh-meter and unique load identification algorithms. This modern kWh-meter with a serial data bus to a laptop personal computer is used as die event recorder. The NIALM-concept of this presentation shows for the first time how a kWh-meter can be used at the same time for billing, power quality and appliance end-use monitoring. An essential part of the developed NIALM-system prototype is the software of load identification algorithms which runs in an off-line personal computer. These algorithms are able to identify, with a certain accuracy, both two-state and multi-state appliances. This prototype requires manual-setup in which the naming of appliances is performed. The results of the prototype NIALMS were verified in a large, single family detached house and they were compared to the results of other prototypes in France and the United States, although this comparison is difficult because of different supply systems, appliance stock and number of tested sites. Different applications of NIALM are discussed. Gathering of load research data, verification of DSM-programs, home automation, failure analysis of appliances and security surveillance of buildings are interesting areas of NIALM. Both utilities and customers can benefit from these applications. It is possible to

Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender

Directory of Open Access Journals (Sweden)

Vasileios C. Pezoulas

2017-04-01

Full Text Available During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high fluid Intelligence Quotient (IQ. Functional magnetic resonance imaging (fMRI data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our results

Knowledge Access in Rural Inter-connected Areas Network ...

International Development Research Centre (IDRC) Digital Library (Canada)

Knowledge Access in Rural Inter-connected Areas Network (KariaNet) - Phase II ... the existing network to include two thematic networks on food security and rural ... Woman conquering male business in Yemen : Waleya's micro-enterprise.

Hoisting appliances and fuel handling equipment at nuclear facilities

International Nuclear Information System (INIS)

1987-01-01

The guide is followed by the Finnish Centre for Radiation and Nuclear Safety (STUK) in regulating hoisting and handling equipment Class 3 at nuclear facilities. The guide is applied e.g. to the following equipment: reactor building overhead cranes, hoisting appliances at nuclear fuel storages, fuel handling machines, other hoisting appliances, which because of nuclear safety aspects are classified in Safety Class 3, and load-bearing devices connected with the above equipment, such as replaceable hoisting tools and auxiliary lifting devices. The regulating of hoisting and handling equipment comprises the following stages: handling of preliminary and final safety analysis reports, inspection of the construction plan, supervision of fabrication and construction inspection, and supervision of initial start-up and commissioning inspection

Default mode network connectivity during task execution.

Science.gov (United States)

Vatansever, D; Menon, D K; Manktelow, A E; Sahakian, B J; Stamatakis, E A

2015-11-15

Initially described as task-induced deactivations during goal-directed paradigms of high attentional load, the unresolved functionality of default mode regions has long been assumed to interfere with task performance. However, recent evidence suggests a potential default mode network involvement in fulfilling cognitive demands. We tested this hypothesis in a finger opposition paradigm with task and fixation periods which we compared with an independent resting state scan using functional magnetic resonance imaging and a comprehensive analysis pipeline including activation, functional connectivity, behavioural and graph theoretical assessments. The results indicate task specific changes in the default mode network topography. Behaviourally, we show that increased connectivity of the posterior cingulate cortex with the left superior frontal gyrus predicts faster reaction times. Moreover, interactive and dynamic reconfiguration of the default mode network regions' functional connections illustrates their involvement with the task at hand with higher-level global parallel processing power, yet preserved small-world architecture in comparison with rest. These findings demonstrate that the default mode network does not disengage during this paradigm, but instead may be involved in task relevant processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Optical computer switching network

Science.gov (United States)

Clymer, B.; Collins, S. A., Jr.

1985-01-01

The design for an optical switching system for minicomputers that uses an optical spatial light modulator such as a Hughes liquid crystal light valve is presented. The switching system is designed to connect 80 minicomputers coupled to the switching system by optical fibers. The system has two major parts: the connection system that connects the data lines by which the computers communicate via a two-dimensional optical matrix array and the control system that controls which computers are connected. The basic system, the matrix-based connecting system, and some of the optical components to be used are described. Finally, the details of the control system are given and illustrated with a discussion of timing.

Topological probability and connection strength induced activity in complex neural networks

International Nuclear Information System (INIS)

Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo

2010-01-01

Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)

Aberrant cerebellar connectivity in motor and association networks in schizophrenia

Directory of Open Access Journals (Sweden)

Ann K. Shinn

2015-03-01

Full Text Available Schizophrenia is a devastating illness characterized by disturbances in multiple domains. The cerebellum is involved in both motor and non-motor functions, and the cognitive dysmetria and dysmetria of thought models propose that abnormalities of the cerebellum may contribute to schizophrenia signs and symptoms. The cerebellum and cerebral cortex are reciprocally connected via a modular, closed-loop network architecture, but few schizophrenia neuroimaging studies have taken into account the topographical and functional heterogeneity of the cerebellum. In this study, using a previously defined 17-network cerebral cortical parcellation system as the basis for our functional connectivity seeds, we systematically investigated connectivity abnormalities within the cerebellum of 44 schizophrenia patients and 28 healthy control participants. We found selective alterations in cerebro-cerebellar functional connectivity. Specifically, schizophrenia patients showed decreased cerebro-cerebellar functional connectivity in higher level association networks (ventral attention, salience, control, and default mode networks relative to healthy control participants. Schizophrenia patients also showed increased cerebro-cerebellar connectivity in somatomotor and default mode networks, with the latter showing no overlap with the regions found to be hypoconnected within the same default mode network. Finally, we found evidence to suggest that somatomotor and default mode networks may be inappropriately linked in schizophrenia. The relationship of these dysconnectivities to schizophrenia symptoms, such as neurological soft signs and altered sense of agency, is discussed. We conclude that the cerebellum ought to be considered for analysis in all future studies of network abnormalities in SZ, and further suggest the cerebellum as a potential target for further elucidation, and possibly treatment, of the underlying mechanisms and network abnormalities producing symptoms of

Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

Directory of Open Access Journals (Sweden)

Christopher E Hart

2006-12-01

Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

Computing networks from cluster to cloud computing

CERN Document Server

Vicat-Blanc, Pascale; Guillier, Romaric; Soudan, Sebastien

2013-01-01

"Computing Networks" explores the core of the new distributed computing infrastructures we are using today:  the networking systems of clusters, grids and clouds. It helps network designers and distributed-application developers and users to better understand the technologies, specificities, constraints and benefits of these different infrastructures' communication systems. Cloud Computing will give the possibility for millions of users to process data anytime, anywhere, while being eco-friendly. In order to deliver this emerging traffic in a timely, cost-efficient, energy-efficient, and

Dynamic causal modeling of hippocampal links within the human default mode network: Lateralization and computational stability of effective connections

Directory of Open Access Journals (Sweden)

Vadim Leonidovich Ushakov

2016-10-01

Full Text Available The purpose of this paper was to study causal relationships between left and right hippocampal regions (LHIP and RHIP, respectively within the default mode network (DMN as represented by its key structures: the medial prefrontal cortex (MPFC, posterior cingulate cortex (PCC and the inferior parietal cortex of left (LIPC and right (RIPC hemispheres. Furthermore, we were interested in testing the stability of the connectivity patterns when adding or deleting regions of interest. The functional magnetic resonance imaging (fMRI data from a group of 30 healthy right-handed subjects in the resting state were collected and a connectivity analysis was performed. To model the effective connectivity, we used the spectral Dynamic Causal Modeling (DCM. Three DCM analyses were completed. Two of them modeled interaction between five nodes that included four DMN key structures in addition to either LHIP or RHIP. The last DCM analysis modeled interactions between four nodes whereby one of the main DMN structures, PCC, was excluded from the analysis. The results of all DCM analyses indicated a high level of stability in the computational method: those parts of the winning models that included the key DMN structures demonstrated causal relations known from recent research. However, we discovered new results as well. First of all, we found a pronounced asymmetry in LHIP and RHIP connections. LHIP demonstrated a high involvement of DMN activity with preponderant information outflow to all other DMN regions. Causal interactions of LHIP were bidirectional only in the case of LIPC. On the contrary, RHIP was primarily affected by inputs from LIPC, RIPC and LHIP without influencing these or other DMN key structures. For the first time, an inhibitory link was found from MPFC to LIPC, which may indicate the subjects’ effort to maintain a resting state. Functional connectivity data echoed these results, though they also showed links not reflected in the patterns of

Modular organization of functional network connectivity in healthy controls and patients with schizophrenia during the resting state

Directory of Open Access Journals (Sweden)

Qingbao eYu

2012-01-01

Full Text Available Neuroimaging studies have shown that functional brain networks composed from select regions of interest (ROIs have a modular community structure. However, the organization of functional network connectivity (FNC, comprising a purely data-driven network built from spatially independent brain components, is not yet clear. The aim of this study is to explore the modular organization of FNC in both healthy controls (HCs and patients with schizophrenia (SZs. Resting state functional magnetic resonance imaging (R-fMRI data of HCs and SZs were decomposed into independent components (ICs by group independent component analysis (ICA. Then weighted brain networks (in which nodes are brain components were built based on correlations among of ICA time courses. Clustering coefficients and connectivity strength of the networks were computed. A dynamic branch cutting algorithm was used to identify modules of the FNC in HCs and SZs. Results show stronger connectivity strength and higher clustering coefficient in HCs with more and smaller modules in SZs. In addition, HCs and SZs had some different hubs. Our findings demonstrate altered modular architecture of the FNC in schizophrenia and provide insights into abnormal topological organization of intrinsic brain networks in this mental illness.

Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease

Science.gov (United States)

Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M.; Leonardo, Cassandra D.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matthew A.; Thompson, Paul M.

2015-01-01

Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. PMID:26640830

Emissions from wood domestic heating appliances

International Nuclear Information System (INIS)

Collet, S.

2009-01-01

Much research has been carried out to study emissions from wood domestic heating appliances. This work reviews the available emission factors about pollutants produced in different types of wood domestic heating appliances. The main sources of pollutants are older stoves that in most cases are used as an additional heating appliance. These stoves causes higher emissions than modern appliances. Then, substitution of an old type wood appliance with a modern appliance or boiler or a pellet boilers, would reduce considerably emissions in this sector. The efficiency of this measure is estimated for each pollutant. (author)

Activating and inhibiting connections in biological network dynamics

Directory of Open Access Journals (Sweden)

Knight Rob

2008-12-01

Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

Towards Self-Powered Wireless Sensor Networks

OpenAIRE

SPENZA, DORA

2013-01-01

Ubiquitous computing aims at creating smart environments in which computational and communication capabilities permeate the word at all scales, improving the human experience and quality of life in a totally unobtrusive yet completely reliable manner. According to this vision, an huge variety of smart devices and products (e.g., wireless sensor nodes, mobile phones, cameras, sensors, home appliances and industrial machines) are interconnected to realize a network of distributed agents that co...

A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing.

Science.gov (United States)

Sillin, Henry O; Aguilera, Renato; Shieh, Hsien-Hang; Avizienis, Audrius V; Aono, Masakazu; Stieg, Adam Z; Gimzewski, James K

2013-09-27

Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated the model against various experimental results highlighting the possibility to functionalize the network plasticity and the differences between an atomic switch in isolation and its behaviors in a network. The effects of changing connectivity density on the nonlinear dynamics were examined as characterized by higher harmonic generation in response to AC inputs. To demonstrate their utility for computation, we subjected the simulated network to training within the framework of reservoir computing and showed initial evidence of the ASN acting as a reservoir which may be optimized for specific tasks by adjusting the input gain. The work presented represents steps in a unified approach to experimentation and theory of complex systems to make ASNs a uniquely scalable platform for neuromorphic computing.

Social sciences via network analysis and computation

CERN Document Server

Kanduc, Tadej

2015-01-01

In recent years information and communication technologies have gained significant importance in the social sciences. Because there is such rapid growth of knowledge, methods and computer infrastructure, research can now seamlessly connect interdisciplinary fields such as business process management, data processing and mathematics. This study presents some of the latest results, practices and state-of-the-art approaches in network analysis, machine learning, data mining, data clustering and classifications in the contents of social sciences. It also covers various real-life examples such as t

Oral appliances and functional orthopaedic appliances for obstructive sleep apnoea in children.

Science.gov (United States)

Carvalho, F R; Lentini-Oliveira, D; Machado, M A C; Prado, G F; Prado, L B F; Saconato, H

2007-04-18

Apnoea is a breathing disorder marked by the absence of airflow at the nose or mouth. In children, risk factors include adenotonsillar hypertrophy, obesity, neuromuscular disorders and craniofacial anomalies. The most common treatment for obstructive sleep apnoea syndrome (OSAS) in childhood is adenotonsillectomy. This approach is limited by its surgical risks, mostly in children with comorbities and, in some patients, by recurrence that can be associated with craniofacial problems. Oral appliances and functional orthopaedic appliances have been used for patients who have OSAS and craniofacial anomalies because they change the mandible posture forwards and potentially enlarge the upper airway and increase the upper airspace, improving the respiratory function. To assess the effectiveness of oral appliances or functional orthopaedic appliances for OSAS in children. A sensitive search was developed for the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2005, Issue 3); PubMed (January 1966 to September 2005); EMBASE (1980 to September 2005); Lilacs (1982 to September 2005); BBO-Bibliografia Brasileira de Odontologia (1986 to September 2005); and SciELO (1997 to September 2005). There was no restriction of language or source of information. All randomised or quasi-randomised controlled trials comparing all types of oral and functional orthopaedic appliances with placebo or no treatment, in children 15 years old or younger. reduction of apnoea to less than one episode per hour. dental and skeletal relationship, sleep parameters improvement, cognitive and phonoaudiologic function, behavioural problems, drop outs and withdrawals, quality of life, side effects (tolerability), economic evaluation. Data were independently extracted by two review authors. Authors were contacted for additional information. Risk ratios with 95% confidence intervals were calculated for all important dichotomous outcomes. The initial search identified 384 trials

Impact of Radio Link Unreliability on the Connectivity of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Gorce Jean-Marie

2007-01-01

Full Text Available Many works have been devoted to connectivity of ad hoc networks. This is an important feature for wireless sensor networks (WSNs to provide the nodes with the capability of communicating with one or several sinks. In most of these works, radio links are assumed ideal, that is, with no transmission errors. To fulfil this assumption, the reception threshold should be high enough to guarantee that radio links have a low transmission error probability. As a consequence, all unreliable links are dismissed. This approach is suboptimal concerning energy consumption because unreliable links should permit to reduce either the transmission power or the number of active nodes. The aim of this paper is to quantify the contribution of unreliable long hops to an increase of the connectivity of WSNs. In our model, each node is assumed to be connected to each other node in a probabilistic manner. Such a network is modeled as a complete random graph, that is, all edges exist. The instantaneous node degree is then defined as the number of simultaneous valid single-hop receptions of the same message, and finally the mean node degree is computed analytically in both AWGN and block-fading channels. We show the impact on connectivity of two MACs and routing parameters. The first one is the energy detection level such as the one used in carrier sense mechanisms. The second one is the reliability threshold used by the routing layer to select stable links only. Both analytic and simulation results show that using opportunistic protocols is challenging.

Impact of Radio Link Unreliability on the Connectivity of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jean-Marie Gorce

2007-06-01

Full Text Available Many works have been devoted to connectivity of ad hoc networks. This is an important feature for wireless sensor networks (WSNs to provide the nodes with the capability of communicating with one or several sinks. In most of these works, radio links are assumed ideal, that is, with no transmission errors. To fulfil this assumption, the reception threshold should be high enough to guarantee that radio links have a low transmission error probability. As a consequence, all unreliable links are dismissed. This approach is suboptimal concerning energy consumption because unreliable links should permit to reduce either the transmission power or the number of active nodes. The aim of this paper is to quantify the contribution of unreliable long hops to an increase of the connectivity of WSNs. In our model, each node is assumed to be connected to each other node in a probabilistic manner. Such a network is modeled as a complete random graph, that is, all edges exist. The instantaneous node degree is then defined as the number of simultaneous valid single-hop receptions of the same message, and finally the mean node degree is computed analytically in both AWGN and block-fading channels. We show the impact on connectivity of two MACs and routing parameters. The first one is the energy detection level such as the one used in carrier sense mechanisms. The second one is the reliability threshold used by the routing layer to select stable links only. Both analytic and simulation results show that using opportunistic protocols is challenging.

European Gas Appliances Directive and the Dutch Decree on Gas Appliances. Special section

International Nuclear Information System (INIS)

De Bruin, B.; Venhorst, T.; Van Tricht, A.

1998-01-01

The Gas Appliances Decree is the Dutch translation of the European Gas Appliances Directive. The Decree and the EU Directive contain substantial information, provided they will be read carefully. The EU Directive lays down general safety requirements for gas appliances. They serve as a practical tool for manufacturers and service engineers. In two articles, the Directive is explained, addressing uncertainties and answering important questions. 5 ills

Periodic Hydraulic Testing for Discerning Fracture Network Connections

Science.gov (United States)

Becker, M.; Le Borgne, T.; Bour, O.; Guihéneuf, N.; Cole, M.

2015-12-01

Discrete fracture network (DFN) models often predict highly variable hydraulic connections between injection and pumping wells used for enhanced oil recovery, geothermal energy extraction, and groundwater remediation. Such connections can be difficult to verify in fractured rock systems because standard pumping or pulse interference tests interrogate too large a volume to pinpoint specific connections. Three field examples are presented in which periodic hydraulic tests were used to obtain information about hydraulic connectivity in fractured bedrock. The first site, a sandstone in New York State, involves only a single fracture at a scale of about 10 m. The second site, a granite in Brittany, France, involves a fracture network at about the same scale. The third site, a granite/schist in the U.S. State of New Hampshire, involves a complex network at scale of 30-60 m. In each case periodic testing provided an enhanced view of hydraulic connectivity over previous constant rate tests. Periodic testing is particularly adept at measuring hydraulic diffusivity, which is a more effective parameter than permeability for identify the complexity of flow pathways between measurement locations. Periodic tests were also conducted at multiple frequencies which provides a range in the radius of hydraulic penetration away from the oscillating well. By varying the radius of penetration, we attempt to interrogate the structure of the fracture network. Periodic tests, therefore, may be uniquely suited for verifying and/or calibrating DFN models.

Node-based measures of connectivity in genetic networks.

Science.gov (United States)

Koen, Erin L; Bowman, Jeff; Wilson, Paul J

2016-01-01

At-site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at-site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at-site processes, where network nodes are used to model site-level effects. We used simulated genetic networks to compare and contrast the performance of 7 node-based (as opposed to edge-based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at-site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node-based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at-site habitat conditions on the immigration and settlement phases of dispersal. © 2015 John Wiley & Sons Ltd.

Orthodontic treatment with a series of removable appliances.

Science.gov (United States)

Chenin, David A; Trosien, Andrew H; Fong, Patricia F; Miller, Robert A; Lee, Rodney S

2003-09-01

In the United States, the demand for straight white teeth has never been more important to patients. Crowded, poorly aligned teeth are not esthetically pleasing and are difficult to keep clean. However, until recently, the process of straightening the teeth typically has involved appliances involving bands, brackets and wires that also can be difficult to clean. The desire for a cosmetic solution to misaligned teeth has led to an increase in the number of patients seeking veneers, crowns and other laboratory-fabricated cosmetic restorations. Some clinicians are not aware that there are other ways to align teeth without either significant enamel reduction or conspicuous fixed orthodontic appliances. An alternative method of treatment, involving a series of clear removable appliances, circumvents this shortcoming and enables tooth alignment while avoiding deterioration in the cosmetics of the smile during treatment. This article describes a method of treatment, Invisalign (Align Technology, Santa Clara, Calif.), that clinicians can use in conjunction with 3-D computer models to accomplish the esthetic and oral hygiene objectives during and after treatment. The authors present three case reports, all involving a chief concern of crowding. The first case involved treatment of both arches by interproximal reduction, alignment of teeth and leveling the curve of Spee. The second case involved treatment of both arches by proclination, expansion and minor interproximal reduction. The final case shows relief of lower-arch crowding via lower-incisor extraction. In addition to satisfying the patient's chief concern of desiring straight teeth, this method of treatment satisfies additional objectives of esthetic treatment and esthetic results with significant oral hygiene benefits. Clinicians can address a patient's chief concern effectively without requiring an inventory of appliances (such as bands, brackets, wires and instruments). Furthermore, the use of 3-D computer models

Social network of an internationally connected nurse leader.

Science.gov (United States)

Benton, David

2016-03-01

Over the past decade, there has been a proliferation of social media sites offering the opportunity for colleagues to connect with each other locally, nationally and internationally. Meanwhile, nurses have been increasingly using social network analytical techniques to look at team functioning and communication pathways. This article uses the author's LinkedIn social network to illustrate how analysis can offer insights into the connections, and how the results can be used to professional advantage.

Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to Crystallized IQ and Gender.

Science.gov (United States)

Pezoulas, Vasileios C; Zervakis, Michalis; Michelogiannis, Sifis; Klados, Manousos A

2017-01-01

During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high crystallized Intelligence Quotient (IQ). Functional magnetic resonance imaging (fMRI) data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP) database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject) using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST) was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our results reveal that

Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to Crystallized IQ and Gender

Directory of Open Access Journals (Sweden)

Vasileios C. Pezoulas

2017-04-01

Full Text Available During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high crystallized Intelligence Quotient (IQ. Functional magnetic resonance imaging (fMRI data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our

Finite connectivity attractor neural networks

International Nuclear Information System (INIS)

Wemmenhove, B; Coolen, A C C

2003-01-01

We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous

Computer networks and advanced communications

International Nuclear Information System (INIS)

Koederitz, W.L.; Macon, B.S.

1992-01-01

One of the major methods for getting the most productivity and benefits from computer usage is networking. However, for those who are contemplating a change from stand-alone computers to a network system, the investigation of actual networks in use presents a paradox: network systems can be highly productive and beneficial; at the same time, these networks can create many complex, frustrating problems. The issue becomes a question of whether the benefits of networking are worth the extra effort and cost. In response to this issue, the authors review in this paper the implementation and management of an actual network in the LSU Petroleum Engineering Department. The network, which has been in operation for four years, is large and diverse (50 computers, 2 sites, PC's, UNIX RISC workstations, etc.). The benefits, costs, and method of operation of this network will be described, and an effort will be made to objectively weigh these elements from the point of view of the average computer user

Connectivity, cycles, and persistence thresholds in metapopulation networks.

Directory of Open Access Journals (Sweden)

Yael Artzy-Randrup

2010-08-01

Full Text Available Synthesising the relationships between complexity, connectivity, and the stability of large biological systems has been a longstanding fundamental quest in theoretical biology and ecology. With the many exciting developments in modern network theory, interest in these issues has recently come to the forefront in a range of multidisciplinary areas. Here we outline a new theoretical analysis specifically relevant for the study of ecological metapopulations focusing primarily on marine systems, where subpopulations are generally connected via larval dispersal. Our work determines the qualitative and quantitative conditions by which dispersal and network structure control the persistence of a set of age-structured patch populations. Mathematical modelling combined with a graph theoretic analysis demonstrates that persistence depends crucially on the topology of cycles in the dispersal network which tend to enhance the effect of larvae "returning home." Our method clarifies the impact directly due to network structure, but this almost by definition can only be achieved by examining the simplified case in which patches are identical; an assumption that we later relax. The methodology identifies critical migration routes, whose presence are vital to overall stability, and therefore should have high conservation priority. In contrast, "lonely links," or links in the network that do not participate in a cyclical component, have no impact on persistence and thus have low conservation priority. A number of other intriguing criteria for persistence are derived. Our modelling framework reveals new insights regarding the determinants of persistence, stability, and thresholds in complex metapopulations. In particular, while theoretical arguments have, in the past, suggested that increasing connectivity is a destabilizing feature in complex systems, this is not evident in metapopulation networks where connectivity, cycles, coherency, and heterogeneity all tend

Path connectivity based spectral defragmentation in flexible bandwidth networks.

Science.gov (United States)

Wang, Ying; Zhang, Jie; Zhao, Yongli; Zhang, Jiawei; Zhao, Jie; Wang, Xinbo; Gu, Wanyi

2013-01-28

Optical networks with flexible bandwidth provisioning have become a very promising networking architecture. It enables efficient resource utilization and supports heterogeneous bandwidth demands. In this paper, two novel spectrum defragmentation approaches, i.e. Maximum Path Connectivity (MPC) algorithm and Path Connectivity Triggering (PCT) algorithm, are proposed based on the notion of Path Connectivity, which is defined to represent the maximum variation of node switching ability along the path in flexible bandwidth networks. A cost-performance-ratio based profitability model is given to denote the prons and cons of spectrum defragmentation. We compare these two proposed algorithms with non-defragmentation algorithm in terms of blocking probability. Then we analyze the differences of defragmentation profitability between MPC and PCT algorithms.

Educational Electrical Appliance Power Meter and Logger

Science.gov (United States)

Nunn, John

2013-01-01

The principles behind two different designs of inductive power meter are presented. They both make use of the microphone input of a computer which, together with a custom-written program, can record the instantaneous power of a domestic electrical appliance. The device can be built quickly and can be calibrated with reference to a known power…

Chimera states in networks of logistic maps with hierarchical connectivities

Science.gov (United States)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

24 CFR 3280.709 - Installation of appliances.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Installation of appliances. 3280... Fuel Burning Systems § 3280.709 Installation of appliances. (a) The installation of each appliance... the manufacturer's instructions attached to the appliance. Every appliance shall be secured in place...

24 CFR 3280.707 - Heat producing appliances.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Heat producing appliances. 3280.707... Systems § 3280.707 Heat producing appliances. (a) Heat-producing appliances and vents, roof jacks and... appliance, the heating appliance shall be installed by the manufacturer of the manufactured home in...

Decreased triple network connectivity in patients with post-traumatic stress disorder

Science.gov (United States)

Liu, Yang; Li, Liang; Li, Baojuan; Zhang, Xi; Lu, Hongbing

2017-03-01

The triple network model provides a common framework for understanding affective and neurocognitive dysfunctions across multiple disorders, including central executive network (CEN), default mode network (DMN), and salience network (SN). Considering the effect of traumatic experience on post-traumatic stress disorder (PTSD), this study aims to explore the alteration of triple network connectivity in a specific PTSD induced by a single prolonged trauma exposure. With arterial spin labeling sequence, three networks were identified using independent component analysis in 10 PTSD patients and 10 healthy survivors, who experienced the same coal mining flood disaster. In PTSD patients, decreased connectivity was identified in left middle frontal gyrus of CEN, left precuneus and bilateral superior frontal gyrus of DMN, and right anterior insula of SN. The decreased connectivity in left middle frontal gyrus was identified to associate with clinical severity. These results indicated the decreased triple network connectivity, which not only supported the proposal of the triple network model, but also prompted possible neurobiology mechanism of cognitive dysfunction for this kind of PTSD.

Connectivities and synchronous firing in cortical neuronal networks

International Nuclear Information System (INIS)

Jia, L.C.; Sano, M.; Lai, P.-Y.; Chan, C.K.

2004-01-01

Network connectivities (k-bar) of cortical neural cultures are studied by synchronized firing and determined from measured correlations between fluorescence intensities of firing neurons. The bursting frequency (f) during synchronized firing of the networks is found to be an increasing function of k-bar. With f taken to be proportional to k-bar, a simple random model with a k-bar dependent connection probability p(k-bar) has been constructed to explain our experimental findings successfully

Hydraulic Stability of Heat Networks for Connection of New Consumers

Science.gov (United States)

Seminenko, A. S.; Sheremet, E. O.; Gushchin, S. V.; Elistratova, J. V.; Kireev, V. M.

2018-03-01

Nowadays due to intensive urban construction, there is a need to connect new consumers to existing heating networks. Often the connection of new consumers leads to a hydraulic misalignment of the network, which in turn affects supplying existing consumers with heat. In order to minimize the possibility of misalignment, appropriate recommendations are needed that can be obtained during the research. In the article, the authors carried out a required experiment aimed at revealing the influence of the new consumers’ connection on the hydraulic stability of the entire network. The result of the research is relevant recommendations that will be useful for engineering specialists both for the design of new networks and the reconstruction of the old ones.

Domestic appliances energy optimization with model predictive control

International Nuclear Information System (INIS)

Rodrigues, E.M.G.; Godina, R.; Pouresmaeil, E.; Ferreira, J.R.; Catalão, J.P.S.

2017-01-01

Highlights: • An alternative power management control for home appliances that require thermal regulation is presented. • A Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat. • Problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. • A modulation scheme of a two-level Model Predictive Control signal as an interface block is presented. • The implementation costs in home appliances with thermal regulation requirements are reduced. - Abstract: A vital element in making a sustainable world is correctly managing the energy in the domestic sector. Thus, this sector evidently stands as a key one for to be addressed in terms of climate change goals. Increasingly, people are aware of electricity savings by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Much of the reduction was due to technological improvements, however with the advancing of the years new types of control arise. Domestic appliances with the purpose of heating and cooling rely on thermostatic regulation technique. The study in this paper is focused on the subject of an alternative power management control for home appliances that require thermal regulation. In this paper a Model Predictive Control scheme is assessed and its performance studied and compared to the thermostat with the aim of minimizing the cooling energy consumption through the minimization of the energy cost while satisfying the adequate temperature range for the human comfort. In addition, the Model Predictive Control problem formulation is explored through tuning weights with the aim of reducing energetic consumption and cost. For this purpose, the typical consumption of a 24 h period of a summer day was simulated a three-level tariff scheme was used. The new

Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

Directory of Open Access Journals (Sweden)

Christian Nowke

2018-06-01

Full Text Available Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed.

Women’s connectivity in extreme networks

Science.gov (United States)

Manrique, Pedro; Cao, Zhenfeng; Gabriel, Andrew; Horgan, John; Gill, Paul; Qi, Hong; Restrepo, Elvira M.; Johnson, Daniela; Wuchty, Stefan; Song, Chaoming; Johnson, Neil

2016-01-01

A popular stereotype is that women will play more minor roles than men as environments become more dangerous and aggressive. Our analysis of new longitudinal data sets from offline and online operational networks [for example, ISIS (Islamic State)] shows that although men dominate numerically, women emerge with superior network connectivity that can benefit the underlying system’s robustness and survival. Our observations suggest new female-centric approaches that could be used to affect such networks. They also raise questions about how individual contributions in high-pressure systems are evaluated. PMID:27386564

Educational Technology Network: a computer conferencing system dedicated to applications of computers in radiology practice, research, and education.

Science.gov (United States)

D'Alessandro, M P; Ackerman, M J; Sparks, S M

1993-11-01

Educational Technology Network (ET Net) is a free, easy to use, on-line computer conferencing system organized and funded by the National Library of Medicine that is accessible via the SprintNet (SprintNet, Reston, VA) and Internet (Merit, Ann Arbor, MI) computer networks. It is dedicated to helping bring together, in a single continuously running electronic forum, developers and users of computer applications in the health sciences, including radiology. ET Net uses the Caucus computer conferencing software (Camber-Roth, Troy, NY) running on a microcomputer. This microcomputer is located in the National Library of Medicine's Lister Hill National Center for Biomedical Communications and is directly connected to the SprintNet and the Internet networks. The advanced computer conferencing software of ET Net allows individuals who are separated in space and time to unite electronically to participate, at any time, in interactive discussions on applications of computers in radiology. A computer conferencing system such as ET Net allows radiologists to maintain contact with colleagues on a regular basis when they are not physically together. Topics of discussion on ET Net encompass all applications of computers in radiological practice, research, and education. ET Net has been in successful operation for 3 years and has a promising future aiding radiologists in the exchange of information pertaining to applications of computers in radiology.

Connectivity strategies to enhance the capacity of weight-bearing networks

International Nuclear Information System (INIS)

Janaki, T.M.; Gupte, Neelima

2003-01-01

The connectivity properties of a weight-bearing network are exploited to enhance its capacity. We study a 2D network of sites where the weight-bearing capacity of a given site depends on the capacities of the sites connected to it in the layers above. The network consists of clusters, viz., a set of sites connected with each other with the largest such collection of sites being denoted as the maximal cluster. New connections are made between sites in successive layers using two distinct strategies. The key element of our strategies consists of adding as many disjoint clusters as possible to the sites on the trunk T of the maximal cluster. In the first strategy the reconnections start from the last layer upwards and stop when no new sites are added. In the second case, the reconnections start from the top layer and go all the way down to the last layer. The new networks can bear much higher weights than the original networks and have much lower failure rates. The first strategy leads to a greater enhancement of stability, whereas the second leads to a greater enhancement of capacity compared to the original networks. The original network used here is a typical example of the branching hierarchical class. However, the application of strategies similar to ours can yield useful results in other types of networks as well

Knowledge Access in Rural Inter-connected Areas Network ...

International Development Research Centre (IDRC) Digital Library (Canada)

Knowledge Access in Rural Inter-connected Areas Network (KariaNet) - Phase II ... poor by sharing innovations, best practices and indigenous knowledge using ... A third thematic network - on knowledge management strategies - will play an ...

Regulating electricity demand peaks for home appliances using reversible fair scheduling

DEFF Research Database (Denmark)

Kardaras, Georgios; Rossello Busquet, Ana; Iversen, Villy Bæk

2010-01-01

This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregati...

Impact of connected vehicle guidance information on network-wide average travel time

Directory of Open Access Journals (Sweden)

Jiangfeng Wang

2016-12-01

Full Text Available With the emergence of connected vehicle technologies, the potential positive impact of connected vehicle guidance on mobility has become a research hotspot by data exchange among vehicles, infrastructure, and mobile devices. This study is focused on micro-modeling and quantitatively evaluating the impact of connected vehicle guidance on network-wide travel time by introducing various affecting factors. To evaluate the benefits of connected vehicle guidance, a simulation architecture based on one engine is proposed representing the connected vehicle–enabled virtual world, and connected vehicle route guidance scenario is established through the development of communication agent and intelligent transportation systems agents using connected vehicle application programming interface considering the communication properties, such as path loss and transmission power. The impact of connected vehicle guidance on network-wide travel time is analyzed by comparing with non-connected vehicle guidance in response to different market penetration rate, following rate, and congestion level. The simulation results explore that average network-wide travel time in connected vehicle guidance shows a significant reduction versus that in non–connected vehicle guidance. Average network-wide travel time in connected vehicle guidance have an increase of 42.23% comparing to that in non-connected vehicle guidance, and average travel time variability (represented by the coefficient of variance increases as the travel time increases. Other vital findings include that higher penetration rate and following rate generate bigger savings of average network-wide travel time. The savings of average network-wide travel time increase from 17% to 38% according to different congestion levels, and savings of average travel time in more serious congestion have a more obvious improvement for the same penetration rate or following rate.

Technical guide to the connection of generation to the distribution network

Energy Technology Data Exchange (ETDEWEB)

Jarrett, K.; Hedgecock, J.; Gregory, R.; Warham, T.

2003-07-01

This guide provides a 'route map' of the processes of getting a generation scheme connected to the network and is intended to help developers of any form of distributed generation connected to the UK's local electricity networks, eg: renewable energy schemes; waste-to-energy schemes; on-site generation and combined heat and power (CHP) schemes; and peak lopping schemes using back-up generators. Where necessary, the guide distinguishes between arrangements that apply in Scotland and those that apply in England and Wales. The guide aims to: provide background information about the electricity industry; highlight common technical issues that arise during connection negotiation and their implications for distribution network operators (DNOs) and developers; examine the main factors affecting connection costs and timescales for achieving connections; and identify the different types of contracts relating to connection. The report considers the connection process, the connection application process and timescales, costs and charges, competition in connection, the structure of the UK electricity industry, the statutory framework, the effects of distributed generation of the distribution system, earthing and protection design, safety issues and DNO network information. It includes a glossary, checklists, useful contact details and information about standards and other useful documents.

Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment

Directory of Open Access Journals (Sweden)

Nicolai Franzmeier

2017-08-01

Full Text Available Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer’s disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44. Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education and better maintenance of memory in mild cognitive impairment (MCI. Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC and in an independent validation sample (23 MCI/32 HC. Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN, but positively correlated with the dorsal-attention network (DAN. Greater education predicted stronger LFC-DMN-connectivity (anti-correlation and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI.

Photovoltaic power supply for appliances and small systems. Final report; Photovoltaik fuer Geraete und Kleinsysteme. Schlussbericht

Energy Technology Data Exchange (ETDEWEB)

Roth, W.; Anton, L.; Benz, J.; Kaiser, R.; Kuhmann, J.; Puls, H.G.; Pfanner, N.; Schmidt, H.; Schulz, W.; Steinhueser, A.

2002-06-01

The economic prospects of PV power supply to appliances and small systems were investigated. The research project was aimed at improving the conditions for efficient development of appliances and small systems with photovoltaic power supply and autonomous systems not connected to the grid. Innovative products were developed and tested in cooperation with industrial organizations. The project is to help small and medium-sized organizations with a technological orientation and enhance technology transfer between science and industry.

Artificial intelligence. Application of the Statistical Neural Networks computer program in nuclear medicine

International Nuclear Information System (INIS)

Stefaniak, B.; Cholewinski, W.; Tarkowska, A.

2005-01-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer application of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. In this paper practical aspects of scientific application of ANN in medicine using the Statistical Neural Networks Computer program, were presented. Several steps of data analysis with the above ANN software package were discussed shortly, from material selection and its dividing into groups to the types of obtained results. The typical problems connected with assessing scintigrams by ANN were also described. (author)

Changes of functional connectivity in the left frontoparietal network following aphasic stroke

Directory of Open Access Journals (Sweden)

Dan eZhu

2014-05-01

Full Text Available Language is an essential higher cognitive function supported by large-scale brain networks. In this study, we investigated functional connectivity changes in the left frontoparietal network (LFPN, a language-cognition related brain network in aphasic patients. We enrolled thirteen aphasic patients who had undergone a stroke in the left hemisphere and age-, gender-, educational level-matched controls and analyzed the data by integrating independent component analysis (ICA with a network connectivity analysis method. Resting state functional magnetic resonance imaging (fMRI and clinical evaluation of language function were assessed at two stages: one and two months after stroke onset. We found reduced functional connectivity between the LFPN and the right middle frontal cortex, medial frontal cortex and right inferior frontal cortex in aphasic patients as compared to controls. Correlation analysis showed that stronger functional connectivity between the LFPN and the right middle frontal cortex and medial frontal cortex coincided with more preserved language comprehension ability after stroke. Network connectivity analysis showed reduced LFPN connectivity as indicated by the mean network connectivity index of key regions in the LFPN of aphasic patients. The decreased LFPN connectivity in stroke patients was significantly associated with the impairment of language function in their comprehension ability. We also found significant association between recovery of comprehension ability and the mean changes in intrinsic LFPN connectivity. Our findings suggest that brain lesions may influence language comprehension by altering functional connectivity between regions and that the patterns of abnormal functional connectivity may contribute to the recovery of language deficits.

Virtual terrain: a security-based representation of a computer network

Science.gov (United States)

Holsopple, Jared; Yang, Shanchieh; Argauer, Brian

2008-03-01

Much research has been put forth towards detection, correlating, and prediction of cyber attacks in recent years. As this set of research progresses, there is an increasing need for contextual information of a computer network to provide an accurate situational assessment. Typical approaches adopt contextual information as needed; yet such ad hoc effort may lead to unnecessary or even conflicting features. The concept of virtual terrain is, therefore, developed and investigated in this work. Virtual terrain is a common representation of crucial information about network vulnerabilities, accessibilities, and criticalities. A virtual terrain model encompasses operating systems, firewall rules, running services, missions, user accounts, and network connectivity. It is defined as connected graphs with arc attributes defining dynamic relationships among vertices modeling network entities, such as services, users, and machines. The virtual terrain representation is designed to allow feasible development and maintenance of the model, as well as efficacy in terms of the use of the model. This paper will describe the considerations in developing the virtual terrain schema, exemplary virtual terrain models, and algorithms utilizing the virtual terrain model for situation and threat assessment.

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks

OpenAIRE

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-01-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control...

Network topology and functional connectivity disturbances precede the onset of Huntington's disease.

Science.gov (United States)

Harrington, Deborah L; Rubinov, Mikail; Durgerian, Sally; Mourany, Lyla; Reece, Christine; Koenig, Katherine; Bullmore, Ed; Long, Jeffrey D; Paulsen, Jane S; Rao, Stephen M

2015-08-01

Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease

Intrinsic connectivity networks from childhood to late adolescence: Effects of age and sex

Directory of Open Access Journals (Sweden)

Cristina Solé-Padullés

2016-02-01

Full Text Available There is limited evidence on the effects of age and sex on intrinsic connectivity of networks underlying cognition during childhood and adolescence. Independent component analysis was conducted in 113 subjects aged 7–18; the default mode, executive control, anterior salience, basal ganglia, language and visuospatial networks were identified. The effect of age was examined with multiple regression, while sex and ‘age × sex’ interactions were assessed by dividing the sample according to age (7–12 and 13–18 years. As age increased, connectivity in the dorsal and ventral default mode network became more anterior and posterior, respectively, while in the executive control network, connectivity increased within frontoparietal regions. The basal ganglia network showed increased engagement of striatum, thalami and precuneus. The anterior salience network showed greater connectivity in frontal areas and anterior cingulate, and less connectivity of orbitofrontal, middle cingulate and temporoparietal regions. The language network presented increased connectivity of inferior frontal and decreased connectivity within the right middle frontal and left inferior parietal cortices. The visuospatial network showed greater engagement of inferior parietal and frontal cortices. No effect of sex, nor age by sex interactions was observed. These findings provide evidence of strengthening of cortico-cortical and cortico-subcortical networks across childhood and adolescence.

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

Science.gov (United States)

Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

Optimal joint scheduling of electrical and thermal appliances in a smart home environment

International Nuclear Information System (INIS)

Shirazi, Elham; Zakariazadeh, Alireza; Jadid, Shahram

2015-01-01

Highlights: • Thermal appliances are scheduled based on desired temperature and energy prices. • A discomfort index has been introduced within the home energy scheduling model. • Appliances are scheduled based on activity probability and desired options. • Starting probability depends on the social random factor and consumption behavior. - Abstract: With the development of home area network, residents have the opportunity to schedule their power usage in the home by themselves aiming at reducing electricity expenses. Moreover, as renewable energy sources are deployed in home, a home energy management system needs to consider both energy consumption and generation simultaneously to minimize the energy cost. In this paper, a smart home energy management model has been presented in which electrical and thermal appliances are jointly scheduled. The proposed method aims at minimizing the electricity cost of a residential customer by scheduling various type of appliances considering the residents consumption behavior, seasonal probability, social random factor, discomfort index and appliances starting probability functions. In this model, the home central controller receives the electricity price information, environmental factors data as well as the resident desired options in order to optimally schedule appliances including electrical and thermal. The scheduling approach is tested on a typical home including variety of home appliances, a small wind turbine, photovoltaic panel, combined heat and power unit, boiler and electrical and thermal storages over a 24-h period. The results show that the scheduling of different appliances can be reached simultaneously by using the proposed formulation. Moreover, simulation results evidenced that the proposed home energy management model exhibits a lower cost and, therefore, is more economical.

Network structure shapes spontaneous functional connectivity dynamics.

Science.gov (United States)

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

A Model of Trusted Connection Architecture

Directory of Open Access Journals (Sweden)

Zhang Xun

2017-01-01

Full Text Available According to that traditional trusted network connection architecture (TNC has limitations on dynamic network environment and the user behavior support, we develop TCA to propose a trusted connection architecture supporting behavior measurement (TCA-SBM, besides, the structure diagram of network architecture is given. Through introducing user behavior measure elements, TCA-SBM can conduct measurement on the whole network in time dimension periodically, and refine the measurement on network behavior in measure dimension to conduct fine-grained dynamic trusted measurement. As a result, TCA-SBM enhances the TCA’s ability to adapt to the dynamic change of network and makes up the deficiency of trusted computing framework in the network connection.

Modelling computer networks

International Nuclear Information System (INIS)

Max, G

2011-01-01

Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

Low-stress bicycling and network connectivity.

Science.gov (United States)

2012-05-01

For a bicycling network to attract the widest possible segment of the population, its most fundamental attribute should be low-stress connectivity, that is, providing routes between peoples origins and destinations that do not require cyclists to ...

Analysis and Relative Evaluation of Connectivity of a Mobile Multi-Hop Network

Science.gov (United States)

Nakano, Keisuke; Miyakita, Kazuyuki; Sengoku, Masakazu; Shinoda, Shoji

In mobile multi-hop networks, a source node S and a destination node D sometimes encounter a situation where there is no multi-hop path between them when a message M, destined for D, arrives at S. In this situation, we cannot send M from S to D immediately; however, we can deliver M to D after waiting some time with the help of two capabilities of mobility. One of the capabilities is to construct a connected multi-hop path by changing the topology of the network during the waiting time (Capability 1), and the other is to move M closer to D during the waiting time (Capability 2). In this paper, we consider three methods to deliver M from S to D by using these capabilities in different ways. Method 1 uses Capability 1 and sends M from S to D after waiting until a connected multi-hop path appears between S and D. Method 2 uses Capability 2 and delivers M to D by allowing a mobile node to carry M from S to D. Method 3 is a combination of Methods 1 and 2 and minimizes the waiting time. We evaluate and compare these three methods in terms of the mean waiting time, from the time when M arrives at S to the time when D starts receiving M, as a new approach to connectivity evaluation. We consider a one-dimensional mobile multi-hop network consisting of mobile nodes flowing in opposite directions along a street. First, we derive some approximate equations and propose an estimation method to compute the mean waiting time of Method 1. Second, we theoretically analyze the mean waiting time of Method 2, and compute a lower bound of that of Method 3. By comparing the three methods under the same assumptions using results of the analyses and some simulation results, we show relations between the mean waiting times of these methods and show how Capabilities 1 and 2 differently affect the mean waiting time.

Blockchain-Empowered Fair Computational Resource Sharing System in the D2D Network

Directory of Open Access Journals (Sweden)

Zhen Hong

2017-11-01

Full Text Available Device-to-device (D2D communication is becoming an increasingly important technology in future networks with the climbing demand for local services. For instance, resource sharing in the D2D network features ubiquitous availability, flexibility, low latency and low cost. However, these features also bring along challenges when building a satisfactory resource sharing system in the D2D network. Specifically, user mobility is one of the top concerns for designing a cooperative D2D computational resource sharing system since mutual communication may not be stably available due to user mobility. A previous endeavour has demonstrated and proven how connectivity can be incorporated into cooperative task scheduling among users in the D2D network to effectively lower average task execution time. There are doubts about whether this type of task scheduling scheme, though effective, presents fairness among users. In other words, it can be unfair for users who contribute many computational resources while receiving little when in need. In this paper, we propose a novel blockchain-based credit system that can be incorporated into the connectivity-aware task scheduling scheme to enforce fairness among users in the D2D network. Users’ computational task cooperation will be recorded on the public blockchain ledger in the system as transactions, and each user’s credit balance can be easily accessible from the ledger. A supernode at the base station is responsible for scheduling cooperative computational tasks based on user mobility and user credit balance. We investigated the performance of the credit system, and simulation results showed that with a minor sacrifice of average task execution time, the level of fairness can obtain a major enhancement.

Connected Dominating Set Based Topology Control in Wireless Sensor Networks

Science.gov (United States)

He, Jing

2012-01-01

Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

The Determination of Load Profiles and Power Consumptions of Home Appliances

Directory of Open Access Journals (Sweden)

Fatih Issi

2018-03-01

Full Text Available In recent years, the increment of distributed electricity generation based on renewable energy sources and improvement of communication technologies have caused the development of next-generation power grids known as smart grids. The structures of smart grids have bidirectional communication capability and enable the connection of energy generated from distributed sources to any point on the grid. They also support consumers in energy efficiency by creating opportunities for management of power consumption. The information on power consumption and load profiles of home appliances is essential to perform load management in the dwelling accurately. In this study, the power consumption data for all the basic home appliances, utilized in a two-person family in Çankırı, Turkey, was obtained with high resolution in one-second intervals. The detailed power consumption analysis and load profile were executed for each home appliance. The obtained data is not only the average power consumption of each appliance but also characterizes different operating modes or their cycles. In addition, the impact of these devices on home energy management studies and their standby power consumptions were also discussed. The acquired data is an important source to determine the load profile of individual home appliances precisely in home energy management studies. Although the results of this study do not completely reflect the energy consumption behavior of the people who live in this region, they can reveal the trends in load demands based on a real sample and customer consumption behavior of a typical two-person family.

Oral appliances and functional orthopaedic appliances for obstructive sleep apnoea in children.

Science.gov (United States)

Carvalho, Fernando R; Lentini-Oliveira, Débora A; Prado, Lucila Bf; Prado, Gilmar F; Carvalho, Luciane Bc

2016-10-05

Apnoea is a breathing disorder marked by the absence of airflow at the nose or mouth. In children, risk factors include adenotonsillar hypertrophy, obesity, neuromuscular disorders and craniofacial anomalies. The most common treatment for obstructive sleep apnoea syndrome (OSAS) in childhood is adeno-tonsillectomy. This approach is limited by its surgical risks, mostly in children with comorbidities and, in some patients, by recurrence that can be associated with craniofacial problems. Oral appliances and functional orthopaedic appliances have been used for patients who have OSAS and craniofacial anomalies because they hold the lower jaw (mandible) forwards which potentially enlarges the upper airway and increases the upper airspace, improving the respiratory function. To assess the effects of oral appliances or functional orthopaedic appliances for obstructive sleep apnoea in children. We searched the following electronic databases: Cochrane Oral Health's Trials Register (to 7 April 2016); Cochrane Central Register of Controlled Trials (CENTRAL; 2016, Issue 3) in the Cochrane Library (searched 7 April 2016); MEDLINE Ovid (1946 to 7 April 2016); Embase Ovid (1980 to 7 April 2016); LILACS BIREME (from 1982 to 7 April 2016); BBO BIREME (from 1986 to 7 April 2016) and SciELO Web of Science (from 1997 to 7 April 2016). We searched ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform for ongoing trials on 7 April 2016. We placed no restrictions on the language or date of publication when searching the electronic databases. All randomised or quasi-randomised controlled trials comparing all types of oral and functional orthopaedic appliances with placebo or no treatment, in children 15 years old or younger. reduction of apnoea to less than one episode per hour. dental and skeletal relationship, sleep parameters improvement, cognitive and phonoaudiological function, behavioural problems, quality of life, side effects

Lagrangian Flow Network: a new tool to evaluate connectivity and understand the structural complexity of marine populations

Science.gov (United States)

Rossi, V.; Dubois, M.; Ser-Giacomi, E.; Monroy, P.; Lopez, C.; Hernandez-Garcia, E.

2016-02-01

Assessing the spatial structure and dynamics of marine populations is still a major challenge for ecologists. The necessity to manage marine resources from a large-scale perspective and considering the whole ecosystem is now recognized but the absence of appropriate tools to address these objectives limits the implementation of globally pertinent conservation planning. Inspired from Network Theory, we present a new methodological framework called Lagrangian Flow Network which allows a systematic characterization of multi-scale dispersal and connectivity of early life history stages of marine organisms. The network is constructed by subdividing the basin into an ensemble of equal-area subregions which are interconnected through the transport of propagules by ocean currents. The present version allows the identification of hydrodynamical provinces and the computation of various connectivity proxies measuring retention and exchange of larvae. Due to our spatial discretization and subsequent network representation, as well as our Lagrangian approach, further methodological improvements are handily accessible. These future developments include a parametrization of habitat patchiness, the implementation of realistic larval traits and the consideration of abiotic variables (e.g. temperature, salinity, planktonic resources...) and their effects on larval production and survival. While the model is potentially tunable to any species whose biological traits and ecological preferences are precisely known, it can also be used in a more generic configuration by efficient computing and analysis of a large number of experiments with relevant ecological parameters. It permits a better characterization of population connectivity at multiple scales and it informs its ecological and managerial interpretations.

Connect the dot: Computing feed-links with minimum dilation

NARCIS (Netherlands)

Aronov, B.; Buchin, K.; Buchin, M.; Kreveld, van M.J.; Löffler, M.; Luo, J.; Silveira, R.I.; Speckmann, B.; Dehne, F.; Gavrilova, M.; Sack, J.-R.; Tóth, C.D.

2009-01-01

A feed-link is an artificial connection from a given location p to a real-world network. It is most commonly added to an incomplete network to improve the results of network analysis, by making p part of the network. The feed-link has to be "reasonable", hence we use the concept of dilation to

Chaos in complex motor networks induced by Newman—Watts small-world connections

International Nuclear Information System (INIS)

Wei Du-Qu; Luo Xiao-Shu; Zhang Bo

2011-01-01

We investigate how dynamical behaviours of complex motor networks depend on the Newman—Watts small-world (NWSW) connections. Network elements are described by the permanent magnet synchronous motor (PMSM) with the values of parameters at which each individual PMSM is stable. It is found that with the increase of connection probability p, the motor in networks becomes periodic and falls into chaotic motion as p further increases. These phenomena imply that NWSW connections can induce and enhance chaos in motor networks. The possible mechanism behind the action of NWSW connections is addressed based on stability theory. (interdisciplinary physics and related areas of science and technology)

Probability of islanding in utility networks due to grid connected photovoltaic power systems

Energy Technology Data Exchange (ETDEWEB)

Verhoeven, B.

2002-09-15

This report for the International Energy Agency (IEA) made by Task 5 of the Photovoltaic Power Systems (PVPS) programme takes a look at the probability of islanding in utility networks due to grid-connected photovoltaic power systems. The mission of the Photovoltaic Power Systems Programme is to enhance the international collaboration efforts which accelerate the development and deployment of photovoltaic solar energy. Task 5 deals with issues concerning grid-interconnection and distributed PV power systems. This report summarises the results on a study on the probability of islanding in power networks with a high penetration level of grid connected PV-systems. The results are based on measurements performed during one year in a Dutch utility network. The measurements of active and reactive power were taken every second for two years and stored in a computer for off-line analysis. The area examined and its characteristics are described, as are the test set-up and the equipment used. The ratios between load and PV-power are discussed. The general conclusion is that the probability of islanding is virtually zero for low, medium and high penetration levels of PV-systems.

Altered cerebellar functional connectivity with intrinsic connectivity networks in adults with major depressive disorder.

Directory of Open Access Journals (Sweden)

Li Liu

Full Text Available BACKGROUND: Numerous studies have demonstrated the higher-order functions of the cerebellum, including emotion regulation and cognitive processing, and have indicated that the cerebellum should therefore be included in the pathophysiological models of major depressive disorder. The aim of this study was to compare the resting-state functional connectivity of the cerebellum in adults with major depression and healthy controls. METHODS: Twenty adults with major depression and 20 gender-, age-, and education-matched controls were investigated using seed-based resting-state functional connectivity magnetic resonance imaging. RESULTS: Compared with the controls, depressed patients showed significantly increased functional connectivity between the cerebellum and the temporal poles. However, significantly reduced cerebellar functional connectivity was observed in the patient group in relation to both the default-mode network, mainly including the ventromedial prefrontal cortex and the posterior cingulate cortex/precuneus, and the executive control network, mainly including the superior frontal cortex and orbitofrontal cortex. Moreover, the Hamilton Depression Rating Scale score was negatively correlated with the functional connectivity between the bilateral Lobule VIIb and the right superior frontal gyrus in depressed patients. CONCLUSIONS: This study demonstrated increased cerebellar coupling with the temporal poles and reduced coupling with the regions in the default-mode and executive control networks in adults with major depression. These differences between patients and controls could be associated with the emotional disturbances and cognitive control function deficits that accompany major depression. Aberrant cerebellar connectivity during major depression may also imply a substantial role for the cerebellum in the pathophysiological models of depression.

Connectivity, topology and dynamics in climate networks

Czech Academy of Sciences Publication Activity Database

Paluš, Milan; Hartman, David; Hlinka, Jaroslav; Vejmelka, Martin

2012-01-01

Roč. 14, - (2012), s. 8397 ISSN 1607-7962. [European Geosciences Union General Assembly 2012. 22.04.2012-27.04.2012, Vienna] R&D Projects: GA ČR GCP103/11/J068 Institutional support: RVO:67985807 Keywords : complex networks * climate network * connectivity * entropy rate * El Nino Southern Oscillation * North Atlantic Oscillation Subject RIV: BB - Applied Statistics, Operational Research

Intrinsic connectivity networks within cerebellum and beyond in eating disorders.

Science.gov (United States)

Amianto, F; D'Agata, F; Lavagnino, L; Caroppo, P; Abbate-Daga, G; Righi, D; Scarone, S; Bergui, M; Mortara, P; Fassino, S

2013-10-01

Cerebellum seems to have a role both in feeding behavior and emotion regulation; therefore, it is a region that warrants further neuroimaging studies in eating disorders, severe conditions that determine a significant impairment in the physical and psychological domain. The aim of this study was to examine the cerebellum intrinsic connectivity during functional magnetic resonance imaging resting state in anorexia nervosa (AN), bulimia nervosa (BN), and healthy controls (CN). Resting state brain activity was decomposed into intrinsic connectivity networks (ICNs) using group spatial independent component analysis on the resting blood oxygenation level dependent time courses of 12 AN, 12 BN, and 10 CN. We extracted the cerebellar ICN and compared it between groups. Intrinsic connectivity within the cerebellar network showed some common alterations in eating disordered compared to healthy subjects (e.g., a greater connectivity with insulae, vermis, and paravermis and a lesser connectivity with parietal lobe); AN and BN patients were characterized by some peculiar alterations in connectivity patterns (e.g., greater connectivity with the insulae in AN compared to BN, greater connectivity with anterior cingulate cortex in BN compared to AN). Our data are consistent with the presence of different alterations in the cerebellar network in AN and BN patients that could be related to psychopathologic dimensions of eating disorders.

24 CFR 3280.807 - Fixtures and appliances.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Fixtures and appliances. 3280.807... Fixtures and appliances. (a) Electrical materials, devices, appliances, fittings, and other equipment... fasten appliances when the manufactured home is in transit. (See § 3280.809.) (b) Specifically listed...

Network Restoration for Next-Generation Communication and Computing Networks

Directory of Open Access Journals (Sweden)

B. S. Awoyemi

2018-01-01

Full Text Available Network failures are undesirable but inevitable occurrences for most modern communication and computing networks. A good network design must be robust enough to handle sudden failures, maintain traffic flow, and restore failed parts of the network within a permissible time frame, at the lowest cost achievable and with as little extra complexity in the network as possible. Emerging next-generation (xG communication and computing networks such as fifth-generation networks, software-defined networks, and internet-of-things networks have promises of fast speeds, impressive data rates, and remarkable reliability. To achieve these promises, these complex and dynamic xG networks must be built with low failure possibilities, high network restoration capacity, and quick failure recovery capabilities. Hence, improved network restoration models have to be developed and incorporated in their design. In this paper, a comprehensive study on network restoration mechanisms that are being developed for addressing network failures in current and emerging xG networks is carried out. Open-ended problems are identified, while invaluable ideas for better adaptation of network restoration to evolving xG communication and computing paradigms are discussed.

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

OpenAIRE

Rosenberg, Monica D.; Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S.; Shen, Xilin; Constable, R. Todd; Li, Chiang-Shan R.; Chun, Marvin M.

2016-01-01

Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained...

A solution for heterogeneous domotic systems integration

OpenAIRE

Miori, Vittorio; Russo, Dario; Bianchi Bandinelli, Rolando

2010-01-01

The Information and Communication technologies spread across our life to make easier our everyday tasks and to increase the quality of our existence in every domain, realizing the Pervasive Computing vision. As in other domains, also in home environments many appliances are rapidly becoming computationally enabled, equipped with different communications protocols, and therefore connected to home networks. Domotic systems, variously called "smart homes", "smart environment systems", "intellige...

Cephalometric effects of the Jones Jig appliance followed by fixed appliances in Class II malocclusion treatment.

Science.gov (United States)

Patel, Mayara Paim; Henriques, José Fernando Castanha; Freitas, Karina Maria Salvatore; Grec, Roberto Henrique da Costa

2014-01-01

The aim of this study was to cephalometrically assess the skeletal and dentoalveolar effects of Class II malocclusion treatment performed with the Jones Jig appliance followed by fixed appliances. The sample comprised 25 patients with Class II malocclusion treated with the Jones Jig appliance followed by fixed appliances, at a mean initial age of 12.90 years old. The mean time of the entire orthodontic treatment was 3.89 years. The distalization phase lasted for 0.85 years, after which the fixed appliance was used for 3.04 years. Cephalograms were used at initial (T1), post-distalization (T2) and final phases of treatment (T3). For intragroup comparison of the three phases evaluated, dependent ANOVA and Tukey tests were used. Jones Jig appliance did not interfere in the maxillary and mandibular component and did not change maxillomandibular relationship. Jones Jig appliance promoted distalization of first molars with anchorage loss, mesialization and significant extrusion of first and second premolars, as well as a significant increase in anterior face height at the end of treatment. The majority of adverse effects that occur during intraoral distalization are subsequently corrected during corrective mechanics. Buccal inclination and protrusion of mandibular incisors were identified. By the end of treatment, correction of overjet and overbite was observed. Jones Jig appliance promoted distalization of first molars with anchorage loss represented by significant mesial movement and extrusion of first and second premolars, in addition to a significant increase in anterior face height.

On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks.

Science.gov (United States)

Yu, Jiguo; Chen, Ying; Ma, Liran; Huang, Baogui; Cheng, Xiuzhen

2016-01-15

Coverage and connectivity are two important performance evaluation indices for wireless sensor networks (WSNs). In this paper, we focus on the connected target k-coverage (CTC k) problem in heterogeneous wireless sensor networks (HWSNs). A centralized connected target k-coverage algorithm (CCTC k) and a distributed connected target k-coverage algorithm (DCTC k) are proposed so as to generate connected cover sets for energy-efficient connectivity and coverage maintenance. To be specific, our proposed algorithms aim at achieving minimum connected target k-coverage, where each target in the monitored region is covered by at least k active sensor nodes. In addition, these two algorithms strive to minimize the total number of active sensor nodes and guarantee that each sensor node is connected to a sink, such that the sensed data can be forwarded to the sink. Our theoretical analysis and simulation results show that our proposed algorithms outperform a state-of-art connected k-coverage protocol for HWSNs.

Two Distinct Scene-Processing Networks Connecting Vision and Memory.

Science.gov (United States)

Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

2016-01-01

A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

49 CFR 173.219 - Life-saving appliances.

Science.gov (United States)

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Life-saving appliances. 173.219 Section 173.219... Life-saving appliances. (a) A life-saving appliance, self-inflating or non-self-inflating, containing small quantities of hazardous materials that are required as part of the life-saving appliance must...

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

Science.gov (United States)

Al-Anzi, Bader; Arpp, Patrick; Gerges, Sherif; Ormerod, Christopher; Olsman, Noah; Zinn, Kai

2015-05-01

An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

Aberrant functional connectivity of resting state networks in transient ischemic attack.

Directory of Open Access Journals (Sweden)

Rong Li

Full Text Available BACKGROUND: Transient ischemic attack (TIA is usually defined as a neurologic ischemic disorder without permanent cerebral infarction. Studies have showed that patients with TIA can have lasting cognitive functional impairment. Inherent brain activity in the resting state is spatially organized in a set of specific coherent patterns named resting state networks (RSNs, which epitomize the functional architecture of memory, language, attention, visual, auditory and somato-motor networks. Here, we aimed to detect differences in RSNs between TIA patients and healthy controls (HCs. METHODS: Twenty one TIA patients suffered an ischemic event and 21 matched HCs were enrolled in the study. All subjects were investigated using cognitive tests, psychiatric tests and functional magnetic resonance imaging (fMRI. Independent component analysis (ICA was adopted to acquire the eight brain RSNs. Then one-sample t-tests were calculated in each group to gather the spatial maps of each RSNs, followed by second level analysis to investigate statistical differences on RSNs between twenty one TIA patients and 21 controls. Furthermore, a correlation analysis was performed to explore the relationship between functional connectivity (FC and cognitive and psychiatric scales in TIA group. RESULTS: Compared with the controls, TIA patients exhibited both decreased and increased functional connectivity in default mode network (DMN and self-referential network (SRN, and decreased functional connectivity in dorsal attention network (DAN, central-executive network (CEN, core network (CN, somato-motor network (SMN, visual network (VN and auditory network (AN. There was no correlation between neuropsychological scores and functional connectivity in regions of RSNs. CONCLUSIONS: We observed selective impairments of RSN intrinsic FC in TIA patients, whose all eight RSNs had aberrant functional connectivity. These changes indicate that TIA is a disease with widely abnormal brain

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback.

Science.gov (United States)

Ramot, Michal; Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

2017-09-16

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants' awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

Science.gov (United States)

Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

2017-01-01

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns. PMID:28917059

Multimedia architectures: from desktop systems to portable appliances

Science.gov (United States)

Bhaskaran, Vasudev; Konstantinides, Konstantinos; Natarajan, Balas R.

1997-01-01

Future desktop and portable computing systems will have as their core an integrated multimedia system. Such a system will seamlessly combine digital video, digital audio, computer animation, text, and graphics. Furthermore, such a system will allow for mixed-media creation, dissemination, and interactive access in real time. Multimedia architectures that need to support these functions have traditionally required special display and processing units for the different media types. This approach tends to be expensive and is inefficient in its use of silicon. Furthermore, such media-specific processing units are unable to cope with the fluid nature of the multimedia market wherein the needs and standards are changing and system manufacturers may demand a single component media engine across a range of products. This constraint has led to a shift towards providing a single-component multimedia specific computing engine that can be integrated easily within desktop systems, tethered consumer appliances, or portable appliances. In this paper, we review some of the recent architectural efforts in developing integrated media systems. We primarily focus on two efforts, namely the evolution of multimedia-capable general purpose processors and a more recent effort in developing single component mixed media co-processors. Design considerations that could facilitate the migration of these technologies to a portable integrated media system also are presented.

Hoisting appliances and fuel handling equipment at nuclear facilities

Energy Technology Data Exchange (ETDEWEB)

NONE

1988-12-31

The guide is followed by the Finnish Centre for Radiation and Nuclear Safety (STUK) in regulating hoisting and handling equipment Class 3 at nuclear facilities. The guide is applied e.g. to the following equipment: reactor building overhead cranes, hoisting appliances at nuclear fuel storages, fuel handling machines, other hoisting appliances, which because of nuclear safety aspects are classified in Safety Class 3, and load-bearing devices connected with the above equipment, such as replaceable hoisting tools and auxiliary lifting devices. The regulating of hoisting and handling equipment comprises the following stages: handling of preliminary and final safety analysis reports, inspection of the construction plan, supervision of fabrication and construction inspection, and supervision of initial start-up and commissioning inspection. 36 refs. Translation. The original text is published under the same guide number. The guide is valid from 5 January 1987 and will be in force until further notice.

Effects of mandibular protraction appliance associated to fixed appliance in adults

Directory of Open Access Journals (Sweden)

Bruno D'Aurea Furquim

2013-10-01

Full Text Available OBJECTIVE: This retrospective study aimed to conduct a cephalometric evaluation of the skeletal, dental and soft tissue effects resulting from treatment of adult patients presenting Class II malocclusion, performed with a Mandibular Protraction Appliance (MPA combined with a fixed orthodontic appliance. METHODS: The sample consisted of teleradiographs obtained before and after treatment of 9 adult patients (initial mean age of 22.48 years with bilateral Class II, division 1, malocclusion. Paired t test (p < 0.05 was applied to compare initial and final values. RESULTS: t test revealed an increase in anteroinferior facial height and posterior facial height. The dental changes include: extrusion of upper incisors, buccal inclination, protrusion of lower incisors, mesialization and extrusion of mandibular molars. Regarding the soft tissue component, there was an increase in nasolabial angle in addition to upper lip retrusion. CONCLUSIONS: The effects of treating Class II malocclusion adult patients, by means of using Mandibular Protraction Appliance (MPA combined with a fixed appliance were mostly observed in the mandibular arch, and consisted of buccal inclination, protrusion and intrusion of incisors, and mesialization and extrusion of the molars.

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

Science.gov (United States)

Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

2015-01-01

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.

Do different maxillary expansion appliances influence the outcomes of the treatment?

Science.gov (United States)

Algharbi, Muteb; Bazargani, Farhan; Dimberg, Lillemor

2018-01-23

There is no consensus in the literature regarding which rapid maxillary expansion (RME) design or activation rate benefits the patients the most. Therefore, the primary aim of this systematic review was to see whether there is a difference in the skeletal and dentoalveolar effects of different RME appliances in children and growing adolescents. The secondary aim was to see whether these effects are different when using different activation protocols for these appliances. The search was done in three databases (PubMed, Cochrane Library, and Web of Science). The following inclusion criteria were used: randomized controlled trial, prospective controlled studies, 15 or more patients in each study, human subjects up to 18 years of age, and RME effects had to be assessed by computed tomography/cone beam computed tomography. Quality of the methodology was classified according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines as high, moderate, or low. The search resulted in 145 titles and abstracts; 109 of them were excluded based on pre-established criteria. Thirty-six full-text articles were assessed for eligibility and 18 of which satisfied the inclusion criteria. Finally, seven articles were deemed eligible for full inclusion and revealed that all appliances and protocols showed significant expansion in the mid-palatal suture. No evidence was found for the cause of dental tipping. In this systematic review, having different age groups in each study and using different anatomical landmarks and outcome measures for assessing the skeletal and dental effects made it difficult to conduct a meta-analysis. There is moderate evidence that all designs produce significant expansion at the mid-palatal suture. However, lack of studies comparing appliances and protocols has been found. Finally, no evidence-based conclusions could be drawn about the appliance effect on teeth tipping. No appliance appears to be superior when it comes to

Reconstruction of sparse connectivity in neural networks from spike train covariances

International Nuclear Information System (INIS)

Pernice, Volker; Rotter, Stefan

2013-01-01

The inference of causation from correlation is in general highly problematic. Correspondingly, it is difficult to infer the existence of physical synaptic connections between neurons from correlations in their activity. Covariances in neural spike trains and their relation to network structure have been the subject of intense research, both experimentally and theoretically. The influence of recurrent connections on covariances can be characterized directly in linear models, where connectivity in the network is described by a matrix of linear coupling kernels. However, as indirect connections also give rise to covariances, the inverse problem of inferring network structure from covariances can generally not be solved unambiguously. Here we study to what degree this ambiguity can be resolved if the sparseness of neural networks is taken into account. To reconstruct a sparse network, we determine the minimal set of linear couplings consistent with the measured covariances by minimizing the L 1 norm of the coupling matrix under appropriate constraints. Contrary to intuition, after stochastic optimization of the coupling matrix, the resulting estimate of the underlying network is directed, despite the fact that a symmetric matrix of count covariances is used for inference. The performance of the new method is best if connections are neither exceedingly sparse, nor too dense, and it is easily applicable for networks of a few hundred nodes. Full coupling kernels can be obtained from the matrix of full covariance functions. We apply our method to networks of leaky integrate-and-fire neurons in an asynchronous–irregular state, where spike train covariances are well described by a linear model. (paper)

Appliance based control for Home Power Management Systems

International Nuclear Information System (INIS)

Özkan, Hanife Apaydın

2016-01-01

This study scrutinizes energy-friendly smart home appliances (hereafter ‘smart appliances’), control of these appliances and their effects on the efficient use of energy. To accomplish this, smart appliances and their operation principles are introduced and their energy savings compared to conventional appliances are analyzed using precise measurements. Then, a real-time Appliance-based Home Power Management System (Ab-HPMS) which manages power consumption of smart appliances and that of the house as a whole is proposed. For Ab-HPMS, an appliance control algorithm, called Appliance-based Rolling Wave Planning (Ab-RWP), is developed with the aim of reducing electricity cost and improving energy efficiency while maintaining user comfort. Ab-RWP algorithm interacts with appliances in a priority order based on user comfort which is determined by utilizing their smart operational characteristics. Operations of smart appliances and their integrations with Ab-HPMS are modeled with Petri nets to verify that they meet the requirements expressed in the specifications. Simulation results demonstrate that proposed Ab-HPMS provides improvements in terms of the energy consumption reduction of about 5%–16%, cost reduction of about 10%–24% and peak reduction at high demand period of about 38%–53% compared to conventional appliances usage. - Highlights: • The effects of smart home appliances on energy saving are investigated. • Petri nets models of smart appliances are developed to simulate their operations in smart home. • A real-time appliance-based home power management system (Ab-HPMS) is proposed. • Power density function is evaluated to interrupt the operation of smart washing machine.

Network-based analysis reveals functional connectivity related to internet addiction tendency

Directory of Open Access Journals (Sweden)

Tanya eWen

2016-02-01

Full Text Available IntroductionPreoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills. Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction.

24 CFR 3285.503 - Optional appliances.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Optional appliances. 3285.503... appliances. (a) Comfort cooling systems. When not provided and installed by the home manufacturer, any comfort cooling systems that are installed must be installed according to the appliance manufacturer's...

Connection machine: a computer architecture based on cellular automata

Energy Technology Data Exchange (ETDEWEB)

Hillis, W D

1984-01-01

This paper describes the connection machine, a programmable computer based on cellular automata. The essential idea behind the connection machine is that a regular locally-connected cellular array can be made to behave as if the processing cells are connected into any desired topology. When the topology of the machine is chosen to match the topology of the application program, the result is a fast, powerful computing engine. The connection machine was originally designed to implement knowledge retrieval operations in artificial intelligence programs, but the hardware and the programming techniques are apparently applicable to a much larger class of problems. A machine with 100000 processing cells is currently being constructed. 27 references.

Connectivity effects in the dynamic model of neural networks

International Nuclear Information System (INIS)

Choi, J; Choi, M Y; Yoon, B-G

2009-01-01

We study, via extensive Monte Carlo calculations, the effects of connectivity in the dynamic model of neural networks, to observe that the Mattis-state order parameter increases with the number of coupled neurons. Such effects appear more pronounced when the average number of connections is increased by introducing shortcuts in the network. In particular, the power spectra of the order parameter at stationarity are found to exhibit power-law behavior, depending on how the average number of connections is increased. The cluster size distribution of the 'memory-unmatched' sites also follows a power law and possesses strong correlations with the power spectra. It is further observed that the distribution of waiting times for neuron firing fits roughly to a power law, again depending on how neuronal connections are increased

Intercluster Connection in Cognitive Wireless Mesh Networks Based on Intelligent Network Coding

Science.gov (United States)

Chen, Xianfu; Zhao, Zhifeng; Jiang, Tao; Grace, David; Zhang, Honggang

2009-12-01

Cognitive wireless mesh networks have great flexibility to improve spectrum resource utilization, within which secondary users (SUs) can opportunistically access the authorized frequency bands while being complying with the interference constraint as well as the QoS (Quality-of-Service) requirement of primary users (PUs). In this paper, we consider intercluster connection between the neighboring clusters under the framework of cognitive wireless mesh networks. Corresponding to the collocated clusters, data flow which includes the exchanging of control channel messages usually needs four time slots in traditional relaying schemes since all involved nodes operate in half-duplex mode, resulting in significant bandwidth efficiency loss. The situation is even worse at the gateway node connecting the two colocated clusters. A novel scheme based on network coding is proposed in this paper, which needs only two time slots to exchange the same amount of information mentioned above. Our simulation shows that the network coding-based intercluster connection has the advantage of higher bandwidth efficiency compared with the traditional strategy. Furthermore, how to choose an optimal relaying transmission power level at the gateway node in an environment of coexisting primary and secondary users is discussed. We present intelligent approaches based on reinforcement learning to solve the problem. Theoretical analysis and simulation results both show that the intelligent approaches can achieve optimal throughput for the intercluster relaying in the long run.

The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes.

Science.gov (United States)

Kelly, Jack; Knottenbelt, William

2015-01-01

Many countries are rolling out smart electricity meters. These measure a home's total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the 'ground truth' demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

Computational modeling of neural plasticity for self-organization of neural networks.

Science.gov (United States)

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Brain network connectivity in individuals with schizophrenia and their siblings.

Science.gov (United States)

Repovs, Grega; Csernansky, John G; Barch, Deanna M

2011-05-15

Research on brain activity in schizophrenia has shown that changes in the function of any single region cannot explain the range of cognitive and affective impairments in this illness. Rather, neural circuits that support sensory, cognitive, and emotional processes are now being investigated as substrates for cognitive and affective impairments in schizophrenia, a shift in focus consistent with long-standing hypotheses about schizophrenia as a disconnection syndrome. Our goal was to further examine alterations in functional connectivity within and between the default mode network and three cognitive control networks (frontal-parietal, cingulo-opercular, and cerebellar) as a basis for such impairments. Resting state functional magnetic resonance imaging was collected from 40 individuals with DSM-IV-TR schizophrenia, 31 siblings of individuals with schizophrenia, 15 healthy control subjects, and 18 siblings of healthy control subjects while they rested quietly with their eyes closed. Connectivity metrics were compared between patients and control subjects for both within- and between-network connections and were used to predict clinical symptoms and cognitive function. Individuals with schizophrenia showed reduced distal and somewhat enhanced local connectivity between the cognitive control networks compared with control subjects. Additionally, greater connectivity between the frontal-parietal and cerebellar regions was robustly predictive of better cognitive performance across groups and predictive of fewer disorganization symptoms among patients. These results are consistent with the hypothesis that impairments of executive function and cognitive control result from disruption in the coordination of activity across brain networks and additionally suggest that these might reflect impairments in normal pattern of brain connectivity development. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

Science.gov (United States)

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

Parallel computing and networking; Heiretsu keisanki to network

Energy Technology Data Exchange (ETDEWEB)

Asakawa, E; Tsuru, T [Japan National Oil Corp., Tokyo (Japan); Matsuoka, T [Japan Petroleum Exploration Co. Ltd., Tokyo (Japan)

1996-05-01

This paper describes the trend of parallel computers used in geophysical exploration. Around 1993 was the early days when the parallel computers began to be used for geophysical exploration. Classification of these computers those days was mainly MIMD (multiple instruction stream, multiple data stream), SIMD (single instruction stream, multiple data stream) and the like. Parallel computers were publicized in the 1994 meeting of the Geophysical Exploration Society as a `high precision imaging technology`. Concerning the library of parallel computers, there was a shift to PVM (parallel virtual machine) in 1993 and to MPI (message passing interface) in 1995. In addition, the compiler of FORTRAN90 was released with support implemented for data parallel and vector computers. In 1993, networks used were Ethernet, FDDI, CDDI and HIPPI. In 1995, the OC-3 products under ATM began to propagate. However, ATM remains to be an interoffice high speed network because the ATM service has not spread yet for the public network. 1 ref.

Low Computational Complexity Network Coding For Mobile Networks

DEFF Research Database (Denmark)

Heide, Janus

2012-01-01

Network Coding (NC) is a technique that can provide benefits in many types of networks, some examples from wireless networks are: In relay networks, either the physical or the data link layer, to reduce the number of transmissions. In reliable multicast, to reduce the amount of signaling and enable......-flow coding technique. One of the key challenges of this technique is its inherent computational complexity which can lead to high computational load and energy consumption in particular on the mobile platforms that are the target platform in this work. To increase the coding throughput several...

Magnetic fields from electric toothbrushes promote corrosion in orthodontic stainless steel appliances but not in titanium appliances.

Science.gov (United States)

Kameda, Takashi; Ohkuma, Kazuo; Oda, Hirotake; Sano, Natsuki; Batbayar, Nomintsetseg; Terashima, Yukari; Sato, Soh; Terada, Kazuto

2013-01-01

Electric toothbrushes are widely used, and their electric motors have been reported to produce low-frequency electromagnetic fields that induced electric currents in metallic objects worn by the users. In this study, we showed that electric toothbrushes generated low-frequency magnetic fields (MFs) and induced electric currents in orthodontic appliances in artificial saliva (AS), which accelerated corrosion in stainless steel (SUS) appliances, but not in titanium (Ti) appliances; the corrosion was evaluated by using an inductively coupled plasma-optical emission spectrometer and a three-dimensional laser confocal microscope. The pH of AS used for appliance immersion did not change during or after MF exposure. These results suggested that MF-induced currents from electric toothbrushes could erode SUS appliances, but not Ti appliances, because of their high corrosion potentials. Further studies are required to clarify the mechanisms of metallic corrosion by induced currents in dental fields, which may trigger metal allergies in patients.

Spike-timing computation properties of a feed-forward neural network model

Directory of Open Access Journals (Sweden)

Drew Benjamin Sinha

2014-01-01

Full Text Available Brain function is characterized by dynamical interactions among networks of neurons. These interactions are mediated by network topology at many scales ranging from microcircuits to brain areas. Understanding how networks operate can be aided by understanding how the transformation of inputs depends upon network connectivity patterns, e.g. serial and parallel pathways. To tractably determine how single synapses or groups of synapses in such pathways shape transformations, we modeled feed-forward networks of 7-22 neurons in which synaptic strength changed according to a spike-timing dependent plasticity rule. We investigated how activity varied when dynamics were perturbed by an activity-dependent electrical stimulation protocol (spike-triggered stimulation; STS in networks of different topologies and background input correlations. STS can successfully reorganize functional brain networks in vivo, but with a variability in effectiveness that may derive partially from the underlying network topology. In a simulated network with a single disynaptic pathway driven by uncorrelated background activity, structured spike-timing relationships between polysynaptically connected neurons were not observed. When background activity was correlated or parallel disynaptic pathways were added, however, robust polysynaptic spike timing relationships were observed, and application of STS yielded predictable changes in synaptic strengths and spike-timing relationships. These observations suggest that precise input-related or topologically induced temporal relationships in network activity are necessary for polysynaptic signal propagation. Such constraints for polysynaptic computation suggest potential roles for higher-order topological structure in network organization, such as maintaining polysynaptic correlation in the face of relatively weak synapses.

Meta-connectomics: human brain network and connectivity meta-analyses.

Science.gov (United States)

Crossley, N A; Fox, P T; Bullmore, E T

2016-04-01

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Controlling Voltage Levels of Distribution Network-Radial Feeder after Connecting Wind Turbines to the Network

Directory of Open Access Journals (Sweden)

Muhammad Al Badri

2017-11-01

Full Text Available Several factors in power generation and supply need to be taken into account such as shortages of energy supply, system stability, and energy quality and system disruption due to network losses, industrial development and population expansion. The addition of wind turbines to the distribution network is of great benefit in providing additional power and solving these problems, but this addition is accompanied by the problem of low voltage network. This research found optimal solutions to the problem of low voltage distribution network after connecting wind turbines. The main idea of this paper is to optimize the low-voltage problem as a result of connecting the wind turbines to the "far end" of the radial feeder for a distribution network and to obtain a voltage level within an acceptable and stable range. The problem of low voltage solved by using the load-drop compensation, capacitor-bank and “doubly-fed” induction generators. The results of this study were based on the operation of the entire design of the simulation system which would be compatible with the reality of the energy flow of all network components by using the PSCAD program. The present analysis program revealed an optimum solution for the low voltage profile of the distribution network after connecting the wind turbine.

Brain intrinsic network connectivity in individuals with frequent tanning behavior.

Science.gov (United States)

Ketcherside, Ariel; Filbey, Francesca M; Aubert, Pamela M; Seibyl, John P; Price, Julianne L; Adinoff, Bryon

2018-05-01

Emergent studies suggest a bidirectional relationship between brain functioning and the skin. This neurocutaneous connection may be responsible for the reward response to tanning and, thus, may contribute to excessive tanning behavior. To date, however, this association has not yet been examined. To explore whether intrinsic brain functional connectivity within the default mode network (DMN) is related to indoor tanning behavior. Resting state functional connectivity (rsFC) was obtained in twenty adults (16 females) with a history of indoor tanning. Using a seed-based [(posterior cingulate cortex (PCC)] approach, the relationship between tanning severity and FC strength was assessed. Tanning severity was measured with symptom count from the Structured Clinical Interview for Tanning Abuse and Dependence (SITAD) and tanning intensity (lifetime indoor tanning episodes/years tanning). rsFC strength between the PCC and other DMN regions (left globus pallidus, left medial frontal gyrus, left superior frontal gyrus) is positively correlated with tanning symptom count. rsFC strength between the PCC and salience network regions (right anterior cingulate cortex, left inferior parietal lobe, left inferior temporal gyrus) is correlated with tanning intensity. Greater connectivity between tanning severity and DMN and salience network connectivity suggests that heightened self-awareness of salient stimuli may be a mechanism that underlies frequent tanning behavior. These findings add to the growing evidence of brain-skin connection and reflect dysregulation in the reward processing networks in those with frequent tanning.

Compliance with removable orthodontic appliances.

Science.gov (United States)

Shah, Nirmal

2017-12-22

Data sourcesMedline via OVID, PubMed, Cochrane Central Register of Controlled Trials, Web of Science Core Collection, LILACS and BBO databases. Unpublished clinical trials accessed using ClinicalTrials.gov, National Research Register, ProQuest Dissertation and Thesis database.Study selectionTwo authors searched studies from inception until May 2016 without language restrictions. Quantitative and qualitative studies incorporating objective data on compliance with removable appliances, barriers to appliance wear compliance, and interventions to improve compliance were included.Data extraction and synthesisQuality of research was assessed using the Cochrane Collaboration's risk of bias tool, the risk of bias in non-randomised studies of interventions (ROBINS-I), and the mixed methods appraisal tool. Statistical heterogeneity was investigated by examining a graphic display of the estimated compliance levels in conjunction with 95% confidence intervals and quantified using the I-squared statistic. A weighted estimate of objective compliance levels for different appliances in relation to stipulated wear and self-reported levels was also calculated. Risk of publication bias was assessed using funnel plots. Meta-regression was undertaken to assess the relative effects of appliance type on compliance levels.ResultsTwenty-four studies met the inclusion criteria. Of these, 11 were included in the quantitative synthesis. The mean duration of objectively measured wear was considerably lower than stipulated wear time amongst all appliances. Headgear had the greatest discrepancy (5.81 hours, 95% confidence interval, 4.98, 6.64). Self-reported wear time was consistently higher than objectively measured wear time amongst all appliances. Headgear had the greatest discrepancy (5.02 hours, 95% confidence interval, 3.64, 6.40). Two studies found an increase in compliance with headgear and Hawley retainers when patients were aware of monitoring. Five studies found younger age groups to

computer networks

Directory of Open Access Journals (Sweden)

N. U. Ahmed

2002-01-01

Full Text Available In this paper, we construct a new dynamic model for the Token Bucket (TB algorithm used in computer networks and use systems approach for its analysis. This model is then augmented by adding a dynamic model for a multiplexor at an access node where the TB exercises a policing function. In the model, traffic policing, multiplexing and network utilization are formally defined. Based on the model, we study such issues as (quality of service QoS, traffic sizing and network dimensioning. Also we propose an algorithm using feedback control to improve QoS and network utilization. Applying MPEG video traces as the input traffic to the model, we verify the usefulness and effectiveness of our model.

Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

Directory of Open Access Journals (Sweden)

Silvia Scarpetta

2010-08-01

Full Text Available We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate-and-fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre- and post-synaptic activity. We store multiple patterns and study the network capacity. For the analog model, we find that the network capacity scales linearly with the network size, and that both capacity and the oscillation frequency of the retrieval state depend on the asymmetry of the learning time window. In addition to fully-connected networks, we study sparse networks, where each neuron is connected only to a small number $zll N$ of other neurons. Connections can be short range, between neighboring neurons placed on a regular lattice, or long range, between randomly chosen pairs of neurons. We find that a small fraction of long range connections is able to amplify the capacity of the network. This imply that a small-world-network topology is optimal, as a compromise between the cost of long range connections and the capacity increase. Also in the spiking integrate and fire model the crucial result of storing and retrieval of multiple phase-coded patterns is observed. The capacity of the fully-connected spiking network is investigated, together with the relation between oscillation frequency of retrieval state and window asymmetry.

Basics of Computer Networking

CERN Document Server

Robertazzi, Thomas

2012-01-01

Springer Brief Basics of Computer Networking provides a non-mathematical introduction to the world of networks. This book covers both technology for wired and wireless networks. Coverage includes transmission media, local area networks, wide area networks, and network security. Written in a very accessible style for the interested layman by the author of a widely used textbook with many years of experience explaining concepts to the beginner.

Development of a measurement system for the mechanical load of functional appliances.

Science.gov (United States)

Shimazaki, Aya; Kimura, Hitoshi; Inou, Norio; Maki, Koutaro

2017-10-03

Devices called functional appliances are commonly used in orthodontics for treating maxillary protrusion. These devices mechanically force the mandible forward to apply traction force to the mandibular condyle. This promotes cartilaginous growth in the small mandible. However, no studies have clarified how much traction force is applied to the mandibular condyle. Moreover, it remains unknown as to how anatomical characteristics affect this traction force. Therefore, in this study, we developed a device for measuring the amount of force generated while individual patients wore functional appliances, and we investigated the relationship between forces with structures surrounding the mandibular condyle. We compared traction force values with cone-beam computed tomography image data in eight subjects. The functional appliance resulted in a traction force of 339-1477gf/mm, with a mean value of 196.5gf/mm for the elastic modulus of the mandible. A comparison with cone-beam computed tomography image data suggested that the mandibular traction force was affected by the mandibular condyle and shape of the articular eminence. This method can contribute to discovering efficient treatment techniques more suited to individual patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generalized connectivity of graphs

CERN Document Server

Li, Xueliang

2016-01-01

Noteworthy results, proof techniques, open problems and conjectures in generalized (edge-) connectivity are discussed in this book. Both theoretical and practical analyses for generalized (edge-) connectivity of graphs are provided. Topics covered in this book include: generalized (edge-) connectivity of graph classes, algorithms, computational complexity, sharp bounds, Nordhaus-Gaddum-type results, maximum generalized local connectivity, extremal problems, random graphs, multigraphs, relations with the Steiner tree packing problem and generalizations of connectivity. This book enables graduate students to understand and master a segment of graph theory and combinatorial optimization. Researchers in graph theory, combinatorics, combinatorial optimization, probability, computer science, discrete algorithms, complexity analysis, network design, and the information transferring models will find this book useful in their studies.

Light Manipulation in Metallic Nanowire Networks with Functional Connectivity

KAUST Repository

Galinski, Henning; Fratalocchi, Andrea; Dö beli, Max; Capasso, Federico

2016-01-01

Guided by ideas from complex systems, a new class of network metamaterials is introduced for light manipulation, which are based on the functional connectivity among heterogeneous subwavelength components arranged in complex networks. The model

Retrospective evaluation of appliance price trends

International Nuclear Information System (INIS)

Dale, Larry; Antinori, Camille; McNeil, Michael; McMahon, James E.; Sydny Fujita, K.

2009-01-01

Real prices of major appliances (refrigerators, dishwashers, heating and cooling equipment) have been falling since the late 1970s despite increases in appliance efficiency and other quality variables. This paper demonstrates that historic increases in efficiency over time, including those resulting from minimum efficiency standards, incur smaller price increases than were expected by the Department of Energy (DOE) forecasts made in conjunction with standards. This effect can be explained by technological innovation, which lowers the cost of efficiency, and by market changes contributing to lower markups and economies of scale in production of higher efficiency units. We reach four principal conclusions about appliance trends and retail price setting: 1.For the past several decades, the retail price of appliances has been steadily falling while efficiency has been increasing. 2.Past retail price predictions made by the DOE analyses of efficiency standards, assuming constant prices over time, have tended to overestimate retail prices. 3.The average incremental price to increase appliance efficiency has declined over time. DOE technical support documents have typically overestimated this incremental price and retail prices. 4.Changes in retail markups and economies of scale in production of more efficient appliances may have contributed to declines in prices of efficient appliances

Multi-kanban mechanism for appliance disassembly

Science.gov (United States)

Udomsawat, Gun; Gupta, Surendra M.

2005-11-01

The use of household appliances continues to rise every year. A significant number of End-Of-Life (EOL) appliances are generated because of the introduction of newer models that are more attractive, efficient and affordable. Others are, of course, generated when they become non-functional. Many regulations encourage recycling of EOL appliances to reduce the amount of waste sent to landfills. In addition, EOL appliances offer the appliance manufacturing and remanufacturing industries a source of less expensive raw materials and components. For this reason product recovery has become a subject of interest during the past decade. In this paper, we study the disassembly line for appliance disassembly. We discuss and incorporate some of the complications that are inherent in disassembly line including product arrival, demand arrival, inventory fluctuation and production control mechanisms. We show how to overcome such complications by implementing a multi-kanban system in the appliance disassembly line setting. The multi-kanban system (MKS) relies on dynamic routing of kanbans according to the state of the system. We investigate the multi-kanban mechanism using simulation and explore the effect of product mix on performance of the traditional push system (TPS) and MKS in terms of controlling the system's inventory while attempting to achieve a decent customer service level.

24 CFR 3280.714 - Appliances, cooling.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Appliances, cooling. 3280.714... Systems § 3280.714 Appliances, cooling. (a) Every air conditioning unit or a combination air conditioning... accordance with ANSI Z21.40.1-1996, Gas Fired, Heat Activated, Air Conditioning and Heat Pump Appliances, and...

49 CFR 238.429 - Safety appliances.

Science.gov (United States)

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Safety appliances. 238.429 Section 238.429... Equipment § 238.429 Safety appliances. (a) Couplers. (1) The leading and the trailing ends of a semi... appliance mechanical strength and fasteners. (1) All handrails, handholds, and sill steps shall be made of 1...

Directed connectivity of brain default networks in resting state using GCA and motif.

Science.gov (United States)

Jiao, Zhuqing; Wang, Huan; Ma, Kai; Zou, Ling; Xiang, Jianbo

2017-06-01

Nowadays, there is a lot of interest in assessing functional interactions between key brain regions. In this paper, Granger causality analysis (GCA) and motif structure are adopted to study directed connectivity of brain default mode networks (DMNs) in resting state. Firstly, the time series of functional magnetic resonance imaging (fMRI) data in resting state were extracted, and the causal relationship values of the nodes representing related brain regions are analyzed in time domain to construct a default network. Then, the network structures were searched from the default networks of controls and patients to determine the fixed connection mode in the networks. The important degree of motif structures in directed connectivity of default networks was judged according to p-value and Z-score. Both node degree and average distance were used to analyze the effect degree an information transfer rate of brain regions in motifs and default networks, and efficiency of the network. Finally, activity and functional connectivity strength of the default brain regions are researched according to the change of energy distributions between the normals and the patients' brain regions. Experimental results demonstrate that, both normal subjects and stroke patients have some corresponding fixed connection mode of three nodes, and the efficiency and power spectrum of the patient's default network is somewhat lower than that of the normal person. In particular, the Right Posterior Cingulate Gyrus (PCG.R) has a larger change in functional connectivity and its activity. The research results verify the feasibility of the application of GCA and motif structure to study the functional connectivity of default networks in resting state.

Embedded generation connection incentives for distribution network operators

Energy Technology Data Exchange (ETDEWEB)

Williams, P.; Andrews, S.

2002-07-01

This is the final report with respect to work commissioned by the Department of Trade and Industry (DTI) as part of the New and Renewable Energy Programme into incentives for distribution network operators (DNOs) for the connection of embedded generation. This report, which incorporates the contents of the interim report submitted in February 2002, considers the implications of changes in the structure and regulation in the UK electricity industry on the successful technical and commercial integrated of embedded generation into distribution networks. The report examines: the obligations of public electricity suppliers (PESs); current DNO practices regarding the connection of embedded generation; the changes introduced by the Utilities Act 2000, including the impact of new obligations placed on DNOs on the connection of embedded generation and the requirements of the new Electricity Distribution Standard Licence conditions; and problems and prospects for DNO incentives.

Computer networks ISE a systems approach

CERN Document Server

Peterson, Larry L

2007-01-01

Computer Networks, 4E is the only introductory computer networking book written by authors who have had first-hand experience with many of the protocols discussed in the book, who have actually designed some of them as well, and who are still actively designing the computer networks today. This newly revised edition continues to provide an enduring, practical understanding of networks and their building blocks through rich, example-based instruction. The authors' focus is on the why of network design, not just the specifications comprising today's systems but how key technologies and p

Full 3-dimensional digital workflow for multicomponent dental appliances: A proof of concept.

Science.gov (United States)

van der Meer, W Joerd; Vissink, Arjan; Ren, Yijin

2016-04-01

The authors used a 3-dimensional (3D) printer and a bending robot to produce a multicomponent dental appliance to assess whether 3D digital models of the dentition are applicable for a full digital workflow. The authors scanned a volunteer's dentition with an intraoral scanner (Lava Chairside Oral Scanner C.O.S., 3M). A digital impression was used to design 2 multicomponent orthodontic appliances. Biocompatible acrylic baseplates were produced with the aid of a 3D printer. The metal springs and clasps were produced by a bending robot. The fit of the 2 appliances was assessed by 2 experienced orthodontists. The authors assessed both orthodontic appliances with the volunteer's dentition and found the fit to be excellent. Clinicians can fully produce a multicomponent dental appliance consisting of both an acrylic baseplate and other parts, such as clasps, springs, or screws, using a digital workflow process without the need for a physical model of the patient's dentition. Plaster models can be superfluous for orthodontic treatment as digital models can be used in all phases of a full digital workflow in orthodontics. The arduous task of making a multicomponent dental appliance that involves bending wires can possibly be replaced by a computer, design software, a 3D printer, and a bending robot. Copyright © 2016 American Dental Association. Published by Elsevier Inc. All rights reserved.

Minat Masyarakat dalam Menggunakan Smart Appliances

Directory of Open Access Journals (Sweden)

Diah Yuniarti

2014-09-01

Full Text Available Harga sumber energi yang semakin naik dari tahun ke tahun dan kemajuan teknologi telah mendorong perkembangan smart grid. Smart appliance merupakan salah satu komponen penting dalam smart grid. Penerapan smart appliance sejalan dengan kebijakan untuk mengurangi konsumsi energi, mengurangi emisi karbon dan penyediaan energi dari energi terbarukan. Penetrasi telepon bergerak turut memudahkan manajemen energi dan otomatisasi home appliance. Penelitian ini dilakukan untuk menganalisis minat masyarakat, yang merupakan aktor aktif dalam konsumsi dan manajemen energi di rumah tangga. Data penelitian dianalisis  dengan menggunakan metode structural equation modeling (SEM Hasil penelitian menunjukkan bahwa variabel enjoyment memiliki pengaruh yang signifikan terhadap minat dalam menggunakan smart appliance. Sedangkan, variabel compatibility ease of use, relative advantage dan image tidak memiliki pengaruh yang signifikan terhadap minat menggunakan smart appliance.

Double Super-Exchange in Silicon Quantum Dots Connected by Short-Bridged Networks

Science.gov (United States)

Li, Huashan; Wu, Zhigang; Lusk, Mark

2013-03-01

Silicon quantum dots (QDs) with diameters in the range of 1-2 nm are attractive for photovoltaic applications. They absorb photons more readily, transport excitons with greater efficiency, and show greater promise in multiple-exciton generation and hot carrier collection paradigms. However, their high excitonic binding energy makes it difficult to dissociate excitons into separate charge carriers. One possible remedy is to create dot assemblies in which a second material creates a Type-II heterojunction with the dot so that exciton dissociation occurs locally. This talk will focus on such a Type-II heterojunction paradigm in which QDs are connected via covalently bonded, short-bridge molecules. For such interpenetrating networks of dots and molecules, our first principles computational investigation shows that it is possible to rapidly and efficiently separate electrons to QDs and holes to bridge units. The bridge network serves as an efficient mediator of electron superexchange between QDs while the dots themselves play the complimentary role of efficient hole superexchange mediators. Dissociation, photoluminescence and carrier transport rates will be presented for bridge networks of silicon QDs that exhibit such double superexchange. This material is based upon work supported by the Renewable Energy Materials Research Science and Engineering Center (REMRSEC) under Grant No. DMR-0820518 and Golden Energy Computing Organization (GECO).

Flexible modulation of network connectivity related to cognition in Alzheimer’s disease

Science.gov (United States)

McLaren, Donald G.; Sperling, Reisa A.; Atria, Alireza

2014-01-01

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer’s disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54–82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive

Collective Classification in Network Data

OpenAIRE

Sen, Prithviraj; Namata, Galileo; Bilgic, Mustafa; Getoor, Lise; University of Maryland; Galligher, Brian; Eliassi-Rad, Tina

2008-01-01

Many real-world applications produce networked data such as the world-wide web (hypertext documents connected via hyperlinks), social networks (for example, people connected by friendship links), communication networks (computers connected via communication links) and biological networks (for example, protein interaction networks). A recent focus in machine learning research has been to extend traditional machine learning classification techniques to classify nodes in such networks. In this a...

Network connectivity paradigm for the large data produced by weather radar systems

Science.gov (United States)

Guenzi, Diego; Bechini, Renzo; Boraso, Rodolfo; Cremonini, Roberto; Fratianni, Simona

2014-05-01

The traffic over Internet is constantly increasing; this is due in particular to social networks activities but also to the enormous exchange of data caused especially by the so-called "Internet of Things". With this term we refer to every device that has the capability of exchanging information with other devices on the web. In geoscience (and, in particular, in meteorology and climatology) there is a constantly increasing number of sensors that are used to obtain data from different sources (like weather radars, digital rain gauges, etc.). This information-gathering activity, frequently, must be followed by a complex data analysis phase, especially when we have large data sets that can be very difficult to analyze (very long historical series of large data sets, for example), like the so called big data. These activities are particularly intensive in resource consumption and they lead to new computational models (like cloud computing) and new methods for storing data (like object store, linked open data, NOSQL or NewSQL). The weather radar systems can be seen as one of the sensors mentioned above: it transmit a large amount of raw data over the network (up to 40 megabytes every five minutes), with 24h/24h continuity and in any weather condition. Weather radar are often located in peaks and in wild areas where connectivity is poor. For this reason radar measurements are sometimes processed partially on site and reduced in size to adapt them to the limited bandwidth currently available by data transmission systems. With the aim to preserve the maximum flow of information, an innovative network connectivity paradigm for the large data produced by weather radar system is here presented. The study is focused on the Monte Settepani operational weather radar system, located over a wild peak summit in north-western Italy.

Optimizing network connectivity for mobile health technologies in sub-Saharan Africa.

Science.gov (United States)

Siedner, Mark J; Lankowski, Alexander; Musinga, Derrick; Jackson, Jonathon; Muzoora, Conrad; Hunt, Peter W; Martin, Jeffrey N; Bangsberg, David R; Haberer, Jessica E

2012-01-01

Mobile health (mHealth) technologies hold incredible promise to improve healthcare delivery in resource-limited settings. Network reliability across large catchment areas can be a major challenge. We performed an analysis of network failure frequency as part of a study of real-time adherence monitoring in rural Uganda. We hypothesized that the addition of short messaging service (SMS+GPRS) to the standard cellular network modality (GPRS) would reduce network disruptions and improve transmission of data. Participants were enrolled in a study of real-time adherence monitoring in southwest Uganda. In June 2011, we began using Wisepill devices that transmit data each time the pill bottle is opened. We defined network failures as medication interruptions of >48 hours duration that were transmitted when network connectivity was re-established. During the course of the study, we upgraded devices from GPRS to GPRS+SMS compatibility. We compared network failure rates between GPRS and GPRS+SMS periods and created geospatial maps to graphically demonstrate patterns of connectivity. One hundred fifty-seven participants met inclusion criteria of seven days of SMS and seven days of SMS+GPRS observation time. Seventy-three percent were female, median age was 40 years (IQR 33-46), 39% reported >1-hour travel time to clinic and 17% had home electricity. One hundred one had GPS coordinates recorded and were included in the geospatial maps. The median number of network failures per person-month for the GPRS and GPRS+SMS modalities were 1.5 (IQR 1.0-2.2) and 0.3 (IQR 0-0.9) respectively, (mean difference 1.2, 95%CI 1.0-1.3, p-valueImprovements in network connectivity were notable throughout the region. Study costs increased by approximately $1USD per person-month. Addition of SMS to standard GPRS cellular network connectivity can significantly reduce network connection failures for mobile health applications in remote areas. Projects depending on mobile health data in resource

Wave speed in excitable random networks with spatially constrained connections.

Directory of Open Access Journals (Sweden)

Nikita Vladimirov

Full Text Available Very fast oscillations (VFO in neocortex are widely observed before epileptic seizures, and there is growing evidence that they are caused by networks of pyramidal neurons connected by gap junctions between their axons. We are motivated by the spatio-temporal waves of activity recorded using electrocorticography (ECoG, and study the speed of activity propagation through a network of neurons axonally coupled by gap junctions. We simulate wave propagation by excitable cellular automata (CA on random (Erdös-Rényi networks of special type, with spatially constrained connections. From the cellular automaton model, we derive a mean field theory to predict wave propagation. The governing equation resolved by the Fisher-Kolmogorov PDE fails to describe wave speed. A new (hyperbolic PDE is suggested, which provides adequate wave speed v( that saturates with network degree , in agreement with intuitive expectations and CA simulations. We further show that the maximum length of connection is a much better predictor of the wave speed than the mean length. When tested in networks with various degree distributions, wave speeds are found to strongly depend on the ratio of network moments / rather than on mean degree , which is explained by general network theory. The wave speeds are strikingly similar in a diverse set of networks, including regular, Poisson, exponential and power law distributions, supporting our theory for various network topologies. Our results suggest practical predictions for networks of electrically coupled neurons, and our mean field method can be readily applied for a wide class of similar problems, such as spread of epidemics through spatial networks.

Using network metrics to investigate football team players' connections: A pilot study

Directory of Open Access Journals (Sweden)

Filipe Manuel Clemente

2014-09-01

Full Text Available The aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on "meso" and "micro" analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team's properties, thus supporting decision-making and improving sports training based on match analysis.

NASF transposition network: A computing network for unscrambling p-ordered vectors

Science.gov (United States)

Lim, R. S.

1979-01-01

The viewpoints of design, programming, and application of the transportation network (TN) is presented. The TN is a programmable combinational logic network that connects 521 memory modules to 512 processors. The unscrambling of p-ordered vectors to 1-ordered vectors in one cycle is described. The TN design is based upon the concept of cyclic groups from abstract algebra and primitive roots and indices from number theory. The programming of the TN is very simple, requiring only 20 bits: 10 bits for offset control and 10 bits for barrel switch shift control. This simple control is executed by the control unit (CU), not the processors. Any memory access by a processor must be coordinated with the CU and wait for all other processors to come to a synchronization point. These wait and synchronization events can be a degradation in performance to a computation. The TN application is for multidimensional data manipulation, matrix processing, and data sorting, and can also perform a perfect shuffle. Unlike other more complicated and powerful permutation networks, the TN cannot, if possible at all, unscramble non-p-ordered vectors in one cycle.

Proceedings: Distributed digital systems, plant process computers, and networks

International Nuclear Information System (INIS)

1995-03-01

These are the proceedings of a workshop on Distributed Digital Systems, Plant Process Computers, and Networks held in Charlotte, North Carolina on August 16--18, 1994. The purpose of the workshop was to provide a forum for technology transfer, technical information exchange, and education. The workshop was attended by more than 100 representatives of electric utilities, equipment manufacturers, engineering service organizations, and government agencies. The workshop consisted of three days of presentations, exhibitions, a panel discussion and attendee interactions. Original plant process computers at the nuclear power plants are becoming obsolete resulting in increasing difficulties in their effectiveness to support plant operations and maintenance. Some utilities have already replaced their plant process computers by more powerful modern computers while many other utilities intend to replace their aging plant process computers in the future. Information on recent and planned implementations are presented. Choosing an appropriate communications and computing network architecture facilitates integrating new systems and provides functional modularity for both hardware and software. Control room improvements such as CRT-based distributed monitoring and control, as well as digital decision and diagnostic aids, can improve plant operations. Commercially available digital products connected to the plant communications system are now readily available to provide distributed processing where needed. Plant operations, maintenance activities, and engineering analyses can be supported in a cost-effective manner. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

Directory of Open Access Journals (Sweden)

Bader Al-Anzi

2015-05-01

Full Text Available An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae. A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

Computer Networking Laboratory for Undergraduate Computer Technology Program

National Research Council Canada - National Science Library

Naghedolfeizi, Masoud

2000-01-01

...) To improve the quality of education in the existing courses related to computer networks and data communications as well as other computer science courses such programming languages and computer...

Just-in-time connectivity for large spiking networks.

Science.gov (United States)

Lytton, William W; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

2008-11-01

The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON's standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that added items to the queue only when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run.

Genes2FANs: connecting genes through functional association networks

Science.gov (United States)

2012-01-01

Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our finding that disease genes in

Okanagan indoor wood burning appliance inventory survey

International Nuclear Information System (INIS)

2001-01-01

A survey was conducted to determine the usage and nature of wood burning appliances used by residents in British Columbia's Okanagan region. The objective was to better understand this source of air quality concern and to facilitate strategic planning, guidelines and legislation. The survey also provides a baseline to track the effectiveness of any reduction strategies. It identifies the different types of wood burning appliances used in the community and presents residential options about potential bylaws to protect air quality. The receptivity of households to switch to more efficient wood burning appliances was also examined. The survey completes a portion of an overall emissions inventory for the Okanagan Valley. Environment Canada uses the particulate loading results to model the air quality in the airshed. Results showed that approximately 21 per cent of the households in the Okanagan use indoor wood burning appliances, and burn an average of 2.3 cords of wood each year. Only 11 per cent of the appliances are considered to have advanced burning technology. It is projected that the use of wood burning appliances in the Okanagan will increase by 5 to 7 per cent in the next 2 years. Most residents have good burning habits, but some improvements can still be made. Many residents are considering exchanging old wood burning appliances for clean burning technology appliances for environmental and health reasons. Most households would support a bylaw to control nuisance amounts of smoke from wood burning appliances. 20 tabs., 5 figs

NEPTUNIX 2: Operating on computers network - Catalogued procedures

International Nuclear Information System (INIS)

Roux, Pierre.

1982-06-01

NEPTUNIX 2 is a package which carries out the simulation of complex processes described by numerous non linear algebro-differential equations. Main features are: non linear or time dependent parameters, implicit form, stiff systems, dynamic change of equations leading to discontinuities on some variables. Thus the mathematical model is built with an equations set F(x,x',1,t), where t is the independent variable, x' the derivative of x and 1 an ''algebrized'' logical variable. The NEPTUNIX 2 package is divided into two successive major steps: a non numerical step and a numerical step. The numerical step, using results from a picture of the model translated in FORTRAN language, in a form fitted for the executive computer, carries out the simulmations; in this way, NEPTUNIX 2 numerical step is portable. On the opposite, the non numerical step must be executed on a series 370 IBM computer or on a compatible computer. The present manual describes NEPTUNIX 2 operating procedures when the two steps are executed on the same computer and also when the numerical step is executed on an other computer connected or not on the same computing network [fr

The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes

Science.gov (United States)

Kelly, Jack; Knottenbelt, William

2015-03-01

Many countries are rolling out smart electricity meters. These measure a home’s total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the ‘ground truth’ demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

Hidden Connectivity in Networks with Vulnerable Classes of Nodes

Directory of Open Access Journals (Sweden)

Sebastian M. Krause

2016-10-01

Full Text Available In many complex systems representable as networks, nodes can be separated into different classes. Often these classes can be linked to a mutually shared vulnerability. Shared vulnerabilities may be due to a shared eavesdropper or correlated failures. In this paper, we show the impact of shared vulnerabilities on robust connectivity and how the heterogeneity of node classes can be exploited to maintain functionality by utilizing multiple paths. Percolation is the field of statistical physics that is generally used to analyze connectivity in complex networks, but in its existing forms, it cannot treat the heterogeneity of multiple vulnerable classes. To analyze the connectivity under these constraints, we describe each class as a color and develop a “color-avoiding” percolation. We present an analytic theory for random networks and a numerical algorithm for all networks, with which we can determine which nodes are color-avoiding connected and whether the maximal set percolates in the system. We find that the interaction of topology and color distribution implies a rich critical behavior, with critical values and critical exponents depending both on the topology and on the color distribution. Applying our physics-based theory to the Internet, we show how color-avoiding percolation can be used as the basis for new topologically aware secure communication protocols. Beyond applications to cybersecurity, our framework reveals a new layer of hidden structure in a wide range of natural and technological systems.

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

Science.gov (United States)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Altered Functional Connectivity of the Default Mode Network in Low-Empathy Subjects.

Science.gov (United States)

Kim, Seung Jun; Kim, Sung Eun; Kim, Hyo Eun; Han, Kiwan; Jeong, Bumseok; Kim, Jae Jin; Namkoong, Kee; Kim, Ji Woong

2017-09-01

Empathy is the ability to identify with or make a vicariously experience of another person's feelings or thoughts based on memory and/or self-referential mental simulation. The default mode network in particular is related to self-referential empathy. In order to elucidate the possible neural mechanisms underlying empathy, we investigated the functional connectivity of the default mode network in subjects from a general population. Resting state functional magnetic resonance imaging data were acquired from 19 low-empathy subjects and 18 medium-empathy subjects. An independent component analysis was used to identify the default mode network, and differences in functional connectivity strength were compared between the two groups. The low-empathy group showed lower functional connectivity of the medial prefrontal cortex and anterior cingulate cortex (Brodmann areas 9 and 32) within the default mode network, compared to the medium-empathy group. The results of the present study suggest that empathy is related to functional connectivity of the medial prefrontal cortex/anterior cingulate cortex within the default mode network. Functional decreases in connectivity among low-empathy subjects may reflect an impairment of self-referential mental simulation. © Copyright: Yonsei University College of Medicine 2017.

Abnormal Functional Connectivity Between Default and Salience Networks in Pediatric Bipolar Disorder.

Science.gov (United States)

Lopez-Larson, Melissa P; Shah, Lubdha M; Weeks, Howard R; King, Jace B; Mallik, Atul K; Yurgelun-Todd, Deborah A; Anderson, Jeffrey S

2017-01-01

Pediatric bipolar disorder (PBD) (occurring prior to 18 years of age) is a developmental brain disorder that is among the most severe and disabling psychiatric conditions affecting youth. Despite increasing evidence that brain connectivity is atypical in adults with bipolar disorder, it is not clear how brain connectivity may be altered in youths with PBD. This cross-sectional resting-state functional magnetic resonance imaging study included 80 participants recruited over 4 years: 32 youths with PBD, currently euthymic (13 males; 15.1 years old), and 48 healthy control (HC) subjects (27 males; 14.5 years old). Functional connectivity between eight major intrinsic connectivity networks, along with connectivity measurements between 333 brain regions, was compared between PBD and HC subjects. Additionally, connectivity differences were evaluated between PBD and HC samples in negatively correlated connections, as defined by 839 subjects of the Human Connectome Project dataset. We found increased inter- but not intranetwork functional connectivity in PBD between the default mode and salience networks (p = .0017). Throughout the brain, atypical connections showed failure to develop anticorrelation with age during adolescence in PBD but not HC samples among connections that exhibit negative correlation in adulthood. Youths with PBD demonstrate reduced anticorrelation between default mode and salience networks. Further evaluation of the interaction between these networks is needed in development and with other mood states such as depression and mania to clarify if this atypical connectivity is a PBD trait biomarker. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Connecting Mobile Users Through Mobile Social Networks

Directory of Open Access Journals (Sweden)

Faisal Alkhateeb

2012-10-01

Full Text Available Nowadays, social networks become popular with the emerging of web-based social networking services. Recently, several mobile services are developed to connect users to their favourite social networks such as Facebook, Twitter, Flickr, etc. However, these services depends upon the existing web-based social networks. In this paper, we present a mobile service for joining groups across communities. The originality of the work is that the framework of the service allows creating and joining social networks that are self-contained for mobile company servers. The service consists of several sub-services such as users invitation, group finding and others. Users, regardless of their disability, can use the service and its sub-services without the need to create their own accounts on social web sites and thus their own groups. We also propose a privacy control policy for mobile social networks.

Ethical Issues in Network System Design

Directory of Open Access Journals (Sweden)

Duncan Langford

1997-05-01

Full Text Available Today, most desktop computers and PCs are networked that is, they have the ability to link to other machines, usually to access data and other information held remotely. Such machines may sometimes be connected directly to each other, as part of an office or company computer system. More frequently, however, connected machines are at a considerable distance from each other, typically connected through links to global systems such as the Internet, or World Wide Web (WWW. The networked machine itself may be anything from a powerful company computer with direct Internet connections, to a small hobbyist machine, accessing a bulletin board through telephone and modem. It is important to remember that, whatever the type or the location of networked machines, their access to the network, and the network itself, was planned and constructed following deliberate design considerations. In this paper I discuss some ways in which the technical design of computer systems might appropriately be influenced by ethical issues, and examine pressures on computer scientists and others to technically control network related actions perceived as 'unethical'. After examination of the current situation, I draw together the issues, and conclude by suggesting some ethically based recommendations for the future design of networked systems.

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

Directory of Open Access Journals (Sweden)

Hongzhi Hu

2015-01-01

Full Text Available Due to the extensive social influence, public health emergency has attracted great attention in today’s society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event’s social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback based on ACP simulation system which was successfully applied to the analysis of A (H1N1 Flu emergency.

Development and application of computer network for working out of researches on high energy physics

International Nuclear Information System (INIS)

Boos, Eh.G.; Tashimov, M.A.

2001-01-01

Computer network of the Physical and Technological Institute of the Ministry and Science and Education of the Republic of Kazakhstan (FTI of MSE RK) jointing a number of the research institutions, leading universities and other enterprises of Almaty city. At the present time more than 350 computers are connected to this network, the velocity of satellite channel is increased up to 192 k bit/s per one reception. The university segments of the network are separated in individual domen. A new software for analysis and proceeding of experimental data are implemented and other measures are carried out as well. However an increasing volume of information exchange between nuclear-physical center demanding the further information network development. So for providing consumers demands in information exchange in the nearest years in the paper the possibility for following measures maintenance are considered: (1) Increase of satellite channel velocity up to 1-2 M bit/s by replace of the existing SDM-100 modem on a rapid one. Now using the Kedr-M station and the CISCO-2501 tracer allowing to provide such velocity; (2) Convert of the Institute local calculation network on the new Fast Ethernet technology permitting to increase the information transmission velocity up to 100 M bit/s at the complete succession of existing Ethernet; (3) The Proxy-server (Firewaal) install at the network support assay, that giving the possibility for discharging of satellite channel and localization of segment of the network, connected with learning on the Internet not in damage to educational process. In the framework of cooperation with DESY German accelerating center with help of the indicated network the data about 2 hundred thousand deep inelastic interactions of electrons with protons measured at ZEUS detector are obtained. Data about 10 thousand of events simulated at the OPAL installation are received as well. Besides the computer network is using for operative information exchange and

Muscle networks: Connectivity analysis of EMG activity during postural control

Science.gov (United States)

Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

2015-12-01

Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

Computer hardware fault administration

Science.gov (United States)

Archer, Charles J.; Megerian, Mark G.; Ratterman, Joseph D.; Smith, Brian E.

2010-09-14

Computer hardware fault administration carried out in a parallel computer, where the parallel computer includes a plurality of compute nodes. The compute nodes are coupled for data communications by at least two independent data communications networks, where each data communications network includes data communications links connected to the compute nodes. Typical embodiments carry out hardware fault administration by identifying a location of a defective link in the first data communications network of the parallel computer and routing communications data around the defective link through the second data communications network of the parallel computer.

Connectivity, excitability and activity patterns in neuronal networks

International Nuclear Information System (INIS)

Le Feber, Joost; Stoyanova, Irina I; Chiappalone, Michela

2014-01-01

Extremely synchronized firing patterns such as those observed in brain diseases like epilepsy may result from excessive network excitability. Although network excitability is closely related to (excitatory) connectivity, a direct measure for network excitability remains unavailable. Several methods currently exist for estimating network connectivity, most of which are related to cross-correlation. An example is the conditional firing probability (CFP) analysis which calculates the pairwise probability (CFP i,j ) that electrode j records an action potential at time t = τ, given that electrode i recorded a spike at t = 0. However, electrode i often records multiple spikes within the analysis interval, and CFP values are biased by the on-going dynamic state of the network. Here we show that in a linear approximation this bias may be removed by deconvoluting CFP i,j with the autocorrelation of i (i.e. CFP i,i ), to obtain the single pulse response (SPR i,j )—the average response at electrode j to a single spike at electrode i. Thus, in a linear system SPRs would be independent of the dynamic network state. Nonlinear components of synaptic transmission, such as facilitation and short term depression, will however still affect SPRs. Therefore SPRs provide a clean measure of network excitability. We used carbachol and ghrelin to moderately activate cultured cortical networks to affect their dynamic state. Both neuromodulators transformed the bursting firing patterns of the isolated networks into more dispersed firing. We show that the influence of the dynamic state on SPRs is much smaller than the effect on CFPs, but not zero. The remaining difference reflects the alteration in network excitability. We conclude that SPRs are less contaminated by the dynamic network state and that mild excitation may decrease network excitability, possibly through short term synaptic depression. (papers)

Energy use and appliance ownership in Ireland

International Nuclear Information System (INIS)

Leahy, Eimear; Lyons, Sean

2010-01-01

This paper examines household energy use and appliance ownership in Ireland. Logit regression analyses on a large micro-dataset reveal how household characteristics can help explain the ownership of energy using appliances. Using OLS regression models, we explore the factors affecting residential energy demand conditional on appliance ownership. Results suggest that the methods of space and water heating employed by a household are even more important than electrical appliances in explaining domestic energy usage. However, the stock of appliances must be included in such models so that results will not be biased. The methods employed in this paper can be easily adopted for studies of household energy use in other countries where household expenditure survey data are available.

Nuclear Physics computer networking: Report of the Nuclear Physics Panel on Computer Networking

International Nuclear Information System (INIS)

Bemis, C.; Erskine, J.; Franey, M.; Greiner, D.; Hoehn, M.; Kaletka, M.; LeVine, M.; Roberson, R.; Welch, L.

1990-05-01

This paper discusses: the state of computer networking within nuclear physics program; network requirements for nuclear physics; management structure; and issues of special interest to the nuclear physics program office

Analysis of Various Computer System Monitoring and LCD Projector through the Network TCP/IP

Directory of Open Access Journals (Sweden)

Santoso Budijono

2015-09-01

Full Text Available Many electronic devices have a network connection facility. Projectors today have network facilities to bolster its customer satisfaction in everyday use. By using a device that can be controlled, the expected availability and reliability of the presentation system (computer and projector can be maintained to keep itscondition ready to use for presentation. Nevertheless, there is still a projector device that has no network facilities so that the necessary additional equipment with expensive price. Besides, control equipment in large quantities has problems in timing and the number of technicians in performing controls. This study began with study of literature, from searching for the projectors that has LAN and software to control and finding a number of computer control softwares where the focus is easy to use and affordable. Result of this research is creating asystem which contains suggestions of procurement of computer hardware, hardware and software projectors each of which can be controlled centrally from a distance.

Functional Connectivity Between Anterior Insula and Key Nodes of Frontoparietal Executive Control and Salience Networks Distinguish Bipolar Depression From Unipolar Depression and Healthy Control Subjects.

Science.gov (United States)

Ellard, Kristen K; Zimmerman, Jared P; Kaur, Navneet; Van Dijk, Koene R A; Roffman, Joshua L; Nierenberg, Andrew A; Dougherty, Darin D; Deckersbach, Thilo; Camprodon, Joan A

2018-05-01

Patients with bipolar depression are characterized by dysregulation across the full spectrum of mood, differentiating them from patients with unipolar depression. The ability to switch neural resources among the default mode network, salience network, and executive control network (ECN) has been proposed as a key mechanism for adaptive mood regulation. The anterior insula is implicated in the modulation of functional network switching. Differential connectivity between anterior insula and functional networks may provide insights into pathophysiological differences between bipolar and unipolar mood disorders, with implications for diagnosis and treatment. Resting-state functional magnetic resonance imaging data were collected from 98 subjects (35 unipolar, 24 bipolar, and 39 healthy control subjects). Pearson correlations were computed between bilateral insula seed regions and a priori defined target regions from the default mode network, salience network, and ECN. After r-to-z transformation, a one-way multivariate analysis of covariance was conducted to identify significant differences in connectivity between groups. Post hoc pairwise comparisons were conducted and Bonferroni corrections were applied. Receiver-operating characteristics were computed to assess diagnostic sensitivity. Patients with bipolar depression evidenced significantly altered right anterior insula functional connectivity with the inferior parietal lobule of the ECN relative to patients with unipolar depression and control subjects. Right anterior insula-inferior parietal lobule connectivity significantly discriminated patients with bipolar depression. Impaired functional connectivity between the anterior insula and the inferior parietal lobule of the ECN distinguishes patients with bipolar depression from those with unipolar depression and healthy control subjects. This finding highlights a pathophysiological mechanism with potential as a therapeutic target and a clinical biomarker for bipolar

Computer Network Security- The Challenges of Securing a Computer Network

Science.gov (United States)

Scotti, Vincent, Jr.

2011-01-01

This article is intended to give the reader an overall perspective on what it takes to design, implement, enforce and secure a computer network in the federal and corporate world to insure the confidentiality, integrity and availability of information. While we will be giving you an overview of network design and security, this article will concentrate on the technology and human factors of securing a network and the challenges faced by those doing so. It will cover the large number of policies and the limits of technology and physical efforts to enforce such policies.

46 CFR 199.70 - Personal lifesaving appliances.

Science.gov (United States)

2010-10-01

... 46 Shipping 7 2010-10-01 2010-10-01 false Personal lifesaving appliances. 199.70 Section 199.70 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) LIFESAVING APPLIANCES AND ARRANGEMENTS... appliances. (a) Lifebuoys. Each vessel must carry lifebuoys approved under approval series 160.150 as follows...

Proposal for an ad hoc computer network in the military electronic systems department at the military academy applying bluetooth technology

Directory of Open Access Journals (Sweden)

Miroslav R. Terzić

2011-01-01

Full Text Available The historical development of the Bluetooth module is given in the introduction of this paper. The importance of the Bluetooth standard for wireless connection on small distances is shown as well. The organization of the Department of Military Electronic Systems is presented with its area of duties, subordinate sections and deployment. The concept of a local area network for this Department, using Bluetooth technology, includes network topology and working regimes based on the main characteristics and technical specifications for the connection with Bluetooth technology. The Department's disperse computer network is proposed as a scatter net where one piconetwork includes the Head of Department and the Heads of Sections while other piconetworks are formed from the Heads of Sections and their subordinates. The security aspect of the presented network deals with basic computer network attack categories, protection methods and aspects. The paper concludes with some recommendations for the local area network using Bluetooth technology with respect to its economical and security aspects as well as to the managing principles of the Department.

Computer Networks as a New Data Base.

Science.gov (United States)

Beals, Diane E.

1992-01-01

Discusses the use of communication on computer networks as a data source for psychological, social, and linguistic research. Differences between computer-mediated communication and face-to-face communication are described, the Beginning Teacher Computer Network is discussed, and examples of network conversations are appended. (28 references) (LRW)

Microbiologically influenced corrosion of orthodontic metallic appliances.