Research on moving target defense based on SDN

NASA Astrophysics Data System (ADS)

Chen, Mingyong; Wu, Weimin

2017-08-01

An address mutation strategy was proposed. This strategy provided an unpredictable change in address, replacing the real address of the packet forwarding process and path mutation, thus hiding the real address of the host and path. a mobile object defense technology based on Spatio-temporal Mutation on this basis is proposed, Using the software Defined Network centralized control architecture advantage combines sFlow traffic monitoring technology and Moving Target Defense. A mutated time period which can be changed in real time according to the network traffic is changed, and the destination address is changed while the controller abruptly changes the address while the data packet is transferred between the switches to construct a moving target, confusing the host within the network, thereby protecting the host and network.

PHACK: An Efficient Scheme for Selective Forwarding Attack Detection in WSNs.

PubMed

Liu, Anfeng; Dong, Mianxiong; Ota, Kaoru; Long, Jun

2015-12-09

In this paper, a Per-Hop Acknowledgement (PHACK)-based scheme is proposed for each packet transmission to detect selective forwarding attacks. In our scheme, the sink and each node along the forwarding path generate an acknowledgement (ACK) message for each received packet to confirm the normal packet transmission. The scheme, in which each ACK is returned to the source node along a different routing path, can significantly increase the resilience against attacks because it prevents an attacker from compromising nodes in the return routing path, which can otherwise interrupt the return of nodes' ACK packets. For this case, the PHACK scheme also has better potential to detect abnormal packet loss and identify suspect nodes as well as better resilience against attacks. Another pivotal issue is the network lifetime of the PHACK scheme, as it generates more acknowledgements than previous ACK-based schemes. We demonstrate that the network lifetime of the PHACK scheme is not lower than that of other ACK-based schemes because the scheme just increases the energy consumption in non-hotspot areas and does not increase the energy consumption in hotspot areas. Moreover, the PHACK scheme greatly simplifies the protocol and is easy to implement. Both theoretical and simulation results are given to demonstrate the effectiveness of the proposed scheme in terms of high detection probability and the ability to identify suspect nodes.

PHACK: An Efficient Scheme for Selective Forwarding Attack Detection in WSNs

PubMed Central

Liu, Anfeng; Dong, Mianxiong; Ota, Kaoru; Long, Jun

2015-01-01

In this paper, a Per-Hop Acknowledgement (PHACK)-based scheme is proposed for each packet transmission to detect selective forwarding attacks. In our scheme, the sink and each node along the forwarding path generate an acknowledgement (ACK) message for each received packet to confirm the normal packet transmission. The scheme, in which each ACK is returned to the source node along a different routing path, can significantly increase the resilience against attacks because it prevents an attacker from compromising nodes in the return routing path, which can otherwise interrupt the return of nodes’ ACK packets. For this case, the PHACK scheme also has better potential to detect abnormal packet loss and identify suspect nodes as well as better resilience against attacks. Another pivotal issue is the network lifetime of the PHACK scheme, as it generates more acknowledgements than previous ACK-based schemes. We demonstrate that the network lifetime of the PHACK scheme is not lower than that of other ACK-based schemes because the scheme just increases the energy consumption in non-hotspot areas and does not increase the energy consumption in hotspot areas. Moreover, the PHACK scheme greatly simplifies the protocol and is easy to implement. Both theoretical and simulation results are given to demonstrate the effectiveness of the proposed scheme in terms of high detection probability and the ability to identify suspect nodes. PMID:26690178

Using Trust to Establish a Secure Routing Model in Cognitive Radio Network.

PubMed

Zhang, Guanghua; Chen, Zhenguo; Tian, Liqin; Zhang, Dongwen

2015-01-01

Specific to the selective forwarding attack on routing in cognitive radio network, this paper proposes a trust-based secure routing model. Through monitoring nodes' forwarding behaviors, trusts of nodes are constructed to identify malicious nodes. In consideration of that routing selection-based model must be closely collaborative with spectrum allocation, a route request piggybacking available spectrum opportunities is sent to non-malicious nodes. In the routing decision phase, nodes' trusts are used to construct available path trusts and delay measurement is combined for making routing decisions. At the same time, according to the trust classification, different responses are made specific to their service requests. By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated. Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.

A Routing Path Construction Method for Key Dissemination Messages in Sensor Networks

PubMed Central

Moon, Soo Young; Cho, Tae Ho

2014-01-01

Authentication is an important security mechanism for detecting forged messages in a sensor network. Each cluster head (CH) in dynamic key distribution schemes forwards a key dissemination message that contains encrypted authentication keys within its cluster to next-hop nodes for the purpose of authentication. The forwarding path of the key dissemination message strongly affects the number of nodes to which the authentication keys in the message are actually distributed. We propose a routing method for the key dissemination messages to increase the number of nodes that obtain the authentication keys. In the proposed method, each node selects next-hop nodes to which the key dissemination message will be forwarded based on secret key indexes, the distance to the sink node, and the energy consumption of its neighbor nodes. The experimental results show that the proposed method can increase by 50–70% the number of nodes to which authentication keys in each cluster are distributed compared to geographic and energy-aware routing (GEAR). In addition, the proposed method can detect false reports earlier by using the distributed authentication keys, and it consumes less energy than GEAR when the false traffic ratio (FTR) is ≥10%. PMID:25136649

VehiHealth: An Emergency Routing Protocol for Vehicular Ad Hoc Network to Support Healthcare System.

PubMed

Bhoi, S K; Khilar, P M

2016-03-01

Survival of a patient depends on effective data communication in healthcare system. In this paper, an emergency routing protocol for Vehicular Ad hoc Network (VANET) is proposed to quickly forward the current patient status information from the ambulance to the hospital to provide pre-medical treatment. As the ambulance takes time to reach the hospital, ambulance doctor can provide sudden treatment to the patient in emergency by sending patient status information to the hospital through the vehicles using vehicular communication. Secondly, the experienced doctors respond to the information by quickly sending a treatment information to the ambulance. In this protocol, data is forwarded through that path which has less link breakage problem between the vehicles. This is done by calculating an intersection value I v a l u e for the neighboring intersections by using the current traffic information. Then the data is forwarded through that intersection which has minimum I v a l u e . Simulation results show VehiHealth performs better than P-GEDIR, GyTAR, A-STAR and GSR routing protocols in terms of average end-to-end delay, number of link breakage, path length, and average response time.

Tracing Technological Development Trajectories: A Genetic Knowledge Persistence-Based Main Path Approach.

PubMed

Park, Hyunseok; Magee, Christopher L

2017-01-01

The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method can dramatically reduce network complexity without missing any dominantly important patents. The main paths identified by our approach for two test cases are almost 10x less complex than the main paths identified by the existing approach. The proposed approach identifies all dominantly important patents on the main paths, but the main paths identified by the existing approach miss about 20% of dominantly important patents.

Tracing Technological Development Trajectories: A Genetic Knowledge Persistence-Based Main Path Approach

PubMed Central

2017-01-01

The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method can dramatically reduce network complexity without missing any dominantly important patents. The main paths identified by our approach for two test cases are almost 10x less complex than the main paths identified by the existing approach. The proposed approach identifies all dominantly important patents on the main paths, but the main paths identified by the existing approach miss about 20% of dominantly important patents. PMID:28135304

Fused smart sensor network for multi-axis forward kinematics estimation in industrial robots.

PubMed

Rodriguez-Donate, Carlos; Osornio-Rios, Roque Alfredo; Rivera-Guillen, Jesus Rooney; Romero-Troncoso, Rene de Jesus

2011-01-01

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint's angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot.

Primitives for Active Internet Topology Mapping: Toward High-Frequency Characterization

DTIC Science & Technology

2010-11-03

that a tension exists between the two conflict- ing goals of reducing probing traffic and capturing dynamic forwarding paths. Many networks deploy...perform alias resolution to future work. Acknowledgments The authors would like to thank Young Hyun, k. claffy and CAIDA for measurement

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

An improved PRoPHET routing protocol in delay tolerant network.

PubMed

Han, Seung Deok; Chung, Yun Won

2015-01-01

In delay tolerant network (DTN), an end-to-end path is not guaranteed and packets are delivered from a source node to a destination node via store-carry-forward based routing. In DTN, a source node or an intermediate node stores packets in buffer and carries them while it moves around. These packets are forwarded to other nodes based on predefined criteria and finally are delivered to a destination node via multiple hops. In this paper, we improve the dissemination speed of PRoPHET (probability routing protocol using history of encounters and transitivity) protocol by employing epidemic protocol for disseminating message m, if forwarding counter and hop counter values are smaller than or equal to the threshold values. The performance of the proposed protocol was analyzed from the aspect of delivery probability, average delay, and overhead ratio. Numerical results show that the proposed protocol can improve the delivery probability, average delay, and overhead ratio of PRoPHET protocol by appropriately selecting the threshold forwarding counter and threshold hop counter values.

Enabling Optical Network Test Bed for 5G Tests

NASA Astrophysics Data System (ADS)

Giuntini, Marco; Grazioso, Paolo; Matera, Francesco; Valenti, Alessandro; Attanasio, Vincenzo; Di Bartolo, Silvia; Nastri, Emanuele

2017-03-01

In this work, we show some experimental approaches concerning optical network design dedicated to 5G infrastructures. In particular, we show some implementations of network slicing based on Carrier Ethernet forwarding, which will be very suitable in the context of 5G heterogeneous networks, especially looking at services for vertical enterprises. We also show how to adopt a central unit (orchestrator) to automatically manage such logical paths according to quality-of-service requirements, which can be monitored at the user location. We also illustrate how novel all-optical processes, such as the ones based on all-optical wavelength conversion, can be used for multicasting, enabling development of TV broadcasting based on 4G-5G terminals. These managing and forwarding techniques, operating on optical links, are tested in a wireless environment on Wi-Fi cells and emulating LTE and WiMAX systems by means of the NS-3 code.

Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots

PubMed Central

Rodriguez-Donate, Carlos; Osornio-Rios, Roque Alfredo; Rivera-Guillen, Jesus Rooney; de Jesus Romero-Troncoso, Rene

2011-01-01

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot. PMID:22163850

Efficient Data Gathering in 3D Linear Underwater Wireless Sensor Networks Using Sink Mobility

PubMed Central

Akbar, Mariam; Javaid, Nadeem; Khan, Ayesha Hussain; Imran, Muhammad; Shoaib, Muhammad; Vasilakos, Athanasios

2016-01-01

Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability. PMID:27007373

Efficient Data Gathering in 3D Linear Underwater Wireless Sensor Networks Using Sink Mobility.

PubMed

Akbar, Mariam; Javaid, Nadeem; Khan, Ayesha Hussain; Imran, Muhammad; Shoaib, Muhammad; Vasilakos, Athanasios

2016-03-19

Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability.

Multiple Event Localization in a Sparse Acoustic Sensor Network Using UAVs as Data Mules

DTIC Science & Technology

2012-12-01

necessarily reflect the position or the policy of the Government , and no official endorsement should be inferred. Path Acoustic Sensor Communication Footprint...a Microhard radio to forward the ToAs to the mule-UAV. Two Procerus Unicorn UAVs were used with different payloads. The imaging- UAV was equipped

A Hybrid Path-Oriented Code Assignment CDMA-Based MAC Protocol for Underwater Acoustic Sensor Networks

PubMed Central

Chen, Huifang; Fan, Guangyu; Xie, Lei; Cui, Jun-Hong

2013-01-01

Due to the characteristics of underwater acoustic channel, media access control (MAC) protocols designed for underwater acoustic sensor networks (UWASNs) are quite different from those for terrestrial wireless sensor networks. Moreover, in a sink-oriented network with event information generation in a sensor field and message forwarding to the sink hop-by-hop, the sensors near the sink have to transmit more packets than those far from the sink, and then a funneling effect occurs, which leads to packet congestion, collisions and losses, especially in UWASNs with long propagation delays. An improved CDMA-based MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC), is proposed for UWASNs in this paper. In the proposed MAC protocol, both the round-robin method and CDMA technology are adopted to make the sink receive packets from multiple paths simultaneously. Since the number of paths for information gathering is much less than that of nodes, the length of the spreading code used in the POCA-CDMA-MAC protocol is shorter greatly than that used in the CDMA-based protocols with transmitter-oriented code assignment (TOCA) or receiver-oriented code assignment (ROCA). Simulation results show that the proposed POCA-CDMA-MAC protocol achieves a higher network throughput and a lower end-to-end delay compared to other CDMA-based MAC protocols. PMID:24193100

A hybrid path-oriented code assignment CDMA-based MAC protocol for underwater acoustic sensor networks.

PubMed

Chen, Huifang; Fan, Guangyu; Xie, Lei; Cui, Jun-Hong

2013-11-04

Due to the characteristics of underwater acoustic channel, media access control (MAC) protocols designed for underwater acoustic sensor networks (UWASNs) are quite different from those for terrestrial wireless sensor networks. Moreover, in a sink-oriented network with event information generation in a sensor field and message forwarding to the sink hop-by-hop, the sensors near the sink have to transmit more packets than those far from the sink, and then a funneling effect occurs, which leads to packet congestion, collisions and losses, especially in UWASNs with long propagation delays. An improved CDMA-based MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC), is proposed for UWASNs in this paper. In the proposed MAC protocol, both the round-robin method and CDMA technology are adopted to make the sink receive packets from multiple paths simultaneously. Since the number of paths for information gathering is much less than that of nodes, the length of the spreading code used in the POCA-CDMA-MAC protocol is shorter greatly than that used in the CDMA-based protocols with transmitter-oriented code assignment (TOCA) or receiver-oriented code assignment (ROCA). Simulation results show that the proposed POCA-CDMA-MAC protocol achieves a higher network throughput and a lower end-to-end delay compared to other CDMA-based MAC protocols.

Path optimisation of a mobile robot using an artificial neural network controller

NASA Astrophysics Data System (ADS)

Singh, M. K.; Parhi, D. R.

2011-01-01

This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

Systematic network coding for two-hop lossy transmissions

NASA Astrophysics Data System (ADS)

Li, Ye; Blostein, Steven; Chan, Wai-Yip

2015-12-01

In this paper, we consider network transmissions over a single or multiple parallel two-hop lossy paths. These scenarios occur in applications such as sensor networks or WiFi offloading. Random linear network coding (RLNC), where previously received packets are re-encoded at intermediate nodes and forwarded, is known to be a capacity-achieving approach for these networks. However, a major drawback of RLNC is its high encoding and decoding complexity. In this work, a systematic network coding method is proposed. We show through both analysis and simulation that the proposed method achieves higher end-to-end rate as well as lower computational cost than RLNC for finite field sizes and finite-sized packet transmissions.

A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology

NASA Astrophysics Data System (ADS)

Tan, Mian; Yang, Tinghong; Chen, Xing; Yang, Gang; Zhu, Guoqing; Holme, Petter; Zhao, Jing

2018-03-01

Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming "communication shortcuts" between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes' selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.

Classification and Prediction of RF Coupling inside A-320 and A-319 Airplanes using Feed Forward Neural Networks

NASA Technical Reports Server (NTRS)

Jafri, Madiha; Ely, Jay; Vahala, Linda

2006-01-01

Neural Network Modeling is introduced in this paper to classify and predict Interference Path Loss measurements on Airbus 319 and 320 airplanes. Interference patterns inside the aircraft are classified and predicted based on the locations of the doors, windows, aircraft structures and the communication/navigation system-of-concern. Modeled results are compared with measured data and a plan is proposed to enhance the modeling for better prediction of electromagnetic coupling problems inside aircraft.

A distributed geo-routing algorithm for wireless sensor networks.

PubMed

Joshi, Gyanendra Prasad; Kim, Sung Won

2009-01-01

Geographic wireless sensor networks use position information for greedy routing. Greedy routing works well in dense networks, whereas in sparse networks it may fail and require a recovery algorithm. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costly for resource constrained position-based wireless sensor networks (WSNs). In this paper, we propose a void avoidance algorithm (VAA), a novel idea based on upgrading virtual distance. VAA allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forwarding packets using only greedy routing. In VAA, the stuck node upgrades distance unless it finds a next hop node that is closer to the destination than it is. VAA guarantees packet delivery if there is a topologically valid path. Further, it is completely distributed, immediately responds to node failure or topology changes and does not require planarization of the network. NS-2 is used to evaluate the performance and correctness of VAA and we compare its performance to other protocols. Simulations show our proposed algorithm consumes less energy, has an efficient path and substantially less control overheads.

Load-adaptive practical multi-channel communications in wireless sensor networks.

PubMed

Islam, Md Shariful; Alam, Muhammad Mahbub; Hong, Choong Seon; Lee, Sungwon

2010-01-01

In recent years, a significant number of sensor node prototypes have been designed that provide communications in multiple channels. This multi-channel feature can be effectively exploited to increase the overall capacity and performance of wireless sensor networks (WSNs). In this paper, we present a multi-channel communications system for WSNs that is referred to as load-adaptive practical multi-channel communications (LPMC). LPMC estimates the active load of a channel at the sink since it has a more comprehensive view of the network behavior, and dynamically adds or removes channels based on the estimated load. LPMC updates the routing path to balance the loads of the channels. The nodes in a path use the same channel; therefore, they do not need to switch channels to receive or forward packets. LPMC has been evaluated through extensive simulations, and the results demonstrate that it can effectively increase the delivery ratio, network throughput, and channel utilization, and that it can decrease the end-to-end delay and energy consumption.

Curvature and torsion in growing actin networks

NASA Astrophysics Data System (ADS)

Shaevitz, Joshua W.; Fletcher, Daniel A.

2008-06-01

Intracellular pathogens such as Listeria monocytogenes and Rickettsia rickettsii move within a host cell by polymerizing a comet-tail of actin fibers that ultimately pushes the cell forward. This dense network of cross-linked actin polymers typically exhibits a striking curvature that causes bacteria to move in gently looping paths. Theoretically, tail curvature has been linked to details of motility by considering force and torque balances from a finite number of polymerizing filaments. Here we track beads coated with a prokaryotic activator of actin polymerization in three dimensions to directly quantify the curvature and torsion of bead motility paths. We find that bead paths are more likely to have low rather than high curvature at any given time. Furthermore, path curvature changes very slowly in time, with an autocorrelation decay time of 200 s. Paths with a small radius of curvature, therefore, remain so for an extended period resulting in loops when confined to two dimensions. When allowed to explore a three-dimensional (3D) space, path loops are less evident. Finally, we quantify the torsion in the bead paths and show that beads do not exhibit a significant left- or right-handed bias to their motion in 3D. These results suggest that paths of actin-propelled objects may be attributed to slow changes in curvature, possibly associated with filament debranching, rather than a fixed torque.

On the Feasibility of Wireless Multimedia Sensor Networks over IEEE 802.15.5 Mesh Topologies

PubMed Central

Garcia-Sanchez, Antonio-Javier; Losilla, Fernando; Rodenas-Herraiz, David; Cruz-Martinez, Felipe; Garcia-Sanchez, Felipe

2016-01-01

Wireless Multimedia Sensor Networks (WMSNs) are a special type of Wireless Sensor Network (WSN) where large amounts of multimedia data are transmitted over networks composed of low power devices. Hierarchical routing protocols typically used in WSNs for multi-path communication tend to overload nodes located within radio communication range of the data collection unit or data sink. The battery life of these nodes is therefore reduced considerably, requiring frequent battery replacement work to extend the operational life of the WSN system. In a wireless sensor network with mesh topology, any node may act as a forwarder node, thereby enabling multiple routing paths toward any other node or collection unit. In addition, mesh topologies have proven advantages, such as data transmission reliability, network robustness against node failures, and potential reduction in energy consumption. This work studies the feasibility of implementing WMSNs in mesh topologies and their limitations by means of exhaustive computer simulation experiments. To this end, a module developed for the Synchronous Energy Saving (SES) mode of the IEEE 802.15.5 mesh standard has been integrated with multimedia tools to thoroughly test video sequences encoded using H.264 in mesh networks. PMID:27164106

On the Feasibility of Wireless Multimedia Sensor Networks over IEEE 802.15.5 Mesh Topologies.

PubMed

Garcia-Sanchez, Antonio-Javier; Losilla, Fernando; Rodenas-Herraiz, David; Cruz-Martinez, Felipe; Garcia-Sanchez, Felipe

2016-05-05

Wireless Multimedia Sensor Networks (WMSNs) are a special type of Wireless Sensor Network (WSN) where large amounts of multimedia data are transmitted over networks composed of low power devices. Hierarchical routing protocols typically used in WSNs for multi-path communication tend to overload nodes located within radio communication range of the data collection unit or data sink. The battery life of these nodes is therefore reduced considerably, requiring frequent battery replacement work to extend the operational life of the WSN system. In a wireless sensor network with mesh topology, any node may act as a forwarder node, thereby enabling multiple routing paths toward any other node or collection unit. In addition, mesh topologies have proven advantages, such as data transmission reliability, network robustness against node failures, and potential reduction in energy consumption. This work studies the feasibility of implementing WMSNs in mesh topologies and their limitations by means of exhaustive computer simulation experiments. To this end, a module developed for the Synchronous Energy Saving (SES) mode of the IEEE 802.15.5 mesh standard has been integrated with multimedia tools to thoroughly test video sequences encoded using H.264 in mesh networks.

76 FR 24925 - Solicitation for Public Comment on Potential Alternatives To Resolve Generic Safety Issue 191...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-03

... comment on potential alternatives for risk informing the path forward to resolve Generic Safety Issue (GSI... Notation Vote Paper (SECY-10-0113) which presented to the Commission the regulatory path forward options... the staff, in part, to explore alternative paths forward for resolving GSI-191. Discussion While GSI...

Optimization of OSPF Routing in IP Networks

NASA Astrophysics Data System (ADS)

Bley, Andreas; Fortz, Bernard; Gourdin, Eric; Holmberg, Kaj; Klopfenstein, Olivier; Pióro, Michał; Tomaszewski, Artur; Ümit, Hakan

The Internet is a huge world-wide packet switching network comprised of more than 13,000 distinct subnetworks, referred to as Autonomous Systems (ASs) autonomous system AS . They all rely on the Internet Protocol (IP) internet protocol IP for transport of packets across the network. And most of them use shortest path routing protocols shortest path routing!protocols , such as OSPF or IS-IS, to control the routing of IP packets routing!of IP packets within an AS. The idea of the routing is extremely simple — every packet is forwarded on IP links along the shortest route between its source and destination nodes of the AS. The AS network administrator can manage the routing of packets in the AS by supplying the so-called administrative weights of IP links, which specify the link lengths that are used by the routing protocols for their shortest path computations. The main advantage of the shortest path routing policy is its simplicity, allowing for little administrative overhead. From the network engineering perspective, however, shortest path routing can pose problems in achieving satisfactory traffic handling efficiency. As all routing paths depend on the same routing metric routing!metric , it is not possible to configure the routing paths for the communication demands between different pairs of nodes explicitly or individually; the routing can be controlled only indirectly and only as a whole by modifying the routing metric. Thus, one of the main tasks when planning such networks is to find administrative link weights that induce a globally efficient traffic routing traffic!routing configuration of an AS. It turns out that this task leads to very difficult mathematical optimization problems. In this chapter, we discuss and describe exact integer programming models and solution approaches as well as practically efficient smart heuristics for such shortest path routing problems shortest path routing!problems .

Escalator: An Autonomous Scheduling Scheme for Convergecast in TSCH

PubMed Central

Oh, Sukho; Hwang, DongYeop; Kim, Ki-Hyung; Kim, Kangseok

2018-01-01

Time Slotted Channel Hopping (TSCH) is widely used in the industrial wireless sensor networks due to its high reliability and energy efficiency. Various timeslot and channel scheduling schemes have been proposed for achieving high reliability and energy efficiency for TSCH networks. Recently proposed autonomous scheduling schemes provide flexible timeslot scheduling based on the routing topology, but do not take into account the network traffic and packet forwarding delays. In this paper, we propose an autonomous scheduling scheme for convergecast in TSCH networks with RPL as a routing protocol, named Escalator. Escalator generates a consecutive timeslot schedule along the packet forwarding path to minimize the packet transmission delay. The schedule is generated autonomously by utilizing only the local routing topology information without any additional signaling with other nodes. The generated schedule is guaranteed to be conflict-free, in that all nodes in the network could transmit packets to the sink in every slotframe cycle. We implement Escalator and evaluate its performance with existing autonomous scheduling schemes through a testbed and simulation. Experimental results show that the proposed Escalator has lower end-to-end delay and higher packet delivery ratio compared to the existing schemes regardless of the network topology. PMID:29659508

Escalator: An Autonomous Scheduling Scheme for Convergecast in TSCH.

PubMed

Oh, Sukho; Hwang, DongYeop; Kim, Ki-Hyung; Kim, Kangseok

2018-04-16

Time Slotted Channel Hopping (TSCH) is widely used in the industrial wireless sensor networks due to its high reliability and energy efficiency. Various timeslot and channel scheduling schemes have been proposed for achieving high reliability and energy efficiency for TSCH networks. Recently proposed autonomous scheduling schemes provide flexible timeslot scheduling based on the routing topology, but do not take into account the network traffic and packet forwarding delays. In this paper, we propose an autonomous scheduling scheme for convergecast in TSCH networks with RPL as a routing protocol, named Escalator. Escalator generates a consecutive timeslot schedule along the packet forwarding path to minimize the packet transmission delay. The schedule is generated autonomously by utilizing only the local routing topology information without any additional signaling with other nodes. The generated schedule is guaranteed to be conflict-free, in that all nodes in the network could transmit packets to the sink in every slotframe cycle. We implement Escalator and evaluate its performance with existing autonomous scheduling schemes through a testbed and simulation. Experimental results show that the proposed Escalator has lower end-to-end delay and higher packet delivery ratio compared to the existing schemes regardless of the network topology.

A Pub/Sub Message Distribution Architecture for Disruption Tolerant Networks

NASA Astrophysics Data System (ADS)

Carrilho, Sergio; Esaki, Hiroshi

Access to information is taken for granted in urban areas covered by a robust communication infrastructure. Nevertheless most of the areas in the world, are not covered by such infrastructures. We propose a DTN publish and subscribe system called Hikari, which uses nodes' mobility in order to distribute messages without using a robust infrastructure. The area of Disruption/Delay Tolerant Networks (DTN) focuses on providing connectivity to locations separated by networks with disruptions and delays. The Hikari system does not use node identifiers for message forwarding thus eliminating the complexity of routing associated with many forwarding schemes in DTN. Hikari uses nodes paths' information, advertised by special nodes in the system or predicted by the system itself, for optimizing the message dissemination process. We have used the Paris subway system, due to it's complexity, to validate Hikari and to analyze it's performance. We have shown that Hikari achieves a superior deliver rate while keeping redundant messages in the system low, which is ideal when using devices with limited resources for message dissemination.

Mobile Sinks Assisted Geographic and Opportunistic Routing Based Interference Avoidance for Underwater Wireless Sensor Network

PubMed Central

Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil

2018-01-01

The distinctive features of acoustic communication channel-like high propagation delay, multi-path fading, quick attenuation of acoustic signal, etc. limit the utilization of underwater wireless sensor networks (UWSNs). The immutable selection of forwarder node leads to dramatic death of node resulting in imbalanced energy depletion and void hole creation. To reduce the probability of void occurrence and imbalance energy dissipation, in this paper, we propose mobility assisted geo-opportunistic routing paradigm based on interference avoidance for UWSNs. The network volume is divided into logical small cubes to reduce the interference and to make more informed routing decisions for efficient energy consumption. Additionally, an optimal number of forwarder nodes is elected from each cube based on its proximity with respect to the destination to avoid void occurrence. Moreover, the data packets are recovered from void regions with the help of mobile sinks which also reduce the data traffic on intermediate nodes. Extensive simulations are performed to verify that our proposed work maximizes the network lifetime and packet delivery ratio. PMID:29614794

Mobile Sinks Assisted Geographic and Opportunistic Routing Based Interference Avoidance for Underwater Wireless Sensor Network.

PubMed

Ahmed, Farwa; Wadud, Zahid; Javaid, Nadeem; Alrajeh, Nabil; Alabed, Mohamad Souheil; Qasim, Umar

2018-04-02

The distinctive features of acoustic communication channel-like high propagation delay, multi-path fading, quick attenuation of acoustic signal, etc. limit the utilization of underwater wireless sensor networks (UWSNs). The immutable selection of forwarder node leads to dramatic death of node resulting in imbalanced energy depletion and void hole creation. To reduce the probability of void occurrence and imbalance energy dissipation, in this paper, we propose mobility assisted geo-opportunistic routing paradigm based on interference avoidance for UWSNs. The network volume is divided into logical small cubes to reduce the interference and to make more informed routing decisions for efficient energy consumption. Additionally, an optimal number of forwarder nodes is elected from each cube based on its proximity with respect to the destination to avoid void occurrence. Moreover, the data packets are recovered from void regions with the help of mobile sinks which also reduce the data traffic on intermediate nodes. Extensive simulations are performed to verify that our proposed work maximizes the network lifetime and packet delivery ratio.

75 FR 2057 - Airworthiness Directives; Airbus Model A340-200 and A340-300 Series Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-14

... could lead to the loss of the load path for the forward engine mount and damage to other engine mount... loss of the load path for the forward engine mount and damage to other engine mount structures, which... loss of the load path for the forward engine mount and damage to other engine mount structures, which...

An Investigation on Ground Electrodes of Capacitive Coupling Human Body Communication.

PubMed

Mao, Jingna; Yang, Huazhong; Zhao, Bo

2017-08-01

Utilizing the body surface as the signal transmission medium, capacitive coupling human body communication (CC-HBC) can achieve a much higher energy efficiency than conventional wireless communications in future wireless body area network (WBAN) applications. Under the CC-HBC scheme, the body surface serves as the forward signal path, whereas the backward path is formed by the capacitive coupling between the ground electrodes (GEs) of transmitter (TX) and receiver (RX). So the type of communication benefits from a low forward loss, while the backward loss depending on the GE coupling strength dominates the total transmission loss. However, none of the previous works have shown a complete research on the effects of GEs. In this paper, all kinds of GE effects on CC-HBC are investigated by both finite element method (FEM) analysis and human body measurement. We set the TX GE and RX GE at different heights, separation distances, and dimensions to study the corresponding influence on the overall signal transmission path loss. In addition, we also investigate the effects of GEs with different shapes and different TX-to-RX relative angles. Based on all the investigations, an analytical model is derived to evaluate the GE related variations of channel loss in CC-HBC.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Accelerating Innovation that Enhances Resource Recovery in the Wastewater Sector: Advancing a National Testbed Network.

PubMed

Mihelcic, James R; Ren, Zhiyong Jason; Cornejo, Pablo K; Fisher, Aaron; Simon, A J; Snyder, Seth W; Zhang, Qiong; Rosso, Diego; Huggins, Tyler M; Cooper, William; Moeller, Jeff; Rose, Bob; Schottel, Brandi L; Turgeon, Jason

2017-07-18

This Feature examines significant challenges and opportunities to spur innovation and accelerate adoption of reliable technologies that enhance integrated resource recovery in the wastewater sector through the creation of a national testbed network. The network is a virtual entity that connects appropriate physical testing facilities, and other components needed for a testbed network, with researchers, investors, technology providers, utilities, regulators, and other stakeholders to accelerate the adoption of innovative technologies and processes that are needed for the water resource recovery facility of the future. Here we summarize and extract key issues and developments, to provide a strategy for the wastewater sector to accelerate a path forward that leads to new sustainable water infrastructures.

Cooperative UAV-Based Communications Backbone for Sensor Networks

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

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

NASA Astrophysics Data System (ADS)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks.

PubMed

Wu, Shaobo; Chou, Wusheng; Niu, Jianwei; Guizani, Mohsen

2018-03-18

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, existing schemes fail to guarantee delay requirements while achieving high energy efficiency. This paper proposes a delay-aware energy-efficient routing algorithm for WSNs with a path-fixed mobile sink, named DERM, which can strike a desirable balance between the delivery latency and energy conservation. We characterize the object of DERM as realizing the energy-optimal anycast to time-varying destination regions, and introduce a location-based forwarding technique tailored for this problem. To reduce the control overhead, a lightweight sink location calibration method is devised, which cooperates with the rough estimation based on the mobility pattern to determine the sink location. We also design a fault-tolerant mechanism called track routing to tackle location errors for ensuring reliable and on-time data delivery. We comprehensively evaluate DERM by comparing it with two canonical routing schemes and a baseline solution presented in this work. Extensive evaluation results demonstrate that DERM can provide considerable energy savings while meeting the delay constraint and maintaining a high delivery ratio.

Delay-Aware Energy-Efficient Routing towards a Path-Fixed Mobile Sink in Industrial Wireless Sensor Networks

PubMed Central

Wu, Shaobo; Chou, Wusheng; Niu, Jianwei; Guizani, Mohsen

2018-01-01

Wireless sensor networks (WSNs) involve more mobile elements with their widespread development in industries. Exploiting mobility present in WSNs for data collection can effectively improve the network performance. However, when the sink (i.e., data collector) path is fixed and the movement is uncontrollable, existing schemes fail to guarantee delay requirements while achieving high energy efficiency. This paper proposes a delay-aware energy-efficient routing algorithm for WSNs with a path-fixed mobile sink, named DERM, which can strike a desirable balance between the delivery latency and energy conservation. We characterize the object of DERM as realizing the energy-optimal anycast to time-varying destination regions, and introduce a location-based forwarding technique tailored for this problem. To reduce the control overhead, a lightweight sink location calibration method is devised, which cooperates with the rough estimation based on the mobility pattern to determine the sink location. We also design a fault-tolerant mechanism called track routing to tackle location errors for ensuring reliable and on-time data delivery. We comprehensively evaluate DERM by comparing it with two canonical routing schemes and a baseline solution presented in this work. Extensive evaluation results demonstrate that DERM can provide considerable energy savings while meeting the delay constraint and maintaining a high delivery ratio. PMID:29562628

A Cross-Layer Duty Cycle MAC Protocol Supporting a Pipeline Feature for Wireless Sensor Networks

PubMed Central

Tong, Fei; Xie, Rong; Shu, Lei; Kim, Young-Chon

2011-01-01

Although the conventional duty cycle MAC protocols for Wireless Sensor Networks (WSNs) such as RMAC perform well in terms of saving energy and reducing end-to-end delivery latency, they were designed independently and require an extra routing protocol in the network layer to provide path information for the MAC layer. In this paper, we propose a new cross-layer duty cycle MAC protocol with data forwarding supporting a pipeline feature (P-MAC) for WSNs. P-MAC first divides the whole network into many grades around the sink. Each node identifies its grade according to its logical hop distance to the sink and simultaneously establishes a sleep/wakeup schedule using the grade information. Those nodes in the same grade keep the same schedule, which is staggered with the schedule of the nodes in the adjacent grade. Then a variation of the RTS/CTS handshake mechanism is used to forward data continuously in a pipeline fashion from the higher grade to the lower grade nodes and finally to the sink. No extra routing overhead is needed, thus increasing the network scalability while maintaining the superiority of duty-cycling. The simulation results in OPNET show that P-MAC has better performance than S-MAC and RMAC in terms of packet delivery latency and energy efficiency. PMID:22163895

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

NASA Astrophysics Data System (ADS)

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

2005-06-01

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

[Measurement and performance analysis of functional neural network].

PubMed

Li, Shan; Liu, Xinyu; Chen, Yan; Wan, Hong

2018-04-01

The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.

Neural node network and model, and method of teaching same

DOEpatents

Parlos, A.G.; Atiya, A.F.; Fernandez, B.; Tsai, W.K.; Chong, K.T.

1995-12-26

The present invention is a fully connected feed forward network that includes at least one hidden layer. The hidden layer includes nodes in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device occurring in the feedback path (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit from all the other nodes within the same layer. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk. Subsequent to the gradient propagation, the weights can be normalized, thereby preventing convergence to a local optimum. Education of the network can be incremental both on and off-line. An educated network is suitable for modeling and controlling dynamic nonlinear systems and time series systems and predicting the outputs as well as hidden states and parameters. The educated network can also be further educated during on-line processing. 21 figs.

Neural node network and model, and method of teaching same

DOEpatents

Parlos, Alexander G.; Atiya, Amir F.; Fernandez, Benito; Tsai, Wei K.; Chong, Kil T.

1995-01-01

The present invention is a fully connected feed forward network that includes at least one hidden layer 16. The hidden layer 16 includes nodes 20 in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device 24 occurring in the feedback path 22 (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit 36 from all the other nodes within the same layer 16. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk. Subsequent to the gradient propagation, the weights can be normalized, thereby preventing convergence to a local optimum. Education of the network can be incremental both on and off-line. An educated network is suitable for modeling and controlling dynamic nonlinear systems and time series systems and predicting the outputs as well as hidden states and parameters. The educated network can also be further educated during on-line processing.

An efficient coordination protocol for wireless sensor networks

NASA Astrophysics Data System (ADS)

Paruchuri, Vamsi; Durresi, Arjan; Durresi, Mimoza; Barolli, Leonard

2005-10-01

Backbones infrastructures in wireless sensor networks reduce the communication overhead and energy consumption. In this paper, we present BackBone Routing (BBR), a fully distributed protocol for construction and rotation of backbone networks. BBR reduces energy consumption without significantly diminishing the capacity or connectivity of the network. Another key feature of BBR is its energy balancing nature by distributing the role of being Backbone Node among all the nodes. BBR builds on the observation that when a region of a shared-channel wireless network has a sufficient density of nodes, only a small number of them need be on at any time to forward traffic for active connections. Improvement in system lifetime due to BBR increases as the ratio of idle-to-sleep energy consumption increases, and increases as the density of the network increases. Our experiments show that BBR is more efficient in saving energy and extending network life without deteriorating network performance when compared with geographical shortest path routing.

Performance Evaluation of AODV with Blackhole Attack

NASA Astrophysics Data System (ADS)

Dara, Karuna

2010-11-01

A Mobile Ad Hoc Network (MANET) is a temporary network set up by a wireless mobile computers moving arbitrary in the places that have no network infrastructure. These nodes maintain connectivity in a decentralized manner. Since the nodes communicate with each other, they cooperate by forwarding data packets to other nodes in the network. Thus the nodes find a path to the destination node using routing protocols. However, due to security vulnerabilities of the routing protocols, mobile ad-hoc networks are unprotected to attacks of the malicious nodes. One of these attacks is the Black Hole Attack against network integrity absorbing all data packets in the network. Since the data packets do not reach the destination node on account of this attack, data loss will occur. In this paper, we simulated the black hole attack in various mobile ad-hoc network scenarios using AODV routing protocol of MANET and have tried to find a effect if number of nodes are increased with increase in malicious nodes.

SCODE: A Secure Coordination-Based Data Dissemination to Mobile Sinks in Sensor Networks

NASA Astrophysics Data System (ADS)

Hung, Lexuan; Lee, Sungyoung; Lee, Young-Koo; Lee, Heejo

For many sensor network applications such as military, homeland security, it is necessary for users (sinks) to access sensor networks while they are moving. However, sink mobility brings new challenges to secure routing in large-scale sensor networks. Mobile sinks have to constantly propagate their current location to all nodes, and these nodes need to exchange messages with each other so that the sensor network can establish and maintain a secure multi-hop path between a source node and a mobile sink. This causes significant computation and communication overhead for sensor nodes. Previous studies on sink mobility have mainly focused on efficiency and effectiveness of data dissemination without security consideration. In this paper, we propose a secure and energy-efficient data dissemination protocol — Secure COodination-based Data dissEmination (SCODE) — for mobile sinks in sensor networks. We take advantages of coordination networks (grid structure) based on Geographical Adaptive Fidelity (GAF) protocol to construct a secure and efficient routing path between sources and sinks. Our security analysis demonstrates that the proposed protocol can defend against common attacks in sensor network routing such as replay attacks, selective forwarding attacks, sinkhole and wormhole, Sybil attacks, HELLO flood attacks. Our performance evaluation both in mathematical analysis and simulation shows that the SCODE significantly reduces communication overhead and energy consumption while the latency is similar compared with the existing routing protocols, and it always delivers more than 90 percentage of packets successfully.

WISM - A Wideband Instrument for Snow Measurement: Past Accomplishments, Current Status, and Path Forward

NASA Technical Reports Server (NTRS)

Bonds, Quenton; Racette, Paul; Durham, Tim (Principal Investigator)

2016-01-01

Presented are the prior accomplishments, current status and path forward for GSFC's Wideband Instrument for Snow Measurement (WISM). This work is a high level overview of the project, presented via Webinar to the IEEE young professionals.

Fundamental changes to EPA's research enterprise: the path forward.

PubMed

Anastas, Paul T

2012-01-17

Environmental protection in the United States has reached a critical juncture. It has become clear that to address the complex and interrelated environmental challenges we face, we must augment our traditional approaches. The scientific community must build upon its deep understanding of risk assessment, risk management, and reductionism with tools, technologies, insights and approaches to pursue sustainability. The U.S. Environmental Protection Agency (EPA) has recognized this need for systemic change by implementing a new research paradigm called "The Path Forward." This paper outlines the principles of the Path Forward and the actions taken since 2010 to align EPA's research efforts with the goal of sustainability.

Mutual-Information-Based Incremental Relaying Communications for Wireless Biomedical Implant Systems

PubMed Central

Liao, Yangzhe; Cai, Qing; Ai, Qingsong; Liu, Quan

2018-01-01

Network lifetime maximization of wireless biomedical implant systems is one of the major research challenges of wireless body area networks (WBANs). In this paper, a mutual information (MI)-based incremental relaying communication protocol is presented where several on-body relay nodes and one coordinator are attached to the clothes of a patient. Firstly, a comprehensive analysis of a system model is investigated in terms of channel path loss, energy consumption, and the outage probability from the network perspective. Secondly, only when the MI value becomes smaller than the predetermined threshold is data transmission allowed. The communication path selection can be either from the implanted sensor to the on-body relay then forwards to the coordinator or from the implanted sensor to the coordinator directly, depending on the communication distance. Moreover, mathematical models of quality of service (QoS) metrics are derived along with the related subjective functions. The results show that the MI-based incremental relaying technique achieves better performance in comparison to our previous proposed protocol techniques regarding several selected performance metrics. The outcome of this paper can be applied to intra-body continuous physiological signal monitoring, artificial biofeedback-oriented WBANs, and telemedicine system design. PMID:29419784

Mutual-Information-Based Incremental Relaying Communications for Wireless Biomedical Implant Systems.

PubMed

Liao, Yangzhe; Leeson, Mark S; Cai, Qing; Ai, Qingsong; Liu, Quan

2018-02-08

Network lifetime maximization of wireless biomedical implant systems is one of the major research challenges of wireless body area networks (WBANs). In this paper, a mutual information (MI)-based incremental relaying communication protocol is presented where several on-body relay nodes and one coordinator are attached to the clothes of a patient. Firstly, a comprehensive analysis of a system model is investigated in terms of channel path loss, energy consumption, and the outage probability from the network perspective. Secondly, only when the MI value becomes smaller than the predetermined threshold is data transmission allowed. The communication path selection can be either from the implanted sensor to the on-body relay then forwards to the coordinator or from the implanted sensor to the coordinator directly, depending on the communication distance. Moreover, mathematical models of quality of service (QoS) metrics are derived along with the related subjective functions. The results show that the MI-based incremental relaying technique achieves better performance in comparison to our previous proposed protocol techniques regarding several selected performance metrics. The outcome of this paper can be applied to intra-body continuous physiological signal monitoring, artificial biofeedback-oriented WBANs, and telemedicine system design.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

Forward- and reverse-bias tunneling effects in n/+/p silicon solar cells

NASA Technical Reports Server (NTRS)

Garlick, G. F. J.; Kachare, A. H.

1980-01-01

Excess currents due to field-assisted tunneling in both forward and reverse bias directions have been observed in n(+)-p silicon solar cells. These currents arise from the effect of conducting paths produced in the depletion layer by n(+) diffusion and cell processing. Forward-bias data indicate a small potential barrier with height of 0.04 eV at the n(+) end of conducting paths. Under reverse bias, excess tunneling currents involve a potential barrier at the p end of the conducting paths, the longer paths being associated with smaller barrier heights and dominating at the lower temperatures. Low-reverse-bias data give energy levels of 0.11 eV for lower temperatures (253-293 K) and 0.35 eV for higher temperatures (293-380 K). A model is suggested to explain the results.

Patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks.

PubMed

Aguiar, Manuela A D; Dias, Ana Paula S; Ferreira, Flora

2017-01-01

We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer receive only inputs from cells of the previous layer. An auto-regulation feed-forward neural coupled cell network is a feed-forward neural network where additionally some cells of the first layer have auto-regulation, that is, they have a self-loop. Given a network structure, a robust pattern of synchrony is a space defined in terms of equalities of cell coordinates that is flow-invariant for any coupled cell system (with additive input structure) associated with the network. In this paper, we describe the robust patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks. Regarding feed-forward neural networks, we show that only cells in the same layer can synchronize. On the other hand, in the presence of auto-regulation, we prove that cells in different layers can synchronize in a robust way and we give a characterization of the possible patterns of synchrony that can occur for auto-regulation feed-forward neural networks.

Concerns regarding 24-h sampling for formaldehyde, acetaldehyde, and acrolein using 2,4-dinitrophenylhydrazine (DNPH)-coated solid sorbents

NASA Astrophysics Data System (ADS)

Herrington, Jason S.; Hays, Michael D.

2012-08-01

There is high demand for accurate and reliable airborne carbonyl measurement methods due to the human and environmental health impacts of carbonyls and their effects on atmospheric chemistry. Standardized 2,4-dinitrophenylhydrazine (DNPH)-based sampling methods are frequently applied for measuring gaseous carbonyls in the atmospheric environment. However, there are multiple short-comings associated with these methods that detract from an accurate understanding of carbonyl-related exposure, health effects, and atmospheric chemistry. The purpose of this brief technical communication is to highlight these method challenges and their influence on national ambient monitoring networks, and to provide a logical path forward for accurate carbonyl measurement. This manuscript focuses on three specific carbonyl compounds of high toxicological interest—formaldehyde, acetaldehyde, and acrolein. Further method testing and development, the revision of standardized methods, and the plausibility of introducing novel technology for these carbonyls are considered elements of the path forward. The consolidation of this information is important because it seems clear that carbonyl data produced utilizing DNPH-based methods are being reported without acknowledgment of the method short-comings or how to best address them.

Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks.

PubMed

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-12-13

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

Towards a Hybrid Energy Efficient Multi-Tree-Based Optimized Routing Protocol for Wireless Networks

PubMed Central

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-01-01

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. PMID:23443398

Analysis Report for Exascale Storage Requirements for Scientific Data.

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

Ruwart, Thomas M.

Over the next 10 years, the Department of Energy will be transitioning from Petascale to Exascale Computing resulting in data storage, networking, and infrastructure requirements to increase by three orders of magnitude. The technologies and best practices used today are the result of a relatively slow evolution of ancestral technologies developed in the 1950s and 1960s. These include magnetic tape, magnetic disk, networking, databases, file systems, and operating systems. These technologies will continue to evolve over the next 10 to 15 years on a reasonably predictable path. Experience with the challenges involved in transitioning these fundamental technologies from Terascale tomore » Petascale computing systems has raised questions about how these will scale another 3 or 4 orders of magnitude to meet the requirements imposed by Exascale computing systems. This report is focused on the most concerning scaling issues with data storage systems as they relate to High Performance Computing- and presents options for a path forward. Given the ability to store exponentially increasing amounts of data, far more advanced concepts and use of metadata will be critical to managing data in Exascale computing systems.« less

A Novel Cooperative Opportunistic Routing Scheme for Underwater Sensor Networks

PubMed Central

Ghoreyshi, Seyed Mohammad; Shahrabi, Alireza; Boutaleb, Tuleen

2016-01-01

Increasing attention has recently been devoted to underwater sensor networks (UWSNs) because of their capabilities in the ocean monitoring and resource discovery. UWSNs are faced with different challenges, the most notable of which is perhaps how to efficiently deliver packets taking into account all of the constraints of the available acoustic communication channel. The opportunistic routing provides a reliable solution with the aid of intermediate nodes’ collaboration to relay a packet toward the destination. In this paper, we propose a new routing protocol, called opportunistic void avoidance routing (OVAR), to address the void problem and also the energy-reliability trade-off in the forwarding set selection. OVAR takes advantage of distributed beaconing, constructs the adjacency graph at each hop and selects a forwarding set that holds the best trade-off between reliability and energy efficiency. The unique features of OVAR in selecting the candidate nodes in the vicinity of each other leads to the resolution of the hidden node problem. OVAR is also able to select the forwarding set in any direction from the sender, which increases its flexibility to bypass any kind of void area with the minimum deviation from the optimal path. The results of our extensive simulation study show that OVAR outperforms other protocols in terms of the packet delivery ratio, energy consumption, end-to-end delay, hop count and traversed distance. PMID:26927118

A Novel Cooperative Opportunistic Routing Scheme for Underwater Sensor Networks.

PubMed

Ghoreyshi, Seyed Mohammad; Shahrabi, Alireza; Boutaleb, Tuleen

2016-02-26

Increasing attention has recently been devoted to underwater sensor networks (UWSNs) because of their capabilities in the ocean monitoring and resource discovery. UWSNs are faced with different challenges, the most notable of which is perhaps how to efficiently deliver packets taking into account all of the constraints of the available acoustic communication channel. The opportunistic routing provides a reliable solution with the aid of intermediate nodes' collaboration to relay a packet toward the destination. In this paper, we propose a new routing protocol, called opportunistic void avoidance routing (OVAR), to address the void problem and also the energy-reliability trade-off in the forwarding set selection. OVAR takes advantage of distributed beaconing, constructs the adjacency graph at each hop and selects a forwarding set that holds the best trade-off between reliability and energy efficiency. The unique features of OVAR in selecting the candidate nodes in the vicinity of each other leads to the resolution of the hidden node problem. OVAR is also able to select the forwarding set in any direction from the sender, which increases its flexibility to bypass any kind of void area with the minimum deviation from the optimal path. The results of our extensive simulation study show that OVAR outperforms other protocols in terms of the packet delivery ratio, energy consumption, end-to-end delay, hop count and traversed distance.

Argillite And Crystalline Disposal Research: Accomplishments And Path-Forward.

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

McMahon, Kevin A.; Jove-Colon, Carlos F.; Wang, Yifeng

The intention of this document is to provide a path-forward for research and development (R&D) for two host rock media-specific (argillite and crystalline) disposal research work packages within the Used Fuel Disposition Campaign (UFDC). The two work packages, Argillite Disposal R&D and Crystalline Disposal R&D, support the achievement of the overarching mission and objectives of the Department of Energy Office of Nuclear Energy Fuel Cycle Technologies Program. These two work packages cover many of the fundamental technical issues that will have multiple implications to other disposal research work packages by bridging knowledge gaps to support the development of the safetymore » case. The path-forward begins with the assumption of target dates that are set out in the January 2013 DOE Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste (http://energy.gov/downloads/strategy-management-and-disposal-used-nuclear-fuel-and-high-levelradioactive- waste). The path-forward will be maintained as a living document and will be updated as needed in response to available funding and the progress of multiple R&D tasks in the Used Fuel Disposition Campaign and the Fuel Cycle Technologies Program. This path forward is developed based on the report of “Used Fuel Disposition Campaign Disposal Research and Development Roadmap (FCR&D-USED- 2011-000065 REV0)” (DOE, 2011). This document delineates the goals and objectives of the UFDC R&D program, needs for generic disposal concept design, and summarizes the prioritization of R&D issues.« less

More than a meal: integrating non-feeding interactions into food webs

USGS Publications Warehouse

Kéfi, Sonia; Berlow, Eric L.; Wieters, Evie A.; Navarrete, Sergio A.; Petchey, Owen L.; Wood, Spencer A.; Boit, Alice; Joppa, Lucas N.; Lafferty, Kevin D.; Williams, Richard J.; Martinez, Neo D.; Menge, Bruce A.; Blanchette, Carol A.; Iles, Alison C.; Brose, Ulrich

2012-01-01

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.

Spreading paths in partially observed social networks

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Christakis, Nicholas A.

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

Spreading paths in partially observed social networks.

PubMed

Onnela, Jukka-Pekka; Christakis, Nicholas A

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

A New Path Forward: Four Approaches to Quality Teaching and Better Schools

ERIC Educational Resources Information Center

Weingarten, Randi

2010-01-01

In a global knowledge economy, filling in the bubbles on a standardized test isn't going to prepare children to succeed in life. This is the time to shed the old conflicts and come together. In this article, the author suggests a new path forward--toward a 21st-century education system, a serious and comprehensive reform plan to transform U.S.…

Multicast Routing of Hierarchical Data

NASA Technical Reports Server (NTRS)

Shacham, Nachum

1992-01-01

The issue of multicast of broadband, real-time data in a heterogeneous environment, in which the data recipients differ in their reception abilities, is considered. Traditional multicast schemes, which are designed to deliver all the source data to all recipients, offer limited performance in such an environment, since they must either force the source to overcompress its signal or restrict the destination population to those who can receive the full signal. We present an approach for resolving this issue by combining hierarchical source coding techniques, which allow recipients to trade off reception bandwidth for signal quality, and sophisticated routing algorithms that deliver to each destination the maximum possible signal quality. The field of hierarchical coding is briefly surveyed and new multicast routing algorithms are presented. The algorithms are compared in terms of network utilization efficiency, lengths of paths, and the required mechanisms for forwarding packets on the resulting paths.

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Delay and cost performance analysis of the diffie-hellman key exchange protocol in opportunistic mobile networks

NASA Astrophysics Data System (ADS)

Soelistijanto, B.; Muliadi, V.

2018-03-01

Diffie-Hellman (DH) provides an efficient key exchange system by reducing the number of cryptographic keys distributed in the network. In this method, a node broadcasts a single public key to all nodes in the network, and in turn each peer uses this key to establish a shared secret key which then can be utilized to encrypt and decrypt traffic between the peer and the given node. In this paper, we evaluate the key transfer delay and cost performance of DH in opportunistic mobile networks, a specific scenario of MANETs where complete end-to-end paths rarely exist between sources and destinations; consequently, the end-to-end delays in these networks are much greater than typical MANETs. Simulation results, driven by a random node movement model and real human mobility traces, showed that DH outperforms a typical key distribution scheme based on the RSA algorithm in terms of key transfer delay, measured by average key convergence time; however, DH performs as well as the benchmark in terms of key transfer cost, evaluated by total key (copies) forwards.

Cellular automata simulation of topological effects on the dynamics of feed-forward motifs

PubMed Central

Apte, Advait A; Cain, John W; Bonchev, Danail G; Fong, Stephen S

2008-01-01

Background Feed-forward motifs are important functional modules in biological and other complex networks. The functionality of feed-forward motifs and other network motifs is largely dictated by the connectivity of the individual network components. While studies on the dynamics of motifs and networks are usually devoted to the temporal or spatial description of processes, this study focuses on the relationship between the specific architecture and the overall rate of the processes of the feed-forward family of motifs, including double and triple feed-forward loops. The search for the most efficient network architecture could be of particular interest for regulatory or signaling pathways in biology, as well as in computational and communication systems. Results Feed-forward motif dynamics were studied using cellular automata and compared with differential equation modeling. The number of cellular automata iterations needed for a 100% conversion of a substrate into a target product was used as an inverse measure of the transformation rate. Several basic topological patterns were identified that order the specific feed-forward constructions according to the rate of dynamics they enable. At the same number of network nodes and constant other parameters, the bi-parallel and tri-parallel motifs provide higher network efficacy than single feed-forward motifs. Additionally, a topological property of isodynamicity was identified for feed-forward motifs where different network architectures resulted in the same overall rate of the target production. Conclusion It was shown for classes of structural motifs with feed-forward architecture that network topology affects the overall rate of a process in a quantitatively predictable manner. These fundamental results can be used as a basis for simulating larger networks as combinations of smaller network modules with implications on studying synthetic gene circuits, small regulatory systems, and eventually dynamic whole-cell models. PMID:18304325

Brain-machine interface control of a manipulator using small-world neural network and shared control strategy.

PubMed

Li, Ting; Hong, Jun; Zhang, Jinhua; Guo, Feng

2014-03-15

The improvement of the resolution of brain signal and the ability to control external device has been the most important goal in BMI research field. This paper describes a non-invasive brain-actuated manipulator experiment, which defined a paradigm for the motion control of a serial manipulator based on motor imagery and shared control. The techniques of component selection, spatial filtering and classification of motor imagery were involved. Small-world neural network (SWNN) was used to classify five brain states. To verify the effectiveness of the proposed classifier, we replace the SWNN classifier by a radial basis function (RBF) networks neural network, a standard multi-layered feed-forward backpropagation network (SMN) and a multi-SVM classifier, with the same features for the classification. The results also indicate that the proposed classifier achieves a 3.83% improvement over the best results of other classifiers. We proposed a shared control method consisting of two control patterns to expand the control of BMI from the software angle. The job of path building for reaching the 'end' point was designated as an assessment task. We recorded all paths contributed by subjects and picked up relevant parameters as evaluation coefficients. With the assistance of two control patterns and series of machine learning algorithms, the proposed BMI originally achieved the motion control of a manipulator in the whole workspace. According to experimental results, we confirmed the feasibility of the proposed BMI method for 3D motion control of a manipulator using EEG during motor imagery. Copyright © 2013 Elsevier B.V. All rights reserved.

A novel communication mechanism based on node potential multi-path routing

NASA Astrophysics Data System (ADS)

Bu, Youjun; Zhang, Chuanhao; Jiang, YiMing; Zhang, Zhen

2016-10-01

With the network scales rapidly and new network applications emerge frequently, bandwidth supply for today's Internet could not catch up with the rapid increasing requirements. Unfortunately, irrational using of network sources makes things worse. Actual network deploys single-next-hop optimization paths for data transmission, but such "best effort" model leads to the imbalance use of network resources and usually leads to local congestion. On the other hand Multi-path routing can use the aggregation bandwidth of multi paths efficiently and improve the robustness of network, security, load balancing and quality of service. As a result, multi-path has attracted much attention in the routing and switching research fields and many important ideas and solutions have been proposed. This paper focuses on implementing the parallel transmission of multi next-hop data, balancing the network traffic and reducing the congestion. It aimed at exploring the key technologies of the multi-path communication network, which could provide a feasible academic support for subsequent applications of multi-path communication networking. It proposed a novel multi-path algorithm based on node potential in the network. And the algorithm can fully use of the network link resource and effectively balance network link resource utilization.

Quantum Finance

NASA Astrophysics Data System (ADS)

Baaquie, Belal E.

2007-09-01

Foreword; Preface; Acknowledgements; 1. Synopsis; Part I. Fundamental Concepts of Finance: 2. Introduction to finance; 3. Derivative securities; Part II. Systems with Finite Number of Degrees of Freedom: 4. Hamiltonians and stock options; 5. Path integrals and stock options; 6. Stochastic interest rates' Hamiltonians and path integrals; Part III. Quantum Field Theory of Interest Rates Models: 7. Quantum field theory of forward interest rates; 8. Empirical forward interest rates and field theory models; 9. Field theory of Treasury Bonds' derivatives and hedging; 10. Field theory Hamiltonian of forward interest rates; 11. Conclusions; Appendix A: mathematical background; Brief glossary of financial terms; Brief glossary of physics terms; List of main symbols; References; Index.

Development of a sensor coordinated kinematic model for neural network controller training

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1990-01-01

A robotic benchmark problem useful for evaluating alternative neural network controllers is presented. Specifically, it derives two camera models and the kinematic equations of a multiple degree of freedom manipulator whose end effector is under observation. The mapping developed include forward and inverse translations from binocular images to 3-D target position and the inverse kinematics of mapping point positions into manipulator commands in joint space. Implementation is detailed for a three degree of freedom manipulator with one revolute joint at the base and two prismatic joints on the arms. The example is restricted to operate within a unit cube with arm links of 0.6 and 0.4 units respectively. The development is presented in the context of more complex simulations and a logical path for extension of the benchmark to higher degree of freedom manipulators is presented.

A Self-Adaptive Capacitive Compensation Technique for Body Channel Communication.

PubMed

Mao, Jingna; Yang, Huazhong; Lian, Yong; Zhao, Bo

2017-10-01

In wireless body area network, capacitive-coupling body channel communication (CC-BCC) has the potential to attain better energy efficiency over conventional wireless communication schemes. The CC-BCC scheme utilizes the human body as the forward signal transmission medium, reducing the path loss in wireless body-centric communications. However, the backward path is formed by the coupling capacitance between the ground electrodes (GEs) of transmitter (Tx) and receiver (Rx), which increases the path loss and results in a body posture dependent backward impedance. Conventional methods use a fixed inductor to resonate with the backward capacitor to compensate the path loss, while it's not effective in compensating the variable backward impedance induced by the body movements. In this paper, we propose a self-adaptive capacitive compensation (SACC) technique to address such a problem. A backward distance detector is introduced to estimate the distance between two GEs of Tx and Rx, and a backward capacitance model is built to calculate the backward capacitance. The calculated backward capacitance at varying body posture is compensated by a digitally controlled tunable inductor (DCTI). The proposed SACC technique is validated by a prototype CC-BCC system, and measurements are taken on human subjects. The measurement results show that 9dB-16 dB channel enhancement can be achieved at a backward path distance of 1 cm-10 cm.

Two papers on feed-forward networks

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Weigend, Andreas S.

1991-01-01

Connectionist feed-forward networks, trained with back-propagation, can be used both for nonlinear regression and for (discrete one-of-C) classification, depending on the form of training. This report contains two papers on feed-forward networks. The papers can be read independently. They are intended for the theoretically-aware practitioner or algorithm-designer; however, they also contain a review and comparison of several learning theories so they provide a perspective for the theoretician. The first paper works through Bayesian methods to complement back-propagation in the training of feed-forward networks. The second paper addresses a problem raised by the first: how to efficiently calculate second derivatives on feed-forward networks.

Apply network coding for H.264/SVC multicasting

NASA Astrophysics Data System (ADS)

Wang, Hui; Kuo, C.-C. Jay

2008-08-01

In a packet erasure network environment, video streaming benefits from error control in two ways to achieve graceful degradation. The first approach is application-level (or the link-level) forward error-correction (FEC) to provide erasure protection. The second error control approach is error concealment at the decoder end to compensate lost packets. A large amount of research work has been done in the above two areas. More recently, network coding (NC) techniques have been proposed for efficient data multicast over networks. It was shown in our previous work that multicast video streaming benefits from NC for its throughput improvement. An algebraic model is given to analyze the performance in this work. By exploiting the linear combination of video packets along nodes in a network and the SVC video format, the system achieves path diversity automatically and enables efficient video delivery to heterogeneous receivers in packet erasure channels. The application of network coding can protect video packets against the erasure network environment. However, the rank defficiency problem of random linear network coding makes the error concealment inefficiently. It is shown by computer simulation that the proposed NC video multicast scheme enables heterogenous receiving according to their capacity constraints. But it needs special designing to improve the video transmission performance when applying network coding.

Hybrid Packet-Pheromone-Based Probabilistic Routing for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Kashkouli Nejad, Keyvan; Shawish, Ahmed; Jiang, Xiaohong; Horiguchi, Susumu

Ad-Hoc networks are collections of mobile nodes communicating using wireless media without any fixed infrastructure. Minimal configuration and quick deployment make Ad-Hoc networks suitable for emergency situations like natural disasters or military conflicts. The current Ad-Hoc networks can only support either high mobility or high transmission rate at a time because they employ static approaches in their routing schemes. However, due to the continuous expansion of the Ad-Hoc network size, node-mobility and transmission rate, the development of new adaptive and dynamic routing schemes has become crucial. In this paper we propose a new routing scheme to support high transmission rates and high node-mobility simultaneously in a big Ad-Hoc network, by combining a new proposed packet-pheromone-based approach with the Hint Based Probabilistic Protocol (HBPP) for congestion avoidance with dynamic path selection in packet forwarding process. Because of using the available feedback information, the proposed algorithm does not introduce any additional overhead. The extensive simulation-based analysis conducted in this paper indicates that the proposed algorithm offers small packet-latency and achieves a significantly higher delivery probability in comparison with the available Hint-Based Probabilistic Protocol (HBPP).

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs.

PubMed

Aslam, Muhammad; Hu, Xiaopeng; Wang, Fan

2017-12-13

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR's routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols.

SACFIR: SDN-Based Application-Aware Centralized Adaptive Flow Iterative Reconfiguring Routing Protocol for WSNs

PubMed Central

Hu, Xiaopeng; Wang, Fan

2017-01-01

Smart reconfiguration of a dynamic networking environment is offered by the central control of Software-Defined Networking (SDN). Centralized SDN-based management architectures are capable of retrieving global topology intelligence and decoupling the forwarding plane from the control plane. Routing protocols developed for conventional Wireless Sensor Networks (WSNs) utilize limited iterative reconfiguration methods to optimize environmental reporting. However, the challenging networking scenarios of WSNs involve a performance overhead due to constant periodic iterative reconfigurations. In this paper, we propose the SDN-based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) routing protocol with the centralized SDN iterative solver controller to maintain the load-balancing between flow reconfigurations and flow allocation cost. The proposed SACFIR’s routing protocol offers a unique iterative path-selection algorithm, which initially computes suitable clustering based on residual resources at the control layer and then implements application-aware threshold-based multi-hop report transmissions on the forwarding plane. The operation of the SACFIR algorithm is centrally supervised by the SDN controller residing at the Base Station (BS). This paper extends SACFIR to SDN-based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR) to establish both proactive and reactive reporting. The SAMCFIR transmission phase enables sensor nodes to trigger direct transmissions for main-value reports, while in the case of SACFIR, all reports follow computed routes. Our SDN-enabled proposed models adjust the reconfiguration period according to the traffic burden on sensor nodes, which results in heterogeneity awareness, load-balancing and application-specific reconfigurations of WSNs. Extensive experimental simulation-based results show that SACFIR and SAMCFIR yield the maximum scalability, network lifetime and stability period when compared to existing routing protocols. PMID:29236031

Circuity analyses of HSR network and high-speed train paths in China

PubMed Central

Zhao, Shuo; Huang, Jie; Shan, Xinghua

2017-01-01

Circuity, defined as the ratio of the shortest network distance to the Euclidean distance between one origin–destination (O-D) pair, can be adopted as a helpful evaluation method of indirect degrees of train paths. In this paper, the maximum circuity of the paths of operated trains is set to be the threshold value of the circuity of high-speed train paths. For the shortest paths of any node pairs, if their circuity is not higher than the threshold value, the paths can be regarded as the reasonable paths. With the consideration of a certain relative or absolute error, we cluster the reasonable paths on the basis of their inclusion relationship and the center path of each class represents a passenger transit corridor. We take the high-speed rail (HSR) network in China at the end of 2014 as an example, and obtain 51 passenger transit corridors, which are alternative sets of train paths. Furthermore, we analyze the circuity distribution of paths of all node pairs in the network. We find that the high circuity of train paths can be decreased with the construction of a high-speed railway line, which indicates that the structure of the HSR network in China tends to be more complete and the HSR network can make the Chinese railway network more efficient. PMID:28945757

Device for adapting continuously variable transmissions to infinitely variable transmissions with forward-neutral-reverse capabilities

DOEpatents

Wilkes, Donald F.; Purvis, James W.; Miller, A. Keith

1997-01-01

An infinitely variable transmission is capable of operating between a maximum speed in one direction and a minimum speed in an opposite direction, including a zero output angular velocity, while being supplied with energy at a constant angular velocity. Input energy is divided between a first power path carrying an orbital set of elements and a second path that includes a variable speed adjustment mechanism. The second power path also connects with the orbital set of elements in such a way as to vary the rate of angular rotation thereof. The combined effects of power from the first and second power paths are combined and delivered to an output element by the orbital element set. The transmission can be designed to operate over a preselected ratio of forward to reverse output speeds.

Kinematics of the human mandible for different head postures.

PubMed

Visscher, C M; Huddleston Slater, J J; Lobbezoo, F; Naeije, M

2000-04-01

The influence of head posture on movement paths of the incisal point (IP) and of the mandibular condyles during free open-close movements was studied. Ten persons, without craniomandibular or cervical spine disorders, participated in the study. Open close mandibular movements were recorded with the head in five postures, viz., natural head posture, forward head posture, military posture, and lateroflexion to the right and to the left side, using the Oral Kinesiologic Analysis System (OKAS-3D). This study showed that in a military head posture, the opening movement path of the incisal point is shifted anteriorly relative to the path in a natural head posture. In a forward head posture, the movement path is shifted posteriorly whereas during lateroflexion, it deviates to the side the head has moved to. Moreover, the intra-articular distance in the temporomandibular joint during closing is smaller with the head in military posture and greater in forward head posture, as compared to the natural head posture. During lateroflexion, the intra-articular distance on the ipsilateral side is smaller. The influence of head posture upon the kinematics of the mandible is probably a manifestation of differences in mandibular loading in the different head postures.

Master equations and the theory of stochastic path integrals.

PubMed

Weber, Markus F; Frey, Erwin

2017-04-01

This review provides a pedagogic and self-contained introduction to master equations and to their representation by path integrals. Since the 1930s, master equations have served as a fundamental tool to understand the role of fluctuations in complex biological, chemical, and physical systems. Despite their simple appearance, analyses of master equations most often rely on low-noise approximations such as the Kramers-Moyal or the system size expansion, or require ad-hoc closure schemes for the derivation of low-order moment equations. We focus on numerical and analytical methods going beyond the low-noise limit and provide a unified framework for the study of master equations. After deriving the forward and backward master equations from the Chapman-Kolmogorov equation, we show how the two master equations can be cast into either of four linear partial differential equations (PDEs). Three of these PDEs are discussed in detail. The first PDE governs the time evolution of a generalized probability generating function whose basis depends on the stochastic process under consideration. Spectral methods, WKB approximations, and a variational approach have been proposed for the analysis of the PDE. The second PDE is novel and is obeyed by a distribution that is marginalized over an initial state. It proves useful for the computation of mean extinction times. The third PDE describes the time evolution of a 'generating functional', which generalizes the so-called Poisson representation. Subsequently, the solutions of the PDEs are expressed in terms of two path integrals: a 'forward' and a 'backward' path integral. Combined with inverse transformations, one obtains two distinct path integral representations of the conditional probability distribution solving the master equations. We exemplify both path integrals in analysing elementary chemical reactions. Moreover, we show how a well-known path integral representation of averaged observables can be recovered from them. Upon expanding the forward and the backward path integrals around stationary paths, we then discuss and extend a recent method for the computation of rare event probabilities. Besides, we also derive path integral representations for processes with continuous state spaces whose forward and backward master equations admit Kramers-Moyal expansions. A truncation of the backward expansion at the level of a diffusion approximation recovers a classic path integral representation of the (backward) Fokker-Planck equation. One can rewrite this path integral in terms of an Onsager-Machlup function and, for purely diffusive Brownian motion, it simplifies to the path integral of Wiener. To make this review accessible to a broad community, we have used the language of probability theory rather than quantum (field) theory and do not assume any knowledge of the latter. The probabilistic structures underpinning various technical concepts, such as coherent states, the Doi-shift, and normal-ordered observables, are thereby made explicit.

Developing Generic Image Search Strategies for Large Astronomical Data Sets and Archives using Convolutional Neural Networks and Transfer Learning

NASA Astrophysics Data System (ADS)

Peek, Joshua E. G.; Hargis, Jonathan R.; Jones, Craig K.

2018-01-01

Astronomical instruments produce petabytes of images every year, vastly more than can be inspected by a member of the astronomical community in search of a specific population of structures. Fortunately, the sky is mostly black and source extraction algorithms have been developed to provide searchable catalogs of unconfused sources like stars and galaxies. These tools often fail for studies of more diffuse structures like the interstellar medium and unresolved stellar structures in nearby galaxies, leaving astronomers interested in observations of photodissociation regions, stellar clusters, diffuse interstellar clouds without the crucial ability to search. In this work we present a new path forward for finding structures in large data sets similar to an input structure using convolutional neural networks, transfer learning, and machine learning clustering techniques. We show applications to archival data in the Mikulski Archive for Space Telescopes (MAST).

Optimal forwarding ratio on dynamical networks with heterogeneous mobility

NASA Astrophysics Data System (ADS)

Gan, Yu; Tang, Ming; Yang, Hanxin

2013-05-01

Since the discovery of non-Poisson statistics of human mobility trajectories, more attention has been paid to understand the role of these patterns in different dynamics. In this study, we first introduce the heterogeneous mobility of mobile agents into dynamical networks, and then investigate packet forwarding strategy on the heterogeneous dynamical networks. We find that the faster speed and the higher proportion of high-speed agents can enhance the network throughput and reduce the mean traveling time in random forwarding. A hierarchical structure in the dependence of high-speed is observed: the network throughput remains unchanged at small and large high-speed value. It is also interesting to find that a slightly preferential forwarding to high-speed agents can maximize the network capacity. Through theoretical analysis and numerical simulations, we show that the optimal forwarding ratio stems from the local structural heterogeneity of low-speed agents.

Six paths for the future of social epidemiology.

PubMed

Galea, Sandro; Link, Bruce G

2013-09-15

Social epidemiology is now an accepted part of the academic intellectual landscape. However, in many ways, social epidemiology also runs the risk of losing the identity that distinguished it as a field during its emergence. In the present article, we scan the strengths of social epidemiology to imagine paths forward that will make the field distinct and useful to the understanding of population health in future. We suggest 6 paths to such a future, each emerging from promising research trends in the field in which social epidemiologists can, and should, lead in coming years. Each of these paths contributes to the formation of distinct capacities that social epidemiologists can claim and use to elaborate or fill in gaps in the already strong history of social epidemiology. They present an opportunity for the field to build on its strengths and move forward while leading in new and critical areas in population health.

Six Paths for the Future of Social Epidemiology

PubMed Central

Galea, Sandro; Link, Bruce G.

2013-01-01

Social epidemiology is now an accepted part of the academic intellectual landscape. However, in many ways, social epidemiology also runs the risk of losing the identity that distinguished it as a field during its emergence. In the present article, we scan the strengths of social epidemiology to imagine paths forward that will make the field distinct and useful to the understanding of population health in future. We suggest 6 paths to such a future, each emerging from promising research trends in the field in which social epidemiologists can, and should, lead in coming years. Each of these paths contributes to the formation of distinct capacities that social epidemiologists can claim and use to elaborate or fill in gaps in the already strong history of social epidemiology. They present an opportunity for the field to build on its strengths and move forward while leading in new and critical areas in population health. PMID:24008899

An Energy Scaled and Expanded Vector-Based Forwarding Scheme for Industrial Underwater Acoustic Sensor Networks with Sink Mobility.

PubMed

Wadud, Zahid; Hussain, Sajjad; Javaid, Nadeem; Bouk, Safdar Hussain; Alrajeh, Nabil; Alabed, Mohamad Souheil; Guizani, Nadra

2017-09-30

Industrial Underwater Acoustic Sensor Networks (IUASNs) come with intrinsic challenges like long propagation delay, small bandwidth, large energy consumption, three-dimensional deployment, and high deployment and battery replacement cost. Any routing strategy proposed for IUASN must take into account these constraints. The vector based forwarding schemes in literature forward data packets to sink using holding time and location information of the sender, forwarder, and sink nodes. Holding time suppresses data broadcasts; however, it fails to keep energy and delay fairness in the network. To achieve this, we propose an Energy Scaled and Expanded Vector-Based Forwarding (ESEVBF) scheme. ESEVBF uses the residual energy of the node to scale and vector pipeline distance ratio to expand the holding time. Resulting scaled and expanded holding time of all forwarding nodes has a significant difference to avoid multiple forwarding, which reduces energy consumption and energy balancing in the network. If a node has a minimum holding time among its neighbors, it shrinks the holding time and quickly forwards the data packets upstream. The performance of ESEVBF is analyzed through in network scenario with and without node mobility to ensure its effectiveness. Simulation results show that ESEVBF has low energy consumption, reduces forwarded data copies, and less end-to-end delay.

Red Hat Enterprise Virtualization - KVM-based infrastructure services at BNL

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

Cortijo, D.

2011-06-14

Over the past 18 months, BNL has moved a large percentage of its Linux-based servers and services into a Red Hat Enterprise Virtualization (RHEV) environment. This presentation will address our approach to virtualization, critical decision points, and a discussion of our implementation. Specific topics will include an overview of hardware and software requirements, networking, and storage; discussion of the decision of Red Hat solution over competing products (VMWare, Xen, etc); details on some of the features of RHEV - both current and on their roadmap; Review of performance and reliability gains since deployment completion; path forward for RHEV at BNLmore » and caveats and potential problems.« less

Identification of limit cycles in multi-nonlinearity, multiple path systems

NASA Technical Reports Server (NTRS)

Mitchell, J. R.; Barron, O. L.

1979-01-01

A method of analysis which identifies limit cycles in autonomous systems with multiple nonlinearities and multiple forward paths is presented. The FORTRAN code for implementing the Harmonic Balance Algorithm is reported. The FORTRAN code is used to identify limit cycles in multiple path and nonlinearity systems while retaining the effects of several harmonic components.

An improved global dynamic routing strategy for scale-free network with tunable clustering

NASA Astrophysics Data System (ADS)

Sun, Lina; Huang, Ning; Zhang, Yue; Bai, Yannan

2016-08-01

An efficient routing strategy can deliver packets quickly to improve the network capacity. Node congestion and transmission path length are inevitable real-time factors for a good routing strategy. Existing dynamic global routing strategies only consider the congestion of neighbor nodes and the shortest path, which ignores other key nodes’ congestion on the path. With the development of detection methods and techniques, global traffic information is readily available and important for the routing choice. Reasonable use of this information can effectively improve the network routing. So, an improved global dynamic routing strategy is proposed, which considers the congestion of all nodes on the shortest path and incorporates the waiting time of the most congested node into the path. We investigate the effectiveness of the proposed routing for scale-free network with different clustering coefficients. The shortest path routing strategy and the traffic awareness routing strategy only considering the waiting time of neighbor node are analyzed comparatively. Simulation results show that network capacity is greatly enhanced compared with the shortest path; congestion state increase is relatively slow compared with the traffic awareness routing strategy. Clustering coefficient increase will not only reduce the network throughput, but also result in transmission average path length increase for scale-free network with tunable clustering. The proposed routing is favorable to ease network congestion and network routing strategy design.

Entropy-based link prediction in weighted networks

NASA Astrophysics Data System (ADS)

Xu, Zhongqi; Pu, Cunlai; Ramiz Sharafat, Rajput; Li, Lunbo; Yang, Jian

2017-01-01

Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks. In the previous work (Xu et al, 2016 \\cite{xu2016}), we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight, and propose a weighted prediction index based on the contributions of paths, namely Weighted Path Entropy (WPE), to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three typical weighted indices.

A collaborative network middleware project by Lambda Station, TeraPaths, and Phoebus

NASA Astrophysics Data System (ADS)

Bobyshev, A.; Bradley, S.; Crawford, M.; DeMar, P.; Katramatos, D.; Shroff, K.; Swany, M.; Yu, D.

2010-04-01

The TeraPaths, Lambda Station, and Phoebus projects, funded by the US Department of Energy, have successfully developed network middleware services that establish on-demand and manage true end-to-end, Quality-of-Service (QoS) aware, virtual network paths across multiple administrative network domains, select network paths and gracefully reroute traffic over these dynamic paths, and streamline traffic between packet and circuit networks using transparent gateways. These services improve network QoS and performance for applications, playing a critical role in the effective use of emerging dynamic circuit network services. They provide interfaces to applications, such as dCache SRM, translate network service requests into network device configurations, and coordinate with each other to setup up end-to-end network paths. The End Site Control Plane Subsystem (ESCPS) builds upon the success of the three projects by combining their individual capabilities into the next generation of network middleware. ESCPS addresses challenges such as cross-domain control plane signalling and interoperability, authentication and authorization in a Grid environment, topology discovery, and dynamic status tracking. The new network middleware will take full advantage of the perfSONAR monitoring infrastructure and the Inter-Domain Control plane efforts and will be deployed and fully vetted in the Large Hadron Collider data movement environment.

A Novel Dual Separate Paths (DSP) Algorithm Providing Fault-Tolerant Communication for Wireless Sensor Networks.

PubMed

Tien, Nguyen Xuan; Kim, Semog; Rhee, Jong Myung; Park, Sang Yoon

2017-07-25

Fault tolerance has long been a major concern for sensor communications in fault-tolerant cyber physical systems (CPSs). Network failure problems often occur in wireless sensor networks (WSNs) due to various factors such as the insufficient power of sensor nodes, the dislocation of sensor nodes, the unstable state of wireless links, and unpredictable environmental interference. Fault tolerance is thus one of the key requirements for data communications in WSN applications. This paper proposes a novel path redundancy-based algorithm, called dual separate paths (DSP), that provides fault-tolerant communication with the improvement of the network traffic performance for WSN applications, such as fault-tolerant CPSs. The proposed DSP algorithm establishes two separate paths between a source and a destination in a network based on the network topology information. These paths are node-disjoint paths and have optimal path distances. Unicast frames are delivered from the source to the destination in the network through the dual paths, providing fault-tolerant communication and reducing redundant unicast traffic for the network. The DSP algorithm can be applied to wired and wireless networks, such as WSNs, to provide seamless fault-tolerant communication for mission-critical and life-critical applications such as fault-tolerant CPSs. The analyzed and simulated results show that the DSP-based approach not only provides fault-tolerant communication, but also improves network traffic performance. For the case study in this paper, when the DSP algorithm was applied to high-availability seamless redundancy (HSR) networks, the proposed DSP-based approach reduced the network traffic by 80% to 88% compared with the standard HSR protocol, thus improving network traffic performance.

E-Center: A Collaborative Platform for Wide Area Network Users

NASA Astrophysics Data System (ADS)

Grigoriev, M.; DeMar, P.; Tierney, B.; Lake, A.; Metzger, J.; Frey, M.; Calyam, P.

2012-12-01

The E-Center is a social collaborative web-based platform for assisting network users in understanding network conditions across network paths of interest to them. It is designed to give a user the necessary tools to isolate, identify, and resolve network performance-related problems. E-Center provides network path information on a link-by-link level, as well as from an end-to-end perspective. In addition to providing current and recent network path data, E-Center is intended to provide a social media environment for them to share issues, ideas, concerns, and problems. The product has a modular design that accommodates integration of other network services that make use of the same network path and performance data.

Quantitative impact of small angle forward scatter on whole blood oximetry using a Beer-Lambert absorbance model.

PubMed

LeBlanc, Serge Emile; Atanya, Monica; Burns, Kevin; Munger, Rejean

2011-04-21

It is well known that red blood cell scattering has an impact on whole blood oximetry as well as in vivo retinal oxygen saturation measurements. The goal of this study was to quantify the impact of small angle forward scatter on whole blood oximetry for scattering angles found in retinal oximetry light paths. Transmittance spectra of whole blood were measured in two different experimental setups: one that included small angle scatter in the transmitted signal and one that measured the transmitted signal only, at absorbance path lengths of 25, 50, 100, 250 and 500 µm. Oxygen saturation was determined by multiple linear regression in the 520-600 nm wavelength range and compared between path lengths and experimental setups. Mean calculated oxygen saturation differences between setups were greater than 10% at every absorbance path length. The deviations to the Beer-Lambert absorbance model had different spectral dependences between experimental setups, with the highest deviations found in the 520-540 nm range when scatter was added to the transmitted signal. These results are consistent with other models of forward scatter that predict different spectral dependences of the red blood cell scattering cross-section and haemoglobin extinction coefficients in this wavelength range.

Distributed multiple path routing in complex networks

NASA Astrophysics Data System (ADS)

Chen, Guang; Wang, San-Xiu; Wu, Ling-Wei; Mei, Pan; Yang, Xu-Hua; Wen, Guang-Hui

2016-12-01

Routing in complex transmission networks is an important problem that has garnered extensive research interest in the recent years. In this paper, we propose a novel routing strategy called the distributed multiple path (DMP) routing strategy. For each of the O-D node pairs in a given network, the DMP routing strategy computes and stores multiple short-length paths that overlap less with each other in advance. And during the transmission stage, it rapidly selects an actual routing path which provides low transmission cost from the pre-computed paths for each transmission task, according to the real-time network transmission status information. Computer simulation results obtained for the lattice, ER random, and scale-free networks indicate that the strategy can significantly improve the anti-congestion ability of transmission networks, as well as provide favorable routing robustness against partial network failures.

A Stochastic Sprint in the Vague Direction of Data Science: Perspectives from a Graduate Student and Aspiring Data Scientist.

NASA Astrophysics Data System (ADS)

Barberie, S. R.

2015-12-01

Since data science does not exist as a stand-alone discipline within major universities, learning data science, or even learning that data science exists is, for an aspiring researcher at the graduate or undergraduate level, something that only happens by accident. Here I present my own series of accidents that transformed me from a somewhat aimless graduate student into an aspiring data scientist and the challenges that that aspiration has created in fitting into traditional academic programs and finding a coherent path forward. I also present my current conundrum: with the clear intention of pursuing data science but an academic background in other subjects, where do I go from here? Do I start my education over, pursue professional certification courses and bootcamp programs, or engage in not-very-marketable self study? This career chasm creates a strange environment for aspiring data scientists where we have a destination, but not a clear road to get there. I also discuss how joining a data focused interest group called The Federation of Earth Science Information Partners (ESIP) bridged some of the gap left by Academia in allowing me to network and collaborate with real data scientists from a variety of backgrounds. Organizations like this may someday play an important role in helping aspiring data scientists find their place, although for the moment many gaps and obstacles still remain, and the path forward is far from clear.

Differential equations driven by rough paths with jumps

NASA Astrophysics Data System (ADS)

Friz, Peter K.; Zhang, Huilin

2018-05-01

We develop the rough path counterpart of Itô stochastic integration and differential equations driven by general semimartingales. This significantly enlarges the classes of (Itô/forward) stochastic differential equations treatable with pathwise methods. A number of applications are discussed.

Aircraft automatic-flight-control system with inversion of the model in the feed-forward path using a Newton-Raphson technique for the inversion

NASA Technical Reports Server (NTRS)

Smith, G. A.; Meyer, G.; Nordstrom, M.

1986-01-01

A new automatic flight control system concept suitable for aircraft with highly nonlinear aerodynamic and propulsion characteristics and which must operate over a wide flight envelope was investigated. This exact model follower inverts a complete nonlinear model of the aircraft as part of the feed-forward path. The inversion is accomplished by a Newton-Raphson trim of the model at each digital computer cycle time of 0.05 seconds. The combination of the inverse model and the actual aircraft in the feed-forward path alloys the translational and rotational regulators in the feedback path to be easily designed by linear methods. An explanation of the model inversion procedure is presented. An extensive set of simulation data for essentially the full flight envelope for a vertical attitude takeoff and landing aircraft (VATOL) is presented. These data demonstrate the successful, smooth, and precise control that can be achieved with this concept. The trajectory includes conventional flight from 200 to 900 ft/sec with path accelerations and decelerations, altitude changes of over 6000 ft and 2g and 3g turns. Vertical attitude maneuvering as a tail sitter along all axes is demonstrated. A transition trajectory from 200 ft/sec in conventional flight to stationary hover in the vertical attitude includes satisfactory operation through lift-cure slope reversal as attitude goes from horizontal to vertical at constant altitude. A vertical attitude takeoff from stationary hover to conventional flight is also demonstrated.

Path Network Recovery Using Remote Sensing Data and Geospatial-Temporal Semantic Graphs

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

William C. McLendon III; Brost, Randy C.

Remote sensing systems produce large volumes of high-resolution images that are difficult to search. The GeoGraphy (pronounced Geo-Graph-y) framework [2, 20] encodes remote sensing imagery into a geospatial-temporal semantic graph representation to enable high level semantic searches to be performed. Typically scene objects such as buildings and trees tend to be shaped like blocks with few holes, but other shapes generated from path networks tend to have a large number of holes and can span a large geographic region due to their connectedness. For example, we have a dataset covering the city of Philadelphia in which there is a singlemore » road network node spanning a 6 mile x 8 mile region. Even a simple question such as "find two houses near the same street" might give unexpected results. More generally, nodes arising from networks of paths (roads, sidewalks, trails, etc.) require additional processing to make them useful for searches in GeoGraphy. We have assigned the term Path Network Recovery to this process. Path Network Recovery is a three-step process involving (1) partitioning the network node into segments, (2) repairing broken path segments interrupted by occlusions or sensor noise, and (3) adding path-aware search semantics into GeoQuestions. This report covers the path network recovery process, how it is used, and some example use cases of the current capabilities.« less

Single-hidden-layer feed-forward quantum neural network based on Grover learning.

PubMed

Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

2013-09-01

In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Function and activity classification in network traffic data: existing methods, their weaknesses, and a path forward

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy

2016-05-01

The cyber spaces are increasingly becoming the battlefields between friendly and adversary forces, with normal users caught in the middle. Accordingly, planners of enterprise defensive policies and offensive cyber missions alike have an essential goal to minimize the impact of their own actions and adversaries' attacks on normal operations of the commercial and government networks. To do this, the cyber analysis need accurate "cyber battle maps", where the functions, roles, and activities of individual and groups of devices and users are accurately identified. Most of the research in cyber exploitation has focused on the identification of attacks, attackers, and their devices. Many tools exist for device profiling, malware identification, user attribution, and attack analysis. However, most of the tools are intrusive, sensitive to data obfuscation, or provide anomaly flagging and not able to correctly classify the semantics and causes of network activities. In this paper, we review existing solutions that can identify functional and social roles of entities in cyberspace, discuss their weaknesses, and propose an approach for developing functional and social layers of cyber battle maps.

Two betweenness centrality measures based on Randomized Shortest Paths

PubMed Central

Kivimäki, Ilkka; Lebichot, Bertrand; Saramäki, Jari; Saerens, Marco

2016-01-01

This paper introduces two new closely related betweenness centrality measures based on the Randomized Shortest Paths (RSP) framework, which fill a gap between traditional network centrality measures based on shortest paths and more recent methods considering random walks or current flows. The framework defines Boltzmann probability distributions over paths of the network which focus on the shortest paths, but also take into account longer paths depending on an inverse temperature parameter. RSP’s have previously proven to be useful in defining distance measures on networks. In this work we study their utility in quantifying the importance of the nodes of a network. The proposed RSP betweenness centralities combine, in an optimal way, the ideas of using the shortest and purely random paths for analysing the roles of network nodes, avoiding issues involving these two paradigms. We present the derivations of these measures and how they can be computed in an efficient way. In addition, we show with real world examples the potential of the RSP betweenness centralities in identifying interesting nodes of a network that more traditional methods might fail to notice. PMID:26838176

A high-speed tunable beam splitter for feed-forward photonic quantum information processing.

PubMed

Ma, Xiao-Song; Zotter, Stefan; Tetik, Nuray; Qarry, Angie; Jennewein, Thomas; Zeilinger, Anton

2011-11-07

We realize quantum gates for path qubits with a high-speed, polarization-independent and tunable beam splitter. Two electro-optical modulators act in a Mach-Zehnder interferometer as high-speed phase shifters and rapidly tune its splitting ratio. We test its performance with heralded single photons, observing a polarization-independent interference contrast above 95%. The switching time is about 5.6 ns, and a maximal repetition rate is 2.5 MHz. We demonstrate tunable feed-forward operations of a single-qubit gate of path-encoded qubits and a two-qubit gate via measurement-induced interaction between two photons.

The roadmap for estimation of cell-type-specific neuronal activity from non-invasive measurements

PubMed Central

Uhlirova, Hana; Kılıç, Kıvılcım; Tian, Peifang; Sakadžić, Sava; Thunemann, Martin; Desjardins, Michèle; Saisan, Payam A.; Nizar, Krystal; Yaseen, Mohammad A.; Hagler, Donald J.; Vandenberghe, Matthieu; Djurovic, Srdjan; Andreassen, Ole A.; Silva, Gabriel A.; Masliah, Eliezer; Vinogradov, Sergei; Buxton, Richard B.; Einevoll, Gaute T.; Boas, David A.; Dale, Anders M.; Devor, Anna

2016-01-01

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use non-invasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from non-invasive signals in humans. On the essential path towards this goal is the development of a detailed ‘bottom-up’ forward model bridging neuronal activity at the level of cell-type-specific populations to non-invasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O2 (measurable with quantitative functional Magnetic Resonance Imaging), and electrical currents/potentials (measurable with magneto/electroencephalography). This forward model would then provide the ‘ground truth’ for the development of new tools for tackling the inverse problem—estimation of neuronal activity from multimodal non-invasive imaging data. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574309

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs

PubMed Central

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-01-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network. PMID:28763014

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

PubMed

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-08-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

Structural factoring approach for analyzing stochastic networks

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.; Shier, Douglas R.

1991-01-01

The problem of finding the distribution of the shortest path length through a stochastic network is investigated. A general algorithm for determining the exact distribution of the shortest path length is developed based on the concept of conditional factoring, in which a directed, stochastic network is decomposed into an equivalent set of smaller, generally less complex subnetworks. Several network constructs are identified and exploited to reduce significantly the computational effort required to solve a network problem relative to complete enumeration. This algorithm can be applied to two important classes of stochastic path problems: determining the critical path distribution for acyclic networks and the exact two-terminal reliability for probabilistic networks. Computational experience with the algorithm was encouraging and allowed the exact solution of networks that have been previously analyzed only by approximation techniques.

Supporting Persistent and Networked Special Operations Forces (SOF) Operations: Insights From Forward-Deployed SOF Personnel

DTIC Science & Technology

2017-01-01

network of people and technology to provide sustained, persistent, SOF-specific capabilities and capacities and increased persistent forward- deployed...phase 1 operational activities of forward-deployed SOF personnel and the factors that critically influence the outcomes of their tactical operations can...chronized network of people and technology that provides sustained, persistent, SOF- specific capabilities and capacities and increased persistent

Limited-path-length entanglement percolation in quantum complex networks

NASA Astrophysics Data System (ADS)

Cuquet, Martí; Calsamiglia, John

2011-03-01

We study entanglement distribution in quantum complex networks where nodes are connected by bipartite entangled states. These networks are characterized by a complex structure, which dramatically affects how information is transmitted through them. For pure quantum state links, quantum networks exhibit a remarkable feature absent in classical networks: it is possible to effectively rewire the network by performing local operations on the nodes. We propose a family of such quantum operations that decrease the entanglement percolation threshold of the network and increase the size of the giant connected component. We provide analytic results for complex networks with an arbitrary (uncorrelated) degree distribution. These results are in good agreement with numerical simulations, which also show enhancement in correlated and real-world networks. The proposed quantum preprocessing strategies are not robust in the presence of noise. However, even when the links consist of (noisy) mixed-state links, one can send quantum information through a connecting path with a fidelity that decreases with the path length. In this noisy scenario, complex networks offer a clear advantage over regular lattices, namely, the fact that two arbitrary nodes can be connected through a relatively small number of steps, known as the small-world effect. We calculate the probability that two arbitrary nodes in the network can successfully communicate with a fidelity above a given threshold. This amounts to working out the classical problem of percolation with a limited path length. We find that this probability can be significant even for paths limited to few connections and that the results for standard (unlimited) percolation are soon recovered if the path length exceeds by a finite amount the average path length, which in complex networks generally scales logarithmically with the size of the network.

Morphology suggests noseleaf and pinnae cooperate to enhance bat echolocation.

PubMed

Kuc, Roman

2010-11-01

A protruding noseleaf and concave pinna structures suggest that some bats may use these to enhance their echolocation capabilities. This paper considers two possible mechanisms that each exploit the combination of direct and delayed acoustic paths to achieve more complex emission or sensitivity echolocation patterns. The first is an emission mechanism, in which the protruding noseleaf vibrates to emit sound in both the forward and backward directions, and pinna structures reflect the backward emission to enhance the forward beam. The second is a reception mechanism, which has a direct echo path to the ear canal and a delayed path involving pinna structures reflecting onto the noseleaf and then into the ear canal. A model using Davis' Round-eared Bat illustrates that such direct and delayed acoustic paths provide target elevation cues. The model demonstrates the delayed pinna component can increase the on-axis emission strength, narrow the beam width, and sculpt frequency-dependent beam patterns useful for echolocation.

Comparison of forward (ear-canal) and reverse (round-window) sound stimulation of the cochlea.

PubMed

Stieger, Christof; Rosowski, John J; Nakajima, Hideko Heidi

2013-07-01

The cochlea is normally driven with "forward" stimulation, in which sound is introduced to the ear canal. Alternatively, the cochlea can be stimulated at the round window (RW) using an actuator. During RW "reverse" stimulation, the acoustic flow starting at the RW does not necessarily take the same path as during forward stimulation. To understand the differences between forward and reverse stimulation, we measured ear-canal pressure, stapes velocity, RW velocity, and intracochlear pressures in scala vestibuli (SV) and scala tympani (ST) of fresh human temporal bones. During forward stimulation, the cochlear drive (differential pressure across the partition) results from the large difference in magnitude between the pressures of SV and ST, which occurs due to the high compliance of the RW. During reverse stimulation, the relatively high impedance of the middle ear causes the pressures of SV and ST to have similar magnitudes, and the differential pressure results primarily from the difference in phase of the pressures. Furthermore, the sound path differs between forward and reverse stimulation, such that motion through a third window is more significant during reverse stimulation. Additionally, we determined that although stapes velocity is a good estimate of cochlear drive during forward stimulation, it is not a good measure during reverse stimulation. This article is part of a special issue entitled "MEMRO 2012". Copyright © 2012 Elsevier B.V. All rights reserved.

Dealing with Liars: Misbehavior Identification via Rényi-Ulam Games

NASA Astrophysics Data System (ADS)

Kozma, William; Lazos, Loukas

We address the problem of identifying misbehaving nodes that refuse to forward packets in wireless multi-hop networks. We map the process of locating the misbehaving nodes to the classic Rényi-Ulam game of 20 questions. Compared to previous methods, our mapping allows the evaluation of node behavior on a per-packet basis, without the need for energy-expensive overhearing techniques or intensive acknowledgment schemes. Furthermore, it copes with colluding adversaries that coordinate their behavioral patterns to avoid identification and frame honest nodes. We show via simulations that our algorithms reduce the communication overhead for identifying misbehaving nodes by at least one order of magnitude compared to other methods, while increasing the identification delay logarithmically with the path size.

Innovation Analysis Approach to Design Parameters of High Speed Train Carriage and Their Intrinsic Complexity Relationships

NASA Astrophysics Data System (ADS)

Xiao, Shou-Ne; Wang, Ming-Meng; Hu, Guang-Zhong; Yang, Guang-Wu

2017-09-01

In view of the problem that it's difficult to accurately grasp the influence range and transmission path of the vehicle top design requirements on the underlying design parameters. Applying directed-weighted complex network to product parameter model is an important method that can clarify the relationships between product parameters and establish the top-down design of a product. The relationships of the product parameters of each node are calculated via a simple path searching algorithm, and the main design parameters are extracted by analysis and comparison. A uniform definition of the index formula for out-in degree can be provided based on the analysis of out-in-degree width and depth and control strength of train carriage body parameters. Vehicle gauge, axle load, crosswind and other parameters with higher values of the out-degree index are the most important boundary conditions; the most considerable performance indices are the parameters that have higher values of the out-in-degree index including torsional stiffness, maximum testing speed, service life of the vehicle, and so on; the main design parameters contain train carriage body weight, train weight per extended metre, train height and other parameters with higher values of the in-degree index. The network not only provides theoretical guidance for exploring the relationship of design parameters, but also further enriches the application of forward design method to high-speed trains.

Routing optimization in networks based on traffic gravitational field model

NASA Astrophysics Data System (ADS)

Liu, Longgeng; Luo, Guangchun

2017-04-01

For research on the gravitational field routing mechanism on complex networks, we further analyze the gravitational effect of paths. In this study, we introduce the concept of path confidence degree to evaluate the unblocked reliability of paths that it takes the traffic state of all nodes on the path into account from the overall. On the basis of this, we propose an improved gravitational field routing protocol considering all the nodes’ gravities on the path and the path confidence degree. In order to evaluate the transmission performance of the routing strategy, an order parameter is introduced to measure the network throughput by the critical value of phase transition from a free-flow phase to a jammed phase, and the betweenness centrality is used to evaluate the transmission performance and traffic congestion of the network. Simulation results show that compared with the shortest-path routing strategy and the previous gravitational field routing strategy, the proposed algorithm improves the network throughput considerably and effectively balances the traffic load within the network, and all nodes in the network are utilized high efficiently. As long as γ ≥ α, the transmission performance can reach the maximum and remains unchanged for different α and γ, which ensures that the proposed routing protocol is high efficient and stable.

Path Forward to Space Solar Power using the O'Neill - Glaser Model Modified for Climate Change Demand and Considering the Increasing Risk of Human Self-Extinction if Confined to Earth

NASA Technical Reports Server (NTRS)

Curreri, Peter A.; Nall, Mark

2013-01-01

The cost of energy is humanity's economic exchange rate with the universe. Space solar power is the first great step that our technological species has to utilize the energy of its star. The classic Peter Glaser Solar Power Satellite, SPS, and later designs collect a large area of solar energy in space and beam it back to Earth for use in the electric grid, but even with optimistic launch costs and technology innovation a clear economic path is not evident using Earth launch of SPS. O Neill in 1969 solved the transportation costs problem by a model that uses lunar and asteroid materials to build SPS and locates the labor force permanently in space (O Neill free space habitats). This solution closes the economics and predicts large profits after 17-35 years. However the costs of time have up to now prevented this solution. We discuss a strategy to move forward in SPS with the motivations to stop global warming and prevent human selfextinction. There are near term steps that can be taken that place us on this path forward. First, we must reevaluate the technologies for the classic model and update the parameters to current technology. As technological capability continues to increase exponentially, we need to understand when the monetary potential energy hills are small as the technology gets larger. But the chance for self-extinction, if humanity remains in a single vulnerable habitat, also increased exponentially with time. The path forward is to identify investment points while assessing the risks of non-action.

Pattern recognition and classification of vibrational spectra by artificial neural networks

NASA Astrophysics Data System (ADS)

Yang, Husheng

1999-10-01

A drawback of current open-path Fourier transform infrared (OP/FT-IR) systems is that they need a human expert to determine those compounds that may be quantified from a given spectrum. In this study, three types of artificial neural networks were used to alleviate this problem. Firstly, multi-layer feed-forward neural networks were used to automatically recognize compounds in an OP/FT-IR spectrum. Each neural network was trained to recognize one compound in the presence of up to ten interferents in an OP/FT-IR spectrum. The networks were successfully used to recognize five alcohols and two chlorinated compounds in field-measured controlled-release OP/FT-IR spectra of mixtures of these compounds. It has also been demonstrated that a neural network could correctly identify a spectrum in the presence of an interferent that was not included in the training set and could also reject interferents it has not seen before. Secondly, the possibility of using one- and two- dimensional Kohonen self-organizing maps (SOMs) to recognize similarities in low-resolution vapor-phase infrared spectra without any additional information has been investigated. Both full-range reference spectra and open-path window reference spectra were used to train the networks and the trained networks were then used to classify the reference spectra into several groups. The results showed that the SOMs obtained from the two different training sets were quite different, and it is more appropriate to use the second SOM in OP/FT-IR spectrometry. Thirdly, vapor-phase FT-IR reference spectra of five alcohols along with four baseline spectra were encoded as prototype vectors for a Hopfield network. Inclusion of the baseline spectra allowed the network to classify spectra as unknowns, when the reference spectra of these compounds were not stored as prototype vectors in the network. The network could identify each of the 5 alcohols correctly even in the presence of noise and interfering compounds. Finally, one- and two-dimensional Kohonen SOMs were also successfully used for the unsupervised differentiation of the Fourier transform Raman spectra of hardwoods from softwoods. A semi-quantitative method that is based on the Euclidean distances of the weight matrix has been developed to assist the automatic clustering of the neurons in a two-dimensional SOM.

Wireless Cooperative Networks: Self-Configuration and Optimization

DTIC Science & Technology

2011-09-09

TERMS wireless sensor networks , wireless cooperative networks, resource optimization, ultra-wideband, localization, ranging 16. SECURITY...Communications We consider two prevalent relay protocols for wireless sensor networks : decode-and-forward (DF) and amplify-and-forward (AF). To... sensor networks where each node may have its own sensing data to transmit, since they can maximally conserve energy while helping others as relays

Path connectivity based spectral defragmentation in flexible bandwidth networks.

PubMed

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.

Optimal sensor fusion for land vehicle navigation

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

Morrow, J.D.

1990-10-01

Position location is a fundamental requirement in autonomous mobile robots which record and subsequently follow x,y paths. The Dept. of Energy, Office of Safeguards and Security, Robotic Security Vehicle (RSV) program involves the development of an autonomous mobile robot for patrolling a structured exterior environment. A straight-forward method for autonomous path-following has been adopted and requires digitizing'' the desired road network by storing x,y coordinates every 2m along the roads. The position location system used to define the locations consists of a radio beacon system which triangulates position off two known transponders, and dead reckoning with compass and odometer. Thismore » paper addresses the problem of combining these two measurements to arrive at a best estimate of position. Two algorithms are proposed: the optimal'' algorithm treats the measurements as random variables and minimizes the estimate variance, while the average error'' algorithm considers the bias in dead reckoning and attempts to guarantee an average error. Data collected on the algorithms indicate that both work well in practice. 2 refs., 7 figs.« less

Three-dimensional habitat structure and landscape genetics: a step forward in estimating functional connectivity.

PubMed

Milanesi, P; Holderegger, R; Bollmann, K; Gugerli, F; Zellweger, F

2017-02-01

Estimating connectivity among fragmented habitat patches is crucial for evaluating the functionality of ecological networks. However, current estimates of landscape resistance to animal movement and dispersal lack landscape-level data on local habitat structure. Here, we used a landscape genetics approach to show that high-fidelity habitat structure maps derived from Light Detection and Ranging (LiDAR) data critically improve functional connectivity estimates compared to conventional land cover data. We related pairwise genetic distances of 128 Capercaillie (Tetrao urogallus) genotypes to least-cost path distances at multiple scales derived from land cover data. Resulting β values of linear mixed effects models ranged from 0.372 to 0.495, while those derived from LiDAR ranged from 0.558 to 0.758. The identification and conservation of functional ecological networks suffering from habitat fragmentation and homogenization will thus benefit from the growing availability of detailed and contiguous data on three-dimensional habitat structure and associated habitat quality. © 2016 by the Ecological Society of America.

SDN-based path hopping communication against eavesdropping attack

NASA Astrophysics Data System (ADS)

Zhang, Chuanhao; Bu, Youjun; Zhao, Zheng

2016-10-01

Network eavesdropping is one of the most popular means used by cyber attackers, which has been a severe threat to network communication security. Adversaries could capture and analyze network communication data from network nodes or links, monitor network status and steal sensitive data such as username and password etc. Traditional network usually uses static network configuration, and existing defense methods, including firewall, IDS, IPS etc., cannot prevent eavesdropping, which has no distinguishing characteristic. Network eavesdropping become silent during most of the time of the attacking process, which is why it is difficult to discover and to defend. But A successful eavesdropping attack also has its' precondition, which is the target path should be relatively stable and has enough time of duration. So, In order to resolve this problem, it has to work on the network architecture. In this paper, a path hopping communication(PHC) mechanism based on Software Define Network (SDN) was proposed to solve this problem. In PHC, Ends in communication packets as well as the routing paths were changed dynamically. Therefore, the traffic would be distributed to multiple flows and transmitted along different paths. so that Network eavesdropping attack could be prevented effectively. It was concluded that PHC was able to increase the overhead of Network eavesdropping, as well as the difficulty of communication data recovery.

Adaptive Dynamics, Control, and Extinction in Networked Populations

DTIC Science & Technology

2015-07-09

network geometries. From the pre-history of paths that go extinct, a density function is created from the prehistory of these paths, and a clear local...density plots of Fig. 3b. Using the IAMM to compute the most probable path and comparing it to the prehistory of extinction events on stochastic networks

Fokker-Planck-Based Acceleration for SN Equations with Highly Forward Peaked Scattering in Slab Geometry

NASA Astrophysics Data System (ADS)

Patel, Japan

Short mean free paths are characteristic of charged particles. High energy charged particles often have highly forward peaked scattering cross sections. Transport problems involving such charged particles are also highly optically thick. When problems simultaneously have forward peaked scattering and high optical thickness, their solution, using standard iterative methods, becomes very inefficient. In this dissertation, we explore Fokker-Planck-based acceleration for solving such problems.

Accountability as a Way Forward for Privacy Protection in the Cloud

NASA Astrophysics Data System (ADS)

Pearson, Siani; Charlesworth, Andrew

The issue of how to provide appropriate privacy protection for cloud computing is important, and as yet unresolved. In this paper we propose an approach in which procedural and technical solutions are co-designed to demonstrate accountability as a path forward to resolving jurisdictional privacy and security risks within the cloud.

STEPP--Search Tool for Exploration of Petri net Paths: a new tool for Petri net-based path analysis in biochemical networks.

PubMed

Koch, Ina; Schueler, Markus; Heiner, Monika

2005-01-01

To understand biochemical processes caused by, e. g., mutations or deletions in the genome, the knowledge of possible alternative paths between two arbitrary chemical compounds is of increasing interest for biotechnology, pharmacology, medicine, and drug design. With the steadily increasing amount of data from high-throughput experiments new biochemical networks can be constructed and existing ones can be extended, which results in many large metabolic, signal transduction, and gene regulatory networks. The search for alternative paths within these complex and large networks can provide a huge amount of solutions, which can not be handled manually. Moreover, not all of the alternative paths are generally of interest. Therefore, we have developed and implemented a method, which allows us to define constraints to reduce the set of all structurally possible paths to the truly interesting path set. The paper describes the search algorithm and the constraints definition language. We give examples for path searches using this dedicated special language for a Petri net model of the sucrose-to-starch breakdown in the potato tuber.

STEPP - Search Tool for Exploration of Petri net Paths: A New Tool for Petri Net-Based Path Analysis in Biochemical Networks.

PubMed

Koch, Ina; Schüler, Markus; Heiner, Monika

2011-01-01

To understand biochemical processes caused by, e.g., mutations or deletions in the genome, the knowledge of possible alternative paths between two arbitrary chemical compounds is of increasing interest for biotechnology, pharmacology, medicine, and drug design. With the steadily increasing amount of data from high-throughput experiments new biochemical networks can be constructed and existing ones can be extended, which results in many large metabolic, signal transduction, and gene regulatory networks. The search for alternative paths within these complex and large networks can provide a huge amount of solutions, which can not be handled manually. Moreover, not all of the alternative paths are generally of interest. Therefore, we have developed and implemented a method, which allows us to define constraints to reduce the set of all structurally possible paths to the truly interesting path set. The paper describes the search algorithm and the constraints definition language. We give examples for path searches using this dedicated special language for a Petri net model of the sucrose-to-starch breakdown in the potato tuber. http://sanaga.tfh-berlin.de/~stepp/

A DTN-Based Multiple Access Fast Forward Service for the NASA Space Network

NASA Technical Reports Server (NTRS)

Israel, David; Davis, Faith; Marquart. Jane

2011-01-01

The NASA Space Network provides a demand access return link service capable of providing users a space link "on demand". An equivalent service in the forward link direction is not possible due to Tracking and Data Relay Spacecraft (TDRS) constraints. A Disruption Tolerant Networking (DTN)-based Multiple Access Fast Forward (MAFF) service has been proposed to provide a forward link to a user as soon as possible. Previous concept studies have identified a basic architecture and implementation approach. This paper reviews the user scenarios and benefits of an MAFF service and proposes an implementation approach based on the use of DTN protocols.

Using Hybrid Algorithm to Improve Intrusion Detection in Multi Layer Feed Forward Neural Networks

ERIC Educational Resources Information Center

Ray, Loye Lynn

2014-01-01

The need for detecting malicious behavior on a computer networks continued to be important to maintaining a safe and secure environment. The purpose of this study was to determine the relationship of multilayer feed forward neural network architecture to the ability of detecting abnormal behavior in networks. This involved building, training, and…

From the physics of interacting polymers to optimizing routes on the London Underground

PubMed Central

Yeung, Chi Ho; Saad, David; Wong, K. Y. Michael

2013-01-01

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise. PMID:23898198

From the physics of interacting polymers to optimizing routes on the London Underground.

PubMed

Yeung, Chi Ho; Saad, David; Wong, K Y Michael

2013-08-20

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise.

Privacy-Preserving Relationship Path Discovery in Social Networks

NASA Astrophysics Data System (ADS)

Mezzour, Ghita; Perrig, Adrian; Gligor, Virgil; Papadimitratos, Panos

As social networks sites continue to proliferate and are being used for an increasing variety of purposes, the privacy risks raised by the full access of social networking sites over user data become uncomfortable. A decentralized social network would help alleviate this problem, but offering the functionalities of social networking sites is a distributed manner is a challenging problem. In this paper, we provide techniques to instantiate one of the core functionalities of social networks: discovery of paths between individuals. Our algorithm preserves the privacy of relationship information, and can operate offline during the path discovery phase. We simulate our algorithm on real social network topologies.

Fault tolerant hypercube computer system architecture

NASA Technical Reports Server (NTRS)

Madan, Herb S. (Inventor); Chow, Edward (Inventor)

1989-01-01

A fault-tolerant multiprocessor computer system of the hypercube type comprising a hierarchy of computers of like kind which can be functionally substituted for one another as necessary is disclosed. Communication between the working nodes is via one communications network while communications between the working nodes and watch dog nodes and load balancing nodes higher in the structure is via another communications network separate from the first. A typical branch of the hierarchy reporting to a master node or host computer comprises, a plurality of first computing nodes; a first network of message conducting paths for interconnecting the first computing nodes as a hypercube. The first network provides a path for message transfer between the first computing nodes; a first watch dog node; and a second network of message connecting paths for connecting the first computing nodes to the first watch dog node independent from the first network, the second network provides an independent path for test message and reconfiguration affecting transfers between the first computing nodes and the first switch watch dog node. There is additionally, a plurality of second computing nodes; a third network of message conducting paths for interconnecting the second computing nodes as a hypercube. The third network provides a path for message transfer between the second computing nodes; a fourth network of message conducting paths for connecting the second computing nodes to the first watch dog node independent from the third network. The fourth network provides an independent path for test message and reconfiguration affecting transfers between the second computing nodes and the first watch dog node; and a first multiplexer disposed between the first watch dog node and the second and fourth networks for allowing the first watch dog node to selectively communicate with individual ones of the computing nodes through the second and fourth networks; as well as, a second watch dog node operably connected to the first multiplexer whereby the second watch dog node can selectively communicate with individual ones of the computing nodes through the second and fourth networks. The branch is completed by a first load balancing node; and a second multiplexer connected between the first load balancing node and the first and second watch dog nodes, allowing the first load balancing node to selectively communicate with the first and second watch dog nodes.

Heuristic approaches for energy-efficient shared restoration in WDM networks

NASA Astrophysics Data System (ADS)

Alilou, Shahab

In recent years, there has been ongoing research on the design of energy-efficient Wavelength Division Multiplexing (WDM) networks. The explosive growth of Internet traffic has led to increased power consumption of network components. Network survivability has also been a relevant research topic, as it plays a crucial role in assuring continuity of service with no disruption, regardless of network component failure. Network survivability mechanisms tend to utilize considerable resources such as spare capacity in order to protect and restore information. This thesis investigates techniques for reducing energy demand and enhancing energy efficiency in the context of network survivability. We propose two novel heuristic energy-efficient shared protection approaches for WDM networks. These approaches intend to save energy by setting on sleep mode devices that are not being used while providing shared backup paths to satisfy network survivability. The first approach exploits properties of a math series in order to assign weight to the network links. It aims at reducing power consumption at the network indirectly by aggregating traffic on a set of nodes and links with high traffic load level. Routing traffic on links and nodes that are already under utilization makes it possible for the links and nodes with no load to be set on sleep mode. The second approach is intended to dynamically route traffic through nodes and links with high traffic load level. Similar to the first approach, this approach computes a pair of paths for every newly arrived demand. It computes these paths for every new demand by comparing the power consumption of nodes and links in the network before the demand arrives with their potential power consumption if they are chosen along the paths of this demand. Simulations of two different networks were used to compare the total network power consumption obtained using the proposed techniques against a standard shared-path restoration scheme. Shared-path restoration is a network survivability method in which a link-disjoint backup path and wavelength is reserved at the time of call setup for a working path. However, in order to reduce spare capacity consumption, this reserved backup path and wavelength may be shared with other backup paths. Pool Sharing Scheme (PSS) is employed to implement shared-path restoration scheme [1]. In an optical network, the failure of a single link leads to the failure of all the lightpaths that pass through that particular link. PSS ensures that the amount of backup bandwidth required on a link to restore the failed connections will not be more than the total amount of reserved backup bandwidth on that link. Simulation results indicate that the proposed approaches lead to up to 35% power savings in WDM networks when traffic load is low. However, power saving decreases to 14% at high traffic load level. Furthermore, in terms of the total capacity consumption for working paths, PSS outperforms the two proposed approaches, as expected. In terms of total capacity consumption all the approaches behave similarly. In general, at low traffic load level, the two proposed approaches behave similar to PSS in terms of average link load, and the ratio of block demands. Nevertheless, at high traffic load, the proposed approaches result in higher ratio of blocked demands than PSS. They also lead to higher average link load than PSS for the equal number of generated demands.

Recursively constructing analytic expressions for equilibrium distributions of stochastic biochemical reaction networks.

PubMed

Meng, X Flora; Baetica, Ania-Ariadna; Singhal, Vipul; Murray, Richard M

2017-05-01

Noise is often indispensable to key cellular activities, such as gene expression, necessitating the use of stochastic models to capture its dynamics. The chemical master equation (CME) is a commonly used stochastic model of Kolmogorov forward equations that describe how the probability distribution of a chemically reacting system varies with time. Finding analytic solutions to the CME can have benefits, such as expediting simulations of multiscale biochemical reaction networks and aiding the design of distributional responses. However, analytic solutions are rarely known. A recent method of computing analytic stationary solutions relies on gluing simple state spaces together recursively at one or two states. We explore the capabilities of this method and introduce algorithms to derive analytic stationary solutions to the CME. We first formally characterize state spaces that can be constructed by performing single-state gluing of paths, cycles or both sequentially. We then study stochastic biochemical reaction networks that consist of reversible, elementary reactions with two-dimensional state spaces. We also discuss extending the method to infinite state spaces and designing the stationary behaviour of stochastic biochemical reaction networks. Finally, we illustrate the aforementioned ideas using examples that include two interconnected transcriptional components and biochemical reactions with two-dimensional state spaces. © 2017 The Author(s).

Recursively constructing analytic expressions for equilibrium distributions of stochastic biochemical reaction networks

PubMed Central

Baetica, Ania-Ariadna; Singhal, Vipul; Murray, Richard M.

2017-01-01

Noise is often indispensable to key cellular activities, such as gene expression, necessitating the use of stochastic models to capture its dynamics. The chemical master equation (CME) is a commonly used stochastic model of Kolmogorov forward equations that describe how the probability distribution of a chemically reacting system varies with time. Finding analytic solutions to the CME can have benefits, such as expediting simulations of multiscale biochemical reaction networks and aiding the design of distributional responses. However, analytic solutions are rarely known. A recent method of computing analytic stationary solutions relies on gluing simple state spaces together recursively at one or two states. We explore the capabilities of this method and introduce algorithms to derive analytic stationary solutions to the CME. We first formally characterize state spaces that can be constructed by performing single-state gluing of paths, cycles or both sequentially. We then study stochastic biochemical reaction networks that consist of reversible, elementary reactions with two-dimensional state spaces. We also discuss extending the method to infinite state spaces and designing the stationary behaviour of stochastic biochemical reaction networks. Finally, we illustrate the aforementioned ideas using examples that include two interconnected transcriptional components and biochemical reactions with two-dimensional state spaces. PMID:28566513

Tracking trade transactions in water resource systems: A node-arc optimization formulation

NASA Astrophysics Data System (ADS)

Erfani, Tohid; Huskova, Ivana; Harou, Julien J.

2013-05-01

We formulate and apply a multicommodity network flow node-arc optimization model capable of tracking trade transactions in complex water resource systems. The model uses a simple node to node network connectivity matrix and does not require preprocessing of all possible flow paths in the network. We compare the proposed node-arc formulation with an existing arc-path (flow path) formulation and explain the advantages and difficulties of both approaches. We verify the proposed formulation model on a hypothetical water distribution network. Results indicate the arc-path model solves the problem with fewer constraints, but the proposed formulation allows using a simple network connectivity matrix which simplifies modeling large or complex networks. The proposed algorithm allows converting existing node-arc hydroeconomic models that broadly represent water trading to ones that also track individual supplier-receiver relationships (trade transactions).

Alternative Path Communication in Wide-Scale Cluster-Tree Wireless Sensor Networks Using Inactive Periods

PubMed Central

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-01-01

The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable technology to deploy wide-scale Wireless Sensor Networks (WSNs). These networks are usually designed to support convergecast traffic, where all communication paths go through the PAN (Personal Area Network) coordinator. Nevertheless, peer-to-peer communication relationships may be also required for different types of WSN applications. That is the typical case of sensor and actuator networks, where local control loops must be closed using a reduced number of communication hops. The use of communication schemes optimised just for the support of convergecast traffic may result in higher network congestion and in a potentially higher number of communication hops. Within this context, this paper proposes an Alternative-Route Definition (ARounD) communication scheme for WSNs. The underlying idea of ARounD is to setup alternative communication paths between specific source and destination nodes, avoiding congested cluster-tree paths. These alternative paths consider shorter inter-cluster paths, using a set of intermediate nodes to relay messages during their inactive periods in the cluster-tree network. Simulation results show that the ARounD communication scheme can significantly decrease the end-to-end communication delay, when compared to the use of standard cluster-tree communication schemes. Moreover, the ARounD communication scheme is able to reduce the network congestion around the PAN coordinator, enabling the reduction of the number of message drops due to queue overflows in the cluster-tree network. PMID:28481245

Alternative Path Communication in Wide-Scale Cluster-Tree Wireless Sensor Networks Using Inactive Periods.

PubMed

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-05-06

The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable technology to deploy wide-scale Wireless Sensor Networks (WSNs). These networks are usually designed to support convergecast traffic, where all communication paths go through the PAN (Personal Area Network) coordinator. Nevertheless, peer-to-peer communication relationships may be also required for different types of WSN applications. That is the typical case of sensor and actuator networks, where local control loops must be closed using a reduced number of communication hops. The use of communication schemes optimised just for the support of convergecast traffic may result in higher network congestion and in a potentially higher number of communication hops. Within this context, this paper proposes an Alternative-Route Definition (ARounD) communication scheme for WSNs. The underlying idea of ARounD is to setup alternative communication paths between specific source and destination nodes, avoiding congested cluster-tree paths. These alternative paths consider shorter inter-cluster paths, using a set of intermediate nodes to relay messages during their inactive periods in the cluster-tree network. Simulation results show that the ARounD communication scheme can significantly decrease the end-to-end communication delay, when compared to the use of standard cluster-tree communication schemes. Moreover, the ARounD communication scheme is able to reduce the network congestion around the PAN coordinator, enabling the reduction of the number of message drops due to queue overflows in the cluster-tree network.

Graph Coarsening for Path Finding in Cybersecurity Graphs

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

Hogan, Emilie A.; Johnson, John R.; Halappanavar, Mahantesh

2013-01-01

n the pass-the-hash attack, hackers repeatedly steal password hashes and move through a computer network with the goal of reaching a computer with high level administrative privileges. In this paper we apply graph coarsening in network graphs for the purpose of detecting hackers using this attack or assessing the risk level of the network's current state. We repeatedly take graph minors, which preserve the existence of paths in the graph, and take powers of the adjacency matrix to count the paths. This allows us to detect the existence of paths as well as find paths that have high risk ofmore » being used by adversaries.« less

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

2013-01-01

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of the store-and-forward mechanism, and the interactions among data types within a pass. The novelty of this approach lies in the modeling of the store-and-forward mechanism of each network node. The term store-and-forward refers to the data traffic regulation technique in which data is sent to an intermediate network node where they are temporarily stored and sent at a later time to the destination node or to another intermediate node. Store-and-forward can be applied to both space-based networks that have intermittent connectivity, and ground-based networks with deterministic connectivity. For groundbased networks, the store-and-forward mechanism is used to regulate the network data flow and link resource utilization such that the user data types can be delivered to their destination nodes without violating their respective latency requirements.

Master equations and the theory of stochastic path integrals

NASA Astrophysics Data System (ADS)

Weber, Markus F.; Frey, Erwin

2017-04-01

This review provides a pedagogic and self-contained introduction to master equations and to their representation by path integrals. Since the 1930s, master equations have served as a fundamental tool to understand the role of fluctuations in complex biological, chemical, and physical systems. Despite their simple appearance, analyses of master equations most often rely on low-noise approximations such as the Kramers-Moyal or the system size expansion, or require ad-hoc closure schemes for the derivation of low-order moment equations. We focus on numerical and analytical methods going beyond the low-noise limit and provide a unified framework for the study of master equations. After deriving the forward and backward master equations from the Chapman-Kolmogorov equation, we show how the two master equations can be cast into either of four linear partial differential equations (PDEs). Three of these PDEs are discussed in detail. The first PDE governs the time evolution of a generalized probability generating function whose basis depends on the stochastic process under consideration. Spectral methods, WKB approximations, and a variational approach have been proposed for the analysis of the PDE. The second PDE is novel and is obeyed by a distribution that is marginalized over an initial state. It proves useful for the computation of mean extinction times. The third PDE describes the time evolution of a ‘generating functional’, which generalizes the so-called Poisson representation. Subsequently, the solutions of the PDEs are expressed in terms of two path integrals: a ‘forward’ and a ‘backward’ path integral. Combined with inverse transformations, one obtains two distinct path integral representations of the conditional probability distribution solving the master equations. We exemplify both path integrals in analysing elementary chemical reactions. Moreover, we show how a well-known path integral representation of averaged observables can be recovered from them. Upon expanding the forward and the backward path integrals around stationary paths, we then discuss and extend a recent method for the computation of rare event probabilities. Besides, we also derive path integral representations for processes with continuous state spaces whose forward and backward master equations admit Kramers-Moyal expansions. A truncation of the backward expansion at the level of a diffusion approximation recovers a classic path integral representation of the (backward) Fokker-Planck equation. One can rewrite this path integral in terms of an Onsager-Machlup function and, for purely diffusive Brownian motion, it simplifies to the path integral of Wiener. To make this review accessible to a broad community, we have used the language of probability theory rather than quantum (field) theory and do not assume any knowledge of the latter. The probabilistic structures underpinning various technical concepts, such as coherent states, the Doi-shift, and normal-ordered observables, are thereby made explicit.

Experimental demonstration of spectrum-sliced elastic optical path network (SLICE).

PubMed

Kozicki, Bartłomiej; Takara, Hidehiko; Tsukishima, Yukio; Yoshimatsu, Toshihide; Yonenaga, Kazushige; Jinno, Masahiko

2010-10-11

We describe experimental demonstration of spectrum-sliced elastic optical path network (SLICE) architecture. We employ optical orthogonal frequency-division multiplexing (OFDM) modulation format and bandwidth-variable optical cross-connects (OXC) to generate, transmit and receive optical paths with bandwidths of up to 1 Tb/s. We experimentally demonstrate elastic optical path setup and spectrally-efficient transmission of multiple channels with bit rates ranging from 40 to 140 Gb/s between six nodes of a mesh network. We show dynamic bandwidth scalability for optical paths with bit rates of 40 to 440 Gb/s. Moreover, we demonstrate multihop transmission of a 1 Tb/s optical path over 400 km of standard single-mode fiber (SMF). Finally, we investigate the filtering properties and the required guard band width for spectrally-efficient allocation of optical paths in SLICE.

What is an "ideal" antibiotic? Discovery challenges and path forward.

PubMed

Singh, Sheo B; Young, Katherine; Silver, Lynn L

2017-06-01

An ideal antibiotic is an antibacterial agent that kills or inhibits the growth of all harmful bacteria in a host, regardless of site of infection without affecting beneficial gut microbes (gut flora) or causing undue toxicity to the host. Sadly, no such antibiotics exist. What exist are many effective Gram-positive antibacterial agents as well as broad-spectrum agents that provide treatment of certain Gram-negative bacteria but not holistic treatment of all bacteria. However effectiveness of all antibacterial agents is being rapidly eroded due to resistance. This viewpoint provides an overview of today's antibiotics, challenges and potential path forward of discovery and development of new (ideal) antibiotics. Copyright © 2017 Elsevier Inc. All rights reserved.

Seismic refraction analysis: the path forward

USGS Publications Warehouse

Haines, Seth S.; Zelt, Colin; Doll, William

2012-01-01

Seismic Refraction Methods: Unleashing the Potential and Understanding the Limitations; Tucson, Arizona, 29 March 2012 A workshop focused on seismic refraction methods took place on 29 May 2012, associated with the 2012 Symposium on the Application of Geophysics to Engineering and Environmental Problems. This workshop was convened to assess the current state of the science and discuss paths forward, with a primary focus on near-surface problems but with an eye on all applications. The agenda included talks on these topics from a number of experts interspersed with discussion and a dedicated discussion period to finish the day. Discussion proved lively at times, and workshop participants delved into many topics central to seismic refraction work.

Architecture and design of optical path networks utilizing waveband virtual links

NASA Astrophysics Data System (ADS)

Ito, Yusaku; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi

2016-02-01

We propose a novel optical network architecture that uses waveband virtual links, each of which can carry several optical paths, to directly bridge distant node pairs. Future photonic networks should not only transparently cover extended areas but also expand fiber capacity. However, the traversal of many ROADM nodes impairs the optical signal due to spectrum narrowing. To suppress the degradation, the bandwidth of guard bands needs to be increased, which degrades fiber frequency utilization. Waveband granular switching allows us to apply broader pass-band filtering at ROADMs and to insert sufficient guard bands between wavebands with minimum frequency utilization offset. The scheme resolves the severe spectrum narrowing effect. Moreover, the guard band between optical channels in a waveband can be minimized, which increases the number of paths that can be accommodated per fiber. In the network, wavelength path granular routing is done without utilizing waveband virtual links, and it still suffers from spectrum narrowing. A novel network design algorithm that can bound the spectrum narrowing effect by limiting the number of hops (traversed nodes that need wavelength path level routing) is proposed in this paper. This algorithm dynamically changes the waveband virtual link configuration according to the traffic distribution variation, where optical paths that need many node hops are effectively carried by virtual links. Numerical experiments demonstrate that the number of necessary fibers is reduced by 23% compared with conventional optical path networks.

A dynamic routing strategy with limited buffer on scale-free network

NASA Astrophysics Data System (ADS)

Wang, Yufei; Liu, Feng

2016-04-01

In this paper, we propose an integrated routing strategy based on global static topology information and local dynamic data packet queue lengths to improve the transmission efficiency of scale-free networks. The proposed routing strategy is a combination of a global static routing strategy (based on the shortest path algorithm) and local dynamic queue length management, in which, instead of using an infinite buffer, the queue length of each node i in the proposed routing strategy is limited by a critical queue length Qic. When the network traffic is lower and the queue length of each node i is shorter than its critical queue length Qic, it forwards packets according to the global routing table. With increasing network traffic, when the buffers of the nodes with higher degree are full, they do not receive packets due to their limited buffers and the packets have to be delivered to the nodes with lower degree. The global static routing strategy can shorten the transmission time that it takes a packet to reach its destination, and the local limited queue length can balance the network traffic. The optimal critical queue lengths of nodes have been analysed. Simulation results show that the proposed routing strategy can get better performance than that of the global static strategy based on topology, and almost the same performance as that of the global dynamic routing strategy with less complexity.

The "path" not taken: exploring structural differences in mapped- versus shortest-network-path school travel routes.

PubMed

Buliung, Ron N; Larsen, Kristian; Faulkner, Guy E J; Stone, Michelle R

2013-09-01

School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys = 45%, girls = 54%, unreported gender = 1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems-based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research.

A game theory-based obstacle avoidance routing protocol for wireless sensor networks.

PubMed

Guan, Xin; Wu, Huayang; Bi, Shujun

2011-01-01

The obstacle avoidance problem in geographic forwarding is an important issue for location-based routing in wireless sensor networks. The presence of an obstacle leads to several geographic routing problems such as excessive energy consumption and data congestion. Obstacles are hard to avoid in realistic environments. To bypass obstacles, most routing protocols tend to forward packets along the obstacle boundaries. This leads to a situation where the nodes at the boundaries exhaust their energy rapidly and the obstacle area is diffused. In this paper, we introduce a novel routing algorithm to solve the obstacle problem in wireless sensor networks based on a game-theory model. Our algorithm forms a concave region that cannot forward packets to achieve the aim of improving the transmission success rate and decreasing packet transmission delays. We consider the residual energy, out-degree and forwarding angle to determine the forwarding probability and payoff function of forwarding candidates. This achieves the aim of load balance and reduces network energy consumption. Simulation results show that based on the average delivery delay, energy consumption and packet delivery ratio performances our protocol is superior to other traditional schemes.

Improved Efficient Routing Strategy on Scale-Free Networks

NASA Astrophysics Data System (ADS)

Jiang, Zhong-Yuan; Liang, Man-Gui

Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási-Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs

PubMed Central

Kim, Sang-Ha

2017-01-01

Face routing has been adopted in wireless sensor networks (WSNs) where topological changes occur frequently or maintaining full network information is difficult. For message forwarding in networks, a planar graph is used to prevent looping, and because long edges are removed by planarization and the resulting planar graph is composed of short edges, and messages are forwarded along multiple nodes connected by them even though they can be forwarded directly. To solve this, face routing using information on all nodes within 2-hop range was adopted to forward messages directly to the farthest node within radio range. However, as the density of the nodes increases, network performance plunges because message transfer nodes receive and process increased node information. To deal with this problem, we propose a new face routing using the planar graphs of neighboring nodes to improve transfer efficiency. It forwards a message directly to the farthest neighbor and reduces loads and processing time by distributing network graph construction and planarization to the neighbors. It also decreases the amount of location information to be transmitted by sending information on the planar graph nodes rather than on all neighboring nodes. Simulation results show that it significantly improves transfer efficiency. PMID:29053623

An intercomparison of artificial intelligence approaches for polar scene identification

NASA Technical Reports Server (NTRS)

Tovinkere, V. R.; Penaloza, M.; Logar, A.; Lee, J.; Weger, R. C.; Berendes, T. A.; Welch, R. M.

1993-01-01

The following six different artificial-intelligence (AI) approaches to polar scene identification are examined: (1) a feed forward back propagation neural network, (2) a probabilistic neural network, (3) a hybrid neural network, (4) a 'don't care' feed forward perception model, (5) a 'don't care' feed forward back propagation neural network, and (6) a fuzzy logic based expert system. The ten classes into which six AVHRR local-coverage arctic scenes were classified were: water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over water, cumulus over water, and multilayer cloudiness. It was found that 'don't care' back propagation neural network produced the highest accuracies. This approach has also low CPU requirement.

Extended shortest path selection for package routing of complex networks

NASA Astrophysics Data System (ADS)

Ye, Fan; Zhang, Lei; Wang, Bing-Hong; Liu, Lu; Zhang, Xing-Yi

The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency.

An Application of Multi-Criteria Shortest Path to a Customizable Hex-Map Environment

DTIC Science & Technology

2015-03-26

forces which could act as intermediate destinations or obstacles to movement through the network. This is similar to a traveling salesman problem ...118 Abstract The shortest path problem of finding the optimal path through a complex network is well-studied in the field of operations research. This...research presents an applica- tion of the shortest path problem to a customizable map with terrain features and enemy engagement risk. The PathFinder

Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks

PubMed Central

Robinson, Y. Harold; Rajaram, M.

2015-01-01

Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique. PMID:26819966

Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction.

PubMed

Stringer, Simon M; Rolls, Edmund T

2006-12-01

A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations.

CMPF: class-switching minimized pathfinding in metabolic networks.

PubMed

Lim, Kevin; Wong, Limsoon

2012-01-01

The metabolic network is an aggregation of enzyme catalyzed reactions that converts one compound to another. Paths in a metabolic network are a sequence of enzymes that describe how a chemical compound of interest can be produced in a biological system. As the number of such paths is quite large, many methods have been developed to score paths so that the k-shortest paths represent the set of paths that are biologically meaningful or efficient. However, these approaches do not consider whether the sequence of enzymes can be manufactured in the same pathway/species/localization. As a result, a predicted sequence might consist of groups of enzymes that operate in distinct pathway/species/localization and may not truly reflect the events occurring within cell. We propose a path weighting method CMPF (Class-switching Minimized Pathfinder) to search for routes in a metabolic network which minimizes pathway switching. In biological terms, a pathway is a series of chemical reactions which define a specific function (e.g. glycolysis). We conjecture that routes that cross many pathways are inefficient since different pathways define different metabolic functions. In addition, native routes are also well characterized within pathways, suggesting that reasonable paths should not involve too many pathway switches. Our method can be generalized when reactions participate in a class set (e.g., pathways, species or cellular localization) so that the paths predicted have minimal class crossings. We show that our method generates k-paths that involve the least number of class switching. In addition, we also show that native paths are recoverable and alternative paths deviates less from native paths compared to other methods. This suggests that paths ranked by our method could be a way to predict paths that are likely to occur in biological systems.

Space Link Extension (SLE) Emulation for High-Throughput Network Communication

NASA Technical Reports Server (NTRS)

Murawski, Robert W.; Tchorowski, Nicole; Golden, Bert

2014-01-01

As the data rate requirements for space communications increases, significant stress is placed not only on the wireless satellite communication links, but also on the ground networks which forward data from end-users to remote ground stations. These wide area network (WAN) connections add delay and jitter to the end-to-end satellite communication link, effects which can have significant impacts on the wireless communication link. It is imperative that any ground communication protocol can react to these effects such that the ground network does not become a bottleneck in the communication path to the satellite. In this paper, we present our SCENIC Emulation Lab testbed which was developed to test the CCSDS SLE protocol implementations proposed for use on future NASA communication networks. Our results show that in the presence of realistic levels of network delay, high-throughput SLE communication links can experience significant data rate throttling. Based on our observations, we present some insight into why this data throttling happens, and trace the probable issue back to non-optimal blocking communication which is sup-ported by the CCSDS SLE API recommended practices. These issues were presented as well to the SLE implementation developers which, based on our reports, developed a new release for SLE which we show fixes the SLE blocking issue and greatly improves the protocol throughput. In this paper, we also discuss future developments for our end-to-end emulation lab and how these improvements can be used to develop and test future space communication technologies.

Epidemic extinction paths in complex networks

NASA Astrophysics Data System (ADS)

Hindes, Jason; Schwartz, Ira B.

2017-05-01

We study the extinction of long-lived epidemics on finite complex networks induced by intrinsic noise. Applying analytical techniques to the stochastic susceptible-infected-susceptible model, we predict the distribution of large fluctuations, the most probable or optimal path through a network that leads to a disease-free state from an endemic state, and the average extinction time in general configurations. Our predictions agree with Monte Carlo simulations on several networks, including synthetic weighted and degree-distributed networks with degree correlations, and an empirical high school contact network. In addition, our approach quantifies characteristic scaling patterns for the optimal path and distribution of large fluctuations, both near and away from the epidemic threshold, in networks with heterogeneous eigenvector centrality and degree distributions.

Epidemic extinction paths in complex networks.

PubMed

Hindes, Jason; Schwartz, Ira B

2017-05-01

We study the extinction of long-lived epidemics on finite complex networks induced by intrinsic noise. Applying analytical techniques to the stochastic susceptible-infected-susceptible model, we predict the distribution of large fluctuations, the most probable or optimal path through a network that leads to a disease-free state from an endemic state, and the average extinction time in general configurations. Our predictions agree with Monte Carlo simulations on several networks, including synthetic weighted and degree-distributed networks with degree correlations, and an empirical high school contact network. In addition, our approach quantifies characteristic scaling patterns for the optimal path and distribution of large fluctuations, both near and away from the epidemic threshold, in networks with heterogeneous eigenvector centrality and degree distributions.

A link-adding strategy for transport efficiency of complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Han, Weizhan; Guo, Qing; Wang, Zhenyong; Zhang, Shuai

2016-12-01

The transport efficiency is one of the critical parameters to evaluate the performance of a network. In this paper, we propose an improved efficient (IE) strategy to enhance the network transport efficiency of complex networks by adding a fraction of links to an existing network based on the node’s local degree centrality and the shortest path length. Simulation results show that the proposed strategy can bring better traffic capacity and shorter average shortest path length than the low-degree-first (LDF) strategy under the shortest path routing protocol. It is found that the proposed strategy is beneficial to the improvement of overall traffic handling and delivering ability of the network. This study can alleviate the congestion in networks, and is helpful to design and optimize realistic networks.

Electrical resistance tomography during in-situ trichloroethylene remediation at the Savannah River Site

NASA Astrophysics Data System (ADS)

Daily, W.; Ramirez, A.

1995-04-01

Electrical resistance tomography was used to monitor in-situ remediation processes for removal of volatile organic compounds from subsurface water and soil at the Savannah River Site near Aiken, South Carolina. This work was designed to test the feasibility of injecting a weak mixture of methane in air as a metabolic carbon source for natural microbial populations which are capable of trichloroethylene degradation. Electrical resistance tomograms were constructed of the subsurface during the test to provide detailed images of the process. These images were made using an iterative reconstruction algorithm based on a finite element forward model and Newton-type least-squares minimization. Changes in the subsurface resistivity distribution were imaged by a pixel-by-pixel subtraction of images taken before and during the process. This differential tomography removed all static features of formation resistivity but clearly delineated dynamic features induced by remediation processes. The air-methane mixture was injected into the saturated zone and the intrained air migration paths were tomographically imaged by the increased resistivity of the path as air displaced formation water. We found the flow paths to be confined to a complex three-dimensional network of channels, some of which extended as far as 30 m from the injection well. These channels were not entirely stable over a period of months since new channels appeared to form with time. Also, the resistivity of the air injection paths increased with time. In another series of tests, resistivity images of water infiltration from the surface support similar conclusions about the preferential permeability paths in the vadose zone. In this case, the water infiltration front is confined to narrow channels which have a three-dimensional structure. Here, similar to air injection in the saturated zone, the water flow is controlled by local variations in formation permeability. However, temporal changes in these channels are minor, indicating that the permeable paths do not seem to be modified by continued infiltration.

Road networks as collections of minimum cost paths

NASA Astrophysics Data System (ADS)

Wegner, Jan Dirk; Montoya-Zegarra, Javier Alexander; Schindler, Konrad

2015-10-01

We present a probabilistic representation of network structures in images. Our target application is the extraction of urban roads from aerial images. Roads appear as thin, elongated, partially curved structures forming a loopy graph, and this complex layout requires a prior that goes beyond standard smoothness and co-occurrence assumptions. In the proposed model the network is represented as a union of 1D paths connecting distant (super-)pixels. A large set of putative candidate paths is constructed in such a way that they include the true network as much as possible, by searching for minimum cost paths in the foreground (road) likelihood. Selecting the optimal subset of candidate paths is posed as MAP inference in a higher-order conditional random field. Each path forms a higher-order clique with a type of clique potential, which attracts the member nodes of cliques with high cumulative road evidence to the foreground label. That formulation induces a robust PN -Potts model, for which a global MAP solution can be found efficiently with graph cuts. Experiments with two road data sets show that the proposed model significantly improves per-pixel accuracies as well as the overall topological network quality with respect to several baselines.

Blocking performance approximation in flexi-grid networks

NASA Astrophysics Data System (ADS)

Ge, Fei; Tan, Liansheng

2016-12-01

The blocking probability to the path requests is an important issue in flexible bandwidth optical communications. In this paper, we propose a blocking probability approximation method of path requests in flexi-grid networks. It models the bundled neighboring carrier allocation with a group of birth-death processes and provides a theoretical analysis to the blocking probability under variable bandwidth traffic. The numerical results show the effect of traffic parameters to the blocking probability of path requests. We use the first fit algorithm in network nodes to allocate neighboring carriers to path requests in simulations, and verify approximation results.

Predicting local field potentials with recurrent neural networks.

PubMed

Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

2016-08-01

We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

Geometrical-optics approximation of forward scattering by gradient-index spheres.

PubMed

Li, Xiangzhen; Han, Xiang'e; Li, Renxian; Jiang, Huifen

2007-08-01

By means of geometrical optics we present an approximation method for acceleration of the computation of the scattering intensity distribution within a forward angular range (0-60 degrees ) for gradient-index spheres illuminated by a plane wave. The incident angle of reflected light is determined by the scattering angle, thus improving the approximation accuracy. The scattering angle and the optical path length are numerically integrated by a general-purpose integrator. With some special index models, the scattering angle and the optical path length can be expressed by a unique function and the calculation is faster. This method is proved effective for transparent particles with size parameters greater than 50. It fails to give good approximation results at scattering angles whose refractive rays are in the backward direction. For different index models, the geometrical-optics approximation is effective only for forward angles, typically those less than 60 degrees or when the refractive-index difference of a particle is less than a certain value.

International Legal Framework for Denuclearization and Nuclear Disarmament -- Present Situation and Prospects

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

Gastelum, Zoe N.

This thesis is the culminating project for my participation in the OECD NEA International School of Nuclear Law. This paper will begin by providing a historical background to current disarmament and denuclearization treaties. This paper will discuss the current legal framework based on current and historical activities related to denuclearization and nuclear disarmament. Then, it will propose paths forward for the future efforts, and describe the necessary legal considerations. Each treaty or agreement will be examined in respect to its requirements for: 1) limitations and implementation; 2) and verification and monitoring. Then, lessons learned in each of the two areasmore » (limitations and verification) will be used to construct a proposed path forward at the end of this paper.« less

Reflexivity and Self-Development of Competencies as Key Drivers in Individuals' Learning and Career Paths: Cases from Italy

ERIC Educational Resources Information Center

Tomassini, Massimo; Zanazzi, Silvia

2014-01-01

The article is aimed at analysing the qualitative interviews (in the form of short life stories) carried out within the Learning and Career Paths (LCP) project in Italy. Theories, such as those of reflexivity, agency, self-construction, competencies, and transformation put forward by relevant authors in the sociological and educational field, are…

Three layers multi-granularity OCDM switching system based on learning-stateful PCE

NASA Astrophysics Data System (ADS)

Wang, Yubao; Liu, Yanfei; Sun, Hao

2017-10-01

In the existing three layers multi-granularity OCDM switching system (TLMG-OCDMSS), F-LSP, L-LSP and OC-LSP can be bundled as switching granularity. For CPU-intensive network, the node not only needs to compute the path but also needs to bundle the switching granularity so that the load of single node is heavy. The node will paralyze when the traffic of the node is too heavy, which will impact the performance of the whole network seriously. The introduction of stateful PCE(S-PCE) will effectively solve these problems. PCE is composed of two parts, namely, the path computation element and the database (TED and LSPDB), and returns the result of path computation to PCC (path computation clients) after PCC sends the path computation request to it. In this way, the pressure of the distributed path computation in each node is reduced. In this paper, we propose the concept of Learning PCE (L-PCE), which uses the existing LSPDB as the data source of PCE's learning. By this means, we can simplify the path computation and reduce the network delay, as a result, improving the performance of network.

The “Path” Not Taken: Exploring Structural Differences in Mapped- Versus Shortest-Network-Path School Travel Routes

PubMed Central

Larsen, Kristian; Faulkner, Guy E. J.; Stone, Michelle R.

2013-01-01

Objectives. School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. Methods. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys = 45%, girls = 54%, unreported gender = 1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. Results. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. Conclusions. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems–based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research. PMID:23865648

IJS: An Intelligent Junction Selection Based Routing Protocol for VANET to Support ITS Services.

PubMed

Bhoi, Sourav Kumar; Khilar, Pabitra Mohan

2014-01-01

Selecting junctions intelligently for data transmission provides better intelligent transportation system (ITS) services. The main problem in vehicular communication is high disturbances of link connectivity due to mobility and less density of vehicles. If link conditions are predicted earlier, then there is a less chance of performance degradation. In this paper, an intelligent junction selection based routing protocol (IJS) is proposed to transmit the data in a quickest path, in which the vehicles are mostly connected and have less link connectivity problem. In this protocol, a helping vehicle is set at every junction to control the communication by predicting link failures or network gaps in a route. Helping vehicle at the junction produces a score for every neighboring junction to forward the data to the destination by considering the current traffic information and selects that junction which has minimum score. IJS protocol is implemented and compared with GyTAR, A-STAR, and GSR routing protocols. Simulation results show that IJS performs better in terms of average end-to-end delay, network gap encounter, and number of hops.

IJS: An Intelligent Junction Selection Based Routing Protocol for VANET to Support ITS Services

PubMed Central

Khilar, Pabitra Mohan

2014-01-01

Selecting junctions intelligently for data transmission provides better intelligent transportation system (ITS) services. The main problem in vehicular communication is high disturbances of link connectivity due to mobility and less density of vehicles. If link conditions are predicted earlier, then there is a less chance of performance degradation. In this paper, an intelligent junction selection based routing protocol (IJS) is proposed to transmit the data in a quickest path, in which the vehicles are mostly connected and have less link connectivity problem. In this protocol, a helping vehicle is set at every junction to control the communication by predicting link failures or network gaps in a route. Helping vehicle at the junction produces a score for every neighboring junction to forward the data to the destination by considering the current traffic information and selects that junction which has minimum score. IJS protocol is implemented and compared with GyTAR, A-STAR, and GSR routing protocols. Simulation results show that IJS performs better in terms of average end-to-end delay, network gap encounter, and number of hops. PMID:27433485

802.16e System Profile for NASA Extra-Vehicular Activities

NASA Technical Reports Server (NTRS)

Foore, Lawrence R.; Chelmins, David T.; Nguyen, Hung D.; Downey, Joseph A.; Finn, Gregory G.; Cagley, Richard E.; Bakula, Casey J.

2009-01-01

This report identifies an 802.16e system profile that is applicable to a lunar surface wireless network, and specifically for meeting extra-vehicular activity (EVA) data flow requirements. EVA suit communication needs are addressed. Design-driving operational scenarios are considered. These scenarios are then used to identify a configuration of the 802.16e system (system profile) that meets EVA requirements, but also aim to make the radio realizable within EVA constraints. Limitations of this system configuration are highlighted. An overview and development status is presented by Toyon Research Corporation concerning the development of an 802.16e compatible modem under NASA s Small Business Innovative Research (SBIR) Program. This modem is based on the recommended system profile developed as part of this report. Last, a path forward is outlined that presents an evolvable solution for the EVA radio system and lunar surface radio networks. This solution is based on a custom link layer, and 802.16e compliant physical layer compliant to the identified system profile, and a later progression to a fully interoperable 802.16e system.

Forward scattering in two-beam laser interferometry

NASA Astrophysics Data System (ADS)

Mana, G.; Massa, E.; Sasso, C. P.

2018-04-01

A fractional error as large as 25 pm mm-1 at the zero optical-path difference has been observed in an optical interferometer measuring the displacement of an x-ray interferometer used to determine the lattice parameter of silicon. Detailed investigations have brought to light that the error was caused by light forward-scattered from the beam feeding the interferometer. This paper reports on the impact of forward-scattered light on the accuracy of two-beam optical interferometry applied to length metrology, and supplies a model capable of explaining the observed error.

Path statistics, memory, and coarse-graining of continuous-time random walks on networks

PubMed Central

Kion-Crosby, Willow; Morozov, Alexandre V.

2015-01-01

Continuous-time random walks (CTRWs) on discrete state spaces, ranging from regular lattices to complex networks, are ubiquitous across physics, chemistry, and biology. Models with coarse-grained states (for example, those employed in studies of molecular kinetics) or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics. However, existing methods for analyzing CTRWs on complex energy landscapes do not address these effects. Here we use statistical mechanics of the nonequilibrium path ensemble to characterize first-passage CTRWs on networks with arbitrary connectivity, energy landscape, and waiting time distributions. Our approach can be applied to calculating higher moments (beyond the mean) of path length, time, and action, as well as statistics of any conservative or non-conservative force along a path. For homogeneous networks, we derive exact relations between length and time moments, quantifying the validity of approximating a continuous-time process with its discrete-time projection. For more general models, we obtain recursion relations, reminiscent of transfer matrix and exact enumeration techniques, to efficiently calculate path statistics numerically. We have implemented our algorithm in PathMAN (Path Matrix Algorithm for Networks), a Python script that users can apply to their model of choice. We demonstrate the algorithm on a few representative examples which underscore the importance of non-exponential distributions, memory, and coarse-graining in CTRWs. PMID:26646868

Routing and spectrum assignment based on ant colony optimization of minimum consecutiveness loss in elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Fu; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Tian, Qinghua; Zhang, Qi; Rao, Lan; Tian, Feng; Luo, Biao; Liu, Yingjun; Tang, Bao

2016-10-01

Elastic Optical Networks are considered to be a promising technology for future high-speed network. In this paper, we propose a RSA algorithm based on the ant colony optimization of minimum consecutiveness loss (ACO-MCL). Based on the effect of the spectrum consecutiveness loss on the pheromone in the ant colony optimization, the path and spectrum of the minimal impact on the network are selected for the service request. When an ant arrives at the destination node from the source node along a path, we assume that this path is selected for the request. We calculate the consecutiveness loss of candidate-neighbor link pairs along this path after the routing and spectrum assignment. Then, the networks update the pheromone according to the value of the consecutiveness loss. We save the path with the smallest value. After multiple iterations of the ant colony optimization, the final selection of the path is assigned for the request. The algorithms are simulated in different networks. The results show that ACO-MCL algorithm performs better in blocking probability and spectrum efficiency than other algorithms. Moreover, the ACO-MCL algorithm can effectively decrease spectrum fragmentation and enhance available spectrum consecutiveness. Compared with other algorithms, the ACO-MCL algorithm can reduce the blocking rate by at least 5.9% in heavy load.

Modeling and optimization of Quality of Service routing in Mobile Ad hoc Networks

NASA Astrophysics Data System (ADS)

Rafsanjani, Marjan Kuchaki; Fatemidokht, Hamideh; Balas, Valentina Emilia

2016-01-01

Mobile ad hoc networks (MANETs) are a group of mobile nodes that are connected without using a fixed infrastructure. In these networks, nodes communicate with each other by forming a single-hop or multi-hop network. To design effective mobile ad hoc networks, it is important to evaluate the performance of multi-hop paths. In this paper, we present a mathematical model for a routing protocol under energy consumption and packet delivery ratio of multi-hop paths. In this model, we use geometric random graphs rather than random graphs. Our proposed model finds effective paths that minimize the energy consumption and maximizes the packet delivery ratio of the network. Validation of the mathematical model is performed through simulation.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system.

PubMed

Gao, Xiangyun; Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-03-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion.

Modelling cointegration and Granger causality network to detect long-term equilibrium and diffusion paths in the financial system

PubMed Central

Huang, Shupei; Sun, Xiaoqi; Hao, Xiaoqing; An, Feng

2018-01-01

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion. PMID:29657804

Insights into Lithium-ion battery degradation and safety mechanisms from mesoscale simulations using experimentally reconstructed mesostructures

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

Roberts, Scott A.; Mendoza, Hector; Brunini, Victor E.

Battery performance, while observed at the macroscale, is primarily governed by the bicontinuous mesoscale network of the active particles and a polymeric conductive binder in its electrodes. Manufacturing processes affect this mesostructure, and therefore battery performance, in ways that are not always clear outside of empirical relationships. Directly studying the role of the mesostructure is difficult due to the small particle sizes (a few microns) and large mesoscale structures. Mesoscale simulation, however, is an emerging technique that allows the investigation into how particle-scale phenomena affect electrode behavior. In this manuscript, we discuss our computational approach for modeling electrochemical, mechanical, andmore » thermal phenomena of lithium-ion batteries at the mesoscale. Here, we review our recent and ongoing simulation investigations and discuss a path forward for additional simulation insights.« less

A computing method for spatial accessibility based on grid partition

NASA Astrophysics Data System (ADS)

Ma, Linbing; Zhang, Xinchang

2007-06-01

An accessibility computing method and process based on grid partition was put forward in the paper. As two important factors impacting on traffic, density of road network and relative spatial resistance for difference land use was integrated into computing traffic cost in each grid. A* algorithms was inducted to searching optimum traffic cost of grids path, a detailed searching process and definition of heuristic evaluation function was described in the paper. Therefore, the method can be implemented more simply and its data source is obtained more easily. Moreover, by changing heuristic searching information, more reasonable computing result can be obtained. For confirming our research, a software package was developed with C# language under ArcEngine9 environment. Applying the computing method, a case study on accessibility of business districts in Guangzhou city was carried out.

Insights into Lithium-ion battery degradation and safety mechanisms from mesoscale simulations using experimentally reconstructed mesostructures

DOE PAGES

Roberts, Scott A.; Mendoza, Hector; Brunini, Victor E.; ...

2016-10-20

Battery performance, while observed at the macroscale, is primarily governed by the bicontinuous mesoscale network of the active particles and a polymeric conductive binder in its electrodes. Manufacturing processes affect this mesostructure, and therefore battery performance, in ways that are not always clear outside of empirical relationships. Directly studying the role of the mesostructure is difficult due to the small particle sizes (a few microns) and large mesoscale structures. Mesoscale simulation, however, is an emerging technique that allows the investigation into how particle-scale phenomena affect electrode behavior. In this manuscript, we discuss our computational approach for modeling electrochemical, mechanical, andmore » thermal phenomena of lithium-ion batteries at the mesoscale. Here, we review our recent and ongoing simulation investigations and discuss a path forward for additional simulation insights.« less

An Improved Forwarding of Diverse Events with Mobile Sinks in Underwater Wireless Sensor Networks.

PubMed

Raza, Waseem; Arshad, Farzana; Ahmed, Imran; Abdul, Wadood; Ghouzali, Sanaa; Niaz, Iftikhar Azim; Javaid, Nadeem

2016-11-04

In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput.

Traffic engineering and regenerator placement in GMPLS networks with restoration

NASA Astrophysics Data System (ADS)

Yetginer, Emre; Karasan, Ezhan

2002-07-01

In this paper we study regenerator placement and traffic engineering of restorable paths in Generalized Multipro-tocol Label Switching (GMPLS) networks. Regenerators are necessary in optical networks due to transmission impairments. We study a network architecture where there are regenerators at selected nodes and we propose two heuristic algorithms for the regenerator placement problem. Performances of these algorithms in terms of required number of regenerators and computational complexity are evaluated. In this network architecture with sparse regeneration, offline computation of working and restoration paths is studied with bandwidth reservation and path rerouting as the restoration scheme. We study two approaches for selecting working and restoration paths from a set of candidate paths and formulate each method as an Integer Linear Programming (ILP) prob-lem. Traffic uncertainty model is developed in order to compare these methods based on their robustness with respect to changing traffic patterns. Traffic engineering methods are compared based on number of additional demands due to traffic uncertainty that can be carried. Regenerator placement algorithms are also evaluated from a traffic engineering point of view.

Rapid cell-free forward engineering of novel genetic ring oscillators

PubMed Central

Niederholtmeyer, Henrike; Sun, Zachary Z; Hori, Yutaka; Yeung, Enoch; Verpoorte, Amanda; Murray, Richard M; Maerkl, Sebastian J

2015-01-01

While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the ‘repressilator’, a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hr. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior. DOI: http://dx.doi.org/10.7554/eLife.09771.001 PMID:26430766

Detecting unknown attacks in wireless sensor networks that contain mobile nodes.

PubMed

Banković, Zorana; Fraga, David; Moya, José M; Vallejo, Juan Carlos

2012-01-01

As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

Modelling information flow along the human connectome using maximum flow.

PubMed

Lyoo, Youngwook; Kim, Jieun E; Yoon, Sujung

2018-01-01

The human connectome is a complex network that transmits information between interlinked brain regions. Using graph theory, previously well-known network measures of integration between brain regions have been constructed under the key assumption that information flows strictly along the shortest paths possible between two nodes. However, it is now apparent that information does flow through non-shortest paths in many real-world networks such as cellular networks, social networks, and the internet. In the current hypothesis, we present a novel framework using the maximum flow to quantify information flow along all possible paths within the brain, so as to implement an analogy to network traffic. We hypothesize that the connection strengths of brain networks represent a limit on the amount of information that can flow through the connections per unit of time. This allows us to compute the maximum amount of information flow between two brain regions along all possible paths. Using this novel framework of maximum flow, previous network topological measures are expanded to account for information flow through non-shortest paths. The most important advantage of the current approach using maximum flow is that it can integrate the weighted connectivity data in a way that better reflects the real information flow of the brain network. The current framework and its concept regarding maximum flow provides insight on how network structure shapes information flow in contrast to graph theory, and suggests future applications such as investigating structural and functional connectomes at a neuronal level. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

PubMed Central

Cao, Youfang; Liang, Jie

2013-01-01

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively by comparing simulation results with true answers. Overall, ABSIS can accurately and efficiently estimate rare event probabilities for all examples, often with smaller variance than other importance sampling algorithms. The ABSIS method is general and can be applied to study rare events of other stochastic networks with complex probability landscape. PMID:23862966

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

NASA Astrophysics Data System (ADS)

Cao, Youfang; Liang, Jie

2013-07-01

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively by comparing simulation results with true answers. Overall, ABSIS can accurately and efficiently estimate rare event probabilities for all examples, often with smaller variance than other importance sampling algorithms. The ABSIS method is general and can be applied to study rare events of other stochastic networks with complex probability landscape.

Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method.

PubMed

Cao, Youfang; Liang, Jie

2013-07-14

Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively by comparing simulation results with true answers. Overall, ABSIS can accurately and efficiently estimate rare event probabilities for all examples, often with smaller variance than other importance sampling algorithms. The ABSIS method is general and can be applied to study rare events of other stochastic networks with complex probability landscape.

Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

PubMed

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

2015-02-01

Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have specific patterns and tissue-specificity, which are driven by aging and other cancer-inducing agents. This framework represents the logics of complex cancer biology as a myriad of phenotypic complexities governed by a limited set of underlying organizing principles. It therefore adds to our understanding of tumor evolution and tumorigenesis, and moreover, potential usefulness of predicting tumors' evolutionary paths and clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for cancer patients, as well as cancer risks for healthy individuals are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial impact on timely diagnosis, personalized treatment and personalized prevention of cancer. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

PRP Comments for ICF Q1/Q2 FY17 Experiments 3/10/16

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

Kauffman, R.

2016-04-14

The PRP generally endorsed the Program plan during the short time for discussions. We agree that the strategy to develop a hohlraum that is symmetric and has low laser-plasma instabilities and to develop an alternative method for supporting the capsule is the best path forward for making progress in understanding ignition performance. The Program is oriented toward a milestone in 2020 for “determining the efficacy of NIF for ignition and credible physics-scaling to multi-megajoule yields for all ICF approaches.” We are concerned that the time and resources are not sufficient to vet all of the various approaches that are beingmore » pursued to make an informed decision by this date. For NIF to meet this goal, a process will be needed to to select the most promising paths forward. We recommend that the Program develop this process for selecting the path forward to optimize resources. We were glad to see that the direct drive program took our comments under consideration. We think that the proposed experiments have the program headed in a better direction. The PRP had only a short time to discuss the detailed experimental proposals. The following are comments on the detailed proposals. We did not have time to discuss them as a group. They represent individual opinions and provided to you as feedback to your proposals.« less

Vertical Field of View Reference Point Study for Flight Path Control and Hazard Avoidance

NASA Technical Reports Server (NTRS)

Comstock, J. Raymond, Jr.; Rudisill, Marianne; Kramer, Lynda J.; Busquets, Anthony M.

2002-01-01

Researchers within the eXternal Visibility System (XVS) element of the High-Speed Research (HSR) program developed and evaluated display concepts that will provide the flight crew of the proposed High-Speed Civil Transport (HSCT) with integrated imagery and symbology to permit path control and hazard avoidance functions while maintaining required situation awareness. The challenge of the XVS program is to develop concepts that would permit a no-nose-droop configuration of an HSCT and expanded low visibility HSCT operational capabilities. This study was one of a series of experiments exploring the 'design space' restrictions for physical placement of an XVS display. The primary experimental issues here was 'conformality' of the forward display vertical position with respect to the side window in simulated flight. 'Conformality' refers to the case such that the horizon and objects appear in the same relative positions when viewed through the forward windows or display and the side windows. This study quantified the effects of visual conformality on pilot flight path control and hazard avoidance performance. Here, conformality related to the positioning and relationship of the artificial horizon line and associated symbology presented on the forward display and the horizon and associated ground, horizon, and sky textures as they would appear in the real view through a window presented in the side window display. No significant performance consequences were found for the non-conformal conditions.

MO-F-CAMPUS-T-03: Continuous Dose Delivery with Gamma Knife Perfexion

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

Ghobadi,; Li, W; Chung, C

2015-06-15

Purpose: We propose continuous dose delivery techniques for stereotactic treatments delivered by Gamma Knife Perfexion using inverse treatment planning system that can be applied to various tumour sites in the brain. We test the accuracy of the plans on Perfexion’s planning system (GammaPlan) to ensure the obtained plans are viable. This approach introduces continuous dose delivery for Perefxion, as opposed to the currently employed step-and-shoot approaches, for different tumour sites. Additionally, this is the first realization of automated inverse planning on GammaPlan. Methods: The inverse planning approach is divided into two steps of identifying a quality path inside the target,more » and finding the best collimator composition for the path. To find a path, we select strategic regions inside the target volume and find a path that visits each region exactly once. This path is then passed to a mathematical model which finds the best combination of collimators and their durations. The mathematical model minimizes the dose spillage to the surrounding tissues while ensuring the prescribed dose is delivered to the target(s). Organs-at-risk and their corresponding allowable doses can also be added to the model to protect adjacent organs. Results: We test this approach on various tumour sizes and sites. The quality of the obtained treatment plans are comparable or better than forward plans and inverse plans that use step- and-shoot technique. The conformity indices in the obtained continuous dose delivery plans are similar to those of forward plans while the beam-on time is improved on average (see Table 1 in supporting document). Conclusion: We employ inverse planning for continuous dose delivery in Perfexion for brain tumours. The quality of the obtained plans is similar to forward and inverse plans that use conventional step-and-shoot technique. We tested the inverse plans on GammaPlan to verify clinical relevance. This research was partially supported by Elekta, Sweden (vendor of Gamma Knife Perfexion)« less

Multi-criteria robustness analysis of metro networks

NASA Astrophysics Data System (ADS)

Wang, Xiangrong; Koç, Yakup; Derrible, Sybil; Ahmad, Sk Nasir; Pino, Willem J. A.; Kooij, Robert E.

2017-05-01

Metros (heavy rail transit systems) are integral parts of urban transportation systems. Failures in their operations can have serious impacts on urban mobility, and measuring their robustness is therefore critical. Moreover, as physical networks, metros can be viewed as topological entities, and as such they possess measurable network properties. In this article, by using network science and graph theory, we investigate ten theoretical and four numerical robustness metrics and their performance in quantifying the robustness of 33 metro networks under random failures or targeted attacks. We find that the ten theoretical metrics capture two distinct aspects of robustness of metro networks. First, several metrics place an emphasis on alternative paths. Second, other metrics place an emphasis on the length of the paths. To account for all aspects, we standardize all ten indicators and plot them on radar diagrams to assess the overall robustness for metro networks. Overall, we find that Tokyo and Rome are the most robust networks. Rome benefits from short transferring and Tokyo has a significant number of transfer stations, both in the city center and in the peripheral area of the city, promoting both a higher number of alternative paths and overall relatively short path-lengths.

Adaptive Reliable Routing Protocol Using Combined Link Stability Estimation for Mobile Ad hoc Networks

NASA Astrophysics Data System (ADS)

Vadivel, R.; Bhaskaran, V. Murali

2010-10-01

The main reason for packet loss in ad hoc networks is the link failure or node failure. In order to increase the path stability, it is essential to distinguish and moderate the failures. By knowing individual link stability along a path, path stability can be identified. In this paper, we develop an adaptive reliable routing protocol using combined link stability estimation for mobile ad hoc networks. The main objective of this protocol is to determine a Quality of Service (QoS) path along with prolonging the network life time and to reduce the packet loss. We calculate a combined metric for a path based on the parameters Link Expiration Time, Node Remaining Energy and Node Velocity and received signal strength to predict the link stability or lifetime. Then, a bypass route is established to retransmit the lost data, when a link failure occurs. By simulation results, we show that the proposed reliable routing protocol achieves high delivery ratio with reduced delay and packet drop.

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

Drivers anticipate lead-vehicle conflicts during automated longitudinal control: Sensory cues capture driver attention and promote appropriate and timely responses.

PubMed

Morando, Alberto; Victor, Trent; Dozza, Marco

2016-12-01

Adaptive Cruise Control (ACC) has been shown to reduce the exposure to critical situations by maintaining a safe speed and headway. It has also been shown that drivers adapt their visual behavior in response to the driving task demand with ACC, anticipating an impending lead vehicle conflict by directing their eyes to the forward path before a situation becomes critical. The purpose of this paper is to identify the causes related to this anticipatory mechanism, by investigating drivers' visual behavior while driving with ACC when a potential critical situation is encountered, identified as a forward collision warning (FCW) onset (including false positive warnings). This paper discusses how sensory cues capture attention to the forward path in anticipation of the FCW onset. The analysis used the naturalistic database EuroFOT to examine visual behavior with respect to two manually-coded metrics, glance location and glance eccentricity, and then related the findings to vehicle data (such as speed, acceleration, and radar information). Three sensory cues (longitudinal deceleration, looming, and brake lights) were found to be relevant for capturing driver attention and increase glances to the forward path in anticipation of the threat; the deceleration cue seems to be dominant. The results also show that the FCW acts as an effective attention-orienting mechanism when no threat anticipation is present. These findings, relevant to the study of automation, provide additional information about drivers' response to potential lead-vehicle conflicts when longitudinal control is automated. Moreover, these results suggest that sensory cues are important for alerting drivers to an impending critical situation, allowing for a prompt reaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Windshear certification data base for forward-look detection systems

NASA Technical Reports Server (NTRS)

Switzer, George F.; Hinton, David A.; Proctor, Fred H.

1994-01-01

Described is an introduction to a comprehensive database that is to be used for certification testing of airborne forward-look windshear detection systems. The database was developed by NASA Langley Research Center, at the request of the Federal Aviation Administration (FAA), to support the industry initiative to certify and produce forward-looking windshear detection equipment. The database contains high-resolution three-dimensional fields for meteorological variables that may be sensed by forward-looking systems. The database is made up of seven case studies that are generated by the Terminal Area Simulation System, a state-of-the-art numerical system for the realistic modeling of windshear phenomena. The selected cases contained in the certification documentation represent a wide spectrum of windshear events. The database will be used with vendor-developed sensor simulation software and vendor-collected ground-clutter data to demonstrate detection performance in a variety of meteorological conditions using NASA/FAA pre-defined path scenarios for each of the certification cases. A brief outline of the contents and sample plots from the database documentation are included. These plots show fields of hazard factor, or F-factor (Bowles 1990), radar reflectivity, and velocity vectors on a horizontal plane overlayed with the applicable certification paths. For the plot of the F-factor field the region of 0.105 and above signify an area of hazardous, performance decreasing windshear, while negative values indicate regions of performance increasing windshear. The values of F-factor are based on 1-Km averaged segments along horizontal flight paths, assuming an air speed of 150 knots (approx. 75 m/s). The database has been released to vendors participating in the certification process. The database and associated document have been transferred to the FAA for archival storage and distribution.

Modeling the average shortest-path length in growth of word-adjacency networks

NASA Astrophysics Data System (ADS)

Kulig, Andrzej; DroŻdŻ, Stanisław; Kwapień, Jarosław; OświÈ©cimka, Paweł

2015-03-01

We investigate properties of evolving linguistic networks defined by the word-adjacency relation. Such networks belong to the category of networks with accelerated growth but their shortest-path length appears to reveal the network size dependence of different functional form than the ones known so far. We thus compare the networks created from literary texts with their artificial substitutes based on different variants of the Dorogovtsev-Mendes model and observe that none of them is able to properly simulate the novel asymptotics of the shortest-path length. Then, we identify the local chainlike linear growth induced by grammar and style as a missing element in this model and extend it by incorporating such effects. It is in this way that a satisfactory agreement with the empirical result is obtained.

[Not Available].

PubMed

Yanashima, Ryoji; Kitagawa, Noriyuki; Matsubara, Yoshiya; Weatheritt, Robert; Oka, Kotaro; Kikuchi, Shinichi; Tomita, Masaru; Ishizaki, Shun

2009-01-01

The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

Evolvable Neuronal Paths: A Novel Basis for Information and Search in the Brain

PubMed Central

Fernando, Chrisantha; Vasas, Vera; Szathmáry, Eörs; Husbands, Phil

2011-01-01

We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques) which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard ‘genetic’ informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA) is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain. PMID:21887266

Design and Analysis of A Beacon-Less Routing Protocol for Large Volume Content Dissemination in Vehicular Ad Hoc Networks.

PubMed

Hu, Miao; Zhong, Zhangdui; Ni, Minming; Baiocchi, Andrea

2016-11-01

Large volume content dissemination is pursued by the growing number of high quality applications for Vehicular Ad hoc NETworks(VANETs), e.g., the live road surveillance service and the video-based overtaking assistant service. For the highly dynamical vehicular network topology, beacon-less routing protocols have been proven to be efficient in achieving a balance between the system performance and the control overhead. However, to the authors' best knowledge, the routing design for large volume content has not been well considered in the previous work, which will introduce new challenges, e.g., the enhanced connectivity requirement for a radio link. In this paper, a link Lifetime-aware Beacon-less Routing Protocol (LBRP) is designed for large volume content delivery in VANETs. Each vehicle makes the forwarding decision based on the message header information and its current state, including the speed and position information. A semi-Markov process analytical model is proposed to evaluate the expected delay in constructing one routing path for LBRP. Simulations show that the proposed LBRP scheme outperforms the traditional dissemination protocols in providing a low end-to-end delay. The analytical model is shown to exhibit a good match on the delay estimation with Monte Carlo simulations, as well.

Design and Analysis of A Beacon-Less Routing Protocol for Large Volume Content Dissemination in Vehicular Ad Hoc Networks

PubMed Central

Hu, Miao; Zhong, Zhangdui; Ni, Minming; Baiocchi, Andrea

2016-01-01

Large volume content dissemination is pursued by the growing number of high quality applications for Vehicular Ad hoc NETworks(VANETs), e.g., the live road surveillance service and the video-based overtaking assistant service. For the highly dynamical vehicular network topology, beacon-less routing protocols have been proven to be efficient in achieving a balance between the system performance and the control overhead. However, to the authors’ best knowledge, the routing design for large volume content has not been well considered in the previous work, which will introduce new challenges, e.g., the enhanced connectivity requirement for a radio link. In this paper, a link Lifetime-aware Beacon-less Routing Protocol (LBRP) is designed for large volume content delivery in VANETs. Each vehicle makes the forwarding decision based on the message header information and its current state, including the speed and position information. A semi-Markov process analytical model is proposed to evaluate the expected delay in constructing one routing path for LBRP. Simulations show that the proposed LBRP scheme outperforms the traditional dissemination protocols in providing a low end-to-end delay. The analytical model is shown to exhibit a good match on the delay estimation with Monte Carlo simulations, as well. PMID:27809285

A Data-Gathering Scheme with Joint Routing and Compressive Sensing Based on Modified Diffusion Wavelets in Wireless Sensor Networks.

PubMed

Gu, Xiangping; Zhou, Xiaofeng; Sun, Yanjing

2018-02-28

Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measurement task, resulting in high energy consumption, and do not guarantee load balance. In this paper, we propose a sparser analysis that depends on modified diffusion wavelets, which exploit sensor readings' spatial correlation in WSNs. In particular, a novel data-gathering scheme with joint routing and CS is presented. A modified ant colony algorithm is adopted, where next hop node selection takes a node's residual energy and path length into consideration simultaneously. Moreover, in order to speed up the coverage rate and avoid the local optimal of the algorithm, an improved pheromone impact factor is put forward. More importantly, theoretical proof is given that the equivalent sensing matrix generated can satisfy the restricted isometric property (RIP). The simulation results demonstrate that the modified diffusion wavelets' sparsity affects the sensor signal and has better reconstruction performance than DFT. Furthermore, our data gathering with joint routing and CS can dramatically reduce the energy consumption of WSNs, balance the load, and prolong the network lifetime in comparison to state-of-the-art CS-based methods.

Diversified Control Paths: A Significant Way Disease Genes Perturb the Human Regulatory Network

PubMed Central

Wang, Bingbo; Gao, Lin; Zhang, Qingfang; Li, Aimin; Deng, Yue; Guo, Xingli

2015-01-01

Background The complexity of biological systems motivates us to use the underlying networks to provide deep understanding of disease etiology and the human diseases are viewed as perturbations of dynamic properties of networks. Control theory that deals with dynamic systems has been successfully used to capture systems-level knowledge in large amount of quantitative biological interactions. But from the perspective of system control, the ways by which multiple genetic factors jointly perturb a disease phenotype still remain. Results In this work, we combine tools from control theory and network science to address the diversified control paths in complex networks. Then the ways by which the disease genes perturb biological systems are identified and quantified by the control paths in a human regulatory network. Furthermore, as an application, prioritization of candidate genes is presented by use of control path analysis and gene ontology annotation for definition of similarities. We use leave-one-out cross-validation to evaluate the ability of finding the gene-disease relationship. Results have shown compatible performance with previous sophisticated works, especially in directed systems. Conclusions Our results inspire a deeper understanding of molecular mechanisms that drive pathological processes. Diversified control paths offer a basis for integrated intervention techniques which will ultimately lead to the development of novel therapeutic strategies. PMID:26284649

A source-controlled data center network model.

PubMed

Yu, Yang; Liang, Mangui; Wang, Zhe

2017-01-01

The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN) model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA) as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1) The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2) Vector switches (VS) developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3) The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4) We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS.

A source-controlled data center network model

PubMed Central

Yu, Yang; Liang, Mangui; Wang, Zhe

2017-01-01

The construction of data center network by applying SDN technology has become a hot research topic. The SDN architecture has innovatively separated the control plane from the data plane which makes the network more software-oriented and agile. Moreover, it provides virtual multi-tenancy, effective scheduling resources and centralized control strategies to meet the demand for cloud computing data center. However, the explosion of network information is facing severe challenges for SDN controller. The flow storage and lookup mechanisms based on TCAM device have led to the restriction of scalability, high cost and energy consumption. In view of this, a source-controlled data center network (SCDCN) model is proposed herein. The SCDCN model applies a new type of source routing address named the vector address (VA) as the packet-switching label. The VA completely defines the communication path and the data forwarding process can be finished solely relying on VA. There are four advantages in the SCDCN architecture. 1) The model adopts hierarchical multi-controllers and abstracts large-scale data center network into some small network domains that has solved the restriction for the processing ability of single controller and reduced the computational complexity. 2) Vector switches (VS) developed in the core network no longer apply TCAM for table storage and lookup that has significantly cut down the cost and complexity for switches. Meanwhile, the problem of scalability can be solved effectively. 3) The SCDCN model simplifies the establishment process for new flows and there is no need to download flow tables to VS. The amount of control signaling consumed when establishing new flows can be significantly decreased. 4) We design the VS on the NetFPGA platform. The statistical results show that the hardware resource consumption in a VS is about 27% of that in an OFS. PMID:28328925

The 3 R's of Learning Time: Rethink, Reshape, Reclaim

ERIC Educational Resources Information Center

Sackey, Shera Carter

2012-01-01

The Learning School Alliance is a network of schools collaborating about professional practice. The network embodies Learning Forward's purpose to advance effective job-embedded professional learning that leads to student outcomes. A key component of Learning Forward's Standards for Professional Learning is a focus on collaborative learning,…

Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

NASA Astrophysics Data System (ADS)

Hoomod, Haider K.; Kareem Jebur, Tuka

2018-05-01

Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

Path scanning for the detection of anomalous subgraphs and use of DNS requests and host agents for anomaly/change detection and network situational awareness

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

Neil, Joshua Charles; Fisk, Michael Edward; Brugh, Alexander William

A system, apparatus, computer-readable medium, and computer-implemented method are provided for detecting anomalous behavior in a network. Historical parameters of the network are determined in order to determine normal activity levels. A plurality of paths in the network are enumerated as part of a graph representing the network, where each computing system in the network may be a node in the graph and the sequence of connections between two computing systems may be a directed edge in the graph. A statistical model is applied to the plurality of paths in the graph on a sliding window basis to detect anomalousmore » behavior. Data collected by a Unified Host Collection Agent ("UHCA") may also be used to detect anomalous behavior.« less

Positioning of Ionospheric Irregularities and the Earth's Surface Roughness Using an Over-the-Horizon HF Radar

NASA Astrophysics Data System (ADS)

Uryadov, V. P.; Vertogradov, G. G.; Sklyarevsky, M. S.; Vybornov, F. I.

2018-02-01

We realize the possibilities for positioning of ionospheric irregularities and the Earth's surface roughness with the chirp-signal ionosonde-radio direction finder used as an over-the-horizon HF radar of bistatic configuration on the Cyprus — Rostov-on-Don and Australia — Rostov-on-Don paths. It is established that the small-amplitude diffuse signals coming from azimuths of 310°-50° on the Cyprus — Rostov-on-Don path in the evening and at night at frequencies above the maximum observable frequency (MOF) of the forward signal are due to backscattering by small-scale irregularities of the mid-latitude ionospheric F Layer. It is shown that the backward obliquesounding signals recorded on the Cyprus — Rostov-on-Don path are caused by the sideband scattering of radio waves from the Caucasus mountain ranges, the Iranian highlands, and the Balkan mountains. It is found that the anomalous signals observed on the Alice Springs (Australia) — Rostov-on-Don path, which come from azimuths of 10°-25° with delays by 10-16 ms exceeding the delay of the forward signal are due to scattering of radio waves by the high-latitude ionospheric F-layer irregularities localized in the evening sector of the auroral oval at latitudes of 70°-80° N.

Quality of service routing in wireless ad hoc networks

NASA Astrophysics Data System (ADS)

Sane, Sachin J.; Patcha, Animesh; Mishra, Amitabh

2003-08-01

An efficient routing protocol is essential to guarantee application level quality of service running on wireless ad hoc networks. In this paper we propose a novel routing algorithm that computes a path between a source and a destination by considering several important constraints such as path-life, availability of sufficient energy as well as buffer space in each of the nodes on the path between the source and destination. The algorithm chooses the best path from among the multiples paths that it computes between two endpoints. We consider the use of control packets that run at a priority higher than the data packets in determining the multiple paths. The paper also examines the impact of different schedulers such as weighted fair queuing, and weighted random early detection among others in preserving the QoS level guarantees. Our extensive simulation results indicate that the algorithm improves the overall lifetime of a network, reduces the number of dropped packets, and decreases the end-to-end delay for real-time voice application.

Zero-Slack, Noncritical Paths

ERIC Educational Resources Information Center

Simons, Jacob V., Jr.

2017-01-01

The critical path method/program evaluation and review technique method of project scheduling is based on the importance of managing a project's critical path(s). Although a critical path is the longest path through a network, its location in large projects is facilitated by the computation of activity slack. However, logical fallacies in…

The DSFPN, a new neural network for optical character recognition.

PubMed

Morns, L P; Dlay, S S

1999-01-01

A new type of neural network for recognition tasks is presented in this paper. The network, called the dynamic supervised forward-propagation network (DSFPN), is based on the forward only version of the counterpropagation network (CPN). The DSFPN, trains using a supervised algorithm and can grow dynamically during training, allowing subclasses in the training data to be learnt in an unsupervised manner. It is shown to train in times comparable to the CPN while giving better classification accuracies than the popular backpropagation network. Both Fourier descriptors and wavelet descriptors are used for image preprocessing and the wavelets are proven to give a far better performance.

A mathematical model for adaptive transport network in path finding by true slime mold.

PubMed

Tero, Atsushi; Kobayashi, Ryo; Nakagaki, Toshiyuki

2007-02-21

We describe here a mathematical model of the adaptive dynamics of a transport network of the true slime mold Physarum polycephalum, an amoeboid organism that exhibits path-finding behavior in a maze. This organism possesses a network of tubular elements, by means of which nutrients and signals circulate through the plasmodium. When the organism is put in a maze, the network changes its shape to connect two exits by the shortest path. This process of path-finding is attributed to an underlying physiological mechanism: a tube thickens as the flux through it increases. The experimental evidence for this is, however, only qualitative. We constructed a mathematical model of the general form of the tube dynamics. Our model contains a key parameter corresponding to the extent of the feedback regulation between the thickness of a tube and the flux through it. We demonstrate the dependence of the behavior of the model on this parameter.

Path integration of head direction: updating a packet of neural activity at the correct speed using axonal conduction delays.

PubMed

Walters, Daniel; Stringer, Simon; Rolls, Edmund

2013-01-01

The head direction cell system is capable of accurately updating its current representation of head direction in the absence of visual input. This is known as the path integration of head direction. An important question is how the head direction cell system learns to perform accurate path integration of head direction. In this paper we propose a model of velocity path integration of head direction in which the natural time delay of axonal transmission between a linked continuous attractor network and competitive network acts as a timing mechanism to facilitate the correct speed of path integration. The model effectively learns a "look-up" table for the correct speed of path integration. In simulation, we show that the model is able to successfully learn two different speeds of path integration across two different axonal conduction delays, and without the need to alter any other model parameters. An implication of this model is that, by learning look-up tables for each speed of path integration, the model should exhibit a degree of robustness to damage. In simulations, we show that the speed of path integration is not significantly affected by degrading the network through removing a proportion of the cells that signal rotational velocity.

Path Integration of Head Direction: Updating a Packet of Neural Activity at the Correct Speed Using Axonal Conduction Delays

PubMed Central

Walters, Daniel; Stringer, Simon; Rolls, Edmund

2013-01-01

The head direction cell system is capable of accurately updating its current representation of head direction in the absence of visual input. This is known as the path integration of head direction. An important question is how the head direction cell system learns to perform accurate path integration of head direction. In this paper we propose a model of velocity path integration of head direction in which the natural time delay of axonal transmission between a linked continuous attractor network and competitive network acts as a timing mechanism to facilitate the correct speed of path integration. The model effectively learns a “look-up” table for the correct speed of path integration. In simulation, we show that the model is able to successfully learn two different speeds of path integration across two different axonal conduction delays, and without the need to alter any other model parameters. An implication of this model is that, by learning look-up tables for each speed of path integration, the model should exhibit a degree of robustness to damage. In simulations, we show that the speed of path integration is not significantly affected by degrading the network through removing a proportion of the cells that signal rotational velocity. PMID:23526976

Network Design for Reliability and Resilience to Attack

DTIC Science & Technology

2014-03-01

attacker can destroy n arcs in the network SPNI Shortest-Path Network-Interdiction problem TSP Traveling Salesman Problem UB upper bound UKR Ukraine...elimination from the traveling salesman problem (TSP). Literature calls a walk that does not contain a cycle a path [19]. The objective function in...arc lengths as random variables with known probability distributions. The m-median problem seeks to design a network with minimum average travel cost

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks

PubMed Central

Mahjoub, Reem K.; Elleithy, Khaled

2017-01-01

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation. PMID:28420102

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks.

PubMed

Mahjoub, Reem K; Elleithy, Khaled

2017-04-14

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.

Remote Asynchronous Message Service Gateway

NASA Technical Reports Server (NTRS)

Wang, Shin-Ywan; Burleigh, Scott C.

2011-01-01

The Remote Asynchronous Message Service (RAMS) gateway is a special-purpose AMS application node that enables exchange of AMS messages between nodes residing in different AMS "continua," notionally in different geographical locations. JPL s implementation of RAMS gateway functionality is integrated with the ION (Interplanetary Overlay Network) implementation of the DTN (Delay-Tolerant Networking) bundle protocol, and with JPL s implementation of AMS itself. RAMS protocol data units are encapsulated in ION bundles and are forwarded to the neighboring RAMS gateways identified in the source gateway s AMS management information base. Each RAMS gateway has interfaces in two communication environments: the AMS message space it serves, and the RAMS network - the grid or tree of mutually aware RAMS gateways - that enables AMS messages produced in one message space to be forwarded to other message spaces of the same venture. Each gateway opens persistent, private RAMS network communication channels to the RAMS gateways of other message spaces for the same venture, in other continua. The interconnected RAMS gateways use these communication channels to forward message petition assertions and cancellations among themselves. Each RAMS gateway subscribes locally to all subjects that are of interest in any of the linked message spaces. On receiving its copy of a message on any of these subjects, the RAMS gateway node uses the RAMS network to forward the message to every other RAMS gateway whose message space contains at least one node that has subscribed to messages on that subject. On receiving a message via the RAMS network from some other RAMS gateway, the RAMS gateway node forwards the message to all subscribers in its own message space.

A mixed incoherent feed-forward loop contributes to the regulation of bacterial photosynthesis genes.

PubMed

Mank, Nils N; Berghoff, Bork A; Klug, Gabriele

2013-03-01

Living cells use a variety of regulatory network motifs for accurate gene expression in response to changes in their environment or during differentiation processes. In Rhodobacter sphaeroides, a complex regulatory network controls expression of photosynthesis genes to guarantee optimal energy supply on one hand and to avoid photooxidative stress on the other hand. Recently, we identified a mixed incoherent feed-forward loop comprising the transcription factor PrrA, the sRNA PcrZ and photosynthesis target genes as part of this regulatory network. This point-of-view provides a comparison to other described feed-forward loops and discusses the physiological relevance of PcrZ in more detail.

A mixed incoherent feed-forward loop contributes to the regulation of bacterial photosynthesis genes

PubMed Central

Mank, Nils N.; Berghoff, Bork A.; Klug, Gabriele

2013-01-01

Living cells use a variety of regulatory network motifs for accurate gene expression in response to changes in their environment or during differentiation processes. In Rhodobacter sphaeroides, a complex regulatory network controls expression of photosynthesis genes to guarantee optimal energy supply on one hand and to avoid photooxidative stress on the other hand. Recently, we identified a mixed incoherent feed-forward loop comprising the transcription factor PrrA, the sRNA PcrZ and photosynthesis target genes as part of this regulatory network. This point-of-view provides a comparison to other described feed-forward loops and discusses the physiological relevance of PcrZ in more detail. PMID:23392242

14 CFR 25.1321 - Arrangement and visibility.

Code of Federal Regulations, 2010 CFR

2010-01-01

... and line of vision when he is looking forward along the flight path. (b) The flight instruments... center position. (c) Required powerplant instruments must be closely grouped on the instrument panel. In...

14 CFR 25.1321 - Arrangement and visibility.

Code of Federal Regulations, 2011 CFR

2011-01-01

... and line of vision when he is looking forward along the flight path. (b) The flight instruments... center position. (c) Required powerplant instruments must be closely grouped on the instrument panel. In...

A framework for assessing cumulative effects in watersheds: an introduction to Canadian case studies.

PubMed

Dubé, Monique G; Duinker, Peter; Greig, Lorne; Carver, Martin; Servos, Mark; McMaster, Mark; Noble, Bram; Schreier, Hans; Jackson, Lee; Munkittrick, Kelly R

2013-07-01

From 2008 to 2013, a series of studies supported by the Canadian Water Network were conducted in Canadian watersheds in an effort to improve methods to assess cumulative effects. These studies fit under a common framework for watershed cumulative effects assessment (CEA). This article presents an introduction to the Special Series on Watershed CEA in IEAM including the framework and its impetus, a brief introduction to each of the articles in the series, challenges, and a path forward. The framework includes a regional water monitoring program that produces 3 core outputs: an accumulated state assessment, stressor-response relationships, and development of predictive cumulative effects scenario models. The framework considers core values, indicators, thresholds, and use of consistent terminology. It emphasizes that CEA requires 2 components, accumulated state quantification and predictive scenario forecasting. It recognizes both of these components must be supported by a regional, multiscale monitoring program. Copyright © 2013 SETAC.

Guiding electrical current in nanotube circuits using structural defects: a step forward in nanoelectronics.

PubMed

Romo-Herrera, Jose M; Terrones, Mauricio; Terrones, Humberto; Meunier, Vincent

2008-12-23

Electrical current could be efficiently guided in 2D nanotube networks by introducing specific topological defects within the periodic framework. Using semiempirical transport calculations coupled with Landauer-Buttiker formalism of quantum transport in multiterminal nanoscale systems, we provide a detailed analysis of the processes governing the atomic-scale design of nanotube circuits. We found that when defects are introduced as patches in specific sites, they act as bouncing centers that reinject electrons along specific paths, via a wave reflection process. This type of defects can be incorporated while preserving the 3-fold connectivity of each carbon atom embedded within the graphitic lattice. Our findings open up a new way to explore bottom-up design, at the nanometer scale, of complex nanotube circuits which could be extended to 3D nanosystems and applied in the fabrication of nanoelectronic devices.

Introduction to multiprotocol over ATM (MPOA)

NASA Astrophysics Data System (ADS)

Fredette, Andre N.

1997-10-01

Multiprotocol over ATM (MPOA) is a new protocol specified by the ATM Forum. MPOA provides a framework for effectively synthesizing bridging and routing with ATM in an environment of diverse protocols and network technologies. The primary goal of MPOA is the efficient transfer of inter-subnet unicast data in a LAN Emulation (LANE) environment. MPOA integrates LANE and the next hop resolution protocol (NHRP) to preserve the benefits of LAN Emulation, while allowing inter-subnet, internetwork layer protocol communication over ATM VCCs without requiring routers in the data path. It reduces latency and the internetwork layer forwarding load on backbone routers by enabling direct connectivity between ATM-attached edge devices (i.e., shortcuts). To establish these shortcuts, MPOA uses both routing and bridging information to locate the edge device closest to the addressed end station. By integrating LANE and NHRP, MPOA allows the physical separation of internetwork layer route calculation and forwarding, a technique known as virtual routing. This separation provides a number of key benefits including enhanced manageability and reduced complexity of internetwork layer capable edge devices. This paper provides an overview of MPOA that summarizes the goals, architecture, and key attributes of the protocol. In presenting this overview, the salient attributes of LANE and NHRP are described as well.

Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search

PubMed Central

Riesco, Adrián; Santos-Buitrago, Beatriz; De Las Rivas, Javier; Knapp, Merrill; Talcott, Carolyn

2017-01-01

In biological systems, pathways define complex interaction networks where multiple molecular elements are involved in a series of controlled reactions producing responses to specific biomolecular signals. These biosystems are dynamic and there is a need for mathematical and computational methods able to analyze the symbolic elements and the interactions between them and produce adequate readouts of such systems. In this work, we use rewriting logic to analyze the cellular signaling of epidermal growth factor (EGF) and its cell surface receptor (EGFR) in order to induce cellular proliferation. Signaling is initiated by binding the ligand protein EGF to the membrane-bound receptor EGFR so as to trigger a reactions path which have several linked elements through the cell from the membrane till the nucleus. We present two different types of search for analyzing the EGF/proliferation system with the help of Pathway Logic tool, which provides a knowledge-based development environment to carry out the modeling of the signaling. The first one is a standard (forward) search. The second one is a novel approach based on narrowing, which allows us to trace backwards the causes of a given final state. The analysis allows the identification of critical elements that have to be activated to provoke proliferation. PMID:28191459

Towards Internet QoS provisioning based on generic distributed QoS adaptive routing engine.

PubMed

Haikal, Amira Y; Badawy, M; Ali, Hesham A

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature.

Towards Internet QoS Provisioning Based on Generic Distributed QoS Adaptive Routing Engine

PubMed Central

Haikal, Amira Y.; Badawy, M.; Ali, Hesham A.

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature. PMID:25309955

Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search.

PubMed

Riesco, Adrián; Santos-Buitrago, Beatriz; De Las Rivas, Javier; Knapp, Merrill; Santos-García, Gustavo; Talcott, Carolyn

2017-01-01

In biological systems, pathways define complex interaction networks where multiple molecular elements are involved in a series of controlled reactions producing responses to specific biomolecular signals. These biosystems are dynamic and there is a need for mathematical and computational methods able to analyze the symbolic elements and the interactions between them and produce adequate readouts of such systems. In this work, we use rewriting logic to analyze the cellular signaling of epidermal growth factor (EGF) and its cell surface receptor (EGFR) in order to induce cellular proliferation. Signaling is initiated by binding the ligand protein EGF to the membrane-bound receptor EGFR so as to trigger a reactions path which have several linked elements through the cell from the membrane till the nucleus. We present two different types of search for analyzing the EGF/proliferation system with the help of Pathway Logic tool, which provides a knowledge-based development environment to carry out the modeling of the signaling. The first one is a standard (forward) search. The second one is a novel approach based on narrowing , which allows us to trace backwards the causes of a given final state. The analysis allows the identification of critical elements that have to be activated to provoke proliferation.

PathCase-SB architecture and database design

PubMed Central

2011-01-01

Background Integration of metabolic pathways resources and regulatory metabolic network models, and deploying new tools on the integrated platform can help perform more effective and more efficient systems biology research on understanding the regulation in metabolic networks. Therefore, the tasks of (a) integrating under a single database environment regulatory metabolic networks and existing models, and (b) building tools to help with modeling and analysis are desirable and intellectually challenging computational tasks. Description PathCase Systems Biology (PathCase-SB) is built and released. The PathCase-SB database provides data and API for multiple user interfaces and software tools. The current PathCase-SB system provides a database-enabled framework and web-based computational tools towards facilitating the development of kinetic models for biological systems. PathCase-SB aims to integrate data of selected biological data sources on the web (currently, BioModels database and KEGG), and to provide more powerful and/or new capabilities via the new web-based integrative framework. This paper describes architecture and database design issues encountered in PathCase-SB's design and implementation, and presents the current design of PathCase-SB's architecture and database. Conclusions PathCase-SB architecture and database provide a highly extensible and scalable environment with easy and fast (real-time) access to the data in the database. PathCase-SB itself is already being used by researchers across the world. PMID:22070889

Simulation and modeling of the temporal performance of path-based restoration schemes in planar mesh networks

NASA Astrophysics Data System (ADS)

Bhardwaj, Manish; McCaughan, Leon; Olkhovets, Anatoli; Korotky, Steven K.

2006-12-01

We formulate an analytic framework for the restoration performance of path-based restoration schemes in planar mesh networks. We analyze various switch architectures and signaling schemes and model their total restoration interval. We also evaluate the network global expectation value of the time to restore a demand as a function of network parameters. We analyze a wide range of nominally capacity-optimal planar mesh networks and find our analytic model to be in good agreement with numerical simulation data.

Deforestation and Industrial Forest Patterns in Colombia: a Case Study

NASA Astrophysics Data System (ADS)

Huo, L. Z.; Boschetti, L.; Sparks, A. M.; Clerici, N.

2017-12-01

The recent peace agreement between the government and the Revolutionary Armed Forces of Colombia (FARC) offers new opportunities for peaceful and sustainable development, but at the same time requires a timely effort to protect biological resources, and ecosystem services (Clerici et al., 2016). In this context, we use the 2001-2017 Landsat data record to prototype a methodology to establish a baseline of deforestation, afforestation and industrial forest practices (i.e. establishment and harvest of forest plantations), and to monitor future changes. Two study areas, which have seen considerable deforestation in recent years, were selected: one in the South of the country, at the edge of the Amazon Forest (WRS path 008 row 059) and one in the center, in mixed forest (WRS path 008 row 055). The time series of all the available cloud free Landsat 5, Landsat 7 and Landsat 8 data was classified into a sequence of binary forest/non forest maps using a deep learning model, successfully used in the natural language processing field, trained to detect forest transitions. Recurrent Neural Networks (RNN) is a class of artificial neural network that extends the conventional neural network with loops in the connections (Graves et al., 2013). Unlike a feed-forward neural network, an RNN is able to process the sequential inputs by having a recurrent hidden state whose activation at each step depends on that of the previous steps. In this manner, the RNN provides a good framework to dynamically model time series data, and has been successfully applied to natural language processing in Google (Sutskever et al., 2014). The sequence of forest cover state maps was subsequently post-processed to differentiate between deforestation (e.g. transition from forest to non forest land use) and industrial forest harvest (i.e. timber harvest followed by regrowth), by integrating the detection of temporal patterns, and spatial patterns. References Clerici, N., et al., (2016). Colombia: Dealing in conservation. Science, 354(6309), 190-190. Sutskever I.,et al. (2014). Sequence to sequence learning with neural networks. Advances in neural information processing systems, 3104-3112. Graves A., et al. (2013). Speech recognition with deep recurrent neural networks. In Proc. IEEE Int. Conf. Acoust. Speech Signal Process., 6645-6649.

Heterogeneous path ensembles for conformational transitions in semi–atomistic models of adenylate kinase

PubMed Central

Bhatt, Divesh; Zuckerman, Daniel M.

2010-01-01

We performed “weighted ensemble” path–sampling simulations of adenylate kinase, using several semi–atomistic protein models. The models have an all–atom backbone with various levels of residue interactions. The primary result is that full statistically rigorous path sampling required only a few weeks of single–processor computing time with these models, indicating the addition of further chemical detail should be readily feasible. Our semi–atomistic path ensembles are consistent with previous biophysical findings: the presence of two distinct pathways, identification of intermediates, and symmetry of forward and reverse pathways. PMID:21660120

Design and development of flapping wing micro air vehicle

NASA Astrophysics Data System (ADS)

Hynes, N. Rajesh Jesudoss; Solomon, A. Jeffey Markus; Kathiresh, E.; Brighton, D.; Velu, P. Shenbaga

2018-05-01

Birds and insects have different methods of producing lift and thrust for hovering and forward flight. Most birds, however, cannot hover. Wing tips of birds follow simple paths in flight, whereas insects have very complicated wing tip paths, for hovering and forward flight, which vary with each species. FMAV based on avian flight. Development of Flapping Wing Air Vehicle (FWAV) is an on-going quest to master the natural flyers by mechanical means. It is characterized by unsteady aerodynamics, whose knowledge is still developing. The present work aims at include being capable of manoeuvring around and over obstacles by adjusting pitch, yaw, and roll, able to glide for five seconds under its own power, skilful at alternating between flapping and gliding with minimal disruption of flight pattern and being durable enough to withstand impacts with minimal to no damage.

Inflow measurement made with a laser velocimeter on a helicopter model in forward flight. Volume 3: Rectangular planform blades at an advance ratio of 0.30

NASA Technical Reports Server (NTRS)

Elliott, Joe W.; Althoff, Susan L.; Sailey, Richard H.

1988-01-01

An experimental investigation was conducted in the 14- by 22-Foot Subsonic Tunnel at NASA Langley Research Center to measure the inflow into a scale model helicopter rotor in forward flight (micron sub infinity = 0.30). The measurements were made with a two component Laser Velocimeter (LV) one chord above the plane formed by the path of the rotor tips (tip path plane). A conditional sampling technique was employed to determine the azimuthal position of the rotor at the time that each velocity measurement was made so that the azimuthal fluctuations in velocity could be determined. Measurements were made at a total of 180 separate locations in order to clearly define the inflow character. These data are presented without analysis.

Time signal distribution in communication networks based on synchronous digital hierarchy

NASA Technical Reports Server (NTRS)

Imaoka, Atsushi; Kihara, Masami

1993-01-01

A new method that uses round-trip paths to accurately measure transmission delay for time synchronization is proposed. The performance of the method in Synchronous Digital Hierarchy networks is discussed. The feature of this method is that it separately measures the initial round trip path delay and the variations in round-trip path delay. The delay generated in SDH equipment is determined by measuring the initial round-trip path delay. In an experiment with actual SDH equipment, the error of initial delay measurement was suppressed to 30ns.

Hopfield networks for solving Tower of Hanoi problems

NASA Astrophysics Data System (ADS)

Kaplan, G. B.; Güzeliş, Cüneyt

2001-08-01

In this paper, Hopfield neural networks have been considered in solving the Tower of Hanoi test which is used in the determining of deficit of planning capability of the human prefrontal cortex. The main difference between this paper and the ones in the literature which use neural networks is that the Tower of Hanoi problem has been formulated here as a special shortest-path problem. In the literature, some Hopfield networks are developed for solving the shortest path problem which is a combinatorial optimization problem having a diverse field of application. The approach given in this paper gives the possibility of solving the Tower of Hanoi problem using these Hopfield networks. Also, the paper proposes new Hopfield network models for the shortest path and hence the Tower of Hanoi problems and compares them to the available ones in terms of the memory and time (number of steps) needed in the simulations.

pathChirp: Efficient Available Bandwidth Estimation for Network Paths

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

Cottrell, Les

2003-04-30

This paper presents pathChirp, a new active probing tool for estimating the available bandwidth on a communication network path. Based on the concept of ''self-induced congestion,'' pathChirp features an exponential flight pattern of probes we call a chirp. Packet chips offer several significant advantages over current probing schemes based on packet pairs or packet trains. By rapidly increasing the probing rate within each chirp, pathChirp obtains a rich set of information from which to dynamically estimate the available bandwidth. Since it uses only packet interarrival times for estimation, pathChirp does not require synchronous nor highly stable clocks at the sendermore » and receiver. We test pathChirp with simulations and Internet experiments and find that it provides good estimates of the available bandwidth while using only a fraction of the number of probe bytes that current state-of-the-art techniques use.« less

Selection of test paths for solder joint intermittent connection faults under DC stimulus

NASA Astrophysics Data System (ADS)

Huakang, Li; Kehong, Lv; Jing, Qiu; Guanjun, Liu; Bailiang, Chen

2018-06-01

The test path of solder joint intermittent connection faults under direct-current stimulus is examined in this paper. According to the physical structure of the circuit, a network model is established first. A network node is utilised to represent the test node. The path edge refers to the number of intermittent connection faults in the path. Then, the selection criteria of the test path based on the node degree index are proposed and the solder joint intermittent connection faults are covered using fewer test paths. Finally, three circuits are selected to verify the method. To test if the intermittent fault is covered by the test paths, the intermittent fault is simulated by a switch. The results show that the proposed method can detect the solder joint intermittent connection fault using fewer test paths. Additionally, the number of detection steps is greatly reduced without compromising fault coverage.

Sink-oriented Dynamic Location Service Protocol for Mobile Sinks with an Energy Efficient Grid-Based Approach.

PubMed

Jeon, Hyeonjae; Park, Kwangjin; Hwang, Dae-Joon; Choo, Hyunseung

2009-01-01

Sensor nodes transmit the sensed information to the sink through wireless sensor networks (WSNs). They have limited power, computational capacities and memory. Portable wireless devices are increasing in popularity. Mechanisms that allow information to be efficiently obtained through mobile WSNs are of significant interest. However, a mobile sink introduces many challenges to data dissemination in large WSNs. For example, it is important to efficiently identify the locations of mobile sinks and disseminate information from multi-source nodes to the multi-mobile sinks. In particular, a stationary dissemination path may no longer be effective in mobile sink applications, due to sink mobility. In this paper, we propose a Sink-oriented Dynamic Location Service (SDLS) approach to handle sink mobility. In SDLS, we propose an Eight-Direction Anchor (EDA) system that acts as a location service server. EDA prevents intensive energy consumption at the border sensor nodes and thus provides energy balancing to all the sensor nodes. Then we propose a Location-based Shortest Relay (LSR) that efficiently forwards (or relays) data from a source node to a sink with minimal delay path. Our results demonstrate that SDLS not only provides an efficient and scalable location service, but also reduces the average data communication overhead in scenarios with multiple and moving sinks and sources.

On Channel-Discontinuity-Constraint Routing in Wireless Networks☆

PubMed Central

Sankararaman, Swaminathan; Efrat, Alon; Ramasubramanian, Srinivasan; Agarwal, Pankaj K.

2011-01-01

Multi-channel wireless networks are increasingly deployed as infrastructure networks, e.g. in metro areas. Network nodes frequently employ directional antennas to improve spatial throughput. In such networks, between two nodes, it is of interest to compute a path with a channel assignment for the links such that the path and link bandwidths are the same. This is achieved when any two consecutive links are assigned different channels, termed as “Channel-Discontinuity-Constraint” (CDC). CDC-paths are also useful in TDMA systems, where, preferably, consecutive links are assigned different time-slots. In the first part of this paper, we develop a t-spanner for CDC-paths using spatial properties; a sub-network containing O(n/θ) links, for any θ > 0, such that CDC-paths increase in cost by at most a factor t = (1−2 sin (θ/2))−2. We propose a novel distributed algorithm to compute the spanner using an expected number of O(n log n) fixed-size messages. In the second part, we present a distributed algorithm to find minimum-cost CDC-paths between two nodes using O(n2) fixed-size messages, by developing an extension of Edmonds’ algorithm for minimum-cost perfect matching. In a centralized implementation, our algorithm runs in O(n2) time improving the previous best algorithm which requires O(n3) running time. Moreover, this running time improves to O(n/θ) when used in conjunction with the spanner developed. PMID:24443646

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

NASA Technical Reports Server (NTRS)

Alena, Richard I.; Lee, Charles

2004-01-01

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Chain-Based Communication in Cylindrical Underwater Wireless Sensor Networks

PubMed Central

Javaid, Nadeem; Jafri, Mohsin Raza; Khan, Zahoor Ali; Alrajeh, Nabil; Imran, Muhammad; Vasilakos, Athanasios

2015-01-01

Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs). Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS) and Congestion adjusted PEGASIS (C-PEGASIS). Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate. PMID:25658394

All-Optical Wavelength-Path Service With Quality Assurance by Multilayer Integration System

NASA Astrophysics Data System (ADS)

Yagi, Mikio; Tanaka, Shinya; Satomi, Shuichi; Ryu, Shiro; Asano, Shoichiro

2006-09-01

In the future all-optical network controlled by generalized multiprotocol label switching (GMPLS), the wavelength path between end nodes will change dynamically. This inevitably means that the fiber parameters along the wavelength path will also vary. This variation in fiber parameters influences the signal quality of high-speed-transmission system (bit rates over 40 Gb/s). Therefore, at a path setup, the fiber-parameter effect should be adequately compensated. Moreover, the path setup must be completed fast enough to meet the network-application demands. To realize the rapid setup of adequate paths, a multilayer integration system for all-optical wavelength-path quality assurance is proposed. This multilayer integration system is evaluated in a field trial. In the trial, the GMPLS control plane, measurement plane, and data plane coordinated to maintain the quality of a 40-Gb/s wavelength path that would otherwise be degraded by the influence of chromatic dispersion. It is also demonstrated that the multilayer integration system can assure the signal quality in the face of not only chromatic dispersion but also degradation in the optical signal-to-noise ratio by the use of a 2R regeneration system. Our experiments confirm that the proposed multilayer integration system is an essential part of future all-optical networks.

Apparatus for mixing fuel in a gas turbine nozzle

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

Barker, Carl Robert

A fuel nozzle in a combustion turbine engine that includes: a fuel plenum defined between an circumferentially extending shroud and axially by a forward tube-sheet and an aft tube-sheet; and a mixing-tube that extends across the fuel plenum that defines a passageway connecting an inlet formed through the forward tube-sheet and an outlet formed through the aft tube-sheet, the mixing-tube comprising one or more fuel ports that fluidly communicate with the fuel plenum. The mixing-tube may include grooves on an outer surface, and be attached to the forward tube-sheet by a connection having a fail-safe leakage path.

Visualizing Transmedia Networks: Links, Paths and Peripheries

ERIC Educational Resources Information Center

Ruppel, Marc Nathaniel

2012-01-01

'Visualizing Transmedia Networks: Links, Paths and Peripheries' examines the increasingly complex rhetorical intersections between narrative and media ("old" and "new") in the creation of transmedia fictions, loosely defined as multisensory and multimodal stories told extensively across a diverse media set. In order…

Valley Fill Design and Construction Alternatives to Improve Ecological Performance

EPA Pesticide Factsheets

This presentation discusses; current challenges, comprehensive approaches, BMPs, the Middlefork Development, the Guy Cove project, and a path forward when looking at construction alternatives to improve the ecological performance of valley fills.

Water Softener NOI Meeting Summary

EPA Pesticide Factsheets

A public meeting webinar was held on cation exchange water softeners to explain the specification development process, clarify the Notification of Intent (NOI), discuss stakeholder feedback, and gather input on a path forward for labeling this product.

Final Environmental Assessment for Shared Use Paths (SUP), Eglin Air Force Base, Florida

DTIC Science & Technology

2011-07-01

NEPA; 40 Code of Federal Regulations [CFR] 1500-1508); the USAF environmental impact analysis process as effectuated by 32 CFR Part 989; and DoD...alternatives were considered, but not carried forward for analysis . Alternative B This alternative would consist of constructing a 10’ wide SUP...EA Section 2.3.1, page 12) No-Action Alternative This alternative also was carried forward for analysis . (EA Section 2.4.1, page 16) ENVIRONMENTAL

Folksonomical P2P File Sharing Networks Using Vectorized KANSEI Information as Search Tags

NASA Astrophysics Data System (ADS)

Ohnishi, Kei; Yoshida, Kaori; Oie, Yuji

We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web from the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their dot product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown, through simulations, to be superior to or equal to the random-walk based one in terms of search speed.

All-optical two-way relaying free-space optical communications for HAP-based broadband backhaul networks

NASA Astrophysics Data System (ADS)

Vu, Minh Q.; Nguyen, Nga T. T.; Pham, Hien T. T.; Dang, Ngoc T.

2018-03-01

High-altitude platforms (HAPs) are flexible, non-pollutant and cost-effective infrastructures compared to satellite or old terrestrial systems. They are being researched and developed widely in Europe, USA, Japan, Korea, and so on. However, the current limited data rates and the overload of radio frequency (RF) spectrum are problems which the developers for HAPs are confronting because most of them use RF links to communicate with the ground stations (GSs) or each other. In this paper, we propose an all-optical two-way half-duplex relaying free-space optical (FSO) communication for HAP-based backhaul networks, which connect the base transceiver station (BTS) to the core network (CN) via a single HAP. Our proposed backhaul solution can be deployed quickly and flexibly for disaster relief and for serving users in both urban environments and remote areas. The key subsystem of HAP is an optical regenerate-and-forward (ORF) equipped with an optical hard-limiter (OHL) and an optical XOR gate to perform all-optical processing and help mitigate the background noise. In addition, two-way half-duplex relaying can be provided thanks to the use of network coding scheme. The closed-form expression for the bit error rate (BER) of our proposed system under the effect of path loss, atmospheric turbulence, and noise induced by the background light is formulated. The numerical results are demonstrated to prove the feasibility of our proposed system with the verification by using Monte-Carlo (M-C) simulations.

Space Link Extension (SLE) Emulation for High-Throughput Network Communication

NASA Technical Reports Server (NTRS)

Murawski, Robert; Tchorowski, Nicole; Golden, Bert

2014-01-01

As the data rate requirements for space communications increases, signicant stressis placed not only on the wireless satellite communication links, but also on the groundnetworks which forward data from end-users to remote ground stations. These wide areanetwork (WAN) connections add delay and jitter to the end-to-end satellite communicationlink, eects which can have signicant impacts on the wireless communication link. It isimperative that any ground communication protocol can react to these eects such that theground network does not become a bottleneck in the communication path to the satellite.In this paper, we present our SCENIC Emulation Lab testbed which was developed to testthe CCSDS SLE protocol implementations proposed for use on future NASA communica-tion networks. Our results show that in the presence of realistic levels of network delay,high-throughput SLE communication links can experience signicant data rate throttling.Based on our observations, we present some insight into why this data throttling happens,and trace the probable issue back to non-optimal blocking communication which is sup-ported by the CCSDS SLE API recommended practices. These issues were presented aswell to the SLE implementation developers which, based on our reports, developed a newrelease for SLE which we show xes the SLE blocking issue and greatly improves the pro-tocol throughput. In this paper, we also discuss future developments for our end-to-endemulation lab and how these improvements can be used to develop and test future spacecommunication technologies.

Safe Active Scanning for Energy Delivery Systems Final Report

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

Helms, J.; Salazar, B.; Scheibel, P.

The Department of Energy’s Cybersecurity for Energy Delivery Systems Program has funded Safe(r) Active Scanning for Energy Delivery Systems, led by Lawrence Livermore National Laboratory, to investigate and analyze the impacts of active scanning in the operational environment of energy delivery systems. In collaboration with Pacific Northwest National Laboratory and Idaho National Laboratory, active scans across three testbeds including 38 devices were performed. This report gives a summary of the initial literature survey performed on the SASEDS project as well as industry partner interview summaries and main findings from Phase 1 of the project. Additionally, the report goes into themore » details of scanning techniques, methodologies for testing, testbed descriptions, and scanning results, with appendices to elaborate on the specific scans that were performed. As a result of testing, a single device out of 38 exhibited problems when actively scanned, and a reboot was required to fix it. This single failure indicates that active scanning is not likely to have a detrimental effect on the safety and resilience of energy delivery systems. We provide a path forward for future research that could enable wide adoption of active scanning and lead utilities to incorporate active scanning as part of their default network security plans to discover and rectify rogue devices, adversaries, and services that may be on the network. This increased network visibility will allow operational technology cybersecurity practitioners to improve their situational awareness of networks and their vulnerabilities.« less

Path integrals and large deviations in stochastic hybrid systems.

PubMed

Bressloff, Paul C; Newby, Jay M

2014-04-01

We construct a path-integral representation of solutions to a stochastic hybrid system, consisting of one or more continuous variables evolving according to a piecewise-deterministic dynamics. The differential equations for the continuous variables are coupled to a set of discrete variables that satisfy a continuous-time Markov process, which means that the differential equations are only valid between jumps in the discrete variables. Examples of stochastic hybrid systems arise in biophysical models of stochastic ion channels, motor-driven intracellular transport, gene networks, and stochastic neural networks. We use the path-integral representation to derive a large deviation action principle for a stochastic hybrid system. Minimizing the associated action functional with respect to the set of all trajectories emanating from a metastable state (assuming that such a minimization scheme exists) then determines the most probable paths of escape. Moreover, evaluating the action functional along a most probable path generates the so-called quasipotential used in the calculation of mean first passage times. We illustrate the theory by considering the optimal paths of escape from a metastable state in a bistable neural network.

Optimizing Retransmission Threshold in Wireless Sensor Networks

PubMed Central

Bi, Ran; Li, Yingshu; Tan, Guozhen; Sun, Liang

2016-01-01

The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is OnΔ·max1≤i≤n{ui}, where ui is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based (1+pmin)-approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O(1)-approximation algorithm with time complexity O(1) is proposed. Experimental results show that the proposed algorithms have better performance. PMID:27171092

Pulse based sensor networking using mechanical waves through metal substrates

NASA Astrophysics Data System (ADS)

Lorenz, S.; Dong, B.; Huo, Q.; Tomlinson, W. J.; Biswas, S.

2013-05-01

This paper presents a novel wireless sensor networking technique using ultrasonic signal as the carrier wave for binary data exchange. Using the properties of lamb wave propagation through metal substrates, the proposed network structure can be used for runtime transport of structural fault information to ultrasound access points. Primary applications of the proposed sensor networking technique will include conveying fault information on an aircraft wing or on a bridge to an ultrasonic access point using ultrasonic wave through the structure itself (i.e. wing or bridge). Once a fault event has been detected, a mechanical pulse is forwarded to the access node using shortest path multi-hop ultrasonic pulse routing. The advantages of mechanical waves over traditional radio transmission using pulses are the following: First, unlike radio frequency, surface acoustic waves are not detectable outside the medium, which increases the inherent security for sensitive environments in respect to tapping. Second, event detection can be represented by the injection of a single mechanical pulse at a specific temporal position, whereas radio messages usually take several bits. The contributions of this paper are: 1) Development of a transceiver for transmitting/receiving ultrasound pulses with a pulse loss rate below 2·10-5 and false positive rate with an upper bound of 2·10-4. 2) A novel one-hop distance estimation based on the properties of lamb wave propagation with an accuracy of above 80%. 3) Implementation of a wireless sensor network using mechanical wave propagation for event detection on a 2024 aluminum alloy commonly used for aircraft skin construction.

High Fidelity Simulations of Large-Scale Wireless Networks

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

Onunkwo, Uzoma; Benz, Zachary

The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulationsmore » (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.« less

Calculation method of water injection forward modeling and inversion process in oilfield water injection network

NASA Astrophysics Data System (ADS)

Liu, Long; Liu, Wei

2018-04-01

A forward modeling and inversion algorithm is adopted in order to determine the water injection plan in the oilfield water injection network. The main idea of the algorithm is shown as follows: firstly, the oilfield water injection network is inversely calculated. The pumping station demand flow is calculated. Then, forward modeling calculation is carried out for judging whether all water injection wells meet the requirements of injection allocation or not. If all water injection wells meet the requirements of injection allocation, calculation is stopped, otherwise the demand injection allocation flow rate of certain step size is reduced aiming at water injection wells which do not meet requirements, and next iterative operation is started. It is not necessary to list the algorithm into water injection network system algorithm, which can be realized easily. Iterative method is used, which is suitable for computer programming. Experimental result shows that the algorithm is fast and accurate.

Modelling the role of electron attachment rates on column density ratios for C n H-/C n H (n=4,6,8) in dense molecular clouds

NASA Astrophysics Data System (ADS)

Gianturco, F. A.; Grassi, T.; Wester, R.

2016-10-01

The fairly recent detection of a variety of anions in the interstellar molecular clouds have underlined the importance of realistically modelling the processes governing their abundance. To pursue this task, our earlier calculations for the radiative electron attachment (REA) rates for C4H-, C6H-, and C8H- are employed in the present work, within a broad network of other concurrent reactions, to generate the corresponding column density ratios of anion/neutral (A/N) relative abundances. The latter are then compared with those obtained in recent years from observational measurements. The calculations involved the time-dependent solutions of a large network of chemical processes over an extended time interval and included a series of runs in which the values of REA rates were repeatedly scaled over several orders of magnitude. Macroscopic parameters for the Clouds’ modelling were also varied to cover a broad range of physical environments. It was found that, within the range and quality of the processes included in the present network,and selected from state-of-the-art astrophysical databases, the REA values required to match the observed A/N ratios needed to be reduced by orders of magnitude for C4H- case, while the same rates for C6H- and C8H- only needed to be scaled by much smaller factors. The results suggest that the generally proposed formation of interstellar anions by REA mechanism is overestimated by current models for the C4H- case, for which is likely to be an inefficient path to formation. This path is thus providing a rather marginal contribution to the observed abundances of C4H-, the latter being more likely to originate from other chemical processes in the network, as we discuss in some detail in the present work. Possible physical reasons for the much smaller differences against observations found instead for the values of the (A/N) ratios in two other, longer members of the series are put forward and analysed within the evolutionary modelling discussed in the present work.

Routing and wavelength assignment based on normalized resource and constraints for all-optical network

NASA Astrophysics Data System (ADS)

Joo, Seong-Soon; Nam, Hyun-Soon; Lim, Chang-Kyu

2003-08-01

With the rapid growth of the Optical Internet, high capacity pipes is finally destined to support end-to-end IP on the WDM optical network. Newly launched 2D MEMS optical switching module in the market supports that expectations of upcoming a transparent optical cross-connect in the network have encouraged the field applicable research on establishing real all-optical transparent network. To open up a customer-driven bandwidth services, design of the optical transport network becomes more challenging task in terms of optimal network resource usage. This paper presents a practical approach to finding a route and wavelength assignment for wavelength routed all-optical network, which has λ-plane OXC switches and wavelength converters, and supports that optical paths are randomly set up and released by dynamic wavelength provisioning to create bandwidth between end users with timescales on the order of seconds or milliseconds. We suggest three constraints to make the RWA problem become more practical one on deployment for wavelength routed all-optical network in network view: limitation on maximum hop of a route within bearable optical network impairments, limitation on minimum hops to travel before converting a wavelength, and limitation on calculation time to find all routes for connections requested at once. We design the NRCD (Normalized Resource and Constraints for All-Optical Network RWA Design) algorithm for the Tera OXC: network resource for a route is calculated by the number of internal switching paths established in each OXC nodes on the route, and is normalized by ratio of number of paths established and number of paths equipped in a node. We show that it fits for the RWA algorithm of the wavelength routed all-optical network through real experiments on the distributed objects platform.

Regular Topologies for Gigabit Wide-Area Networks. Volume 1

NASA Technical Reports Server (NTRS)

Shacham, Nachum; Denny, Barbara A.; Lee, Diane S.; Khan, Irfan H.; Lee, Danny Y. C.; McKenney, Paul

1994-01-01

In general terms, this project aimed at the analysis and design of techniques for very high-speed networking. The formal objectives of the project were to: (1) Identify switch and network technologies for wide-area networks that interconnect a large number of users and can provide individual data paths at gigabit/s rates; (2) Quantitatively evaluate and compare existing and proposed architectures and protocols, identify their strength and growth potentials, and ascertain the compatibility of competing technologies; and (3) Propose new approaches to existing architectures and protocols, and identify opportunities for research to overcome deficiencies and enhance performance. The project was organized into two parts: 1. The design, analysis, and specification of techniques and protocols for very-high-speed network environments. In this part, SRI has focused on several key high-speed networking areas, including Forward Error Control (FEC) for high-speed networks in which data distortion is the result of packet loss, and the distribution of broadband, real-time traffic in multiple user sessions. 2. Congestion Avoidance Testbed Experiment (CATE). This part of the project was done within the framework of the DARTnet experimental T1 national network. The aim of the work was to advance the state of the art in benchmarking DARTnet's performance and traffic control by developing support tools for network experimentation, by designing benchmarks that allow various algorithms to be meaningfully compared, and by investigating new queueing techniques that better satisfy the needs of best-effort and reserved-resource traffic. This document is the final technical report describing the results obtained by SRI under this project. The report consists of three volumes: Volume 1 contains a technical description of the network techniques developed by SRI in the areas of FEC and multicast of real-time traffic. Volume 2 describes the work performed under CATE. Volume 3 contains the source code of all software developed under CATE.

Optical Circuit Switched Protocol

NASA Technical Reports Server (NTRS)

Monacos, Steve P. (Inventor)

2000-01-01

The present invention is a system and method embodied in an optical circuit switched protocol for the transmission of data through a network. The optical circuit switched protocol is an all-optical circuit switched network and includes novel optical switching nodes for transmitting optical data packets within a network. Each optical switching node comprises a detector for receiving the header, header detection logic for translating the header into routing information and eliminating the header, and a controller for receiving the routing information and configuring an all optical path within the node. The all optical path located within the node is solely an optical path without having electronic storage of the data and without having optical delay of the data. Since electronic storage of the header is not necessary and the initial header is eliminated by the first detector of the first switching node. multiple identical headers are sent throughout the network so that subsequent switching nodes can receive and read the header for setting up an optical data path.

The congestion control algorithm based on queue management of each node in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Wei, Yifei; Chang, Lin; Wang, Yali; Wang, Gaoping

2016-12-01

This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. As the network load increases, local congestion of mobile ad hoc network may lead to network performance degradation, hot node's energy consumption increase even failure. If small energy nodes congested because of forwarding data packets, then when it is used as the source node will cause a lot of packet loss. This paper proposes an active queue management mechanism, considering the node's own ability and its importance in the network to set the queue threshold. Controlling nodes buffer queue in different levels of congestion area probability by adjusting the upper limits and lower limits, thus nodes can adjust responsibility of forwarding data packets according to their own situation. The proposed algorithm will slow down the send rate hop by hop along the data package transmission direction from congestion node to source node so that to prevent further congestion from the source node. The simulation results show that, the algorithm can better play the data forwarding ability of strong nodes, protect the weak nodes, can effectively alleviate the network congestion situation.

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

NASA Astrophysics Data System (ADS)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

Simultaneous Water Vapor and Dry Air Optical Path Length Measurements and Compensation with the Large Binocular Telescope Interferometer

NASA Technical Reports Server (NTRS)

Defrere, D.; Hinz, P.; Downey, E.; Boehm, M.; Danchi, W. C.; Durney, O.; Ertel, S.; Hill, J. M.; Hoffmann, W. F.; Mennesson, B.;

Path finding methods accounting for stoichiometry in metabolic networks

PubMed Central

2011-01-01

Graph-based methods have been widely used for the analysis of biological networks. Their application to metabolic networks has been much discussed, in particular noting that an important weakness in such methods is that reaction stoichiometry is neglected. In this study, we show that reaction stoichiometry can be incorporated into path-finding approaches via mixed-integer linear programming. This major advance at the modeling level results in improved prediction of topological and functional properties in metabolic networks. PMID:21619601

Advance Control Measures & Programs

EPA Pesticide Factsheets

As areas develop their path forward or action plan, they should consider a variety of voluntary and mandatory measures and programs. The resources on this page can help, and participants are also encouraged to talk with their EPA Advance contact

On-Going International Research Program on Irradiated Concrete Conducted by DOE, EPRI and Japan Research Institutions. Roadmap, Achievements and Path Forward

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

Le Pape, Yann; Rosseel, Thomas M.

The Joint Department of Energy (DOE)-Electric Power Research Institute (EPRI) Program (Light Water Reactor Sustainability (LWRS) Program–Material Pathway–Concrete and Long-Term Operation (LTO) Program) and US Nuclear Regulatory Commission (NRC) research studies aim at understanding the most prominent degradation modes and their effects on the long-term operation of concrete structures to nuclear power generation. Based on the results of the Expanded Materials Degradation Analysis (EMDA), (NUREG/CR-7153, ORNL/TM-2011/545), irradiated concrete and alkali-silica reaction (ASR)-affected concrete structures are the two prioritized topics of on-going research. This report focuses specifically on the topic of irradiated concrete and summarizes the main accomplishments obtained by thismore » joint program, but also provides an overview of current relevant activities domestically and internationally. Possible paths forward are also suggested to help near-future orientation of this program.« less

The Teratology Society 2007 strategic planning session: a desire to inspire.

PubMed

2008-05-01

On April 18-20, 2007, the Teratology Society held its third strategic planning session (SPS) in San Diego, CA. The purpose of this session was to build on the successful work generated by the previous strategic plans [Nashville, TN 2002 and Cincinnati, OH 1997] and importantly, to provide a path forward to inspire the Society, create deeper connections with members that speak to their individual passion for the science of teratology and to increase the Society's visibility within the larger scientific community. The following summary report provides an overview of the session's pre-work, objective, and discussions. A total of 24 attendees were present at the session. The group included representation from Council, various committees and different members constituencies. This plan and the activities subsequent to the session will provide a path forward for our Society for the next five years.

Vertical Profiles of Phosphine and Ammonia on Saturn Derived from the First Cassini RSS Occultation Observation Using Forward Modeling

NASA Astrophysics Data System (ADS)

Mohammed, P. N.; Steffes, P. G.; Kliore, A. J.; Anabtawi, A.; Asmar, S. W.; Barbinis, E.; Goltz, G.; Johnston, D.; Marouf, E. A.

2005-08-01

The results from the first Cassini Radio Science Subsystem(RSS) occultation, which occurred at the Rev 7 periapse, are being used to derive profiles of the atmospheric constituents encountered by the three frequency (S-, X-, and Ka-band) radio link. A computer model has been developed to simulate ray paths and the ray path parameters in the atmosphere of Saturn encountered during occultation (see Mohammed and Steffes, Bull. Amer. Astron. Soc., 36, no. 4, 1107, 2004). This forward model, which can be used on any oblate planet, will be used to determine the refractive defocusing and derive the profiles of phosphine and ammonia using data observed at Ka-band (32 GHz or 9.3 mm), X-band (8.4 GHz or 3.6 cm) and S-band (2.3 GHz or 13 cm). The results of laboratory measurements of the 9 mm opacity of phosphine and ammonia (Mohammed and Steffes, ICARUS 166, 425-435, 2003) and the centimeter wavelength opacity of these constituents measured under simulated conditions for Saturn (see, e.g., Hoffman et. al. ICARUS 152, 172-184, 2001) were incorporated into the forward radio occultation model used in these derivations.

Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks

PubMed Central

Furukawa, Hiroshi

2017-01-01

Round Robin based Intermittent Periodic Transmit (RR-IPT) has been proposed which achieves highly efficient multi-hop relays in multi-hop wireless backhaul networks (MWBN) where relay nodes are 2-dimensionally deployed. This paper newly investigates multi-channel packet scheduling and forwarding scheme for RR-IPT. Downlink traffic is forwarded by RR-IPT via one of the channels, while uplink traffic and part of downlink are accommodated in the other channel. By comparing IPT and carrier sense multiple access with collision avoidance (CSMA/CA) for uplink/downlink packet forwarding channel, IPT is more effective in reducing packet loss rate whereas CSMA/CA is better in terms of system throughput and packet delay improvement. PMID:29137164

Study on system for extracted type infrared gas analysis

NASA Astrophysics Data System (ADS)

Gu, Ruirui; Yao, Jun; Li, Wei; Li, Wenzhong; Zhang, Shaohua; Liu, Zhe; Wen, Qiang

2015-12-01

Based on the Beer-Lambert law and the characteristic IR absorption spectrum of CO, a system for extracted type infrared gas analysis has been designed and manufactured, which utilizes different absorptive degrees infrared light gain under different concentration degrees of the gas to be measured to the value of detect CO concentration, including optical path, electric circuit and gas path. A forward and backward gas detection chamber equipped with a micro flow sensor has been used in the optical path as well as a multistage high precision amplifier and filter circuit has been used in the electric circuit. The experimental results accord with the testing standard.

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

DOEpatents

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

2013-04-16

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.

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

NASA Astrophysics Data System (ADS)

Hyman, J.; Hagberg, A.; Srinivasan, G.; Mohd-Yusof, J.; Viswanathan, H. S.

2017-12-01

We present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths. First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. Accurate estimates of first passage times are obtained with an order of magnitude reduction of CPU time and mesh size using the proposed method.

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

NASA Astrophysics Data System (ADS)

Hyman, Jeffrey D.; Hagberg, Aric; Srinivasan, Gowri; Mohd-Yusof, Jamaludin; Viswanathan, Hari

2017-07-01

We present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths. First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. Accurate estimates of first passage times are obtained with an order of magnitude reduction of CPU time and mesh size using the proposed method.

Cross hole GPR traveltime inversion using a fast and accurate neural network as a forward model

NASA Astrophysics Data System (ADS)

Mejer Hansen, Thomas

2017-04-01

Probabilistic formulated inverse problems can be solved using Monte Carlo based sampling methods. In principle both advanced prior information, such as based on geostatistics, and complex non-linear forward physical models can be considered. However, in practice these methods can be associated with huge computational costs that in practice limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error, that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival travel time inversion of cross hole ground-penetrating radar (GPR) data. An accurate forward model, based on 2D full-waveform modeling followed by automatic travel time picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the full forward model, and considerably faster, and more accurate, than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of the types of inverse problems that can be solved using non-linear Monte Carlo sampling techniques.

Multi-Layer Approach for the Detection of Selective Forwarding Attacks

PubMed Central

Alajmi, Naser; Elleithy, Khaled

2015-01-01

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable. PMID:26610499

Multi-Layer Approach for the Detection of Selective Forwarding Attacks.

PubMed

Alajmi, Naser; Elleithy, Khaled

2015-11-19

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.

Topological Vulnerability Analysis

NASA Astrophysics Data System (ADS)

Jajodia, Sushil; Noel, Steven

Traditionally, network administrators rely on labor-intensive processes for tracking network configurations and vulnerabilities. This requires a great deal of expertise, and is error prone because of the complexity of networks and associated security data. The interdependencies of network vulnerabilities make traditional point-wise vulnerability analysis inadequate. We describe a Topological Vulnerability Analysis (TVA) approach that analyzes vulnerability dependencies and shows all possible attack paths into a network. From models of the network vulnerabilities and potential attacker exploits, we compute attack graphs that convey the impact of individual and combined vulnerabilities on overall security. TVA finds potential paths of vulnerability through a network, showing exactly how attackers may penetrate a network. From this, we identify key vulnerabilities and provide strategies for protection of critical network assets.

Understanding Route Aggregation

DTIC Science & Technology

2010-03-09

routing anomalies, and is fingered to be the cause of many reported loops and blackholes . In this paper, we posit that the problem arises from a lack of...Route aggre- gation can also result in blackholes [18], which are surprisingly prevalent in the Internet [11]. We illustrate these known anomalies with...advertisement Forwarding paths A B C 10.1.30.0/24 10.1.16.0/22 10.1.16.0/2010.1.16.0/20 Figure 4: Illustration of a blackhole . forwards the packet to Y

Membrane Bioreactor/Ultra Low Energy Reverse Osmosis Membrane Process for Forward Operating Base Wastewater Reuse

DTIC Science & Technology

2014-08-01

of the GEGR pilot membrane coater; b) configuration of the coating station; and c) web path of the dip-knife coating process for RO membrane...Energy-dispersive X-ray spectroscopy EPA Environmental Protection Agency F:M Food-To-Microorganism Ratio FOB Forward Operating Base FT- IR Fourier...report 03/2014 3.3 Submit draft Interim report/Go No-Go decision point white paper 05/2013 3.4 Submit final report 05/2014 3.5 Final debrief

Data Science in Radiology: A Path Forward.

PubMed

Aerts, Hugo J W L

2018-02-01

Artificial intelligence (AI), especially deep learning, has the potential to fundamentally alter clinical radiology. AI algorithms, which excel in quantifying complex patterns in data, have shown remarkable progress in applications ranging from self-driving cars to speech recognition. The AI application within radiology, known as radiomics, can provide detailed quantifications of the radiographic characteristics of underlying tissues. This information can be used throughout the clinical care path to improve diagnosis and treatment planning, as well as assess treatment response. This tremendous potential for clinical translation has led to a vast increase in the number of research studies being conducted in the field, a number that is expected to rise sharply in the future. Many studies have reported robust and meaningful findings; however, a growing number also suffer from flawed experimental or analytic designs. Such errors could not only result in invalid discoveries, but also may lead others to perpetuate similar flaws in their own work. This perspective article aims to increase awareness of the issue, identify potential reasons why this is happening, and provide a path forward. Clin Cancer Res; 24(3); 532-4. ©2017 AACR . ©2017 American Association for Cancer Research.

Real-time video streaming using H.264 scalable video coding (SVC) in multihomed mobile networks: a testbed approach

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos

2011-03-01

Users of the next generation wireless paradigm known as multihomed mobile networks expect satisfactory quality of service (QoS) when accessing streamed multimedia content. The recent H.264 Scalable Video Coding (SVC) extension to the Advanced Video Coding standard (AVC), offers the facility to adapt real-time video streams in response to the dynamic conditions of multiple network paths encountered in multihomed wireless mobile networks. Nevertheless, preexisting streaming algorithms were mainly proposed for AVC delivery over multipath wired networks and were evaluated by software simulation. This paper introduces a practical, hardware-based testbed upon which we implement and evaluate real-time H.264 SVC streaming algorithms in a realistic multihomed wireless mobile networks environment. We propose an optimised streaming algorithm with multi-fold technical contributions. Firstly, we extended the AVC packet prioritisation schemes to reflect the three-dimensional granularity of SVC. Secondly, we designed a mechanism for evaluating the effects of different streamer 'read ahead window' sizes on real-time performance. Thirdly, we took account of the previously unconsidered path switching and mobile networks tunnelling overheads encountered in real-world deployments. Finally, we implemented a path condition monitoring and reporting scheme to facilitate the intelligent path switching. The proposed system has been experimentally shown to offer a significant improvement in PSNR of the received stream compared with representative existing algorithms.

Quantifying Cell Fate Decisions for Differentiation and Reprogramming of a Human Stem Cell Network: Landscape and Biological Paths

PubMed Central

Li, Chunhe; Wang, Jin

2013-01-01

Cellular reprogramming has been recently intensively studied experimentally. We developed a global potential landscape and kinetic path framework to explore a human stem cell developmental network composed of 52 genes. We uncovered the underlying landscape for the stem cell network with two basins of attractions representing stem and differentiated cell states, quantified and exhibited the high dimensional biological paths for the differentiation and reprogramming process, connecting the stem cell state and differentiated cell state. Both the landscape and non-equilibrium curl flux determine the dynamics of cell differentiation jointly. Flux leads the kinetic paths to be deviated from the steepest descent gradient path, and the corresponding differentiation and reprogramming paths are irreversible. Quantification of paths allows us to find out how the differentiation and reprogramming occur and which important states they go through. We show the developmental process proceeds as moving from the stem cell basin of attraction to the differentiation basin of attraction. The landscape topography characterized by the barrier heights and transition rates quantitatively determine the global stability and kinetic speed of cell fate decision process for development. Through the global sensitivity analysis, we provided some specific predictions for the effects of key genes and regulation connections on the cellular differentiation or reprogramming process. Key links from sensitivity analysis and biological paths can be used to guide the differentiation designs or reprogramming tactics. PMID:23935477

Path Searching Based Fault Automated Recovery Scheme for Distribution Grid with DG

NASA Astrophysics Data System (ADS)

Xia, Lin; Qun, Wang; Hui, Xue; Simeng, Zhu

2016-12-01

Applying the method of path searching based on distribution network topology in setting software has a good effect, and the path searching method containing DG power source is also applicable to the automatic generation and division of planned islands after the fault. This paper applies path searching algorithm in the automatic division of planned islands after faults: starting from the switch of fault isolation, ending in each power source, and according to the line load that the searching path traverses and the load integrated by important optimized searching path, forming optimized division scheme of planned islands that uses each DG as power source and is balanced to local important load. Finally, COBASE software and distribution network automation software applied are used to illustrate the effectiveness of the realization of such automatic restoration program.

Assessment of in vitro COPD models for tobacco regulatory science: Workshop proceedings, conclusions and paths forward for in vitro model use.

PubMed

Behrsing, Holger; Raabe, Hans; Manuppello, Joseph; Bombick, Betsy; Curren, Rodger; Sullivan, Kristie; Sethi, Sanjay; Phipps, Richard; Tesfaigzi, Yohannes; Yan, Sherwin; D'Ruiz, Carl; Tarran, Robert; Constant, Samuel; Phillips, Gary; Gaça, Marianna; Hayden, Patrick; Cao, Xuefei; Mathis, Carole; Hoeng, Julia; Braun, Armin; Hill, Erin

2016-05-01

The Family Smoking Prevention and Tobacco Control Act of 2009 established the Food and Drug Administration Center for Tobacco Products (FDA-CTP), and gave it regulatory authority over the marketing, manufacture and distribution of tobacco products, including those termed 'modified risk'. On 8-10 December 2014, IIVS organised a workshop conference, entitled Assessment of In Vitro COPD Models for Tobacco Regulatory Science, to bring together stakeholders representing regulatory agencies, academia, industry and animal protection, to address the research priorities articulated by the FDA-CTP. Specific topics were covered to assess the status of current in vitro technologies as they are applied to understanding the adverse pulmonary events resulting from tobacco product exposure, and in particular, the progression of chronic obstructive pulmonary disease (COPD). The four topics covered were: a) Inflammation and Oxidative Stress; b) Ciliary Dysfunction and Ion Transport; c) Goblet Cell Hyperplasia and Mucus Production; and d) Parenchymal/Bronchial Tissue Destruction and Remodelling. The 2.5 day workshop included 18 expert speakers, plus poster sessions, networking and breakout sessions, which identified key findings and provided recommendations to advance the in vitro technologies and assays used to evaluate tobacco-induced disease etiologies. The workshop summary was reported at the 2015 Society of Toxicology Annual Meeting, and the recommendations led to an IIVS-organised technical workshop in June 2015, entitled Goblet Cell Hyperplasia, Mucus Production, and Ciliary Beating Assays, to assess these assays and to conduct a proof-of-principle multi-laboratory exercise to determine their suitability for standardisation. Here, we report on the proceedings, recommendations and outcomes of the December 2014 workshop, including paths forward to continue the development of non-animal methods to evaluate tissue responses that model the disease processes that may lead to COPD, a major cause of mortality worldwide. 2016 FRAME.

One EPA Web Principles that Guide Content Development

EPA Pesticide Factsheets

The principles of One EPA Web can be applied to better meet the needs and expectations of our audiences, fit their information-seeking behavior, and help them accomplish tasks. Learn about the five paths forward for transforming web content.

TERATOLOGY v2.0 – building a path forward

EPA Science Inventory

Unraveling the complex relationships between environmental factors and early life susceptibility in assessing the risk for adverse pregnancy outcomes requires advanced knowledge of biological systems. Large datasets and deep data-mining tools are emerging resources for predictive...

Statistical Tools And Artificial Intelligence Approaches To Predict Fracture In Bulk Forming Processes

NASA Astrophysics Data System (ADS)

Di Lorenzo, R.; Ingarao, G.; Fonti, V.

2007-05-01

The crucial task in the prevention of ductile fracture is the availability of a tool for the prediction of such defect occurrence. The technical literature presents a wide investigation on this topic and many contributions have been given by many authors following different approaches. The main class of approaches regards the development of fracture criteria: generally, such criteria are expressed by determining a critical value of a damage function which depends on stress and strain paths: ductile fracture is assumed to occur when such critical value is reached during the analysed process. There is a relevant drawback related to the utilization of ductile fracture criteria; in fact each criterion usually has good performances in the prediction of fracture for particular stress - strain paths, i.e. it works very well for certain processes but may provide no good results for other processes. On the other hand, the approaches based on damage mechanics formulation are very effective from a theoretical point of view but they are very complex and their proper calibration is quite difficult. In this paper, two different approaches are investigated to predict fracture occurrence in cold forming operations. The final aim of the proposed method is the achievement of a tool which has a general reliability i.e. it is able to predict fracture for different forming processes. The proposed approach represents a step forward within a research project focused on the utilization of innovative predictive tools for ductile fracture. The paper presents a comparison between an artificial neural network design procedure and an approach based on statistical tools; both the approaches were aimed to predict fracture occurrence/absence basing on a set of stress and strain paths data. The proposed approach is based on the utilization of experimental data available, for a given material, on fracture occurrence in different processes. More in detail, the approach consists in the analysis of experimental tests in which fracture occurs followed by the numerical simulations of such processes in order to track the stress-strain paths in the workpiece region where fracture is expected. Such data are utilized to build up a proper data set which was utilized both to train an artificial neural network and to perform a statistical analysis aimed to predict fracture occurrence. The developed statistical tool is properly designed and optimized and is able to recognize the fracture occurrence. The reliability and predictive capability of the statistical method were compared with the ones obtained from an artificial neural network developed to predict fracture occurrence. Moreover, the approach is validated also in forming processes characterized by a complex fracture mechanics.

Why Does Mptcp Have To Make Things So Complicated : Cross Path Nids Evasion And Countermeasures

DTIC Science & Technology

2016-09-01

previously only establish communication channels over single network paths to communicate over multiple network paths. MPTCP is an enhancement toTCP that...the attacker would fail to create a Command and Control (C2) channel unless the attacker had created a new mapping to the target on the splicing...machine. This would allow the attacker to conduct C2 over a spliced channel . This may even make the attacker’s C2 more evasive. In fact, the effect

Method and apparatus for routing data in an inter-nodal communications lattice of a massively parallel computer system by employing bandwidth shells at areas of overutilization

DOEpatents

Archer, Charles Jens; Musselman, Roy Glenn; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen; Wallenfelt, Brian Paul

2010-04-27

A massively parallel computer system contains an inter-nodal communications network of node-to-node links. An automated routing strategy routes packets through one or more intermediate nodes of the network to reach a final destination. The default routing strategy is altered responsive to detection of overutilization of a particular path of one or more links, and at least some traffic is re-routed by distributing the traffic among multiple paths (which may include the default path). An alternative path may require a greater number of link traversals to reach the destination node.

Path selection rules for droplet trains in single-lane microfluidic networks

NASA Astrophysics Data System (ADS)

Amon, A.; Schmit, A.; Salkin, L.; Courbin, L.; Panizza, P.

2013-07-01

We investigate the transport of periodic trains of droplets through microfluidic networks having one inlet, one outlet, and nodes consisting of T junctions. Variations of the dilution of the trains, i.e., the distance between drops, reveal the existence of various hydrodynamic regimes characterized by the number of preferential paths taken by the drops. As the dilution increases, this number continuously decreases until only one path remains explored. Building on a continuous approach used to treat droplet traffic through a single asymmetric loop, we determine selection rules for the paths taken by the drops and we predict the variations of the fraction of droplets taking these paths with the parameters at play including the dilution. Our results show that as dilution decreases, the paths are selected according to the ascending order of their hydrodynamic resistance in the absence of droplets. The dynamics of these systems controlled by time-delayed feedback is complex: We observe a succession of periodic regimes separated by a wealth of bifurcations as the dilution is varied. In contrast to droplet traffic in single asymmetric loops, the dynamical behavior in networks of loops is sensitive to initial conditions because of extra degrees of freedom.

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

NASA Astrophysics Data System (ADS)

Liu, Xuepeng; Zhao, Dongmei

2017-08-01

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

Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb

NASA Technical Reports Server (NTRS)

Dahl, Kristen P.; Thompson, David R.; McLaren, David; Chao, Yi; Chien, Steve

2011-01-01

This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.

Pseudo paths towards minimum energy states in network dynamics

NASA Astrophysics Data System (ADS)

Hedayatifar, L.; Hassanibesheli, F.; Shirazi, A. H.; Vasheghani Farahani, S.; Jafari, G. R.

2017-10-01

The dynamics of networks forming on Heider balance theory moves towards lower tension states. The condition derived from this theory enforces agents to reevaluate and modify their interactions to achieve equilibrium. These possible changes in network's topology can be considered as various paths that guide systems to minimum energy states. Based on this theory the final destination of a system could reside on a local minimum energy, ;jammed state;, or the global minimum energy, balanced states. The question we would like to address is whether jammed states just appear by chance? Or there exist some pseudo paths that bound a system towards a jammed state. We introduce an indicator to suspect the location of a jammed state based on the Inverse Participation Ratio method (IPR). We provide a margin before a local minimum where the number of possible paths dramatically drastically decreases. This is a condition that proves adequate for ending up on a jammed states.

Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

NASA Technical Reports Server (NTRS)

Decker, Arthur J. (Inventor)

2006-01-01

An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

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

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

Archer, Charles J.; Faraj, Daniel A.; Inglett, Todd A.

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 selectedmore » link to the adjacent compute node connected to the compute node through the selected link.« less

Physarum solver: A biologically inspired method of road-network navigation

NASA Astrophysics Data System (ADS)

Tero, Atsushi; Kobayashi, Ryo; Nakagaki, Toshiyuki

2006-04-01

We have proposed a mathematical model for the adaptive dynamics of the transport network in an amoeba-like organism, the true slime mold Physarum polycephalum. The model is based on physiological observations of this species, but can also be used for path-finding in the complicated networks of mazes and road maps. In this paper, we describe the physiological basis and the formulation of the model, as well as the results of simulations of some complicated networks. The path-finding method used by Physarum is a good example of cellular computation.

Metabolic PathFinding: inferring relevant pathways in biochemical networks.

PubMed

Croes, Didier; Couche, Fabian; Wodak, Shoshana J; van Helden, Jacques

2005-07-01

Our knowledge of metabolism can be represented as a network comprising several thousands of nodes (compounds and reactions). Several groups applied graph theory to analyse the topological properties of this network and to infer metabolic pathways by path finding. This is, however, not straightforward, with a major problem caused by traversing irrelevant shortcuts through highly connected nodes, which correspond to pool metabolites and co-factors (e.g. H2O, NADP and H+). In this study, we present a web server implementing two simple approaches, which circumvent this problem, thereby improving the relevance of the inferred pathways. In the simplest approach, the shortest path is computed, while filtering out the selection of highly connected compounds. In the second approach, the shortest path is computed on the weighted metabolic graph where each compound is assigned a weight equal to its connectivity in the network. This approach significantly increases the accuracy of the inferred pathways, enabling the correct inference of relatively long pathways (e.g. with as many as eight intermediate reactions). Available options include the calculation of the k-shortest paths between two specified seed nodes (either compounds or reactions). Multiple requests can be submitted in a queue. Results are returned by email, in textual as well as graphical formats (available in http://www.scmbb.ulb.ac.be/pathfinding/).

The Impact of Strain Reversal on Microstructure Evolution and Orientation Relationships in Ti-6Al-4V with an Initial Alpha Colony Microstructure

NASA Astrophysics Data System (ADS)

Muszka, K.; Lopez-Pedrosa, M.; Raszka, K.; Thomas, M.; Rainforth, W. M.; Wynne, B. P.

2014-12-01

The effect of forward and reverse torsion on flow behavior and microstructure evolution, particularly dynamic and static spheroidization, on Ti-6Al-4V with an alpha lamella colony microstructure was studied. Testing was undertaken sub beta transus [1088 K (815 °C)] at strain rates of either 0.05 or 0.5 s-1. Quantitative metallography and electron back scatter diffraction has identified that a critical monotonic strain ( ɛ c) in the range of 0.3 to 0.6 is required to initiate rapid dynamic spheroidization of the alpha lamella. For material deformed to strains below ɛ c and then reversed to a zero net strain the orientation relationships between alpha colonies are close to ideal Burgers, enabling prior beta grains to be fully reconstructed. Material deformed to strains greater than ɛ c and reversed lose Burgers and no beta reconstruction is possible, suggesting ɛ c is the strain required to generate break-up of lamella. Static spheroidization is, however, sensitive to strain path around ɛ c. Annealing at 1088 K (815 °C) for 4 hours for material subjected to 0.25 forward + 0.25 forward strain produces 48 pct spheroidized grains while material with 0.25 forward + 0.25 reverse strain has 10 pct spheroidization. This is believed to be a direct consequence of different levels of the stored energy between these two strain paths.

Applications of Temporal Graph Metrics to Real-World Networks

NASA Astrophysics Data System (ADS)

Tang, John; Leontiadis, Ilias; Scellato, Salvatore; Nicosia, Vincenzo; Mascolo, Cecilia; Musolesi, Mirco; Latora, Vito

Real world networks exhibit rich temporal information: friends are added and removed over time in online social networks; the seasons dictate the predator-prey relationship in food webs; and the propagation of a virus depends on the network of human contacts throughout the day. Recent studies have demonstrated that static network analysis is perhaps unsuitable in the study of real world network since static paths ignore time order, which, in turn, results in static shortest paths overestimating available links and underestimating their true corresponding lengths. Temporal extensions to centrality and efficiency metrics based on temporal shortest paths have also been proposed. Firstly, we analyse the roles of key individuals of a corporate network ranked according to temporal centrality within the context of a bankruptcy scandal; secondly, we present how such temporal metrics can be used to study the robustness of temporal networks in presence of random errors and intelligent attacks; thirdly, we study containment schemes for mobile phone malware which can spread via short range radio, similar to biological viruses; finally, we study how the temporal network structure of human interactions can be exploited to effectively immunise human populations. Through these applications we demonstrate that temporal metrics provide a more accurate and effective analysis of real-world networks compared to their static counterparts.

Local excitation-inhibition ratio for synfire chain propagation in feed-forward neuronal networks

NASA Astrophysics Data System (ADS)

Guo, Xinmeng; Yu, Haitao; Wang, Jiang; Liu, Jing; Cao, Yibin; Deng, Bin

2017-09-01

A leading hypothesis holds that spiking activity propagates along neuronal sub-populations which are connected in a feed-forward manner, and the propagation efficiency would be affected by the dynamics of sub-populations. In this paper, how the interaction between local excitation and inhibition effects on synfire chain propagation in feed-forward network (FFN) is investigated. The simulation results show that there is an appropriate excitation-inhibition (EI) ratio maximizing the performance of synfire chain propagation. The optimal EI ratio can significantly enhance the selectivity of FFN to synchronous signals, which thereby increases the stability to background noise. Moreover, the effect of network topology on synfire chain propagation is also investigated. It is found that synfire chain propagation can be maximized by an optimal interlayer linking probability. We also find that external noise is detrimental to synchrony propagation by inducing spiking jitter. The results presented in this paper may provide insights into the effects of network dynamics on neuronal computations.

Effective distance adaptation traffic dispatching in software defined IP over optical network

NASA Astrophysics Data System (ADS)

Duan, Zhiwei; Li, Hui; Liu, Yuze; Ji, Yuefeng; Li, Hongfa; Lin, Yi

2017-10-01

The rapid growth of IP traffic has contributed to the wide deployment of optical devices (ROADM/OXC, etc.). Meanwhile, with the emergence and application of high-performance network services such as ultra-high video transmission, people are increasingly becoming more and more particular about the quality of service (QoS) of network. However, the pass-band shape of WSSs which is utilized in the ROADM/OXC is not ideal, causing narrowing of spectrum. Spectral narrowing can lead to signal impairment. Therefore, guard-bands need to be inserted between adjacent paths. In order to minimize the bandwidth waste due to guard bands, we propose an effective distance-adaptation traffic dispatching algorithm in IP over optical network based on SDON architecture. We use virtualization technology to set up virtual resources direct links by extracting part of the resources on paths which meet certain specific constraints. We also assign different bandwidth to each IP request based on path length. There is no need for guard-bands between the adjacent paths on the virtual link, which can effectively reduce the number of guard-bands and save the spectrum.

Looking forward in geriatric anxiety and depression: implications of basic science for the future.

PubMed

Gershenfeld, Howard K; Philibert, Robert A; Boehm, Gary W

2005-12-01

Major depression and anxiety are common psychiatric illnesses whose etiology remains incompletely understood. This review highlights progress in understanding the etiology of these illnesses through genetic strategies and looks forward to their impact on geriatric psychiatry. We briefly address three broad domains of progress, namely 1) genetic approaches to etiology, including linkage and association studies, pharmacogenetics ("personalized medicine"), and gene x environment interactions; 2) mechanisms of thyroid and testosterone action via nuclear receptors, given these hormones' status as possible augmenters of antidepressants; and 3) the role of the neuroimmune system as a contributor to the stress response. Genetic strategies offer one path for converting correlational findings into causal pathways while complementing studies of a gene's function at the molecular, cellular, network, and whole-organismal levels. Neuroendocrine supplementation (thyroid and testosterone) has a long history and tradition. A molecular understanding of nuclear receptor pathways and their coactivators, the mediator complex proteins, provides a rationale for improved targeting of hormonal action in a tissue-selective manner, yielding drugs with improved safety and efficacy. Neural-immune interactions in psychiatric illness remain tantalizing topics. Research suggests that cytokine pathways may contribute to the maintenance or susceptibility to stress, anxiety, and depressive disorders. The reciprocal and recursive interactions among basic science, drug discovery, and clinical science will continue to provide hopeful themes for improving the lives of patients with treatment-refractive psychiatric illness.

Teleconnection Paths via Climate Network Direct Link Detection.

PubMed

Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

Using Social Media in Exercises

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

Donaldson, Jeff

This presentation discusses the use of social media as a tool during the full-scale exercise Tremor-14 in Las Vegas, and examines Lessons Learned as a path forward in using social media to disseminate Emergency Public Information (EPI) on a regular basis.

Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

NASA Astrophysics Data System (ADS)

Hansen, T. M.; Cordua, K. S.

2017-12-01

Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

Caching Joint Shortcut Routing to Improve Quality of Service for Information-Centric Networking.

PubMed

Huang, Baixiang; Liu, Anfeng; Zhang, Chengyuan; Xiong, Naixue; Zeng, Zhiwen; Cai, Zhiping

2018-05-29

Hundreds of thousands of ubiquitous sensing (US) devices have provided an enormous number of data for Information-Centric Networking (ICN), which is an emerging network architecture that has the potential to solve a great variety of issues faced by the traditional network. A Caching Joint Shortcut Routing (CJSR) scheme is proposed in this paper to improve the Quality of service (QoS) for ICN. The CJSR scheme mainly has two innovations which are different from other in-network caching schemes: (1) Two routing shortcuts are set up to reduce the length of routing paths. Because of some inconvenient transmission processes, the routing paths of previous schemes are prolonged, and users can only request data from Data Centers (DCs) until the data have been uploaded from Data Producers (DPs) to DCs. Hence, the first kind of shortcut is built from DPs to users directly. This shortcut could release the burden of whole network and reduce delay. Moreover, in the second shortcut routing method, a Content Router (CR) which could yield shorter length of uploading routing path from DPs to DCs is chosen, and then data packets are uploaded through this chosen CR. In this method, the uploading path shares some segments with the pre-caching path, thus the overall length of routing paths is reduced. (2) The second innovation of the CJSR scheme is that a cooperative pre-caching mechanism is proposed so that QoS could have a further increase. Besides being used in downloading routing, the pre-caching mechanism can also be used when data packets are uploaded towards DCs. Combining uploading and downloading pre-caching, the cooperative pre-caching mechanism exhibits high performance in different situations. Furthermore, to address the scarcity of storage size, an algorithm that could make use of storage from idle CRs is proposed. After comparing the proposed scheme with five existing schemes via simulations, experiments results reveal that the CJSR scheme could reduce the total number of processed interest packets by 54.8%, enhance the cache hits of each CR and reduce the number of total hop counts by 51.6% and cut down the length of routing path for users to obtain their interested data by 28.6⁻85.7% compared with the traditional NDN scheme. Moreover, the length of uploading routing path could be decreased by 8.3⁻33.3%.

Network Analysis Tools: from biological networks to clusters and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Interactogeneous: Disease Gene Prioritization Using Heterogeneous Networks and Full Topology Scores

PubMed Central

Gonçalves, Joana P.; Francisco, Alexandre P.; Moreau, Yves; Madeira, Sara C.

2012-01-01

Disease gene prioritization aims to suggest potential implications of genes in disease susceptibility. Often accomplished in a guilt-by-association scheme, promising candidates are sorted according to their relatedness to known disease genes. Network-based methods have been successfully exploiting this concept by capturing the interaction of genes or proteins into a score. Nonetheless, most current approaches yield at least some of the following limitations: (1) networks comprise only curated physical interactions leading to poor genome coverage and density, and bias toward a particular source; (2) scores focus on adjacencies (direct links) or the most direct paths (shortest paths) within a constrained neighborhood around the disease genes, ignoring potentially informative indirect paths; (3) global clustering is widely applied to partition the network in an unsupervised manner, attributing little importance to prior knowledge; (4) confidence weights and their contribution to edge differentiation and ranking reliability are often disregarded. We hypothesize that network-based prioritization related to local clustering on graphs and considering full topology of weighted gene association networks integrating heterogeneous sources should overcome the above challenges. We term such a strategy Interactogeneous. We conducted cross-validation tests to assess the impact of network sources, alternative path inclusion and confidence weights on the prioritization of putative genes for 29 diseases. Heat diffusion ranking proved the best prioritization method overall, increasing the gap to neighborhood and shortest paths scores mostly on single source networks. Heterogeneous associations consistently delivered superior performance over single source data across the majority of methods. Results on the contribution of confidence weights were inconclusive. Finally, the best Interactogeneous strategy, heat diffusion ranking and associations from the STRING database, was used to prioritize genes for Parkinson’s disease. This method effectively recovered known genes and uncovered interesting candidates which could be linked to pathogenic mechanisms of the disease. PMID:23185389

Path integration of head direction: updating a packet of neural activity at the correct speed using neuronal time constants.

PubMed

Walters, D M; Stringer, S M

2010-07-01

A key question in understanding the neural basis of path integration is how individual, spatially responsive, neurons may self-organize into networks that can, through learning, integrate velocity signals to update a continuous representation of location within an environment. It is of vital importance that this internal representation of position is updated at the correct speed, and in real time, to accurately reflect the motion of the animal. In this article, we present a biologically plausible model of velocity path integration of head direction that can solve this problem using neuronal time constants to effect natural time delays, over which associations can be learned through associative Hebbian learning rules. The model comprises a linked continuous attractor network and competitive network. In simulation, we show that the same model is able to learn two different speeds of rotation when implemented with two different values for the time constant, and without the need to alter any other model parameters. The proposed model could be extended to path integration of place in the environment, and path integration of spatial view.

An Efficient Wireless Recharging Mechanism for Achieving Perpetual Lifetime of Wireless Sensor Networks

PubMed Central

Yu, Hongli; Chen, Guilin; Zhao, Shenghui; Chang, Chih-Yung; Chin, Yu-Ting

2016-01-01

Energy recharging has received much attention in recent years. Several recharging mechanisms were proposed for achieving perpetual lifetime of a given Wireless Sensor Network (WSN). However, most of them require a mobile recharger to visit each sensor and then perform the recharging task, which increases the length of the recharging path. Another common weakness of these works is the requirement for the mobile recharger to stop at the location of each sensor. As a result, it is impossible for recharger to move with a constant speed, leading to inefficient movement. To improve the recharging efficiency, this paper takes “recharging while moving” into consideration when constructing the recharging path. We propose a Recharging Path Construction (RPC) mechanism, which enables the mobile recharger to recharge all sensors using a constant speed, aiming to minimize the length of recharging path and improve the recharging efficiency while achieving the requirement of perpetual network lifetime of a given WSN. Performance studies reveal that the proposed RPC outperforms existing proposals in terms of path length and energy utilization index, as well as visiting cycle. PMID:28025567

Entanglement-Gradient Routing for Quantum Networks.

PubMed

Gyongyosi, Laszlo; Imre, Sandor

2017-10-27

We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Motivated by models of social insect behavior, the routing is performed using parallel threads to determine the shortest path via the entanglement gradient coefficient, which describes the feasibility of the entangled links and paths of the network. The routing metrics are derived from the characteristics of entanglement transmission and relevant measures of entanglement distribution in quantum networks. The method allows a moderate complexity decentralized routing in quantum repeater networks. The results can be applied in experimental quantum networking, future quantum Internet, and long-distance quantum communications.

Enabling Secure High-Performance Wireless Ad Hoc Networking

DTIC Science & Technology

2003-05-29

destinations, consuming energy and available bandwidth. An attacker may similarly create a routing black hole, in which all packets are dropped: by sending...of the vertex cut, for example by forwarding only routing packets and not data packets, such that the nodes waste energy forwarding packets to the...with limited resources, including network bandwidth and the CPU processing capacity, memory, and battery power ( energy ) of each individual node in the

Multiple-access relaying with network coding: iterative network/channel decoding with imperfect CSI

NASA Astrophysics Data System (ADS)

Vu, Xuan-Thang; Renzo, Marco Di; Duhamel, Pierre

2013-12-01

In this paper, we study the performance of the four-node multiple-access relay channel with binary Network Coding (NC) in various Rayleigh fading scenarios. In particular, two relay protocols, decode-and-forward (DF) and demodulate-and-forward (DMF) are considered. In the first case, channel decoding is performed at the relay before NC and forwarding. In the second case, only demodulation is performed at the relay. The contributions of the paper are as follows: (1) two joint network/channel decoding (JNCD) algorithms, which take into account possible decoding error at the relay, are developed in both DF and DMF relay protocols; (2) both perfect channel state information (CSI) and imperfect CSI at receivers are studied. In addition, we propose a practical method to forward the relays error characterization to the destination (quantization of the BER). This results in a fully practical scheme. (3) We show by simulation that the number of pilot symbols only affects the coding gain but not the diversity order, and that quantization accuracy affects both coding gain and diversity order. Moreover, when compared with the recent results using DMF protocol, our proposed DF protocol algorithm shows an improvement of 4 dB in fully interleaved Rayleigh fading channels and 0.7 dB in block Rayleigh fading channels.

Cyber Fighter Associate

DTIC Science & Technology

2016-01-01

accomplish a patch- management mission while securing a critical path. As a first proof of concept a simulation with a network of 10 nodes and 4...software-agility walk of the “PERFORMANCE Each Threat Managed ” tree is slightly more complex than the network -agility walk. The original design of the...CyFiA was tested to accomplish a patch- management mission while securing a critical path. As a first proof of concept a simulation with a network of 10

#AltPlanets: Exploring the Exoplanet Catalogue with Neural Networks

NASA Astrophysics Data System (ADS)

Laneuville, M.; Tasker, E. J.; Guttenberg, N.

2017-12-01

The launch of Kepler in 2009 brought the number of known exoplanets into the thousands, in a growth explosion that shows no sign of abating. While the data available for individual planets is presently typically restricted to orbital and bulk properties, the quantity of data points allows the potential for meaningful statistical analysis. It is not clear how planet mass, radius, orbital path, stellar properties and neighbouring planets influence one another, therefore it seems inevitable that patterns will be missed simply due to the difficulty of including so many dimensions. Even simple trends may be overlooked if they fall outside our expectation of planet formation; a strong risk in a field where new discoveries have destroyed theories from the first observations of hot Jupiters. A possible way forward is to take advantage of the capabilities of neural network autoencoders. The idea of such algorithms is to learn a representation (encoding) of the data in a lower dimension space, without a priori knowledge about links between the elements. This encoding space can then be used to discover the strongest correlations in the original dataset.The key point is that trends identified by a neural network are independent of any previous analysis and pre-conceived ideas about physical processes. Results can reveal new relationships between planet properties and verify existing trends. We applied this concept to study data from the NASA Exoplanet Archive and while we have begun to explore the potential use of neural networks for exoplanet data, there are many possible extensions. For example, the network can produce a large number of 'alternative planets' whose statistics should match the current distribution. This larger dataset could highlight gaps in the parameter space or indicate observations are missing particular regimes. This could guide instrument proposals towards objects liable to yield the most information.

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

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

Hyman, Jeffrey De'Haven; Hagberg, Aric Arild; Mohd-Yusof, Jamaludin

Here, we present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We also derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths.more » First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. We obtain accurate estimates of first passage times with an order of magnitude reduction of CPU time and mesh size using the proposed method.« less

Predictions of first passage times in sparse discrete fracture networks using graph-based reductions

DOE PAGES

Hyman, Jeffrey De'Haven; Hagberg, Aric Arild; Mohd-Yusof, Jamaludin; ...

2017-07-10

Here, we present a graph-based methodology to reduce the computational cost of obtaining first passage times through sparse fracture networks. We also derive graph representations of generic three-dimensional discrete fracture networks (DFNs) using the DFN topology and flow boundary conditions. Subgraphs corresponding to the union of the k shortest paths between the inflow and outflow boundaries are identified and transport on their equivalent subnetworks is compared to transport through the full network. The number of paths included in the subgraphs is based on the scaling behavior of the number of edges in the graph with the number of shortest paths.more » First passage times through the subnetworks are in good agreement with those obtained in the full network, both for individual realizations and in distribution. We obtain accurate estimates of first passage times with an order of magnitude reduction of CPU time and mesh size using the proposed method.« less

Consciousness Indexing and Outcome Prediction with Resting-State EEG in Severe Disorders of Consciousness.

PubMed

Stefan, Sabina; Schorr, Barbara; Lopez-Rolon, Alex; Kolassa, Iris-Tatjana; Shock, Jonathan P; Rosenfelder, Martin; Heck, Suzette; Bender, Andreas

2018-04-17

We applied the following methods to resting-state EEG data from patients with disorders of consciousness (DOC) for consciousness indexing and outcome prediction: microstates, entropy (i.e. approximate, permutation), power in alpha and delta frequency bands, and connectivity (i.e. weighted symbolic mutual information, symbolic transfer entropy, complex network analysis). Patients with unresponsive wakefulness syndrome (UWS) and patients in a minimally conscious state (MCS) were classified into these two categories by fitting and testing a generalised linear model. We aimed subsequently to develop an automated system for outcome prediction in severe DOC by selecting an optimal subset of features using sequential floating forward selection (SFFS). The two outcome categories were defined as UWS or dead, and MCS or emerged from MCS. Percentage of time spent in microstate D in the alpha frequency band performed best at distinguishing MCS from UWS patients. The average clustering coefficient obtained from thresholding beta coherence performed best at predicting outcome. The optimal subset of features selected with SFFS consisted of the frequency of microstate A in the 2-20 Hz frequency band, path length obtained from thresholding alpha coherence, and average path length obtained from thresholding alpha coherence. Combining these features seemed to afford high prediction power. Python and MATLAB toolboxes for the above calculations are freely available under the GNU public license for non-commercial use ( https://qeeg.wordpress.com ).

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

On/off ratio enhancement in single-walled carbon nanotube field-effect transistor by controlling network density via sonication

NASA Astrophysics Data System (ADS)

Jang, Ho-Kyun; Choi, Jun Hee; Kim, Do-Hyun; Kim, Gyu Tae

2018-06-01

Single-walled carbon nanotube (SWCNT) is generally used as a networked structure in the fabrication of a field-effect transistor (FET) since it is known that one-third of SWCNT is electrically metallic and the remains are semiconducting. In this case, the presence of metallic paths by metallic SWCNT (m-SWCNT) becomes a significant technical barrier which hinders the networks from achieving a semiconducting behavior, resulting in a low on/off ratio. Here, we report on an easy method of controlling the on/off ratio of a FET where semiconducting SWCNT (s-SWCNT) and m-SWCNT constitute networks between source and drain electrodes. A FET with SWCNT networks was simply sonicated under water to control the on/off ratio and network density. As a result, the FET having an almost metallic behavior due to the metallic paths by m-SWCNT exhibited a p-type semiconducting behavior. The on/off ratio ranged from 1 to 9.0 × 104 along sonication time. In addition, theoretical calculations based on Monte-Carlo method and circuit simulation were performed to understand and explain the phenomenon of a change in the on/off ratio and network density by sonication. On the basis of experimental and theoretical results, we found that metallic paths contributed to a high off-state current which leads to a low on/off ratio and that sonication formed sparse SWCNT networks where metallic paths of m-SWCNT were removed, resulting in a high on/off ratio. This method can open a chance to save the device which has been considered as a failed one due to a metallic behavior by a high network density leading to a low on/off ratio.

Advanced Monitoring Technology: Opportunities and Challenges - A Path Forward for EPA and States

EPA Science Inventory

Rapid changes in monitoring technology have the potential to dramatically improve environmental protection by providing industry, government, and the public with more complete and real-time information on pollution releases and environmental conditions. With more real-time monito...

Adaptive Management of Social-Ecological Systems: The Path Forward

EPA Science Inventory

Adaptive management remains at the forefront of environmental management nearly 40 years after its original conception, largely because we have yet to develop other methodologies that offer the same promise. Despite the criticisms of adaptive management and the numerous failed at...

Developmental Neurotoxicity Testing: A Path Forward

EPA Science Inventory

Great progress has been made over the past 40 years in understanding the hazards of exposure to a small number of developmental neurotoxicants. Lead, PCBs, and methylmercury are all good examples of science-based approaches to characterizing the hazard to the developing nervous s...

Orbital Debris and Future Environment Remediation

NASA Technical Reports Server (NTRS)

Liou, Jer-Chyi

2011-01-01

This slide presentation is an overview of the historical and current orbital debris environment. Included is information about: Projected growth of the future debris population, The need for active debris removal (ADR), A grand challenge for the 21st century and The forward path

Dynamic Simulation over Long Time Periods with 100% Solar Generation.

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

Concepcion, Ricky James; Elliott, Ryan Thomas

2015-12-01

This project aimed to identify the path forward for dynamic simulation tools to accommodate these needs by characterizing the properties of power systems (with high PV penetration), analyzing how these properties affect dynamic simulation software, and offering solutions for potential problems.

Organization of feed-forward loop motifs reveals architectural principles in natural and engineered networks.

PubMed

Gorochowski, Thomas E; Grierson, Claire S; di Bernardo, Mario

2018-03-01

Network motifs are significantly overrepresented subgraphs that have been proposed as building blocks for natural and engineered networks. Detailed functional analysis has been performed for many types of motif in isolation, but less is known about how motifs work together to perform complex tasks. To address this issue, we measure the aggregation of network motifs via methods that extract precisely how these structures are connected. Applying this approach to a broad spectrum of networked systems and focusing on the widespread feed-forward loop motif, we uncover striking differences in motif organization. The types of connection are often highly constrained, differ between domains, and clearly capture architectural principles. We show how this information can be used to effectively predict functionally important nodes in the metabolic network of Escherichia coli . Our findings have implications for understanding how networked systems are constructed from motif parts and elucidate constraints that guide their evolution.

Organization of feed-forward loop motifs reveals architectural principles in natural and engineered networks

PubMed Central

Grierson, Claire S.

2018-01-01

Network motifs are significantly overrepresented subgraphs that have been proposed as building blocks for natural and engineered networks. Detailed functional analysis has been performed for many types of motif in isolation, but less is known about how motifs work together to perform complex tasks. To address this issue, we measure the aggregation of network motifs via methods that extract precisely how these structures are connected. Applying this approach to a broad spectrum of networked systems and focusing on the widespread feed-forward loop motif, we uncover striking differences in motif organization. The types of connection are often highly constrained, differ between domains, and clearly capture architectural principles. We show how this information can be used to effectively predict functionally important nodes in the metabolic network of Escherichia coli. Our findings have implications for understanding how networked systems are constructed from motif parts and elucidate constraints that guide their evolution. PMID:29670941

Minimum-Risk Path Finding by an Adaptive Amoebal Network

NASA Astrophysics Data System (ADS)

Nakagaki, Toshiyuki; Iima, Makoto; Ueda, Tetsuo; Nishiura, Yasumasa; Saigusa, Tetsu; Tero, Atsushi; Kobayashi, Ryo; Showalter, Kenneth

2007-08-01

When two food sources are presented to the slime mold Physarum in the dark, a thick tube for absorbing nutrients is formed that connects the food sources through the shortest route. When the light-avoiding organism is partially illuminated, however, the tube connecting the food sources follows a different route. Defining risk as the experimentally measurable rate of light-avoiding movement, the minimum-risk path is exhibited by the organism, determined by integrating along the path. A model for an adaptive-tube network is presented that is in good agreement with the experimental observations.

Critical path method applied to research project planning: Fire Economics Evaluation System (FEES)

Treesearch

Earl B. Anderson; R. Stanton Hales

1986-01-01

The critical path method (CPM) of network analysis (a) depicts precedence among the many activities in a project by a network diagram; (b) identifies critical activities by calculating their starting, finishing, and float times; and (c) displays possible schedules by constructing time charts. CPM was applied to the development of the Forest Service's Fire...

Mathematical modeling of a radio-frequency path for IEEE 802.11ah based wireless sensor networks

NASA Astrophysics Data System (ADS)

Tyshchenko, Igor; Cherepanov, Alexander; Dmitrii, Vakhnin; Popova, Mariia

2017-09-01

This article discusses the process of creating the mathematical model of a radio-frequency path for an IEEE 802.11ah based wireless sensor networks using M atLab Simulink CAD tools. In addition, it describes occurring perturbing effects and determining the presence of a useful signal in the received mixture.

Iterative deep convolutional encoder-decoder network for medical image segmentation.

PubMed

Jung Uk Kim; Hak Gu Kim; Yong Man Ro

2017-07-01

In this paper, we propose a novel medical image segmentation using iterative deep learning framework. We have combined an iterative learning approach and an encoder-decoder network to improve segmentation results, which enables to precisely localize the regions of interest (ROIs) including complex shapes or detailed textures of medical images in an iterative manner. The proposed iterative deep convolutional encoder-decoder network consists of two main paths: convolutional encoder path and convolutional decoder path with iterative learning. Experimental results show that the proposed iterative deep learning framework is able to yield excellent medical image segmentation performances for various medical images. The effectiveness of the proposed method has been proved by comparing with other state-of-the-art medical image segmentation methods.

A scaling law for random walks on networks

PubMed Central

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-01-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics. PMID:25311870

A scaling law for random walks on networks

NASA Astrophysics Data System (ADS)

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

Topology and static response of interaction networks in molecular biology

PubMed Central

Radulescu, Ovidiu; Lagarrigue, Sandrine; Siegel, Anne; Veber, Philippe; Le Borgne, Michel

2005-01-01

We introduce a mathematical framework describing static response of networks occurring in molecular biology. This formalism has many similarities with the Laplace–Kirchhoff equations for electrical networks. We introduce the concept of graph boundary and we show how the response of the biological networks to external perturbations can be related to the Dirichlet or Neumann problems for the corresponding equations on the interaction graph. Solutions to these two problems are given in terms of path moduli (measuring path rigidity with respect to the propagation of interaction along the graph). Path moduli are related to loop products in the interaction graph via generalized Mason–Coates formulae. We apply our results to two specific biological examples: the lactose operon and the genetic regulation of lipogenesis. Our applications show consistency with experimental results and in the case of lipogenesis check some hypothesis on the behaviour of hepatic fatty acids on fasting. PMID:16849230

A scaling law for random walks on networks.

PubMed

Perkins, Theodore J; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-14

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

Adaptive management of social-ecological systems: the path forward

USGS Publications Warehouse

Allen, Craig R.

2015-01-01

Adaptive management remains at the forefront of environmental management nearly 40 years after its original conception, largely because we have yet to develop other methodologies that offer the same promise. Despite the criticisms of adaptive management and the numerous failed attempts to implement it, adaptive management has yet to be replaced with a better alternative. The concept persists because it is simple, allows action despite uncertainty, and fosters learning. Moving forward, adaptive management of social-ecological systems provides policymakers, managers and scientists a powerful tool for managing for resilience in the face of uncertainty.

Hierarchical Control Using Networks Trained with Higher-Level Forward Models

PubMed Central

Wayne, Greg; Abbott, L.F.

2015-01-01

We propose and develop a hierarchical approach to network control of complex tasks. In this approach, a low-level controller directs the activity of a “plant,” the system that performs the task. However, the low-level controller may only be able to solve fairly simple problems involving the plant. To accomplish more complex tasks, we introduce a higher-level controller that controls the lower-level controller. We use this system to direct an articulated truck to a specified location through an environment filled with static or moving obstacles. The final system consists of networks that have memorized associations between the sensory data they receive and the commands they issue. These networks are trained on a set of optimal associations that are generated by minimizing cost functions. Cost function minimization requires predicting the consequences of sequences of commands, which is achieved by constructing forward models, including a model of the lower-level controller. The forward models and cost minimization are only used during training, allowing the trained networks to respond rapidly. In general, the hierarchical approach can be extended to larger numbers of levels, dividing complex tasks into more manageable sub-tasks. The optimization procedure and the construction of the forward models and controllers can be performed in similar ways at each level of the hierarchy, which allows the system to be modified to perform other tasks, or to be extended for more complex tasks without retraining lower-levels. PMID:25058706

Edgeworth expansions of stochastic trading time

NASA Astrophysics Data System (ADS)

Decamps, Marc; De Schepper, Ann

2010-08-01

Under most local and stochastic volatility models the underlying forward is assumed to be a positive function of a time-changed Brownian motion. It relates nicely the implied volatility smile to the so-called activity rate in the market. Following Young and DeWitt-Morette (1986) [8], we propose to apply the Duru-Kleinert process-cum-time transformation in path integral to formulate the transition density of the forward. The method leads to asymptotic expansions of the transition density around a Gaussian kernel corresponding to the average activity in the market conditional on the forward value. The approximation is numerically illustrated for pricing vanilla options under the CEV model and the popular normal SABR model. The asymptotics can also be used for Monte Carlo simulations or backward integration schemes.

Hanford Spent Nuclear Fuel Project recommended path forward

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

Fulton, J.C.

The Spent Nuclear Fuel Project (the Project), in conjunction with the U.S. Department of Energy-commissioned Independent Technical Assessment (ITA) team, has developed engineered alternatives for expedited removal of spent nuclear fuel, including sludge, from the K Basins at Hanford. These alternatives, along with a foreign processing alternative offered by British Nuclear Fuels Limited (BNFL), were extensively reviewed and evaluated. Based on these evaluations, a Westinghouse Hanford Company (WHC) Recommended Path Forward for K Basins spent nuclear fuel has been developed and is presented in Volume I of this document. The recommendation constitutes an aggressive series of projects to construct andmore » operate systems and facilities to safely retrieve, package, transport, process, and store K Basins fuel and sludge. The overall processing and storage scheme is based on the ITA team`s proposed passivation and vault storage process. A dual purpose staging and vault storage facility provides an innovative feature which allows accelerated removal of fuel and sludge from the basins and minimizes programmatic risks beyond any of the originally proposed alternatives. The projects fit within a regulatory and National Environmental Policy Act (NEPA) overlay which mandates a two-phased approach to construction and operation of the needed facilities. The two-phase strategy packages and moves K Basins fuel and sludge to a newly constructed Staging and Storage Facility by the year 2000 where it is staged for processing. When an adjoining facility is constructed, the fuel is cycled through a stabilization process and returned to the Staging and Storage Facility for dry interim (40-year) storage. The estimated total expenditure for this Recommended Path Forward, including necessary new construction, operations, and deactivation of Project facilities through 2012, is approximately $1,150 million (unescalated).« less

Full-Scale Accident Testing in Support of Used Nuclear Fuel Transportation.

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

Durbin, Samuel G.; Lindgren, Eric R.; Rechard, Rob P.

2014-09-01

The safe transport of spent nuclear fuel and high-level radioactive waste is an important aspect of the waste management system of the United States. The Nuclear Regulatory Commission (NRC) currently certifies spent nuclear fuel rail cask designs based primarily on numerical modeling of hypothetical accident conditions augmented with some small scale testing. However, NRC initiated a Package Performance Study (PPS) in 2001 to examine the response of full-scale rail casks in extreme transportation accidents. The objectives of PPS were to demonstrate the safety of transportation casks and to provide high-fidelity data for validating the modeling. Although work on the PPSmore » eventually stopped, the Blue Ribbon Commission on America’s Nuclear Future recommended in 2012 that the test plans be re-examined. This recommendation was in recognition of substantial public feedback calling for a full-scale severe accident test of a rail cask to verify evaluations by NRC, which find that risk from the transport of spent fuel in certified casks is extremely low. This report, which serves as the re-assessment, provides a summary of the history of the PPS planning, identifies the objectives and technical issues that drove the scope of the PPS, and presents a possible path for moving forward in planning to conduct a full-scale cask test. Because full-scale testing is expensive, the value of such testing on public perceptions and public acceptance is important. Consequently, the path forward starts with a public perception component followed by two additional components: accident simulation and first responder training. The proposed path forward presents a series of study options with several points where the package performance study could be redirected if warranted.« less

Comparison of weighted and unweighted network analysis in the case of a pig trade network in Northern Germany.

PubMed

Büttner, Kathrin; Krieter, Joachim

2018-08-01

The analysis of trade networks as well as the spread of diseases within these systems focuses mainly on pure animal movements between farms. However, additional data included as edge weights can complement the informational content of the network analysis. However, the inclusion of edge weights can also alter the outcome of the network analysis. Thus, the aim of the study was to compare unweighted and weighted network analyses of a pork supply chain in Northern Germany and to evaluate the impact on the centrality parameters. Five different weighted network versions were constructed by adding the following edge weights: number of trade contacts, number of delivered livestock, average number of delivered livestock per trade contact, geographical distance and reciprocal geographical distance. Additionally, two different edge weight standardizations were used. The network observed from 2013 to 2014 contained 678 farms which were connected by 1,018 edges. General network characteristics including shortest path structure (e.g. identical shortest paths, shortest path lengths) as well as centrality parameters for each network version were calculated. Furthermore, the targeted and the random removal of farms were performed in order to evaluate the structural changes in the networks. All network versions and edge weight standardizations revealed the same number of shortest paths (1,935). Between 94.4 to 98.9% of the unweighted network and the weighted network versions were identical. Furthermore, depending on the calculated centrality parameters and the edge weight standardization used, it could be shown that the weighted network versions differed from the unweighted network (e.g. for the centrality parameters based on ingoing trade contacts) or did not differ (e.g. for the centrality parameters based on the outgoing trade contacts) with regard to the Spearman Rank Correlation and the targeted removal of farms. The choice of standardization method as well as the inclusion or exclusion of specific farm types (e.g. abattoirs) can alter the results significantly. These facts have to be considered when centrality parameters are to be used for the implementation of prevention and control strategies in the case of an epidemic. Copyright © 2018 Elsevier B.V. All rights reserved.

Reliability analysis of C-130 turboprop engine components using artificial neural network

NASA Astrophysics Data System (ADS)

Qattan, Nizar A.

In this study, we predict the failure rate of Lockheed C-130 Engine Turbine. More than thirty years of local operational field data were used for failure rate prediction and validation. The Weibull regression model and the Artificial Neural Network model including (feed-forward back-propagation, radial basis neural network, and multilayer perceptron neural network model); will be utilized to perform this study. For this purpose, the thesis will be divided into five major parts. First part deals with Weibull regression model to predict the turbine general failure rate, and the rate of failures that require overhaul maintenance. The second part will cover the Artificial Neural Network (ANN) model utilizing the feed-forward back-propagation algorithm as a learning rule. The MATLAB package will be used in order to build and design a code to simulate the given data, the inputs to the neural network are the independent variables, the output is the general failure rate of the turbine, and the failures which required overhaul maintenance. In the third part we predict the general failure rate of the turbine and the failures which require overhaul maintenance, using radial basis neural network model on MATLAB tool box. In the fourth part we compare the predictions of the feed-forward back-propagation model, with that of Weibull regression model, and radial basis neural network model. The results show that the failure rate predicted by the feed-forward back-propagation artificial neural network model is closer in agreement with radial basis neural network model compared with the actual field-data, than the failure rate predicted by the Weibull model. By the end of the study, we forecast the general failure rate of the Lockheed C-130 Engine Turbine, the failures which required overhaul maintenance and six categorical failures using multilayer perceptron neural network (MLP) model on DTREG commercial software. The results also give an insight into the reliability of the engine turbine under actual operating conditions, which can be used by aircraft operators for assessing system and component failures and customizing the maintenance programs recommended by the manufacturer.

Synthetic Biomaterials to Rival Nature's Complexity-a Path Forward with Combinatorics, High-Throughput Discovery, and High-Content Analysis.

PubMed

Zhang, Douglas; Lee, Junmin; Kilian, Kristopher A

2017-10-01

Cells in tissue receive a host of soluble and insoluble signals in a context-dependent fashion, where integration of these cues through a complex network of signal transduction cascades will define a particular outcome. Biomaterials scientists and engineers are tasked with designing materials that can at least partially recreate this complex signaling milieu towards new materials for biomedical applications. In this progress report, recent advances in high throughput techniques and high content imaging approaches that are facilitating the discovery of efficacious biomaterials are described. From microarrays of synthetic polymers, peptides and full-length proteins, to designer cell culture systems that present multiple biophysical and biochemical cues in tandem, it is discussed how the integration of combinatorics with high content imaging and analysis is essential to extracting biologically meaningful information from large scale cellular screens to inform the design of next generation biomaterials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Forward modeling of an atmospheric scenario: path characterization in terms of scattering intensity

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

Bosisio, Ada Vittoria; Cadeddu, Maria P.; Fionda, Ermanno

The knowledge of possible impairments due to atmospheric propagation is of importance in the framework of future 5G mobile networks that use spectrum resource up to the W band. Here, the authors propose the scalar Scatter Indicator (SI), defined as the difference between the simulated TB at 72 GHz and the TB value at the same frequency estimated from a combination of TBs values at 23.8 and 31.4 GHz under assumed scatter-free condition. On the basis of radiosonde profiles observed in Milan, Linate (Italy) in 2005, clear-sky scenarios are used as reference to define a scatter-free TB’s database. A secondmore » database of simulated TBs including scattering effects is generated with ARTS to build the SI. Numerical results show that the SI assumes significant positive values with increasing drop effective radius and total liquid water LWP and it can be used to identify the scattering due to hydrometeor« less

MWR3C physical retrievals of precipitable water vapor and cloud liquid water path

DOE Data Explorer

Cadeddu, Maria

2016-10-12

The data set contains physical retrievals of PWV and cloud LWP retrieved from MWR3C measurements during the MAGIC campaign. Additional data used in the retrieval process include radiosondes and ceilometer. The retrieval is based on an optimal estimation technique that starts from a first guess and iteratively repeats the forward model calculations until a predefined convergence criterion is satisfied. The first guess is a vector of [PWV,LWP] from the neural network retrieval fields in the netcdf file. When convergence is achieved the 'a posteriori' covariance is computed and its square root is expressed in the file as the retrieval 1-sigma uncertainty. The closest radiosonde profile is used for the radiative transfer calculations and ceilometer data are used to constrain the cloud base height. The RMS error between the brightness temperatures is computed at the last iterations as a consistency check and is written in the last column of the output file.

Newberry EGS Seismic Velocity Model

DOE Data Explorer

Templeton, Dennise

2013-10-01

We use ambient noise correlation (ANC) to create a detailed image of the subsurface seismic velocity at the Newberry EGS site down to 5 km. We collected continuous data for the 22 stations in the Newberry network, together with 12 additional stations from the nearby CC, UO and UW networks. The data were instrument corrected, whitened and converted to single bit traces before cross correlation according to the methodology in Benson (2007). There are 231 unique paths connecting the 22 stations of the Newberry network. The additional networks extended that to 402 unique paths crossing beneath the Newberry site.

An industrial robot singular trajectories planning based on graphs and neural networks

NASA Astrophysics Data System (ADS)

Łęgowski, Adrian; Niezabitowski, Michał

2016-06-01

Singular trajectories are rarely used because of issues during realization. A method of planning trajectories for given set of points in task space with use of graphs and neural networks is presented. In every desired point the inverse kinematics problem is solved in order to derive all possible solutions. A graph of solutions is made. The shortest path is determined to define required nodes in joint space. Neural networks are used to define the path between these nodes.

Graphene-based battery electrodes having continuous flow paths

DOEpatents

Zhang, Jiguang; Xiao, Jie; Liu, Jun; Xu, Wu; Li, Xiaolin; Wang, Deyu

2014-05-24

Some batteries can exhibit greatly improved performance by utilizing electrodes having randomly arranged graphene nanosheets forming a network of channels defining continuous flow paths through the electrode. The network of channels can provide a diffusion pathway for the liquid electrolyte and/or for reactant gases. Metal-air batteries can benefit from such electrodes. In particular Li-air batteries show extremely high capacities, wherein the network of channels allow oxygen to diffuse through the electrode and mesopores in the electrode can store discharge products.

Joint Energy Supply and Routing Path Selection for Rechargeable Wireless Sensor Networks.

PubMed

Tang, Liangrui; Cai, Jinqi; Yan, Jiangyu; Zhou, Zhenyu

2018-06-17

The topic of network lifetime has been attracting much research attention because of its importance in prolonging the standing operation of battery-restricted wireless sensor networks, and the rechargeable wireless sensor network has emerged as a promising solution. In this paper, we propose a joint energy supply and routing path selection algorithm to extend the network lifetime based on an initiative power supply. We develop a two-stage energy replenishment strategy to supplement the energy consumption of nodes as much as possible. Furthermore, the influence of charging factors on the selection of next-hop nodes in data routing is considered. The simulation results show that our algorithm effectively prolong the network lifetime, and different demands of network delay and energy consumption can be obtained by dynamically adjusting parameters.

Graph modeling systems and methods

DOEpatents

Neergaard, Mike

2015-10-13

An apparatus and a method for vulnerability and reliability modeling are provided. The method generally includes constructing a graph model of a physical network using a computer, the graph model including a plurality of terminating vertices to represent nodes in the physical network, a plurality of edges to represent transmission paths in the physical network, and a non-terminating vertex to represent a non-nodal vulnerability along a transmission path in the physical network. The method additionally includes evaluating the vulnerability and reliability of the physical network using the constructed graph model, wherein the vulnerability and reliability evaluation includes a determination of whether each terminating and non-terminating vertex represents a critical point of failure. The method can be utilized to evaluate wide variety of networks, including power grid infrastructures, communication network topologies, and fluid distribution systems.

Optimal solution for travelling salesman problem using heuristic shortest path algorithm with imprecise arc length

NASA Astrophysics Data System (ADS)

Bakar, Sumarni Abu; Ibrahim, Milbah

2017-08-01

The shortest path problem is a popular problem in graph theory. It is about finding a path with minimum length between a specified pair of vertices. In any network the weight of each edge is usually represented in a form of crisp real number and subsequently the weight is used in the calculation of shortest path problem using deterministic algorithms. However, due to failure, uncertainty is always encountered in practice whereby the weight of edge of the network is uncertain and imprecise. In this paper, a modified algorithm which utilized heuristic shortest path method and fuzzy approach is proposed for solving a network with imprecise arc length. Here, interval number and triangular fuzzy number in representing arc length of the network are considered. The modified algorithm is then applied to a specific example of the Travelling Salesman Problem (TSP). Total shortest distance obtained from this algorithm is then compared with the total distance obtained from traditional nearest neighbour heuristic algorithm. The result shows that the modified algorithm can provide not only on the sequence of visited cities which shown to be similar with traditional approach but it also provides a good measurement of total shortest distance which is lesser as compared to the total shortest distance calculated using traditional approach. Hence, this research could contribute to the enrichment of methods used in solving TSP.

Real time measurement of transient event emissions of air toxics by tomographic remote sensing in tandem with mobile monitoring

NASA Astrophysics Data System (ADS)

Olaguer, Eduardo P.; Stutz, Jochen; Erickson, Matthew H.; Hurlock, Stephen C.; Cheung, Ross; Tsai, Catalina; Colosimo, Santo F.; Festa, James; Wijesinghe, Asanga; Neish, Bradley S.

2017-02-01

During the Benzene and other Toxics Exposure (BEE-TEX) study, a remote sensing network based on long path Differential Optical Absorption Spectroscopy (DOAS) was set up in the Manchester neighborhood beside the Ship Channel of Houston, Texas in order to perform Computer Aided Tomography (CAT) scans of hazardous air pollutants. On 18-19 February 2015, the CAT scan network detected large nocturnal plumes of toluene and xylenes most likely associated with railcar loading and unloading operations at Ship Channel petrochemical facilities. The presence of such plumes during railcar operations was confirmed by a mobile laboratory equipped with a Proton Transfer Reaction-Mass Spectrometer (PTR-MS), which measured transient peaks of toluene and C2-benzenes of 50 ppb and 57 ppb respectively around 4 a.m. LST on 19 February 2015. Plume reconstruction and source attribution were performed using the 4D variational data assimilation technique and a 3D micro-scale forward and adjoint air quality model based on both tomographic and PTR-MS data. Inverse model estimates of fugitive emissions associated with railcar transfer emissions ranged from 2.0 to 8.2 kg/hr for toluene and from 2.2 to 3.5 kg/hr for xylenes in the early morning of 19 February 2015.

Remediation to restoration to revitalization: A path forward for AOCs progress report

EPA Science Inventory

At the 2016 Great Lakes Areas of Concern (AOC) Conference, researchers from the USEPA Office of Research and Development (ORD) sparked conversation about community revitalization and the different states of progress throughout the basin. The conversation was meant to provide AOC ...

A perspective on forward research and development paths for cost-effective solar energy utilization.

PubMed

Lewis, Nathan S

2009-01-01

Solar electricity has long been recognized as a potential energy source that holds great promise. Several approaches towards converting sunlight into energy are elaborated in this Viewpoint, and discussed with respect to their feasibility for large-scale application.

Life Cycle Impacts of a Commercial Rainwater Harvesting System and Sustainability

EPA Science Inventory

A sustainability paradigm is being recognized globally as a path forward for human prosperity and ecological health in the face of climate change and challenges of the water-energy-food nexus. Rainwater harvesting (RWH) and related green infrastructure practices are receiving ren...

A path forward in the debate over health impacts of endocrine disrupting chemicals.

PubMed

Zoeller, R Thomas; Bergman, Åke; Becher, Georg; Bjerregaard, Poul; Bornman, Riana; Brandt, Ingvar; Iguchi, Taisen; Jobling, Susan; Kidd, Karen A; Kortenkamp, Andreas; Skakkebaek, Niels E; Toppari, Jorma; Vandenberg, Laura N

2014-12-22

Several recent publications reflect debate on the issue of "endocrine disrupting chemicals" (EDCs), indicating that two seemingly mutually exclusive perspectives are being articulated separately and independently. Considering this, a group of scientists with expertise in basic science, medicine and risk assessment reviewed the various aspects of the debate to identify the most significant areas of dispute and to propose a path forward. We identified four areas of debate. The first is about the definitions for terms such as "endocrine disrupting chemical", "adverse effects", and "endocrine system". The second is focused on elements of hormone action including "potency", "endpoints", "timing", "dose" and "thresholds". The third addresses the information needed to establish sufficient evidence of harm. Finally, the fourth focuses on the need to develop and the characteristics of transparent, systematic methods to review the EDC literature. Herein we identify areas of general consensus and propose resolutions for these four areas that would allow the field to move beyond the current and, in our opinion, ineffective debate.

EDOVE: Energy and Depth Variance-Based Opportunistic Void Avoidance Scheme for Underwater Acoustic Sensor Networks

PubMed Central

Eun, Yongsoon

2017-01-01

Underwater Acoustic Sensor Network (UASN) comes with intrinsic constraints because it is deployed in the aquatic environment and uses the acoustic signals to communicate. The examples of those constraints are long propagation delay, very limited bandwidth, high energy cost for transmission, very high signal attenuation, costly deployment and battery replacement, and so forth. Therefore, the routing schemes for UASN must take into account those characteristics to achieve energy fairness, avoid energy holes, and improve the network lifetime. The depth based forwarding schemes in literature use node’s depth information to forward data towards the sink. They minimize the data packet duplication by employing the holding time strategy. However, to avoid void holes in the network, they use two hop node proximity information. In this paper, we propose the Energy and Depth variance-based Opportunistic Void avoidance (EDOVE) scheme to gain energy balancing and void avoidance in the network. EDOVE considers not only the depth parameter, but also the normalized residual energy of the one-hop nodes and the normalized depth variance of the second hop neighbors. Hence, it avoids the void regions as well as balances the network energy and increases the network lifetime. The simulation results show that the EDOVE gains more than 15% packet delivery ratio, propagates 50% less copies of data packet, consumes less energy, and has more lifetime than the state of the art forwarding schemes. PMID:28954395

EDOVE: Energy and Depth Variance-Based Opportunistic Void Avoidance Scheme for Underwater Acoustic Sensor Networks.

PubMed

Bouk, Safdar Hussain; Ahmed, Syed Hassan; Park, Kyung-Joon; Eun, Yongsoon

2017-09-26

Underwater Acoustic Sensor Network (UASN) comes with intrinsic constraints because it is deployed in the aquatic environment and uses the acoustic signals to communicate. The examples of those constraints are long propagation delay, very limited bandwidth, high energy cost for transmission, very high signal attenuation, costly deployment and battery replacement, and so forth. Therefore, the routing schemes for UASN must take into account those characteristics to achieve energy fairness, avoid energy holes, and improve the network lifetime. The depth based forwarding schemes in literature use node's depth information to forward data towards the sink. They minimize the data packet duplication by employing the holding time strategy. However, to avoid void holes in the network, they use two hop node proximity information. In this paper, we propose the Energy and Depth variance-based Opportunistic Void avoidance (EDOVE) scheme to gain energy balancing and void avoidance in the network. EDOVE considers not only the depth parameter, but also the normalized residual energy of the one-hop nodes and the normalized depth variance of the second hop neighbors. Hence, it avoids the void regions as well as balances the network energy and increases the network lifetime. The simulation results show that the EDOVE gains more than 15 % packet delivery ratio, propagates 50 % less copies of data packet, consumes less energy, and has more lifetime than the state of the art forwarding schemes.

Resonant optical scattering in nanoparticle-doped polymer photonic crystals

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

Baumberg, J. J.; Pursiainen, O. L.; Spahn, P.

2009-11-15

A broadband hyperspectral technique is used to measure the coherent optical backscatter across a wide spectral bandwidth, showing the resonant suppression of the photon transport mean free path around the photonic bandgap of a shear-assembled polymer photonic crystal. By doping with carbon nanoscale scatterers that reside at specific points within the photonic crystal lattice, the ratio between photon mean free path and optical penetration is tuned from 10 to 1, enhancing forward scatter at the expense of back-scatter. The back-scattering strength of different polarisations is not explained by any current theory.

The Thinnest Path Problem

DTIC Science & Technology

2013-10-01

of vertices located within the d-dimensional sphere centered at vi 1In [3], it is referred to as the forward hyperarcs. 3 replacements Fig. 1: (a...kr ← kr + 1 · Set the parent of vkr+1 to v ∗ While v can reach vkl−1 · Enqueue vkl−1 and kl ← kl − 1 · Set the parent of vkl−1 to v 3. If the Queue... parent of this vertex on this path. This allows us to take the set union operation when we update the neighbors of this vertex. Given below is the

a Modified Genetic Algorithm for Finding Fuzzy Shortest Paths in Uncertain Networks

NASA Astrophysics Data System (ADS)

Heidari, A. A.; Delavar, M. R.

2016-06-01

In realistic network analysis, there are several uncertainties in the measurements and computation of the arcs and vertices. These uncertainties should also be considered in realizing the shortest path problem (SPP) due to the inherent fuzziness in the body of expert's knowledge. In this paper, we investigated the SPP under uncertainty to evaluate our modified genetic strategy. We improved the performance of genetic algorithm (GA) to investigate a class of shortest path problems on networks with vague arc weights. The solutions of the uncertain SPP with considering fuzzy path lengths are examined and compared in detail. As a robust metaheuristic, GA algorithm is modified and evaluated to tackle the fuzzy SPP (FSPP) with uncertain arcs. For this purpose, first, a dynamic operation is implemented to enrich the exploration/exploitation patterns of the conventional procedure and mitigate the premature convergence of GA technique. Then, the modified GA (MGA) strategy is used to resolve the FSPP. The attained results of the proposed strategy are compared to those of GA with regard to the cost, quality of paths and CPU times. Numerical instances are provided to demonstrate the success of the proposed MGA-FSPP strategy in comparison with GA. The simulations affirm that not only the proposed technique can outperform GA, but also the qualities of the paths are effectively improved. The results clarify that the competence of the proposed GA is preferred in view of quality quantities. The results also demonstrate that the proposed method can efficiently be utilized to handle FSPP in uncertain networks.

Three-tier multi-granularity switching system based on PCE

NASA Astrophysics Data System (ADS)

Wang, Yubao; Sun, Hao; Liu, Yanfei

2017-10-01

With the growing demand for business communications, electrical signal processing optical path switching can't meet the demand. The multi-granularity switch system that can improve node routing and switching capabilities came into being. In the traditional network, each node is responsible for calculating the path; synchronize the whole network state, which will increase the burden on the network, so the concept of path calculation element (PCE) is proposed. The PCE is responsible for routing and allocating resources in the network1. In the traditional band-switched optical network, the wavelength is used as the basic routing unit, resulting in relatively low wavelength utilization. Due to the limitation of wavelength continuity, the routing design of the band technology becomes complicated, which directly affects the utilization of the system. In this paper, optical code granularity is adopted. There is no continuity of the optical code, and the number of optical codes is more flexible than the wavelength. For the introduction of optical code switching, we propose a Code Group Routing Entity (CGRE) algorithm. In short, the combination of three-tier multi-granularity optical switching system and PCE can simplify the network structure, reduce the node load, and enhance the network scalability and survivability. Realize the intelligentization of optical network.

Receiver-Based Ad Hoc On Demand Multipath Routing Protocol for Mobile Ad Hoc Networks

PubMed Central

Al-Nahari, Abdulaziz; Mohamad, Mohd Murtadha

2016-01-01

Decreasing the route rediscovery time process in reactive routing protocols is challenging in mobile ad hoc networks. Links between nodes are continuously established and broken because of the characteristics of the network. Finding multiple routes to increase the reliability is also important but requires a fast update, especially in high traffic load and high mobility where paths can be broken as well. The sender node keeps re-establishing path discovery to find new paths, which makes for long time delay. In this paper we propose an improved multipath routing protocol, called Receiver-based ad hoc on demand multipath routing protocol (RB-AOMDV), which takes advantage of the reliability of the state of the art ad hoc on demand multipath distance vector (AOMDV) protocol with less re-established discovery time. The receiver node assumes the role of discovering paths when finding data packets that have not been received after a period of time. Simulation results show the delay and delivery ratio performances are improved compared with AOMDV. PMID:27258013

An Energy-Efficient and Robust Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks.

PubMed

Singh, Kishor; Moh, Sangman

2017-09-04

Routing in cognitive radio ad hoc networks (CRAHNs) is a daunting task owing to dynamic topology, intermittent connectivity, spectrum heterogeneity, and energy constraints. Other prominent aspects such as channel stability, path reliability, and route discovery frequency should also be exploited. Several routing protocols have been proposed for CRAHNs in the literature. By stressing on one of the aspects more than any other, however, they do not satisfy all requirements of throughput, energy efficiency, and robustness. In this paper, we propose an energy-efficient and robust multipath routing (ERMR) protocol for CRAHNs by considering all prominent aspects including residual energy and channel stability in design. Even when the current routing path fails, the alternative routing path is immediately utilized. In establishing primary and alternative routing paths, both residual energy and channel stability are exploited simultaneously. Our simulation study shows that the proposed ERMR outperforms the conventional protocol in terms of network throughput, packet delivery ratio, energy consumption, and end-to-end delay.

An Energy-Efficient and Robust Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks

PubMed Central

Singh, Kishor

2017-01-01

Routing in cognitive radio ad hoc networks (CRAHNs) is a daunting task owing to dynamic topology, intermittent connectivity, spectrum heterogeneity, and energy constraints. Other prominent aspects such as channel stability, path reliability, and route discovery frequency should also be exploited. Several routing protocols have been proposed for CRAHNs in the literature. By stressing on one of the aspects more than any other, however, they do not satisfy all requirements of throughput, energy efficiency, and robustness. In this paper, we propose an energy-efficient and robust multipath routing (ERMR) protocol for CRAHNs by considering all prominent aspects including residual energy and channel stability in design. Even when the current routing path fails, the alternative routing path is immediately utilized. In establishing primary and alternative routing paths, both residual energy and channel stability are exploited simultaneously. Our simulation study shows that the proposed ERMR outperforms the conventional protocol in terms of network throughput, packet delivery ratio, energy consumption, and end-to-end delay. PMID:28869551

Receiver-Based Ad Hoc On Demand Multipath Routing Protocol for Mobile Ad Hoc Networks.

PubMed

Al-Nahari, Abdulaziz; Mohamad, Mohd Murtadha

2016-01-01

Decreasing the route rediscovery time process in reactive routing protocols is challenging in mobile ad hoc networks. Links between nodes are continuously established and broken because of the characteristics of the network. Finding multiple routes to increase the reliability is also important but requires a fast update, especially in high traffic load and high mobility where paths can be broken as well. The sender node keeps re-establishing path discovery to find new paths, which makes for long time delay. In this paper we propose an improved multipath routing protocol, called Receiver-based ad hoc on demand multipath routing protocol (RB-AOMDV), which takes advantage of the reliability of the state of the art ad hoc on demand multipath distance vector (AOMDV) protocol with less re-established discovery time. The receiver node assumes the role of discovering paths when finding data packets that have not been received after a period of time. Simulation results show the delay and delivery ratio performances are improved compared with AOMDV.

Statistical similarity measures for link prediction in heterogeneous complex networks

NASA Astrophysics Data System (ADS)

Shakibian, Hadi; Charkari, Nasrollah Moghadam

2018-07-01

The majority of the link prediction measures in heterogeneous complex networks rely on the nodes connectivities while less attention has been paid to the importance of the nodes and paths. In this paper, we propose some new meta-path based statistical similarity measures to properly perform link prediction task. The main idea in the proposed measures is to drive some co-occurrence events in a number of co-occurrence matrices that are occurred between the visited nodes obeying a meta-path. The extracted co-occurrence matrices are analyzed in terms of the energy, inertia, local homogeneity, correlation, and information measure of correlation to determine various information theoretic measures. We evaluate the proposed measures, denoted as link energy, link inertia, link local homogeneity, link correlation, and link information measure of correlation, using a standard DBLP network data set. The results of the AUC score and Precision rate indicate the validity and accuracy of the proposed measures in comparison to the popular meta-path based similarity measures.

Defending Tor from Network Adversaries: A Case Study of Network Path Prediction

DTIC Science & Technology

2015-01-01

independence in Tor. 5.1 Vanilla Tor All of our Tor simulations run over the week of January 19– 25, 2014. When producing and analyzing these simulations, we...selection using path simula- tion and our traceroute data, similar to how they were used in Section 5.1 to explore vanilla Tor security. As a byproduct

Tensor Spectral Clustering for Partitioning Higher-order Network Structures.

PubMed

Benson, Austin R; Gleich, David F; Leskovec, Jure

2015-01-01

Spectral graph theory-based methods represent an important class of tools for studying the structure of networks. Spectral methods are based on a first-order Markov chain derived from a random walk on the graph and thus they cannot take advantage of important higher-order network substructures such as triangles, cycles, and feed-forward loops. Here we propose a Tensor Spectral Clustering (TSC) algorithm that allows for modeling higher-order network structures in a graph partitioning framework. Our TSC algorithm allows the user to specify which higher-order network structures (cycles, feed-forward loops, etc.) should be preserved by the network clustering. Higher-order network structures of interest are represented using a tensor, which we then partition by developing a multilinear spectral method. Our framework can be applied to discovering layered flows in networks as well as graph anomaly detection, which we illustrate on synthetic networks. In directed networks, a higher-order structure of particular interest is the directed 3-cycle, which captures feedback loops in networks. We demonstrate that our TSC algorithm produces large partitions that cut fewer directed 3-cycles than standard spectral clustering algorithms.

Tensor Spectral Clustering for Partitioning Higher-order Network Structures

PubMed Central

Benson, Austin R.; Gleich, David F.; Leskovec, Jure

2016-01-01

Spectral graph theory-based methods represent an important class of tools for studying the structure of networks. Spectral methods are based on a first-order Markov chain derived from a random walk on the graph and thus they cannot take advantage of important higher-order network substructures such as triangles, cycles, and feed-forward loops. Here we propose a Tensor Spectral Clustering (TSC) algorithm that allows for modeling higher-order network structures in a graph partitioning framework. Our TSC algorithm allows the user to specify which higher-order network structures (cycles, feed-forward loops, etc.) should be preserved by the network clustering. Higher-order network structures of interest are represented using a tensor, which we then partition by developing a multilinear spectral method. Our framework can be applied to discovering layered flows in networks as well as graph anomaly detection, which we illustrate on synthetic networks. In directed networks, a higher-order structure of particular interest is the directed 3-cycle, which captures feedback loops in networks. We demonstrate that our TSC algorithm produces large partitions that cut fewer directed 3-cycles than standard spectral clustering algorithms. PMID:27812399

Calibration of neural networks using genetic algorithms, with application to optimal path planning

NASA Technical Reports Server (NTRS)

Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel

1987-01-01

Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.

A characterization of the coupled evolution of grain fabric and pore space using complex networks: Pore connectivity and optimized flows in the presence of shear bands

NASA Astrophysics Data System (ADS)

Russell, Scott; Walker, David M.; Tordesillas, Antoinette

2016-03-01

A framework for the multiscale characterization of the coupled evolution of the solid grain fabric and its associated pore space in dense granular media is developed. In this framework, a pseudo-dual graph transformation of the grain contact network produces a graph of pores which can be readily interpreted as a pore space network. Survivability, a new metric succinctly summarizing the connectivity of the solid grain and pore space networks, measures material robustness. The size distribution and the connectivity of pores can be characterized quantitatively through various network properties. Assortativity characterizes the pore space with respect to the parity of the number of particles enclosing the pore. Multiscale clusters of odd parity versus even parity contact cycles alternate spatially along the shear band: these represent, respectively, local jamming and unjamming regions that continually switch positions in time throughout the failure regime. Optimal paths, established using network shortest paths in favor of large pores, provide clues on preferential paths for interstitial matter transport. In systems with higher rolling resistance at contacts, less tortuous shortest paths thread through larger pores in shear bands. Notably the structural patterns uncovered in the pore space suggest that more robust models of interstitial pore flow through deforming granular systems require a proper consideration of the evolution of in situ shear band and fracture patterns - not just globally, but also inside these localized failure zones.

An Experiment of GMPLS-Based Dispersion Compensation Control over In-Field Fibers

NASA Astrophysics Data System (ADS)

Seno, Shoichiro; Horiuchi, Eiichi; Yoshida, Sota; Sugihara, Takashi; Onohara, Kiyoshi; Kamei, Misato; Baba, Yoshimasa; Kubo, Kazuo; Mizuochi, Takashi

As ROADMs (Reconfigurable Optical Add/Drop Multiplexers) are becoming widely used in metro/core networks, distributed control of wavelength paths by extended GMPLS (Generalized MultiProtocol Label Switching) protocols has attracted much attention. For the automatic establishment of an arbitrary wavelength path satisfying dynamic traffic demands over a ROADM or WXC (Wavelength Cross Connect)-based network, precise determination of chromatic dispersion over the path and optimized assignment of dispersion compensation capabilities at related nodes are essential. This paper reports an experiment over in-field fibers where GMPLS-based control was applied for the automatic discovery of chromatic dispersion, path computation, and wavelength path establishment with dynamic adjustment of variable dispersion compensation. The GMPLS-based control scheme, which the authors called GMPLS-Plus, extended GMPLS's distributed control architecture with attributes for automatic discovery, advertisement, and signaling of chromatic dispersion. In this experiment, wavelength paths with distances of 24km and 360km were successfully established and error-free data transmission was verified. The experiment also confirmed path restoration with dynamic compensation adjustment upon fiber failure.

A design of wireless sensor networks for a power quality monitoring system.

PubMed

Lim, Yujin; Kim, Hak-Man; Kang, Sanggil

2010-01-01

Power grids deal with the business of generation, transmission, and distribution of electric power. Recently, interest in power quality in electrical distribution systems has increased rapidly. In Korea, the communication network to deliver voltage, current, and temperature measurements gathered from pole transformers to remote monitoring centers employs cellular mobile technology. Due to high cost of the cellular mobile technology, power quality monitoring measurements are limited and data gathering intervals are large. This causes difficulties in providing the power quality monitoring service. To alleviate the problems, in this paper we present a communication infrastructure to provide low cost, reliable data delivery. The communication infrastructure consists of wired connections between substations and monitoring centers, and wireless connections between pole transformers and substations. For the wireless connection, we employ a wireless sensor network and design its corresponding data forwarding protocol to improve the quality of data delivery. For the design, we adopt a tree-based data forwarding protocol in order to customize the distribution pattern of the power quality information. We verify the performance of the proposed data forwarding protocol quantitatively using the NS-2 network simulator.

A p-i-n junction diode based on locally doped carbon nanotube network

PubMed Central

Liu, Xiaodong; Chen, Changxin; Wei, Liangming; Hu, Nantao; Song, Chuanjuan; Liao, Chenghao; He, Rong; Dong, Xusheng; Wang, Ying; Liu, Qinran; Zhang, Yafei

2016-01-01

A p-i-n junction diode constructed by the locally doped network of single-walled carbon nanotubes (SWNTs) was investigated. In this diode, the two opposite ends of the SWNT-network channel were selectively doped by triethyloxonium hexachloroantimonate (OA) and polyethylenimine (PEI) to obtain the air-stable p- and n-type SWNTs respectively while the central area of the SWNT-network remained intrinsic state, resulting in the formation of a p-i-n junction with a strong built-in electronic field in the SWNTs. The results showed that the forward current and the rectification ratio of the diode increased as the doping degree increased. The forward current of the device could also be increased by decreasing the channel length. A high-performance p-i-n junction diode with a high rectification ratio (~104), large forward current (~12.2 μA) and low reverse saturated current (~1.8 nA) was achieved with the OA and PEI doping time of 5 h and 18 h for a channel length of ~6 μm. PMID:26996610

A p-i-n junction diode based on locally doped carbon nanotube network.

PubMed

Liu, Xiaodong; Chen, Changxin; Wei, Liangming; Hu, Nantao; Song, Chuanjuan; Liao, Chenghao; He, Rong; Dong, Xusheng; Wang, Ying; Liu, Qinran; Zhang, Yafei

2016-03-21

A p-i-n junction diode constructed by the locally doped network of single-walled carbon nanotubes (SWNTs) was investigated. In this diode, the two opposite ends of the SWNT-network channel were selectively doped by triethyloxonium hexachloroantimonate (OA) and polyethylenimine (PEI) to obtain the air-stable p- and n-type SWNTs respectively while the central area of the SWNT-network remained intrinsic state, resulting in the formation of a p-i-n junction with a strong built-in electronic field in the SWNTs. The results showed that the forward current and the rectification ratio of the diode increased as the doping degree increased. The forward current of the device could also be increased by decreasing the channel length. A high-performance p-i-n junction diode with a high rectification ratio (~10(4)), large forward current (~12.2 μA) and low reverse saturated current (~1.8 nA) was achieved with the OA and PEI doping time of 5 h and 18 h for a channel length of ~6 μm.

A p-i-n junction diode based on locally doped carbon nanotube network

NASA Astrophysics Data System (ADS)

Liu, Xiaodong; Chen, Changxin; Wei, Liangming; Hu, Nantao; Song, Chuanjuan; Liao, Chenghao; He, Rong; Dong, Xusheng; Wang, Ying; Liu, Qinran; Zhang, Yafei

2016-03-01

A p-i-n junction diode constructed by the locally doped network of single-walled carbon nanotubes (SWNTs) was investigated. In this diode, the two opposite ends of the SWNT-network channel were selectively doped by triethyloxonium hexachloroantimonate (OA) and polyethylenimine (PEI) to obtain the air-stable p- and n-type SWNTs respectively while the central area of the SWNT-network remained intrinsic state, resulting in the formation of a p-i-n junction with a strong built-in electronic field in the SWNTs. The results showed that the forward current and the rectification ratio of the diode increased as the doping degree increased. The forward current of the device could also be increased by decreasing the channel length. A high-performance p-i-n junction diode with a high rectification ratio (~104), large forward current (~12.2 μA) and low reverse saturated current (~1.8 nA) was achieved with the OA and PEI doping time of 5 h and 18 h for a channel length of ~6 μm.

Effective use of congestion in complex networks

NASA Astrophysics Data System (ADS)

Echagüe, Juan; Cholvi, Vicent; Kowalski, Dariusz R.

2018-03-01

In this paper, we introduce a congestion-aware routing protocol that selects the paths according to the congestion of nodes in the network. The aim is twofold: on one hand, and in order to prevent the networks from collapsing, it provides a good tolerance to nodes' overloads; on the other hand, and in order to guarantee efficient communication, it also incentivize the routes to follow short paths. We analyze the performance of our proposed routing strategy by means of a series of experiments carried out by using simulations. We show that it provides a tolerance to collapse close to the optimal value. Furthermore, the average length of the paths behaves optimally up to the certain value of packet generation rate ρ and it grows in a linear fashion with the increase of ρ.

The Systems Engineering Design of a Smart Forward Operating Base Surveillance System for Forward Operating Base Protection

DTIC Science & Technology

2013-06-01

fixed sensors located along the perimeter of the FOB. The video is analyzed for facial recognition to alert the Network Operations Center (NOC...the UAV is processed on board for facial recognition and video for behavior analysis is sent directly to the Network Operations Center (NOC). Video...captured by the fixed sensors are sent directly to the NOC for facial recognition and behavior analysis processing. The multi- directional signal

Current-flow efficiency of networks

NASA Astrophysics Data System (ADS)

Liu, Kai; Yan, Xiaoyong

2018-02-01

Many real-world networks, from infrastructure networks to social and communication networks, can be formulated as flow networks. How to realistically measure the transport efficiency of these networks is of fundamental importance. The shortest-path-based efficiency measurement has limitations, as it assumes that flow travels only along those shortest paths. Here, we propose a new metric named current-flow efficiency, in which we calculate the average reciprocal effective resistance between all pairs of nodes in the network. This metric takes the multipath effect into consideration and is more suitable for measuring the efficiency of many real-world flow equilibrium networks. Moreover, this metric can handle a disconnected graph and can thus be used to identify critical nodes and edges from the efficiency-loss perspective. We further analyze how the topological structure affects the current-flow efficiency of networks based on some model and real-world networks. Our results enable a better understanding of flow networks and shed light on the design and improvement of such networks with higher transport efficiency.

Planar maneuvering control of underwater snake robots using virtual holonomic constraints.

PubMed

Kohl, Anna M; Kelasidi, Eleni; Mohammadi, Alireza; Maggiore, Manfredi; Pettersen, Kristin Y

2016-11-24

This paper investigates the problem of planar maneuvering control for bio-inspired underwater snake robots that are exposed to unknown ocean currents. The control objective is to make a neutrally buoyant snake robot which is subject to hydrodynamic forces and ocean currents converge to a desired planar path and traverse the path with a desired velocity. The proposed feedback control strategy enforces virtual constraints which encode biologically inspired gaits on the snake robot configuration. The virtual constraints, parametrized by states of dynamic compensators, are used to regulate the orientation and forward speed of the snake robot. A two-state ocean current observer based on relative velocity sensors is proposed. It enables the robot to follow the path in the presence of unknown constant ocean currents. The efficacy of the proposed control algorithm for several biologically inspired gaits is verified both in simulations for different path geometries and in experiments.

Shortest path problem on a grid network with unordered intermediate points

NASA Astrophysics Data System (ADS)

Saw, Veekeong; Rahman, Amirah; Eng Ong, Wen

2017-10-01

We consider a shortest path problem with single cost factor on a grid network with unordered intermediate points. A two stage heuristic algorithm is proposed to find a feasible solution path within a reasonable amount of time. To evaluate the performance of the proposed algorithm, computational experiments are performed on grid maps of varying size and number of intermediate points. Preliminary results for the problem are reported. Numerical comparisons against brute forcing show that the proposed algorithm consistently yields solutions that are within 10% of the optimal solution and uses significantly less computation time.

Remediation to Restoration to Revitalization - a Path Forward for AOCs?

EPA Science Inventory

Remediation and restoration goals for Great Lakes Areas of Concerns (AOCs) are defined by the status of the Beneficial Use Impairments (BUI), or the uses of the Great Lakes ecosystem that have been compromised owing to historical industrial or urban activities. Conceptually, “ben...

Path Forward for the Air Quality Model Evaluation International Initiative (AQMEII)

EPA Science Inventory

This article lays out the objectives for Phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII). The inhalation of air pollutants such as ozone and fine particles has been linked to adverse impacts on human health, and the atmospheric deposition of pollutan...

International Disease Surveillance: United States Government Goals and Paths Forward

DTIC Science & Technology

2010-06-01

convincing case to funders (ie, the U.S. Congress) showing how investment in surveillance for routine disease (eg, rotavirus ) prepares countries to detect...Hemorrhagic Fevers (Lassa, Marburg, Ebola) Viral Hemorrhagic Fevers (Lassa, Marburg, Ebola) Rotavirus Center for Biosecurity of UPMC | June 2010 Page 18

The Blue LED Nobel Prize: Historical context, current scientific understanding, human benefit

DOE PAGES

Tsao, Jeffrey Y.; Han, Jung; Haitz, Roland H.; ...

2015-06-19

Here, the paths that connect scientific understanding with tools and technology are rarely linear. Sometimes scientific understanding leads and enables, sometimes tools and technologies lead and enable. But by feeding on each other, they create virtuous spirals of forward and backward innovation.

Tools Fit for Chemical Risk Prioritization (EC JRC presentation)

EPA Science Inventory

We would like to know more about the risk posed by thousands of chemicals in the environment – which are most worthy of further study? High throughput screening (HTS) provides a path forward for identifying potential hazard. Exposure and dosimetry provide real world context to ha...

The Blue LED Nobel Prize: Historical context, current scientific understanding, human benefit

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

Tsao, Jeffrey Y.; Han, Jung; Haitz, Roland H.

Here, the paths that connect scientific understanding with tools and technology are rarely linear. Sometimes scientific understanding leads and enables, sometimes tools and technologies lead and enable. But by feeding on each other, they create virtuous spirals of forward and backward innovation.

Alternative Test Methods for Developmental Neurotoxicity: A History and Path Forward (OECD EFSA workshop)

EPA Science Inventory

Exposure to environmental contaminants is well documented to adversely impact the development of the nervous system. However, the time, animal and resource intensive EPA and OECD testing guideline methods for developmental neurotoxicity (DNT) are not a viable solution to characte...

An experimental analysis on OSPF-TE convergence time

NASA Astrophysics Data System (ADS)

Huang, S.; Kitayama, K.; Cugini, F.; Paolucci, F.; Giorgetti, A.; Valcarenghi, L.; Castoldi, P.

2008-11-01

Open shortest path first (OSPF) protocol is commonly used as an interior gateway protocol (IGP) in MPLS and generalized MPLS (GMPLS) networks to determine the topology over which label-switched paths (LSPs) can be established. Traffic-engineering extensions (network states such as link bandwidth information, available wavelengths, signal quality, etc) have been recently enabled in OSPF (henceforth, called OSPF-TE) to support shortest path first (SPF) tree calculation upon different purposes, thus possibly achieving optimal path computation and helping improve resource utilization efficiency. Adding these features into routing phase can exploit the OSPF robustness, and no additional network component is required to manage the traffic-engineering information. However, this traffic-engineering enhancement also complicates OSPF behavior. Since network states change frequently upon the dynamic trafficengineered LSP setup and release, the network is easily driven from a stable state to unstable operating regimes. In this paper, we focus on studying the OSPF-TE stability in terms of convergence time. Convergence time is referred to the time spent by the network to go back to steady states upon any network state change. An external observation method (based on black-box method) is employed to estimate the convergence time. Several experimental test-beds are developed to emulate dynamic LSP setup/release, re-routing upon single-link failure. The experimental results show that with OSPF-TE the network requires more time to converge compared to the conventional OSPF protocol without TE extension. Especially, in case of wavelength-routed optical network (WRON), introducing per wavelength availability and wavelength continuity constraint to OSPF-TE suffers severe convergence time and a large number of advertised link state advertisements (LSAs). Our study implies that long convergence time and large number of LSAs flooded in the network might cause scalability problems in OSPF-TE and impose limitations on OSPF-TE applications. New solutions to mitigate the s convergence time and to reduce the amount of state information are desired in the future.

Solute transport with multisegment, equilibrium-controlled, classical reactions: Problem solvability and feed forward method's applicability for complex segments of at most binary participants

USGS Publications Warehouse

Rubin, Jacob

1992-01-01

The feed forward (FF) method derives efficient operational equations for simulating transport of reacting solutes. It has been shown to be applicable in the presence of networks with any number of homogeneous and/or heterogeneous, classical reaction segments that consist of three, at most binary participants. Using a sequential (network type after network type) exploration approach and, independently, theoretical explanations, it is demonstrated for networks with classical reaction segments containing more than three, at most binary participants that if any one of such networks leads to a solvable transport problem then the FF method is applicable. Ways of helping to avoid networks that produce problem insolvability are developed and demonstrated. A previously suggested algebraic, matrix rank procedure has been adapted and augmented to serve as the main, easy-to-apply solvability test for already postulated networks. Four network conditions that often generate insolvability have been identified and studied. Their early detection during network formulation may help to avoid postulation of insolvable networks.

Advanced Aeroservoelastic Testing and Data Analysis (Les Essais Aeroservoelastiques et l’Analyse des Donnees).

DTIC Science & Technology

1995-11-01

network - based AFS concepts. Neural networks can addition of vanes in each engine exhaust for thrust provide...parameter estimation programs 19-11 8.6 Neural Network Based Methods unknown parameters of the postulated state space model Artificial neural network ...Forward Neural Network the network that the applicability of the recurrent neural and ii) Recurrent Neural Network [117-119]. network to

Meta-path based heterogeneous combat network link prediction

NASA Astrophysics Data System (ADS)

Li, Jichao; Ge, Bingfeng; Yang, Kewei; Chen, Yingwu; Tan, Yuejin

2017-09-01

The combat system-of-systems in high-tech informative warfare, composed of many interconnected combat systems of different types, can be regarded as a type of complex heterogeneous network. Link prediction for heterogeneous combat networks (HCNs) is of significant military value, as it facilitates reconfiguring combat networks to represent the complex real-world network topology as appropriate with observed information. This paper proposes a novel integrated methodology framework called HCNMP (HCN link prediction based on meta-path) to predict multiple types of links simultaneously for an HCN. More specifically, the concept of HCN meta-paths is introduced, through which the HCNMP can accumulate information by extracting different features of HCN links for all the six defined types. Next, an HCN link prediction model, based on meta-path features, is built to predict all types of links of the HCN simultaneously. Then, the solution algorithm for the HCN link prediction model is proposed, in which the prediction results are obtained by iteratively updating with the newly predicted results until the results in the HCN converge or reach a certain maximum iteration number. Finally, numerical experiments on the dataset of a real HCN are conducted to demonstrate the feasibility and effectiveness of the proposed HCNMP, in comparison with 30 baseline methods. The results show that the performance of the HCNMP is superior to those of the baseline methods.

Calculation of Crystallographic Texture of BCC Steels During Cold Rolling

NASA Astrophysics Data System (ADS)

Das, Arpan

2017-05-01

BCC alloys commonly tend to develop strong fibre textures and often represent as isointensity diagrams in φ 1 sections or by fibre diagrams. Alpha fibre in bcc steels is generally characterised by <110> crystallographic axis parallel to the rolling direction. The objective of present research is to correlate carbon content, carbide dispersion, rolling reduction, Euler angles (ϕ) (when φ 1 = 0° and φ 2 = 45° along alpha fibre) and the resulting alpha fibre texture orientation intensity. In the present research, Bayesian neural computation has been employed to correlate these and compare with the existing feed-forward neural network model comprehensively. Excellent match to the measured texture data within the bounding box of texture training data set has been already predicted through the feed-forward neural network model by other researchers. Feed-forward neural network prediction outside the bounds of training texture data showed deviations from the expected values. Currently, Bayesian computation has been similarly applied to confirm that the predictions are reasonable in the context of basic metallurgical principles, and matched better outside the bounds of training texture data set than the reported feed-forward neural network. Bayesian computation puts error bars on predicted values and allows significance of each individual parameters to be estimated. Additionally, it is also possible by Bayesian computation to estimate the isolated influence of particular variable such as carbon concentration, which exactly cannot in practice be varied independently. This shows the ability of the Bayesian neural network to examine the new phenomenon in situations where the data cannot be accessed through experiments.

Impact of Repeated Exposures on Information Spreading in Social Networks

PubMed Central

Zhou, Cangqi; Zhao, Qianchuan; Lu, Wenbo

2015-01-01

Clustered structure of social networks provides the chances of repeated exposures to carriers with similar information. It is commonly believed that the impact of repeated exposures on the spreading of information is nontrivial. Does this effect increase the probability that an individual forwards a message in social networks? If so, to what extent does this effect influence people’s decisions on whether or not to spread information? Based on a large-scale microblogging data set, which logs the message spreading processes and users’ forwarding activities, we conduct a data-driven analysis to explore the answer to the above questions. The results show that an overwhelming majority of message samples are more probable to be forwarded under repeated exposures, compared to those under only a single exposure. For those message samples that cover various topics, we observe a relatively fixed, topic-independent multiplier of the willingness of spreading when repeated exposures occur, regardless of the differences in network structure. We believe that this finding reflects average people’s intrinsic psychological gain under repeated stimuli. Hence, it makes sense that the gain is associated with personal response behavior, rather than network structure. Moreover, we find that the gain is robust against the change of message popularity. This finding supports that there exists a relatively fixed gain brought by repeated exposures. Based on the above findings, we propose a parsimonious model to predict the saturated numbers of forwarding activities of messages. Our work could contribute to better understandings of behavioral psychology and social media analytics. PMID:26465749

Protecting core networks with dual-homing: A study on enhanced network availability, resource efficiency, and energy-savings

NASA Astrophysics Data System (ADS)

Abeywickrama, Sandu; Furdek, Marija; Monti, Paolo; Wosinska, Lena; Wong, Elaine

2016-12-01

Core network survivability affects the reliability performance of telecommunication networks and remains one of the most important network design considerations. This paper critically examines the benefits arising from utilizing dual-homing in the optical access networks to provide resource-efficient protection against link and node failures in the optical core segment. Four novel, heuristic-based RWA algorithms that provide dedicated path protection in networks with dual-homing are proposed and studied. These algorithms protect against different failure scenarios (i.e. single link or node failures) and are implemented with different optimization objectives (i.e., minimization of wavelength usage and path length). Results obtained through simulations and comparison with baseline architectures indicate that exploiting dual-homed architecture in the access segment can bring significant improvements in terms of core network resource usage, connection availability, and power consumption.

A Numerical Investigation of Two-Different Drosophila Forward Flight Modes

NASA Astrophysics Data System (ADS)

Sahin, Mehmet; Dilek, Ezgi; Erzincanli, Belkis

2016-11-01

The parallel large-scale unstructured finite volume method based on an Arbitrary Lagrangian-Eulerian (ALE) formulation has been applied in order to investigate the near wake structure of Drosophila in forward flight. DISTENE MeshGems-Hexa algorithm based on the octree method is used to generate the all hexahedral mesh for the wing-body combination. The mesh deformation algorithm is based on the indirect radial basis function (RBF) method at each time level while avoiding remeshing in order to enhance numerical robustness. The large-scale numerical simulations are carried out for a flapping Drosophila in forward flight. In the first case, the wing tip-path plane is tilted forward to generate forward force. In the second case, paddling wing motion is used to generate the forward fore. The λ2-criterion proposed by Jeong and Hussain (1995) is used for investigating the time variation of the Eulerian coherent structures in the near wake. The present simulations reveal highly detailed near wake topology for a hovering Drosophila. This is very useful in terms of understanding physics in biological flights which can provide a very useful tool for designing bio-inspired MAVs.

Group Centric Networking: A new Approach for Wireless Multi-Hop Networking to Enable the Internet of Things

DTIC Science & Technology

2015-11-11

reliable data message delivery. The basic mechanism of link-based routing schemes is the broadcasting of a control message (called a “ hello ”) to all of its...short- est path route to a destination by using the set of ex- changed hello messages between users of the network. With sufficiently high frequency... hello messages are suc- cessfully exchanged across a high error link, and since this link is of longer distance, it gets used to build a shortest path

Group Centric Networking: A new Approach for Wireless Multi-Hop Networking to Enable the Internet of Things

DTIC Science & Technology

2015-09-07

reliable data message delivery. The basic mechanism of link-based routing schemes is the broadcasting of a control message (called a “ hello ”) to all of its...short- est path route to a destination by using the set of ex- changed hello messages between users of the network. With sufficiently high frequency... hello messages are suc- cessfully exchanged across a high error link, and since this link is of longer distance, it gets used to build a shortest path

Bidirectional QoS support for novelty detection applications based on hierarchical wireless sensor network model

NASA Astrophysics Data System (ADS)

Edwards, Mark; Hu, Fei; Kumar, Sunil

2004-10-01

The research on the Novelty Detection System (NDS) (called as VENUS) at the authors' universities has generated exciting results. For example, we can detect an abnormal behavior (such as cars thefts from the parking lot) from a series of video frames based on the cognitively motivated theory of habituation. In this paper, we would like to describe the implementation strategies of lower layer protocols for using large-scale Wireless Sensor Networks (WSN) to NDS with Quality-of-Service (QoS) support. Wireless data collection framework, consisting of small and low-power sensor nodes, provides an alternative mechanism to observe the physical world, by using various types of sensing capabilities that include images (and even videos using Panoptos), sound and basic physical measurements such as temperature. We do not want to lose any 'data query command' packets (in the downstream direction: sink-to-sensors) or have any bit-errors in them since they are so important to the whole sensor network. In the upstream direction (sensors-to-sink), we may tolerate the loss of some sensing data packets. But the 'interested' sensing flow should be assigned a higher priority in terms of multi-hop path choice, network bandwidth allocation, and sensing data packet generation frequency (we hope to generate more sensing data packet for that novel event in the specified network area). The focus of this paper is to investigate MAC-level Quality of Service (QoS) issue in Wireless Sensor Networks (WSN) for Novelty Detection applications. Although QoS has been widely studied in other types of networks including wired Internet, general ad hoc networks and mobile cellular networks, we argue that QoS in WSN has its own characteristics. In wired Internet, the main QoS parameters include delay, jitter and bandwidth. In mobile cellular networks, two most common QoS metrics are: handoff call dropping probability and new call blocking probability. Since the main task of WSN is to detect and report events, the most important QoS parameters should include sensing data packet transmission reliability, lifetime extension degree from sensor sleeping control, event detection latency, congestion reduction level through removal of redundant sensing data. In this paper, we will focus on the following bi-directional QoS topics: (1) Downstream (sink-to-sensor) QoS: Reliable data query command forwarding to particular sensor(s). In other words, we do not want to lose the query command packets; (2) Upstream (sensor-to-sink) QoS: transmission of sensed data with priority control. The more interested data that can help in novelty detection should be transmitted on an optimal path with higher reliability. We propose the use of Differentiated Data Collection. Due to the large-scale nature and resource constraints of typical wireless sensor networks, such as limited energy, small memory (typically RAM < 4K bytes) and short communication range, the above problems become even more challenging. Besides QoS support issue, we will also describe our low-energy Sensing Data Transmission network Architecture. Our research results show the scalability and energy-efficiency of our proposed WSN QoS schemes.

A programmable Si-photonic node for SDN-enabled Bloom filter forwarding in disaggregated data centers

NASA Astrophysics Data System (ADS)

Moralis-Pegios, M.; Terzenidis, N.; Vagionas, C.; Pitris, S.; Chatzianagnostou, E.; Brimont, A.; Zanzi, A.; Sanchis, P.; Marti, J.; Kraft, J.; Rochracher, K.; Dorrestein, S.; Bogdan, M.; Tekin, T.; Syrivelis, D.; Tassiulas, L.; Miliou, A.; Pleros, N.; Vyrsokinos, K.

2017-02-01

Programmable switching nodes supporting Software-Defined Networking (SDN) over optical interconnecting technologies arise as a key enabling technology for future disaggregated Data Center (DC) environments. The SDNenabling roadmap of intra-DC optical solutions is already a reality for rack-to-rack interconnects, with recent research reporting on interesting applications of programmable silicon photonic switching fabrics addressing board-to-board and even on-board applications. In this perspective, simplified information addressing schemes like Bloom filter (BF)-based labels emerge as a highly promising solution for ensuring rapid switch reconfiguration, following quickly the changes enforced in network size, network topology or even in content location. The benefits of BF-based forwarding have been so far successfully demonstrated in the Information-Centric Network (ICN) paradigm, while theoretical studies have also revealed the energy consumption and speed advantages when applied in DCs. In this paper we present for the first time a programmable 4x4 Silicon Photonic switch that supports SDN through the use of BF-labeled router ports. Our scheme significantly simplifies packet forwarding as it negates the need for large forwarding tables, allowing for its remote control through modifications in the assigned BF labels. We demonstrate 1x4 switch operation controlling the Si-Pho switch by a Stratix V FPGA module, which is responsible for processing the packet ID and correlating its destination with the appropriate BF-labeled outgoing port. DAC- and amplifier-less control of the carrier-injection Si-Pho switches is demonstrated, revealing successful switching of 10Gb/s data packets with BF-based forwarding information changes taking place at a time-scale that equals the duration of four consecutive packets.

An efficient routing strategy for traffic dynamics on two-layer complex networks

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Wang, Huiling; Zhang, Zhuxi; Zhang, Yi; Duan, Congwen; Qi, Zhaohui; Liu, Yu

2018-05-01

In order to alleviate traffic congestion on multilayer networks, designing an efficient routing strategy is one of the most important ways. In this paper, a novel routing strategy is proposed to reduce traffic congestion on two-layer networks. In the proposed strategy, the optimal paths in the physical layer are chosen by comprehensively considering the roles of nodes’ degrees of the two layers. Both numerical and analytical results indicate that our routing strategy can reasonably redistribute the traffic load of the physical layer, and thus the traffic capacity of two-layer complex networks are significantly enhanced compared with the shortest path routing (SPR) and the global awareness routing (GAR) strategies. This study may shed some light on the optimization of networked traffic dynamics.

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Evaluation of Flow Paths and Confluences for Saltwater Intrusion and Its Influence on Fish Species Diversity in a Deltaic River Network

NASA Astrophysics Data System (ADS)

Shao, X.; Cui, B.; Zhang, Z.; Fang, Y.; Jawitz, J. W.

2016-12-01

Freshwater in a delta is often at risk of saltwater intrusion, which has been a serious issue in estuarine deltas all over the world. Salinity gradients and hydrologic connectivity in the deltas can be disturbed by saltwater intrusion, which can fluctuate frequently and locally in time and space to affect biotic processes and then to affect the distribution patterns of the riverine fishes throughout the river network. Therefore, identifying the major flow paths or locations at risk of saltwater intrusion in estuarine ecosystems is necessary for saltwater intrusion mitigation and fish species diversity conservation. In this study, we use the betweenness centrality (BC) as the weighted attribute of the river network to identify the critical confluences and detect the preferential flow paths for saltwater intrusion through the least-cost-path algorithm from graph theory approach. Moreover, we analyse the responses of the salinity and fish species diversity to the BC values of confluences calculated in the river network. Our results show that the most likely location of saltwater intrusion is not a simple gradient change from sea to land, but closely dependent on the river segments' characteristics. In addition, a significant positive correlation between the salinity and the BC values of confluences is determined in the Pearl River Delta. Changes in the BC values of confluences can produce significant variation in the fish species diversity. Therefore, the dynamics of saltwater intrusion are a growing consideration for understanding the patterns and subsequent processes driving fish community structure. Freshwater can be diverted into these major flow paths and critical confluences to improve river network management and conservation of fish species diversity under saltwater intrusion.

Efficient collective influence maximization in cascading processes with first-order transitions

PubMed Central

Pei, Sen; Teng, Xian; Shaman, Jeffrey; Morone, Flaviano; Makse, Hernán A.

2017-01-01

In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task for large-scale networks. Here we address this issue by exploring the collective influence in general threshold models of cascading process. Our analysis reveals that the importance of spreaders is fixed by the subcritical paths along which cascades propagate: the number of subcritical paths attached to each spreader determines its contribution to global cascades. The concept of subcritical path allows us to introduce a scalable algorithm for massively large-scale networks. Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given the same number of seeds compared with other scalable heuristic approaches. PMID:28349988

Efficient collective influence maximization in cascading processes with first-order transitions

NASA Astrophysics Data System (ADS)

Pei, Sen; Teng, Xian; Shaman, Jeffrey; Morone, Flaviano; Makse, Hernán A.

2017-03-01

In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task for large-scale networks. Here we address this issue by exploring the collective influence in general threshold models of cascading process. Our analysis reveals that the importance of spreaders is fixed by the subcritical paths along which cascades propagate: the number of subcritical paths attached to each spreader determines its contribution to global cascades. The concept of subcritical path allows us to introduce a scalable algorithm for massively large-scale networks. Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given the same number of seeds compared with other scalable heuristic approaches.

Measuring edge-of-field water quality: Where we have been and the path forward

USDA-ARS?s Scientific Manuscript database

Heightened pressure to demonstrate the resource benefits of conservation practices and continued high-profile water quality impairments and concerns are increasing the need to quantify edge-of-field water quality. With this in mind, this manuscript summarizes previous developments in edge-of-field ...

Quinoa cultivation in western North America: lessons learned and the path forward

USDA-ARS?s Scientific Manuscript database

Quinoa (Chenopodium quinoa Willd) is a relatively new crop to farmers in North America; however recent interest in domestic cultivation of quinoa has skyrocketed due to a rapid, worldwide increase in demand for this nutritious and delicious Andean crop. Researchers at five western U.S. universities ...

Nanotechnology for forest products. Part 2

Treesearch

Theodore Wegner; Phil Jones

2005-01-01

In planning for the Nanotechnology for the Forest products Industry Workshop, we considered many different options for organizing technical focus areas for breakout discussion sessions. We felt the fallowing R&D focus areas provide the best path forward for a nanotechnology roadmap by identifying the underlying science and technology needed: also, they foster...

Imagining Tomorrow's Future Today

ERIC Educational Resources Information Center

St. George, Art

2007-01-01

Today, at the end of 2007, there are evident consolidations in wireless, storage, and virtualization and the path forward seems clearer now than previously. Trends from last year continue strongly, particularly Web 2.0 and the shift to user-driven environments and Internet sites where significant data and video processing is available to those…

49 CFR 38.159 - Mobility aid accessibility.

Code of Federal Regulations, 2013 CFR

2013-10-01

... with the inner barrier (if applicable) down or retracted, gaps between the forward lift platform edge... inches (1220 mm). Such space shall adjoin, and may overlap, an access path. Not more than 6 inches (150 mm) of the required clear floor space may be accommodated for footrests under another seat, modesty...

49 CFR 38.159 - Mobility aid accessibility.

Code of Federal Regulations, 2012 CFR

2012-10-01

... with the inner barrier (if applicable) down or retracted, gaps between the forward lift platform edge... inches (1220 mm). Such space shall adjoin, and may overlap, an access path. Not more than 6 inches (150 mm) of the required clear floor space may be accommodated for footrests under another seat, modesty...

ISEA 2007 Panel: Integration of Better Exposure Characterizations into Disaster Preparedness for Responders and the Public

EPA Science Inventory

An expert panel was convened in October 2007 at the International Society for Exposure Analysis (ISEA) Annual Meeting in Durham, NC, entitled “The Path Forward in Disaster Preparedness Since WTC—Exposure Characterization and Mitigation: Substantial Unfinished Business!” The pane...

Using Motorsports Design Concepts to Further STEM Education

ERIC Educational Resources Information Center

Hylton, Pete

2010-01-01

Few career paths are as dynamic, exciting, and engaging to potential Science, Technology, Engineering and Math (STEM) students as those in motorsports. Secondary school students, looking forward to their initial driver's licenses and their first cars, are captivated by the speed and color of the sport. Indiana University Purdue University…

Civil War. NBER Working Paper No. 14801

ERIC Educational Resources Information Center

Blattman, Christopher; Miguel, Edward

2009-01-01

Most nations have experienced an internal armed conflict since 1960. The past decade has witnessed an explosion of research into the causes and consequences of civil wars, belatedly bringing the topic into the economics mainstream. This article critically reviews this interdisciplinary literature and charts productive paths forward. Formal theory…

Coordinated Autonomy for Persistent Presence in Harbor and Riverine Environments

DTIC Science & Technology

2007-09-30

estimators, and methods designed to deal with real-world problems such as video transmission noise; • OpenCV for basic computer vision functionality as...awareness and forward surveillance of Rocky’s intended path. Aerial video was transmitted to the UAV ground station, where an operator using GIS

Current limitations and a path forward to improve testing for the environmental assessment of endocrine active substances-presentation

EPA Science Inventory

To assess the hazards and risks of possible endocrine active chemicals (EACs), there is a need for robust, validated test methods that detect perturbations of endocrine pathways and provide reliable information for evaluating potential adverse effects on apical endpoints. One iss...

Authentic Assessment in Music Composition: Feedback That Facilitates Creativity

ERIC Educational Resources Information Center

Deutsch, Daniel

2016-01-01

Every composition created by a young composer represents a step in the student's creative path. Assessment, an intrinsic aspect of teaching, fosters learning and propels students forward on their journeys to creative self-expression. Authentic feedback and assessment strategies must be grounded both in the individual musical context of each…

76 FR 38430 - Subcommittee on Forensic Science; Committee on Science; National Science and Technology Council

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-30

... OFFICE OF SCIENCE AND TECHNOLOGY POLICY Subcommittee on Forensic Science; Committee on Science; National Science and Technology Council ACTION: Notice of Panel Session. Public input is requested... Sciences 2009 report: ``Strengthening Forensic Science in the United States: A Path Forward'' ( http://www...

Network-Based Management Procedures.

ERIC Educational Resources Information Center

Buckner, Allen L.

Network-based management procedures serve as valuable aids in organizational management, achievement of objectives, problem solving, and decisionmaking. Network techniques especially applicable to educational management systems are the program evaluation and review technique (PERT) and the critical path method (CPM). Other network charting…

SIMRAND I- SIMULATION OF RESEARCH AND DEVELOPMENT PROJECTS

NASA Technical Reports Server (NTRS)

Miles, R. F.

1994-01-01

The Simulation of Research and Development Projects program (SIMRAND) aids in the optimal allocation of R&D resources needed to achieve project goals. SIMRAND models the system subsets or project tasks as various network paths to a final goal. Each path is described in terms of task variables such as cost per hour, cost per unit, availability of resources, etc. Uncertainty is incorporated by treating task variables as probabilistic random variables. SIMRAND calculates the measure of preference for each alternative network. The networks yielding the highest utility function (or certainty equivalence) are then ranked as the optimal network paths. SIMRAND has been used in several economic potential studies at NASA's Jet Propulsion Laboratory involving solar dish power systems and photovoltaic array construction. However, any project having tasks which can be reduced to equations and related by measures of preference can be modeled. SIMRAND analysis consists of three phases: reduction, simulation, and evaluation. In the reduction phase, analytical techniques from probability theory and simulation techniques are used to reduce the complexity of the alternative networks. In the simulation phase, a Monte Carlo simulation is used to derive statistics on the variables of interest for each alternative network path. In the evaluation phase, the simulation statistics are compared and the networks are ranked in preference by a selected decision rule. The user must supply project subsystems in terms of equations based on variables (for example, parallel and series assembly line tasks in terms of number of items, cost factors, time limits, etc). The associated cumulative distribution functions and utility functions for each variable must also be provided (allowable upper and lower limits, group decision factors, etc). SIMRAND is written in Microsoft FORTRAN 77 for batch execution and has been implemented on an IBM PC series computer operating under DOS.

System for testing properties of a network

DOEpatents

Rawle, Michael; Bartholomew, David B.; Soares, Marshall A.

2009-06-16

A method for identifying properties of a downhole electromagnetic network in a downhole tool sting, including the step of providing an electromagnetic path intermediate a first location and a second location on the electromagnetic network. The method further includes the step of providing a receiver at the second location. The receiver includes a known reference. The analog signal includes a set amplitude, a set range of frequencies, and a set rate of change between the frequencies. The method further includes the steps of sending the analog signal, and passively modifying the signal. The analog signal is sent from the first location through the electromagnetic path, and the signal is modified by the properties of the electromagnetic path. The method further includes the step of receiving a modified signal at the second location and comparing the known reference to the modified signal.

Information spread of emergency events: path searching on social networks.

PubMed

Dai, Weihui; Hu, Hongzhi; Wu, Tunan; Dai, Yonghui

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.

Analysis of Cisco Open Network Environment (ONE) OpenFlow Controller Implementation

DTIC Science & Technology

2014-08-01

Software - Defined Networking ( SDN ), when fully realized, offer many improvements over the current rigid and...functionalities like handshake, connection setup, switch management, and security. 15. SUBJECT TERMS OpenFlow, software - defined networking , Cisco ONE, SDN ...innovating packet-forwarding technologies. Network device roles are strictly defined with little or no flexibility. In Software - Defined Networks ( SDNs ),

Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks.

PubMed

Arunraja, Muruganantham; Malathi, Veluchamy; Sakthivel, Erulappan

2015-11-01

Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

On using multiple routing metrics with destination sequenced distance vector protocol for MultiHop wireless ad hoc networks

NASA Astrophysics Data System (ADS)

Mehic, M.; Fazio, P.; Voznak, M.; Partila, P.; Komosny, D.; Tovarek, J.; Chmelikova, Z.

2016-05-01

A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

Integration of Hierarchical Goal Network Planning and Autonomous Path Planning

DTIC Science & Technology

2016-03-01

Conference on Robotics and Automation (ICRA); 2010 May 3– 7; Anchorage, AK. p. 2902–2908. 4. Ayan NF, Kuter U, Yaman F, Goldman RP. Hotride...DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Automated planning has...world robotic systems. This report documents work to integrate a hierarchical goal network planning algorithm with low-level path planning. The system

The data-driven null models for information dissemination tree in social networks

NASA Astrophysics Data System (ADS)

Zhang, Zhiwei; Wang, Zhenyu

2017-10-01

For the purpose of detecting relatedness and co-occurrence between users, as well as the distribution features of nodes in spreading path of a social network, this paper explores topological characteristics of information dissemination trees (IDT) that can be employed indirectly to probe the information dissemination laws within social networks. Hence, three different null models of IDT are presented in this article, including the statistical-constrained 0-order IDT null model, the random-rewire-broken-edge 0-order IDT null model and the random-rewire-broken-edge 2-order IDT null model. These null models firstly generate the corresponding randomized copy of an actual IDT; then the extended significance profile, which is developed by adding the cascade ratio of information dissemination path, is exploited not only to evaluate degree correlation of two nodes associated with an edge, but also to assess the cascade ratio of different length of information dissemination paths. The experimental correspondences of the empirical analysis for several SinaWeibo IDTs and Twitter IDTs indicate that the IDT null models presented in this paper perform well in terms of degree correlation of nodes and dissemination path cascade ratio, which can be better to reveal the features of information dissemination and to fit the situation of real social networks.

Sentence alignment using feed forward neural network.

PubMed

Fattah, Mohamed Abdel; Ren, Fuji; Kuroiwa, Shingo

2006-12-01

Parallel corpora have become an essential resource for work in multi lingual natural language processing. However, sentence aligned parallel corpora are more efficient than non-aligned parallel corpora for cross language information retrieval and machine translation applications. In this paper, we present a new approach to align sentences in bilingual parallel corpora based on feed forward neural network classifier. A feature parameter vector is extracted from the text pair under consideration. This vector contains text features such as length, punctuate score, and cognate score values. A set of manually prepared training data has been assigned to train the feed forward neural network. Another set of data was used for testing. Using this new approach, we could achieve an error reduction of 60% over length based approach when applied on English-Arabic parallel documents. Moreover this new approach is valid for any language pair and it is quite flexible approach since the feature parameter vector may contain more/less or different features than that we used in our system such as lexical match feature.

NASA/DARPA advanced communications technology satellite project for evaluation of telemedicine outreach using next-generation communications satellite technology: Mayo Foundation participation.

PubMed

Gilbert, B K; Mitchell, M P; Bengali, A R; Khandheria, B K

1999-08-01

To describe the development of telemedicine capabilities-application of remote consultation and diagnostic techniques-and to evaluate the feasibility and practicality of such clinical outreach to rural and underserved communities with limited telecommunications infrastructures. In 1992, Mayo Foundation (Rochester, Minn, Jacksonville, Fla, and Scottsdale, Ariz), the National Aeronautics and Space Administration, and the Defense Advanced Research Projects Agency collaborated to create a complex network of fiberoptic landlines, video recording systems, satellite terminals, and specially developed data translators linking Mayo sites with other locations in the continental United States on an on-demand basis. The purpose was to transmit data via the asynchronous transfer mode (ATM) digital communications protocol over the Advanced Communications Technology Satellite. The links were intended to provide a conduit for transmission of data for patient-specific consultations between physicians, evaluation of medical imagery, and medical education for clinical staffs at remote sites. Low-data-rate (LDR) experiments went live late in 1993. Mayo Clinic Rochester successfully provided medical consultation and services to 2 small regional medical facilities. High-data-rate (HDR) experiments included studies of remote digital echocardiography, store-and-forward telemedicine, cardiac catheterization, and teleconsultation for congenital heart disease. These studies combined landline data transmission with use of the satellite. The complexity of the routing paths and network components, immaturity of available software, and inexperience with existing telecommunications caused significant study delays. These experiments demonstrated that next-generation satellite technology can provide batch and real-time imagery for telemedicine. The first-generation of the ATM and satellite network technology used in these experiments created several technical problems and inconveniences that should be overcome as the network infrastructure matures.

Topics on data transmission problem in software definition network

NASA Astrophysics Data System (ADS)

Gao, Wei; Liang, Li; Xu, Tianwei; Gan, Jianhou

2017-08-01

In normal computer networks, the data transmission between two sites go through the shortest path between two corresponding vertices. However, in the setting of software definition network (SDN), it should monitor the network traffic flow in each site and channel timely, and the data transmission path between two sites in SDN should consider the congestion in current networks. Hence, the difference of available data transmission theory between normal computer network and software definition network is that we should consider the prohibit graph structures in SDN, and these forbidden subgraphs represent the sites and channels in which data can't be passed by the serious congestion. Inspired by theoretical analysis of an available data transmission in SDN, we consider some computational problems from the perspective of the graph theory. Several results determined in the paper imply the sufficient conditions of data transmission in SDN in the various graph settings.

Netest: A Tool to Measure the Maximum Burst Size, Available Bandwidth and Achievable Throughput

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

Jin, Guojun; Tierney, Brian

2003-01-31

Distinguishing available bandwidth and achievable throughput is essential for improving network applications' performance. Achievable throughput is the throughput considering a number of factors such as network protocol, host speed, network path, and TCP buffer space, where as available bandwidth only considers the network path. Without understanding this difference, trying to improve network applications' performance is like ''blind men feeling the elephant'' [4]. In this paper, we define and distinguish bandwidth and throughput, and debate which part of each is achievable and which is available. Also, we introduce and discuss a new concept - Maximum Burst Size that is crucial tomore » the network performance and bandwidth sharing. A tool, netest, is introduced to help users to determine the available bandwidth, and provides information to achieve better throughput with fairness of sharing the available bandwidth, thus reducing misuse of the network.« less

Genetic Algorithm for Solving Fuzzy Shortest Path Problem in a Network with mixed fuzzy arc lengths

NASA Astrophysics Data System (ADS)

Mahdavi, Iraj; Tajdin, Ali; Hassanzadeh, Reza; Mahdavi-Amiri, Nezam; Shafieian, Hosna

2011-06-01

We are concerned with the design of a model and an algorithm for computing a shortest path in a network having various types of fuzzy arc lengths. First, we develop a new technique for the addition of various fuzzy numbers in a path using α -cuts by proposing a linear least squares model to obtain membership functions for the considered additions. Then, using a recently proposed distance function for comparison of fuzzy numbers. we propose a new approach to solve the fuzzy APSPP using of genetic algorithm. Examples are worked out to illustrate the applicability of the proposed model.

Topological versus rheological entanglement length in primitive-path analysis protocols, tube models, and slip-link models

NASA Astrophysics Data System (ADS)

Everaers, Ralf

2012-08-01

We show that the front factor appearing in the shear modulus of a phantom network, Gph=(1-2/f)(ρkBT)/Ns, also controls the ratio of the strand length, Ns, and the number of monomers per Kuhn length of the primitive paths, NphPPKuhn, characterizing the average network conformation. In particular, NphPPKuhn=Ns/(1-2/f) and Gph=(ρkBT)/NphPPKuhn. Neglecting the difference between cross-links and slip-links, these results can be transferred to entangled systems and the interpretation of primitive path analysis data. In agreement with the tube model, the analogy to phantom networks suggest that the rheological entanglement length, Nerheo=(ρkBT)/Ge, should equal NePPKuhn. Assuming binary entanglements with f=4 functional junctions, we expect that Nerheo should be twice as large as the topological entanglement length, Netopo. These results are in good agreement with reported primitive path analysis results for model systems and a wide range of polymeric materials. Implications for tube and slip-link models are discussed.

Minimum expected delay-based routing protocol (MEDR) for Delay Tolerant Mobile Sensor Networks.

PubMed

Feng, Yong; Liu, Ming; Wang, Xiaomin; Gong, Haigang

2010-01-01

It is a challenging work to develop efficient routing protocols for Delay Tolerant Mobile Sensor Networks (DTMSNs), which have several unique characteristics such as sensor mobility, intermittent connectivity, energy limit, and delay tolerability. In this paper, we propose a new routing protocol called Minimum Expected Delay-based Routing (MEDR) tailored for DTMSNs. MEDR achieves a good routing performance by finding and using the connected paths formed dynamically by mobile sensors. In MEDR, each sensor maintains two important parameters: Minimum Expected Delay (MED) and its expiration time. According to MED, messages will be delivered to the sensor that has at least a connected path with their hosting nodes, and has the shortest expected delay to communication directly with the sink node. Because of the changing network topology, the path is fragile and volatile, so we use the expiration time of MED to indicate the valid time of the path, and avoid wrong transmissions. Simulation results show that the proposed MEDR achieves a higher message delivery ratio with lower transmission overhead and data delivery delay than other DTMSN routing approaches.

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

PubMed Central

Lam, William H. K.; Li, Qingquan

2017-01-01

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks. PMID:29210978

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.

PubMed

Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan

2017-12-06

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

WEAMR — A Weighted Energy Aware Multipath Reliable Routing Mechanism for Hotline-Based WSNs

PubMed Central

Tufail, Ali; Qamar, Arslan; Khan, Adil Mehmood; Baig, Waleed Akram; Kim, Ki-Hyung

2013-01-01

Reliable source to sink communication is the most important factor for an efficient routing protocol especially in domains of military, healthcare and disaster recovery applications. We present weighted energy aware multipath reliable routing (WEAMR), a novel energy aware multipath routing protocol which utilizes hotline-assisted routing to meet such requirements for mission critical applications. The protocol reduces the number of average hops from source to destination and provides unmatched reliability as compared to well known reactive ad hoc protocols i.e., AODV and AOMDV. Our protocol makes efficient use of network paths based on weighted cost calculation and intelligently selects the best possible paths for data transmissions. The path cost calculation considers end to end number of hops, latency and minimum energy node value in the path. In case of path failure path recalculation is done efficiently with minimum latency and control packets overhead. Our evaluation shows that our proposal provides better end-to-end delivery with less routing overhead and higher packet delivery success ratio compared to AODV and AOMDV. The use of multipath also increases overall life time of WSN network using optimum energy available paths between sender and receiver in WDNs. PMID:23669714

WEAMR-a weighted energy aware multipath reliable routing mechanism for hotline-based WSNs.

PubMed

Tufail, Ali; Qamar, Arslan; Khan, Adil Mehmood; Baig, Waleed Akram; Kim, Ki-Hyung

2013-05-13

Reliable source to sink communication is the most important factor for an efficient routing protocol especially in domains of military, healthcare and disaster recovery applications. We present weighted energy aware multipath reliable routing (WEAMR), a novel energy aware multipath routing protocol which utilizes hotline-assisted routing to meet such requirements for mission critical applications. The protocol reduces the number of average hops from source to destination and provides unmatched reliability as compared to well known reactive ad hoc protocols i.e., AODV and AOMDV. Our protocol makes efficient use of network paths based on weighted cost calculation and intelligently selects the best possible paths for data transmissions. The path cost calculation considers end to end number of hops, latency and minimum energy node value in the path. In case of path failure path recalculation is done efficiently with minimum latency and control packets overhead. Our evaluation shows that our proposal provides better end-to-end delivery with less routing overhead and higher packet delivery success ratio compared to AODV and AOMDV. The use of multipath also increases overall life time of WSN network using optimum energy available paths between sender and receiver in WDNs.

Integrated forward and reverse supply chain: A tire case study.

PubMed

Pedram, Ali; Yusoff, Nukman Bin; Udoncy, Olugu Ezutah; Mahat, Abu Bakar; Pedram, Payam; Babalola, Ayo

2017-02-01

This paper attempts to integrate both a forward and reverse supply chain to design a closed-loop supply chain network (CLSC). The problem in the design of a CLSC network is uncertainty in demand, return products and the quality of return products. Scenario analyses are generated to overcome this uncertainty. In contrast to the existing supply chain network design models, a new application of a CLSC network was studied in this paper to reduce waste. A multi-product, multi-tier mixed integer linear model is developed for a CLSC network design. The main objective is to maximize profit and provide waste management decision support in order to minimize pollution. The result shows applicability of the model in the tire industry. The model determines the number and the locations of facilities and the material flows between these facilities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

NASA Astrophysics Data System (ADS)

Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

2013-12-01

Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

Methamphetamine Use among Homeless Former Foster Youth: The Mediating Role of Social Networks

PubMed Central

Yoshioka-Maxwell, Amanda; Rice, Eric; Rhoades, Harmony; Winetrobe, Hailey

2015-01-01

Objectives Social network analysis can provide added causal insight into otherwise confusing epidemiologic findings in public health research. Although foster care and homelessness are risk factors for methamphetamine use, current research has failed to explicate why homeless youth with foster care experience engage in methamphetamine use at higher rates than other homeless young adults. This study examined the mediating effect of network engagement and time spent homeless on the relationship between foster care experience and recent methamphetamine use among homeless youth in Los Angeles. Methods Egocentric network data from a cross-sectional community-based sample (n = 652) of homeless youth aged 13–25 were collected from drop-in centers in Los Angeles. Questions addressed foster care experience, time spent homeless, methamphetamine use, and perceived drug use in social networks. Path analysis was performed in SAS to examine mediation. Results Controlling for all other variables, results of path analysis regarding recent methamphetamine use indicated a direct effect between foster care experience and recent methamphetamine use (B = .269, t = 2.73, p < .01). However, this direct effect became statistically nonsignificant when time spent homeless and network methamphetamine use were added to the model, and indirect paths from time spent homeless and network methamphetamine use became statistically significant. Conclusions Foster care experience influenced recent methamphetamine use indirectly through time spent homeless and methamphetamine use by network members. Efforts to reduce methamphetamine use should focus on securing stable housing and addressing network interactions among homeless former foster youth. PMID:26146647

Case report highlighting how wound path identification on CT can help identify organ damage in abdominal blast injuries.

PubMed

Fischer, Tatjana V; Folio, Les R; Backus, Christopher E; Bunger, Rolf

2012-01-01

Penetrating trauma is frequently encountered in forward deployed military combat hospitals. Abdominal blast injuries represent nearly 11% of combat injuries, and multiplanar computed tomography imaging is optimal for injury assessment and surgical planning. We describe a multiplanar approach to assessment of blast and ballistic injuries, which allows for more expeditious detection of missile tracts and damage caused along the path. Precise delineation of the trajectory path and localization of retained fragments enables time-saving and detailed evaluation of associated tissue and vascular injury. For consistent and reproducible documentation of fragment locations in the body, we propose a localization scheme based on Cartesian coordinates to report 3-dimensional locations of fragments and demonstrating the application in three cases of abdominal blast injury.

Logical optical line terminal technologies towards flexible and highly reliable metro- and access-integrated networks

NASA Astrophysics Data System (ADS)

Okamoto, Satoru; Sato, Takehiro; Yamanaka, Naoaki

2017-01-01

In this paper, flexible and highly reliable metro and access integrated networks with network virtualization and software defined networking technologies will be presented. Logical optical line terminal (L-OLT) technologies and active optical distribution networks (ODNs) are the key to introduce flexibility and high reliability into the metro and access integrated networks. In the Elastic Lambda Aggregation Network (EλAN) project which was started in 2012, a concept of the programmable optical line terminal (P-OLT) has been proposed. A role of the P-OLT is providing multiple network services that have different protocols and quality of service requirements by single OLT box. Accommodated services will be Internet access, mobile front-haul/back-haul, data-center access, and leased line. L-OLTs are configured within the P-OLT box to support the functions required for each network service. Multiple P-OLTs and programmable optical network units (P-ONUs) are connected by the active ODN. Optical access paths which have flexible capacity are set on the ODN to provide network services from L-OLT to logical ONUs (L-ONUs). The L-OLT to L-ONU path on the active ODN provides a logical connection. Therefore, introducing virtualization technologies becomes possible. One example is moving an L-OLT from one P-OLT to another P-OLT like a virtual machine. This movement is called L-OLT migration. The L-OLT migration provides flexible and reliable network functions such as energy saving by aggregating L-OLTs to a limited number of P-OLTs, and network wide optical access path restoration. Other L-OLT virtualization technologies and experimental results will be also discussed in the paper.

Pursuit and prediction in the tracking of moving food by a teleost fish (Acanthaluteres spilomelanurus).

PubMed

Lanchester, B S; Mark, R F

1975-12-01

1. The path, eye and body movements of a teleost fish (the leatherjacket Acanthaluteres spilomelanurus) approaching and taking food were measured by cinematography. 2. Fixation of the food by movement of the eyes is an invariable feature of the approach. The eyes then remain aligned with the target while the body moves forward and round to bring the mouth to the food. 3. When pursuing pieces of food moving vertically at constant velocity through the water these fish normally trace out the pathway that can be calculated by assuming the fish aims constantly at the food. Predictive pathways that imply anticipation of the point of intersection with the food are not regularly seen. 4. Deviations from pursuit occur sporadically, usually in the direction of a predictive path, particularly when the fish approach falling food from below. 5. The geometry of the situation suggests that predictive paths may sometimes be generated if the alignment of eye and body during the pursuit of moving food can be delayed. In approaches from below this may be because forward movement of the fish would tend to stabilize the image of the falling food in the retina. 6. We suggest that a simple linked control system using both eye and body movements to fixate retinal images will on occasions generate predictive pathways without any need for the central nervous system to calculate them in advance.

Spectrum efficient distance-adaptive paths for fixed and fixed-alternate routing in elastic optical networks

NASA Astrophysics Data System (ADS)

Agrawal, Anuj; Bhatia, Vimal; Prakash, Shashi

2018-01-01

Efficient utilization of spectrum is a key concern in the soon to be deployed elastic optical networks (EONs). To perform routing in EONs, various fixed routing (FR), and fixed-alternate routing (FAR) schemes are ubiquitously used. FR, and FAR schemes calculate a fixed route, and a prioritized list of a number of alternate routes, respectively, between different pairs of origin o and target t nodes in the network. The route calculation performed using FR and FAR schemes is predominantly based on either the physical distance, known as k -shortest paths (KSP), or on the hop count (HC). For survivable optical networks, FAR usually calculates link-disjoint (LD) paths. These conventional routing schemes have been efficiently used for decades in communication networks. However, in this paper, it has been demonstrated that these commonly used routing schemes cannot utilize the network spectral resources optimally in the newly introduced EONs. Thus, we propose a new routing scheme for EON, namely, k -distance adaptive paths (KDAP) that efficiently utilizes the benefit of distance-adaptive modulation, and bit rate-adaptive superchannel capability inherited by EON to improve spectrum utilization. In the proposed KDAP, routes are found and prioritized on the basis of bit rate, distance, spectrum granularity, and the number of links used for a particular route. To evaluate the performance of KSP, HC, LD, and the proposed KDAP, simulations have been performed for three different sized networks, namely, 7-node test network (TEST7), NSFNET, and 24-node US backbone network (UBN24). We comprehensively assess the performance of various conventional, and the proposed routing schemes by solving both the RSA and the dual RSA problems under homogeneous and heterogeneous traffic requirements. Simulation results demonstrate that there is a variation amongst the performance of KSP, HC, and LD, depending on the o - t pair, and the network topology and its connectivity. However, the proposed KDAP always performs better for all the considered networks and traffic scenarios, as compared to the conventional routing schemes, namely, KSP, HC, and LD. The proposed KDAP achieves up to 60 % , and 10.46 % improvement in terms of spectrum utilization, and resource utilization ratio, respectively, over the conventional routing schemes.

Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks.

PubMed

Wadud, Zahid; Javaid, Nadeem; Khan, Muhammad Awais; Alrajeh, Nabil; Alabed, Mohamad Souheil; Guizani, Nadra

2017-07-21

In Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs), there are two major factors which degrade the performance of the network. One is the void hole which occurs in a particular region due to unavailability of forwarder nodes. The other is the presence of energy hole which occurs due to imbalanced data traffic load on intermediate nodes. Therefore, an optimum transmission strategy is required to maximize the network lifespan via hole alleviation. In this regard, we propose a heterogeneous network solution that is capable to balance energy dissipation among network nodes. In addition, the divide and conquer approach is exploited to evenly distribute number of transmissions over various network areas. An efficient forwarder node selection is performed to alleviate coverage and energy holes. Linear optimization is performed to validate the effectiveness of our proposed work in term of energy minimization. Furthermore, simulations are conducted to show that our claims are well grounded. Results show the superiority of our work as compared to the baseline scheme in terms of energy consumption and network lifetime.

Network Analysis in Community Psychology: Looking Back, Looking Forward.

PubMed

Neal, Zachary P; Neal, Jennifer Watling

2017-09-01

Network analysis holds promise for community psychology given the field's aim to understand the interplay between individuals and their social contexts. Indeed, because network analysis focuses explicitly on patterns of relationships between actors, its theories and methods are inherently extra-individual in nature and particularly well suited to characterizing social contexts. But, to what extent has community psychology taken advantage of this network analysis as a tool for capturing context? To answer these questions, this study provides a review of the use network analysis in articles published in American Journal of Community Psychology. Looking back, we describe and summarize the ways that network analysis has been employed in community psychology research to understand the range of ways community psychologists have found the technique helpful. Looking forward and paying particular attention to analytic issues identified in past applications, we provide some recommendations drawn from the network analysis literature to facilitate future applications of network analysis in community psychology. © 2017 The Authors. American Journal of Community Psychology published by Wiley Periodicals, Inc. on behalf of Society for Community Research and Action.

Lifetime Maximization via Hole Alleviation in IoT Enabling Heterogeneous Wireless Sensor Networks

PubMed Central

Wadud, Zahid; Khan, Muhammad Awais; Alrajeh, Nabil; Alabed, Mohamad Souheil; Guizani, Nadra

2017-01-01

In Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs), there are two major factors which degrade the performance of the network. One is the void hole which occurs in a particular region due to unavailability of forwarder nodes. The other is the presence of energy hole which occurs due to imbalanced data traffic load on intermediate nodes. Therefore, an optimum transmission strategy is required to maximize the network lifespan via hole alleviation. In this regard, we propose a heterogeneous network solution that is capable to balance energy dissipation among network nodes. In addition, the divide and conquer approach is exploited to evenly distribute number of transmissions over various network areas. An efficient forwarder node selection is performed to alleviate coverage and energy holes. Linear optimization is performed to validate the effectiveness of our proposed work in term of energy minimization. Furthermore, simulations are conducted to show that our claims are well grounded. Results show the superiority of our work as compared to the baseline scheme in terms of energy consumption and network lifetime. PMID:28753990

Retaining Underrepresented Minority Undergraduates in STEM through Hands-on Internship Experiences

NASA Astrophysics Data System (ADS)

Bamzai, A.; Mcpherson, R. A.; DeLong, K. L.; Rivera-Monroy, V. H.; Zak, J.; Earl, J.; Owens, K.; Wilson, D.

2015-12-01

The U.S. Department of the Interior's South Central Climate Science Center (SCCSC) hosts an annual 3-week summer internship opportunity for undergraduate students of underrepresented minorities interested in science, technology, engineering and mathematics (STEM) fields. Internship participants travel across the south-central U.S. to visit university campuses and field locations. The students interact with faculty conducting cutting edge research and with resource managers facing decision-making under uncertainty. This internship format allows the participants to see the direct impacts of climate variability and change on the Texas Hill Country, prairie and forest ecosystems and tribal cultures in Oklahoma, and the bayous, delta and coastline of Louisiana. Immersive experiences are key for exposing students to academic research and providing them with the skills and experiences needed to continue on in their professional careers. The SCCSC's program introduces students to how research is conducted, gives them a broad perspective on how collaborations form, and starts each student on the path to building a large and diverse professional network. By providing participants with a "buffet" of options, our internship serves as a launching pad from which each student can move forward towards experiences such as participating in a Research Experiences for Undergraduates program, gaining employment in a STEM-related career path, and being accepted into a graduate degree program. This presentation will describe the components of the SCCSC's internship program and provide a summary of post-internship student successes.

Proactive routing mutation against stealthy Distributed Denial of Service attacks: metrics, modeling, and analysis

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

Duan, Qi; Al-Shaer, Ehab; Chatterjee, Samrat

The Infrastructure Distributed Denial of Service (IDDoS) attacks continue to be one of the most devastating challenges facing cyber systems. The new generation of IDDoS attacks exploit the inherent weakness of cyber infrastructure including deterministic nature of routes, skew distribution of flows, and Internet ossification to discover the network critical links and launch highly stealthy flooding attacks that are not observable at the victim end. In this paper, first, we propose a new metric to quantitatively measure the potential susceptibility of any arbitrary target server or domain to stealthy IDDoS attacks, and es- timate the impact of such susceptibility onmore » enterprises. Second, we develop a proactive route mutation technique to minimize the susceptibility to these attacks by dynamically changing the flow paths periodically to invalidate the adversary knowledge about the network and avoid targeted critical links. Our proposed approach actively changes these network paths while satisfying security and qualify of service requirements. We present an integrated approach of proactive route mutation that combines both infrastructure-based mutation that is based on reconfiguration of switches and routers, and middle-box approach that uses an overlay of end-point proxies to construct a virtual network path free of critical links to reach a destination. We implemented the proactive path mutation technique on a Software Defined Network using the OpendDaylight controller to demonstrate a feasible deployment of this approach. Our evaluation validates the correctness, effectiveness, and scalability of the proposed approaches.« less

A Low Power 2.4 GHz CMOS Mixer Using Forward Body Bias Technique for Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Yin, C. J.; Murad, S. A. Z.; Harun, A.; Ramli, M. M.; Zulkifli, T. Z. A.; Karim, J.

2018-03-01

Wireless sensor network (WSN) is a highly-demanded application since the evolution of wireless generation which is often used in recent communication technology. A radio frequency (RF) transceiver in WSN should have a low power consumption to support long operating times of mobile devices. A down-conversion mixer is responsible for frequency translation in a receiver. By operating a down-conversion mixer at a low supply voltage, the power consumed by WSN receiver can be greatly reduced. This paper presents a development of low power CMOS mixer using forward body bias technique for wireless sensor network. The proposed mixer is implemented using CMOS 0.13 μm Silterra technology. The forward body bias technique is adopted to obtain low power consumption. The simulation results indicate that a low power consumption of 0.91 mW is achieved at 1.6 V supply voltage. Moreover, the conversion gain (CG) of 21.83 dB, the noise figure (NF) of 16.51 dB and the input-referred third-order intercept point (IIP3) of 8.0 dB at 2.4 GHz are obtained. The proposed mixer is suitable for wireless sensor network.

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

DOEpatents

Kouchri, Farrokh Mohammadzadeh

2012-11-06

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

An optimal routing strategy on scale-free networks

NASA Astrophysics Data System (ADS)

Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin

Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

Ten years of the Immune Tolerance Network: an integrated clinical research organization.

PubMed

Bluestone, Jeffrey A; Krensky, Alan M; Turka, Laurence A; Rotrosen, Daniel; Matthews, Jeffrey B

2010-02-17

The U.S. National Institutes of Health Roadmap and the U.S. Food and Drug Administration's Critical Path Initiative have endorsed the establishment of large academic clinical research networks as part of the solution to the growing divide between increased R&D spending and the lagging number of new drugs making it to market. Clearly, the role of these networks as translational science incubators that complement industry-sponsored programs is laudable and much-needed. However, the path to success for such organizations is less clear. Here, drawing on the experiences of the Immune Tolerance Network, a multidisciplinary clinical research network founded in 1999, we discuss some of the barriers inherent in developing such consortia and offer firsthand insight into the planning, resources, and organizational infrastructure required for a successful research program.

Cross Layered Multi-Meshed Tree Scheme for Cognitive Networks

DTIC Science & Technology

2011-06-01

Meshed Tree Routing protocol wireless ad hoc networks ,” Second IEEE International Workshop on Enabling Technologies and Standards for Wireless Mesh ...and Sensor Networks , 2004 43. Chen G.; Stojmenovic I., “Clustering and routing in mobile wireless networks ,” Technical Report TR-99-05, SITE, June...Cross-layer optimization, intra-cluster routing , packet forwarding, inter-cluster routing , mesh network communications,

Iterative blip-summed path integral for quantum dynamics in strongly dissipative environments

NASA Astrophysics Data System (ADS)

Makri, Nancy

2017-04-01

The iterative decomposition of the blip-summed path integral [N. Makri, J. Chem. Phys. 141, 134117 (2014)] is described. The starting point is the expression of the reduced density matrix for a quantum system interacting with a harmonic dissipative bath in the form of a forward-backward path sum, where the effects of the bath enter through the Feynman-Vernon influence functional. The path sum is evaluated iteratively in time by propagating an array that stores blip configurations within the memory interval. Convergence with respect to the number of blips and the memory length yields numerically exact results which are free of statistical error. In situations of strongly dissipative, sluggish baths, the algorithm leads to a dramatic reduction of computational effort in comparison with iterative path integral methods that do not implement the blip decomposition. This gain in efficiency arises from (i) the rapid convergence of the blip series and (ii) circumventing the explicit enumeration of between-blip path segments, whose number grows exponentially with the memory length. Application to an asymmetric dissipative two-level system illustrates the rapid convergence of the algorithm even when the bath memory is extremely long.

Exploring the full catalytic cycle of rhodium(i)–BINAP-catalysed isomerisation of allylic amines: a graph theory approach for path optimisation† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc00401j Click here for additional data file.

PubMed Central

Yoshimura, Takayoshi; Taketsugu, Tetsuya; Sawamura, Masaya

2017-01-01

We explored the reaction mechanism of the cationic rhodium(i)–BINAP complex catalysed isomerisation of allylic amines using the artificial force induced reaction method with the global reaction route mapping strategy, which enabled us to search for various reaction paths without assumption of transition states. The entire reaction network was reproduced in the form of a graph, and reasonable paths were selected from the complicated network using Prim’s algorithm. As a result, a new dissociative reaction mechanism was proposed. Our comprehensive reaction path search provided rationales for the E/Z and S/R selectivities of the stereoselective reaction. PMID:28970877

In vitro exposure systems and dosimetry assessment tools for inhaled tobacco products: Workshop proceedings, conclusions and paths forward for in vitro model use.

PubMed

Behrsing, Holger; Hill, Erin; Raabe, Hans; Tice, Raymond; Fitzpatrick, Suzanne; Devlin, Robert; Pinkerton, Kent; Oberdörster, Günter; Wright, Chris; Wieczorek, Roman; Aufderheide, Michaela; Steiner, Sandro; Krebs, Tobias; Asgharian, Bahman; Corley, Richard; Oldham, Michael; Adamson, Jason; Li, Xiang; Rahman, Irfan; Grego, Sonia; Chu, Pei-Hsuan; McCullough, Shaun; Curren, Rodger

2017-07-01

In 2009, the passing of the Family Smoking Prevention and Tobacco Control Act facilitated the establishment of the FDA Center for Tobacco Products (CTP), and gave it regulatory authority over the marketing, manufacture and distribution of tobacco products, including those termed 'modified risk'. On 4-6 April 2016, the Institute for In Vitro Sciences, Inc. (IIVS) convened a workshop conference entitled, In Vitro Exposure Systems and Dosimetry Assessment Tools for Inhaled Tobacco Products, to bring together stakeholders representing regulatory agencies, academia and industry to address the research priorities articulated by the FDA CTP. Specific topics were covered to assess the status of current in vitro smoke and aerosol/vapour exposure systems, as well as the various approaches and challenges to quantifying the complex exposures in in vitro pulmonary models developed for evaluating adverse pulmonary events resulting from tobacco product exposures. The four core topics covered were: a) Tobacco Smoke and E-Cigarette Aerosols; b) Air-Liquid Interface-In Vitro Exposure Systems; c) Dosimetry Approaches for Particles and Vapours/In Vitro Dosimetry Determinations; and d) Exposure Microenvironment/Physiology of Cells. The 2.5-day workshop included presentations from 20 expert speakers, poster sessions, networking discussions, and breakout sessions which identified key findings and provided recommendations to advance these technologies. Here, we will report on the proceedings, recommendations, and outcome of the April 2016 technical workshop, including paths forward for developing and validating non-animal test methods for tobacco product smoke and next generation tobacco product aerosol/vapour exposures. With the recent FDA publication of the final deeming rule for the governance of tobacco products, there is an unprecedented necessity to evaluate a very large number of tobacco-based products and ingredients. The questionable relevance, high cost, and ethical considerations for the use of in vivo testing methods highlight the necessity of robust in vitro approaches to elucidate tobacco-based exposures and how they may lead to pulmonary diseases that contribute to lung exposure-induced mortality worldwide. 2017 FRAME.

A graph-based system for network-vulnerability analysis

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

Swiler, L.P.; Phillips, C.

1998-06-01

This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low effort cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks,more » broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.« less

Identifying influential spreaders in complex networks through local effective spreading paths

NASA Astrophysics Data System (ADS)

Wang, Xiaojie; Zhang, Xue; Yi, Dongyun; Zhao, Chengli

2017-05-01

How to effectively identify a set of influential spreaders in complex networks is of great theoretical and practical value, which can help to inhibit the rapid spread of epidemics, promote the sales of products by word-of-mouth advertising, and so on. A naive strategy is to select the top ranked nodes as identified by some centrality indices, and other strategies are mainly based on greedy methods and heuristic methods. However, most of those approaches did not concern the connections between nodes. Usually, the distances between the selected spreaders are very close, leading to a serious overlapping of their influence. As a consequence, the global influence of the spreaders in networks will be greatly reduced, which largely restricts the performance of those methods. In this paper, a simple and efficient method is proposed to identify a set of discrete yet influential spreaders. By analyzing the spreading paths in the network, we present the concept of effective spreading paths and measure the influence of nodes via expectation calculation. The numerical analysis in undirected and directed networks all show that our proposed method outperforms many other centrality-based and heuristic benchmarks, especially in large-scale networks. Besides, experimental results on different spreading models and parameters demonstrates the stability and wide applicability of our method.

Grey matter networks in people at increased familial risk for schizophrenia.

PubMed

Tijms, Betty M; Sprooten, Emma; Job, Dominic; Johnstone, Eve C; Owens, David G C; Willshaw, David; Seriès, Peggy; Lawrie, Stephen M

2015-10-01

Grey matter brain networks are disrupted in schizophrenia, but it is still unclear at which point during the development of the illness these disruptions arise and whether these can be associated with behavioural predictors of schizophrenia. We investigated if single-subject grey matter networks were disrupted in a sample of people at familial risk of schizophrenia. Single-subject grey matter networks were extracted from structural MRI scans of 144 high risk subjects, 32 recent-onset patients and 36 healthy controls. The following network properties were calculated: size, connectivity density, degree, path length, clustering coefficient, betweenness centrality and small world properties. People at risk of schizophrenia showed decreased path length and clustering in mostly prefrontal and temporal areas. Within the high risk sample, the path length of the posterior cingulate cortex and the betweenness centrality of the left inferior frontal operculum explained 81% of the variance in schizotypal cognitions, which was previously shown to be the strongest behavioural predictor of schizophrenia in the study. In contrast, local grey matter volume measurements explained 48% of variance in schizotypy. The present results suggest that single-subject grey matter networks can quantify behaviourally relevant biological alterations in people at increased risk for schizophrenia before disease onset. Copyright © 2015 Elsevier B.V. All rights reserved.

A Multi-level Fuzzy Evaluation Method for Smart Distribution Network Based on Entropy Weight

NASA Astrophysics Data System (ADS)

Li, Jianfang; Song, Xiaohui; Gao, Fei; Zhang, Yu

2017-05-01

Smart distribution network is considered as the future trend of distribution network. In order to comprehensive evaluate smart distribution construction level and give guidance to the practice of smart distribution construction, a multi-level fuzzy evaluation method based on entropy weight is proposed. Firstly, focus on both the conventional characteristics of distribution network and new characteristics of smart distribution network such as self-healing and interaction, a multi-level evaluation index system which contains power supply capability, power quality, economy, reliability and interaction is established. Then, a combination weighting method based on Delphi method and entropy weight method is put forward, which take into account not only the importance of the evaluation index in the experts’ subjective view, but also the objective and different information from the index values. Thirdly, a multi-level evaluation method based on fuzzy theory is put forward. Lastly, an example is conducted based on the statistical data of some cites’ distribution network and the evaluation method is proved effective and rational.

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

PubMed

Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin

2017-09-13

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.

Structural support bracket for gas flow path

DOEpatents

None

2016-08-02

A structural support system is provided in a can annular gas turbine engine having an arrangement including a plurality of integrated exit pieces (IEPs) forming an annular chamber for delivering gases from a plurality of combustors to a first row of turbine blades. A bracket structure is connected between an IEP and an inner support structure on the engine. The bracket structure includes an axial bracket member attached to an IEP and extending axially in a forward direction. A transverse bracket member has an end attached to the inner support structure and extends circumferentially to a connection with a forward end of the axial bracket member. The transverse bracket member provides a fixed radial position for the forward end of the axial bracket member and is flexible in the axial direction to permit axial movement of the axial bracket member.

Blip decomposition of the path integral: exponential acceleration of real-time calculations on quantum dissipative systems.

PubMed

Makri, Nancy

2014-10-07

The real-time path integral representation of the reduced density matrix for a discrete system in contact with a dissipative medium is rewritten in terms of the number of blips, i.e., elementary time intervals over which the forward and backward paths are not identical. For a given set of blips, it is shown that the path sum with respect to the coordinates of all remaining time points is isomorphic to that for the wavefunction of a system subject to an external driving term and thus can be summed by an inexpensive iterative procedure. This exact decomposition reduces the number of terms by a factor that increases exponentially with propagation time. Further, under conditions (moderately high temperature and/or dissipation strength) that lead primarily to incoherent dynamics, the "fully incoherent limit" zero-blip term of the series provides a reasonable approximation to the dynamics, and the blip series converges rapidly to the exact result. Retention of only the blips required for satisfactory convergence leads to speedup of full-memory path integral calculations by many orders of magnitude.

Information Spread of Emergency Events: Path Searching on Social Networks

PubMed Central

Hu, Hongzhi; Wu, Tunan

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning. PMID:24600323