Normal mediastinal and hilar lymph nodes in children on multi-detector row chest computed tomography

International Nuclear Information System (INIS)

Jong, Pim A. de; Nievelstein, Rutger-Jan A.

2012-01-01

To study normal mediastinal and hilar lymph nodes on multi-detector chest computed tomography (CT). A cohort of 120 children aged 1-17 years underwent emergency CT, including the chest, after high-energy trauma. Axial 5-mm reconstructions were evaluated for lymph nodes at hilar and various mediastinal levels and the short-axis diameters were measured. At least one lymph node was found in 115 (96%) children, with subcarinal (69%), lower paratracheal (64%) and hilar (60%) nodes being most common. Up to 10 years of age most lymph nodes were smaller than or equal to 7 mm. In older children lymph nodes measuring up to 10-mm-short-axis diameter were found. Lymph nodes were rare along the mammary vessels, at lower oesophageal and at prevascular and posterior mediastinal levels in children. Mediastinal and hilar lymph nodes are more common than previously thought, probably because of increased detection by modern multi-detector CT. Lymph node location and age have to be taken into account when evaluating lymph nodes in the paediatric chest. (orig.)

Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes

Science.gov (United States)

Satymbekov, M. N.; Pak, I. T.; Naizabayeva, L.; Nurzhanov, Ch. A.

2017-12-01

In this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.

Multi-granularity immunization strategy based on SIRS model in scale-free network

Science.gov (United States)

Nian, Fuzhong; Wang, Ke

2015-04-01

In this paper, a new immunization strategy was established to prevent the epidemic spreading based on the principle of "Multi-granularity" and "Pre-warning Mechanism", which send different pre-warning signal with the risk rank of the susceptible node to be infected. The pre-warning means there is a higher risk that the susceptible node is more likely to be infected. The multi-granularity means the susceptible node is linked with multi-infected nodes. In our model, the effect of the different situation of the multi-granularity immunizations is compared and different spreading rates are adopted to describe the epidemic behavior of nodes. In addition the threshold value of epidemic outbreak is investigated, which makes the result more convincing. The theoretical analysis and the simulations indicate that the proposed immunization strategy is effective and it is also economic and feasible.

Processing and Characterisation of the Copper Treated Polylactic Acid and Cotton Fabrics: Thermophysiological Comfort Properties

Directory of Open Access Journals (Sweden)

Muhammet UZUN

2014-04-01

Full Text Available The main objective of this study is to develop a novel copper treatment method and characterise the effect of treatment on the thermophysiological comfort properties of the treated fabrics. It is also aimed to analyse and evaluate the thermophysiological properties of the PLA fabrics. The study was conducted by using polylactic acid (PLA, cotton and their blend yarns. The knitted fabrics, single pique, were made from these yarns by using weft knitting machine. The fabrics were treated with two copper solution concentrations (5 % and 10 % at 20 minutes ultrasonic energy. The results show that the treatment has a critical effect on the tested fabrics in terms of thermal conductivity, thermal resistance, thermal absorbtivity, water vapour permeability, and heat loss. The results also clearly demonstrated that the PLA fabric was successfully treated with the copper solution, and the coated fabrics showed significant change as compared to their untreated counterparts in terms of tested parameters.DOI: http://dx.doi.org/10.5755/j01.ms.20.1.1853

Multi-Channel Multi-Radio Using 802.11 Based Media Access for Sink Nodes in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Kok-Keong Loo

2011-05-01

Full Text Available The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.

Multi-channel multi-radio using 802.11 based media access for sink nodes in wireless sensor networks.

Science.gov (United States)

Campbell, Carlene E-A; Khan, Shafiullah; Singh, Dhananjay; Loo, Kok-Keong

2011-01-01

The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.

Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

Science.gov (United States)

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-10-02

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

High-precision multi-node clock network distribution.

Science.gov (United States)

Chen, Xing; Cui, Yifan; Lu, Xing; Ci, Cheng; Zhang, Xuesong; Liu, Bo; Wu, Hong; Tang, Tingsong; Shi, Kebin; Zhang, Zhigang

2017-10-01

A high precision multi-node clock network for multiple users was built following the precise frequency transmission and time synchronization of 120 km fiber. The network topology adopts a simple star-shaped network structure. The clock signal of a hydrogen maser (synchronized with UTC) was recovered from a 120 km telecommunication fiber link and then was distributed to 4 sub-stations. The fractional frequency instability of all substations is in the level of 10 -15 in a second and the clock offset instability is in sub-ps in root-mean-square average.

Human cold stress of strong local-wind "Hijikawa-arashi" in Japan, based on the UTCI index and thermo-physiological responses

Science.gov (United States)

Ohashi, Yukitaka; Katsuta, Takumi; Tani, Haruka; Okabayashi, Taiki; Miyahara, Satoshi; Miyashita, Ryoji

2018-03-01

We investigated the cold stress caused by a strong local wind called "Hijikawa-arashi," through in situ vital measurements and the Universal Thermal Climate Index (UTCI). This wind is a very interesting winter phenomenon, localized in an area within 1 km of the seashore in Ozu City, Ehime Prefecture in Japan. When a strong Hijikawa-arashi (HA) occurred at 14-15 m s-1, the UTCI decreased to - 30 °C along the bridge where commuting residents are the most exposed to strong and cold winds. On the bridge, most participants in our experiment felt "very cold" or "extremely cold." The UTCI of HA can be predicted from a multiple regression equation using wind speed and air temperature. The cold HA wind is also harmful to human thermo-physiological responses. It leads to higher blood pressure and increased heart rate, both of which act as cardiovascular stress triggers. Increases of 6-10 mmHg and 3-6 bpm for every 10 °C reduction in UTCI were seen on all observational days, including HA and non-HA days. In fact, the participants' body skin temperatures decreased by approximately 1.2 to 1.7 °C for every 10 °C reduction in UTCI. Thus, the UTCI variation due to the HA outbreak corresponded well with the cold sensation and thermo-physiological responses in humans. This result suggests that daily UTCI monitoring enables the prediction of thermo-physiological responses to the HA cold stress.

A Micro-Grid Simulator Tool (SGridSim) using Effective Node-to-Node Complex Impedance (EN2NCI) Models

Energy Technology Data Exchange (ETDEWEB)

Udhay Ravishankar; Milos manic

2013-08-01

This paper presents a micro-grid simulator tool useful for implementing and testing multi-agent controllers (SGridSim). As a common engineering practice it is important to have a tool that simplifies the modeling of the salient features of a desired system. In electric micro-grids, these salient features are the voltage and power distributions within the micro-grid. Current simplified electric power grid simulator tools such as PowerWorld, PowerSim, Gridlab, etc, model only the power distribution features of a desired micro-grid. Other power grid simulators such as Simulink, Modelica, etc, use detailed modeling to accommodate the voltage distribution features. This paper presents a SGridSim micro-grid simulator tool that simplifies the modeling of both the voltage and power distribution features in a desired micro-grid. The SGridSim tool accomplishes this simplified modeling by using Effective Node-to-Node Complex Impedance (EN2NCI) models of components that typically make-up a micro-grid. The term EN2NCI models means that the impedance based components of a micro-grid are modeled as single impedances tied between their respective voltage nodes on the micro-grid. Hence the benefit of the presented SGridSim tool are 1) simulation of a micro-grid is performed strictly in the complex-domain; 2) faster simulation of a micro-grid by avoiding the simulation of detailed transients. An example micro-grid model was built using the SGridSim tool and tested to simulate both the voltage and power distribution features with a total absolute relative error of less than 6%.

Robotic-Assisted Fluorescence Sentinel Lymph Node Mapping Using Multi-Modal Image-Guidance in an Animal Model

Science.gov (United States)

Liss, Michael A.; Stroup, Sean P.; Cand, Zhengtao Qin; Hoh, Carl; Hall, David J.; Vera, David R.; Kane, Christopher J.

2015-01-01

Objectives To investigate PET/CT pre-operative imaging and intraoperative detection of a fluorescent-labeled receptor-targeted radiopharmaceutical in a prostate cancer animal model. Methods Three male Beagle dogs underwent an intra-prostatic injection of fluorescent-tagged tilmanocept radio-labeled with both gallium-68 and technetium-99m. One hour after injection a pelvic PET/CT scan was performed for pre-operative sentinel lymph node (SLN) mapping. Definition of SLN was a standardized uptake value (SUV) that exceeded 5% of the lymph node with the highest SUV. Thirty-six hours later we performed robotic-assisted SLN dissection using a fluorescence-capable camera system. Fluorescent lymph nodes were clipped, the abdomen was opened, and the pelvic and retroperitoneal nodes were excised. All excised nodal packets were assayed by in vitro nuclear counting and reported as percent-of-injected dose. Results Pre-operative PET/CT imaging identified a median of three sentinel lymph nodes per animal. All sentinel lymph nodes (100%) identified by the PET/CT were fluorescent during robotic-assisted lymph node dissection. Of all fluorescent nodes visualized by the camera system, 83% (10/12) satisfied the 5%-rule defined by the PET/CT scan. The two lymph nodes that did not qualify accumulated less than 0.002% of the injected dose. Conclusions Fluorescent-labeled tilmanocept has optimal logistical properties to obtain pre-operative PET/CT and subsequent real-time intraoperative confirmation during robotic-assisted sentinel lymph node dissection. PMID:25139676

Maximizing survivability of acyclic transmission networks with multi-state retransmitters and vulnerable nodes

International Nuclear Information System (INIS)

Levitin, Gregory

2002-01-01

In this paper, an algorithm for optimal allocation of multi-state elements (MEs) in acyclic transmission networks (ATNs) with vulnerable nodes is suggested. The ATNs consist of a number of positions (nodes) in which MEs capable of receiving and sending a signal are allocated. Each network has a root position where the signal source is located, a number of leaf positions that can only receive a signal, and a number of intermediate positions containing MEs capable of transmitting the received signal to some other nodes. Each ME that is located in a nonleaf node can have different states determined by a set of nodes receiving the signal directly from this ME. The probability of each state is assumed to be known for each ME. Each ATN node with all the MEs allocated at this node can be destroyed by external impact (common cause failure) with a given probability. The ATN survivability is defined as the probability that a signal from the root node is transmitted to each leaf node. The optimal distribution of MEs with different characteristics among ATN positions provides the greatest possible ATN survivability. It is shown that the node vulnerability index affects the optimal distribution. The suggested algorithm is based on using a universal generating function technique for network survivability evaluation. A genetic algorithm is used as the optimization tool. Illustrative examples are presented

Human cold stress of strong local-wind "Hijikawa-arashi" in Japan, based on the UTCI index and thermo-physiological responses.

Science.gov (United States)

Ohashi, Yukitaka; Katsuta, Takumi; Tani, Haruka; Okabayashi, Taiki; Miyahara, Satoshi; Miyashita, Ryoji

2018-03-30

We investigated the cold stress caused by a strong local wind called "Hijikawa-arashi," through in situ vital measurements and the Universal Thermal Climate Index (UTCI). This wind is a very interesting winter phenomenon, localized in an area within 1 km of the seashore in Ozu City, Ehime Prefecture in Japan. When a strong Hijikawa-arashi (HA) occurred at 14-15 m s -1 , the UTCI decreased to - 30 °C along the bridge where commuting residents are the most exposed to strong and cold winds. On the bridge, most participants in our experiment felt "very cold" or "extremely cold." The UTCI of HA can be predicted from a multiple regression equation using wind speed and air temperature. The cold HA wind is also harmful to human thermo-physiological responses. It leads to higher blood pressure and increased heart rate, both of which act as cardiovascular stress triggers. Increases of 6-10 mmHg and 3-6 bpm for every 10 °C reduction in UTCI were seen on all observational days, including HA and non-HA days. In fact, the participants' body skin temperatures decreased by approximately 1.2 to 1.7 °C for every 10 °C reduction in UTCI. Thus, the UTCI variation due to the HA outbreak corresponded well with the cold sensation and thermo-physiological responses in humans. This result suggests that daily UTCI monitoring enables the prediction of thermo-physiological responses to the HA cold stress.

Multi-scale modeling strategies in materials science—The ...

Indian Academy of Sciences (India)

Unknown

Multi-scale models; quasicontinuum method; finite elements. 1. Introduction ... boundary with external stresses, and the interaction of a lattice dislocation with a grain ..... mum value of se over the elements that touch node α. The acceleration of ...

Hair coat characteristics and thermophysiological stress response of Nguni and Boran cows raised under hot environmental conditions

Science.gov (United States)

Katiyatiya, C. L. F.; Muchenje, V.

2017-12-01

Breed, age, coat colour, month and temperature humidity index (THI) influence on body weight (W), body condition score (BCS), thermophysiological variables (rectal temperature (Tr), skin temperature (Tsk)) and hair length was studied in Nguni ( n = 19) and Boran ( n = 16). As a result of this study, breed influenced W, BCS and Tsk on the neck and belly ( P cows were higher than the Boran cows. Hair length of both breeds increased from February to August. The THI influenced thermophysiological variables ( P cows (3-8 years) had lower weight and high Tr and Tsk ( P cows had high neck and thurl temperatures in June while Boran cows had the highest in August ( P cows had increased BCS. Nguni cows with red, fawn and white cows had high BCS. Fawn-coloured Nguni cows and white-brown Boran cows had the more weight than cows with other colours compared in the study. White-red Nguni and Boran cows recorded the highest Tr. For Nguni cows, neck and belly temperatures were significantly ( P cows had significant ( P cows were more adapted to the prevailing bioclimatic changes. However, Boran cows have the potential of performing well under heat stress conditions over time.

MSCT multi-criteria: A novel approach in assessment of mediastinal lymph node metastases in non-small cell lung cancer

International Nuclear Information System (INIS)

Volterrani, Luca; Mazzei, Maria Antonietta; Banchi, Benedetta; Voltolini, Luca; La Sala, Filomena; Carbone, Salvatore Francesco; Ricci, Veronica; Gotti, Giuseppe; Zompatori, Maurizio

2011-01-01

Summary: Purpose: To evaluate the accuracy of multi-slice computed tomography (MSCT) in diagnosing mediastinal lymph node metastases in patients with non-small cell lung cancer (NSCLC) using a multi-criteria approach. Methods: We retrospectively reviewed contrast-enhanced MSCT of the chest in 86 consecutive patients with histopathologically proven NSCLC. All patients underwent surgical lymph node resection within 30 days from the CT examination. In all cases pathological and CT results were reviewed and correlated. Results: The sensitivity, specificity, positive and negative predictive values, and accuracy of MSCT using a multi-criteria approach in the detection of the N2 stage were 100%, 98.5%, 100%, 94.4% and 98.8% respectively, whereas using the size criterion alone 64%, 61%, 87%, 40%, and 62% respectively. Conclusions: To improve MSCT accuracy for diagnosing N staging other criteria can be associated with lymph node size. The use of different dimensional cut-offs for each mediastinal lymph node station, the matching of positive nodal stations with tumour location, the structural characteristics and the type of enhancement allow for a high accuracy of MSCT in the staging of mediastinal nodes in NSCLC.

Automated generation of node-splitting models for assessment of inconsistency in network meta-analysis.

Science.gov (United States)

van Valkenhoef, Gert; Dias, Sofia; Ades, A E; Welton, Nicky J

2016-03-01

Network meta-analysis enables the simultaneous synthesis of a network of clinical trials comparing any number of treatments. Potential inconsistencies between estimates of relative treatment effects are an important concern, and several methods to detect inconsistency have been proposed. This paper is concerned with the node-splitting approach, which is particularly attractive because of its straightforward interpretation, contrasting estimates from both direct and indirect evidence. However, node-splitting analyses are labour-intensive because each comparison of interest requires a separate model. It would be advantageous if node-splitting models could be estimated automatically for all comparisons of interest. We present an unambiguous decision rule to choose which comparisons to split, and prove that it selects only comparisons in potentially inconsistent loops in the network, and that all potentially inconsistent loops in the network are investigated. Moreover, the decision rule circumvents problems with the parameterisation of multi-arm trials, ensuring that model generation is trivial in all cases. Thus, our methods eliminate most of the manual work involved in using the node-splitting approach, enabling the analyst to focus on interpreting the results. © 2015 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

Efficient implementation of multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

Science.gov (United States)

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2012-01-10

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

An analytical model for the performance of geographical multi-hop broadcast

NARCIS (Netherlands)

Klein Wolterink, W.; Heijenk, G.; Berg, J.L. van den

2012-01-01

In this paper we present an analytical model accurately describing the behaviour of a multi-hop broadcast protocol. Our model covers the scenario in which a message is forwarded over a straight road and inter-node distances are distributed exponentially. Intermediate forwarders draw a small random

Multi-detector row CT in the assessment of axillary lymph node metastasis in breast cancer

International Nuclear Information System (INIS)

Murakami, Shogo

2003-01-01

The purpose of this study is to evaluate the diagnostic capability instead of clinical efficacy of multi-detector row CT (MDCT) in the assessment of axillary lymph node metastasis in breast cancer. MDCT was performed in 63 patients with breast cancer, and multiplanar reformation (MPR) and volume rendering (VR) images were reconstructed for the evaluation of bilateral axillary lymph nodes. Two hundred sixty eight lymph nodes were depicted with MDCT, and correlation with pathological findings was performed. The short axis length of lymph node was measured on MPR image, and the shape of the nodes was analyzed with the pathological results statistically. The diagnostic criteria on size and shape of lymph node metastasis were discussed Dynamic study with contrast media was also performed, and the CT value ratios (CTVR) of the lymph nodes and breast tumors were calculated. No relevance of axillary lymph node metastasis was noted to the pathological types of breast cancer. The average short axis length of the ipsilateral axillary nodes was 8.9 mm±3.8 (SD) while that of the contralateral nodes was 4.9 mm±1.1 (SD) showing significant difference. More than 6.5 mm in short length of the lymph node was thought to be an effective criterion for positive metastasis, and its sensitivity was 96%. Soybean-shape lymph node was statistically common in metastasis, while non-metastatic nodes were commonly demonstrated as letter ''c'' shape or ring-like shape. Statistical relevance was obtained between the CTVR of axillary lymph nodes and that of breast tumors, suggesting clinical usefulness of dynamic study using contrast media in the evaluation of lymph node metastasis. With MPR and VR images using MDCT, more accurate morphological evaluation of axillary lymph nodes was possible. When soybean-shape node with more than 6.5 mm in short axis is depicted in the axillar region on MDCT metastasis should be the consideration. Comparison with the contralateral side as a control in coronal

Efficient implementation of a multidimensional fast fourier transform on a distributed-memory parallel multi-node computer

Science.gov (United States)

Bhanot, Gyan V [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2008-01-01

The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.

Critical Issues in Modelling Lymph Node Physiology

Directory of Open Access Journals (Sweden)

Dmitry Grebennikov

2016-12-01

Full Text Available In this study, we discuss critical issues in modelling the structure and function of lymph nodes (LNs, with emphasis on how LN physiology is related to its multi-scale structural organization. In addition to macroscopic domains such as B-cell follicles and the T cell zone, there are vascular networks which play a key role in the delivery of information to the inner parts of the LN, i.e., the conduit and blood microvascular networks. We propose object-oriented computational algorithms to model the 3D geometry of the fibroblastic reticular cell (FRC network and the microvasculature. Assuming that a conduit cylinder is densely packed with collagen fibers, the computational flow study predicted that the diffusion should be a dominating process in mass transport than convective flow. The geometry models are used to analyze the lymph flow properties through the conduit network in unperturbed- and damaged states of the LN. The analysis predicts that elimination of up to 60%–90% of edges is required to stop the lymph flux. This result suggests a high degree of functional robustness of the network.

Lagrangian generic second order traffic flow models for node

Directory of Open Access Journals (Sweden)

Asma Khelifi

2018-02-01

Full Text Available This study sheds light on higher order macroscopic traffic flow modeling on road networks, thanks to the generic second order models (GSOM family which embeds a myriad of traffic models. It has been demonstrated that such higher order models are easily solved in Lagrangian coordinates which are compatible with both microscopic and macroscopic descriptions. The generalized GSOM model is reformulated in the Lagrangian coordinate system to develop a more efficient numerical method. The difficulty in applying this approach on networks basically resides in dealing with node dynamics. Traffic flow characteristics at node are different from that on homogeneous links. Different geometry features can lead to different critical research issues. For instance, discontinuity in traffic stream can be an important issue for traffic signal operations, while capacity drop may be crucial for lane-merges. The current paper aims to establish and analyze a new adapted node model for macroscopic traffic flow models by applying upstream and downstream boundary conditions on the Lagrangian coordinates in order to perform simulations on networks of roads, and accompanying numerical method. The internal node dynamics between upstream and downstream links are taken into account of the node model. Therefore, a numerical example is provided to underscore the efficiency of this approach. Simulations show that the discretized node model yields accurate results. Additional kinematic waves and contact discontinuities are induced by the variation of the driver attribute.

Formal Modeling of Greedy Nodes in 802.15.4 WSN

Directory of Open Access Journals (Sweden)

Youcef Hammal

2015-06-01

Full Text Available This paper deals with formal specification of the non-slotted CSMA/CA protocol in wireless sensor networks(WSN whose some nodes own a greedy behavior. This protocol requires sensor nodes to wait some time before initiating a transmission, whereas greedy nodes may try to reduce their waiting duration, which may penalize other nodes. To analyze their impact on WSN mode in operation, we use timed automata of the model-checker UPPAAL to capture the abstract behavior of communication medium, sane, and greedy nodes in WSN. This enables the use of analysis tools to check whether these models satisfy intended properties.

Development of a QTL-environment-based predictive model for node addition rate in common bean.

Science.gov (United States)

Zhang, Li; Gezan, Salvador A; Eduardo Vallejos, C; Jones, James W; Boote, Kenneth J; Clavijo-Michelangeli, Jose A; Bhakta, Mehul; Osorno, Juan M; Rao, Idupulapati; Beebe, Stephen; Roman-Paoli, Elvin; Gonzalez, Abiezer; Beaver, James; Ricaurte, Jaumer; Colbert, Raphael; Correll, Melanie J

2017-05-01

This work reports the effects of the genetic makeup, the environment and the genotype by environment interactions for node addition rate in an RIL population of common bean. This information was used to build a predictive model for node addition rate. To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day - 1 ) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50-90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions.

Programmable multi-node quantum network design and simulation

Science.gov (United States)

Dasari, Venkat R.; Sadlier, Ronald J.; Prout, Ryan; Williams, Brian P.; Humble, Travis S.

2016-05-01

Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to write network applications and to build functional network designs. OpenFlow is a key protocol widely adopted to build programmable networks because of its programmability, flexibility and ability to interconnect heterogeneous network devices. We simulate the functional topology of a multi-node quantum network that uses programmable network principles to manage quantum metadata for protocols such as teleportation, superdense coding, and quantum key distribution. We first show how the OpenFlow protocol can manage the quantum metadata needed to control the quantum channel. We then use numerical simulation to demonstrate robust programmability of a quantum switch via the OpenFlow network controller while executing an application of superdense coding. We describe the software framework implemented to carry out these simulations and we discuss near-term efforts to realize these applications.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

Science.gov (United States)

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

Modeling activity recognition of multi resident using label combination of multi label classification in smart home

Science.gov (United States)

Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah

2017-10-01

Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.

Multi-core processing and scheduling performance in CMS

International Nuclear Information System (INIS)

Hernández, J M; Evans, D; Foulkes, S

2012-01-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resulting in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.

Research on TCP/IP network communication based on Node.js

Science.gov (United States)

Huang, Jing; Cai, Lixiong

2018-04-01

In the face of big data, long connection and high synchronization, TCP/IP network communication will cause performance bottlenecks due to its blocking multi-threading service model. This paper presents a method of TCP/IP network communication protocol based on Node.js. On the basis of analyzing the characteristics of Node.js architecture and asynchronous non-blocking I/O model, the principle of its efficiency is discussed, and then compare and analyze the network communication model of TCP/IP protocol to expound the reasons why TCP/IP protocol stack is widely used in network communication. Finally, according to the large data and high concurrency in the large-scale grape growing environment monitoring process, a TCP server design based on Node.js is completed. The results show that the example runs stably and efficiently.

Improved hydrogen combustion model for multi-compartment analysis

International Nuclear Information System (INIS)

Ogino, Masao; Hashimoto, Takashi

2000-01-01

NUPEC has been improving a hydrogen combustion model in MELCOR code for severe accident analysis. In the proposed combustion model, the flame velocity in a node was predicted using six different flame front shapes of fireball, prism, bubble, spherical jet, plane jet, and parallelepiped. A verification study of the proposed model was carried out using the NUPEC large-scale combustion test results following the previous work in which the GRS/Battelle multi-compartment combustion test results had been used. The selected test cases for the study were the premixed test and the scenario-oriented test which simulated the severe accident sequences of an actual plant. The improved MELCOR code replaced by the proposed model could predict sufficiently both results of the premixed test and the scenario-oriented test of NUPEC large-scale test. The improved MELCOR code was confirmed to simulate the combustion behavior in the multi-compartment containment vessel during a severe accident with acceptable degree of accuracy. Application of the new model to the LWR severe accident analysis will be continued. (author)

A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids

International Nuclear Information System (INIS)

Mashayekh, Salman; Stadler, Michael; Cardoso, Gonçalo; Heleno, Miguel

2017-01-01

Highlights: • This paper presents a MILP model for optimal design of multi-energy microgrids. • Our microgrid design includes optimal technology portfolio, placement, and operation. • Our model includes microgrid electrical power flow and heat transfer equations. • The case study shows advantages of our model over aggregate single-node approaches. • The case study shows the accuracy of the integrated linearized power flow model. - Abstract: Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs.

An evaluation of the multi-state node networks reliability using the traditional binary-state networks reliability algorithm

International Nuclear Information System (INIS)

Yeh, W.-C.

2003-01-01

A system where the components and system itself are allowed to have a number of performance levels is called the Multi-state system (MSS). A multi-state node network (MNN) is a generalization of the MSS without satisfying the flow conservation law. Evaluating the MNN reliability arises at the design and exploitation stage of many types of technical systems. Up to now, the known existing methods can only evaluate a special MNN reliability called the multi-state node acyclic network (MNAN) in which no cyclic is allowed. However, no method exists for evaluating the general MNN reliability. The main purpose of this article is to show first that each MNN reliability can be solved using any the traditional binary-state networks (TBSN) reliability algorithm with a special code for the state probability. A simple heuristic SDP algorithm based on minimal cuts (MC) for estimating the MNN reliability is presented as an example to show how the TBSN reliability algorithm is revised to solve the MNN reliability problem. To the author's knowledge, this study is the first to discuss the relationships between MNN and TBSN and also the first to present methods to solve the exact and approximated MNN reliability. One example is illustrated to show how the exact MNN reliability is obtained using the proposed algorithm

Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support.

Science.gov (United States)

Rosário, Denis; Schimuneck, Matias; Camargo, João; Nobre, Jéferson; Both, Cristiano; Rochol, Juergen; Gerla, Mario

2018-01-24

A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends.

Multi-hop localization algorithm based on grid-scanning for wireless sensor networks.

Science.gov (United States)

Wan, Jiangwen; Guo, Xiaolei; Yu, Ning; Wu, Yinfeng; Feng, Renjian

2011-01-01

For large-scale wireless sensor networks (WSNs) with a minority of anchor nodes, multi-hop localization is a popular scheme for determining the geographical positions of the normal nodes. However, in practice existing multi-hop localization methods suffer from various kinds of problems, such as poor adaptability to irregular topology, high computational complexity, low positioning accuracy, etc. To address these issues in this paper, we propose a novel Multi-hop Localization algorithm based on Grid-Scanning (MLGS). First, the factors that influence the multi-hop distance estimation are studied and a more realistic multi-hop localization model is constructed. Then, the feasible regions of the normal nodes are determined according to the intersection of bounding square rings. Finally, a verifiably good approximation scheme based on grid-scanning is developed to estimate the coordinates of the normal nodes. Additionally, the positioning accuracy of the normal nodes can be improved through neighbors' collaboration. Extensive simulations are performed in isotropic and anisotropic networks. The comparisons with some typical algorithms of node localization confirm the effectiveness and efficiency of our algorithm.

Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy

Directory of Open Access Journals (Sweden)

Changsheng Zhu

2018-03-01

Full Text Available In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.

Open Software Tools Applied to Jordan's National Multi-Agent Water Management Model

Science.gov (United States)

Knox, Stephen; Meier, Philipp; Harou, Julien; Yoon, Jim; Selby, Philip; Lachaut, Thibaut; Klassert, Christian; Avisse, Nicolas; Khadem, Majed; Tilmant, Amaury; Gorelick, Steven

2016-04-01

Jordan is the fourth most water scarce country in the world, where demand exceeds supply in a politically and demographically unstable context. The Jordan Water Project (JWP) aims to perform policy evaluation by modelling the hydrology, economics, and governance of Jordan's water resource system. The multidisciplinary nature of the project requires a modelling software system capable of integrating submodels from multiple disciplines into a single decision making process and communicating results to stakeholders. This requires a tool for building an integrated model and a system where diverse data sets can be managed and visualised. The integrated Jordan model is built using Pynsim, an open-source multi-agent simulation framework implemented in Python. Pynsim operates on network structures of nodes and links and supports institutional hierarchies, where an institution represents a grouping of nodes, links or other institutions. At each time step, code within each node, link and institution can executed independently, allowing for their fully autonomous behaviour. Additionally, engines (sub-models) perform actions over the entire network or on a subset of the network, such as taking a decision on a set of nodes. Pynsim is modular in design, allowing distinct modules to be modified easily without affecting others. Data management and visualisation is performed using Hydra (www.hydraplatform.org), an open software platform allowing users to manage network structure and data. The Hydra data manager connects to Pynsim, providing necessary input parameters for the integrated model. By providing a high-level portal to the model, Hydra removes a barrier between the users of the model (researchers, stakeholders, planners etc) and the model itself, allowing them to manage data, run the model and visualise results all through a single user interface. Pynsim's ability to represent institutional hierarchies, inter-network communication and the separation of node, link and

A Performance-Prediction Model for PIC Applications on Clusters of Symmetric MultiProcessors: Validation with Hierarchical HPF+OpenMP Implementation

Directory of Open Access Journals (Sweden)

Sergio Briguglio

2003-01-01

Full Text Available A performance-prediction model is presented, which describes different hierarchical workload decomposition strategies for particle in cell (PIC codes on Clusters of Symmetric MultiProcessors. The devised workload decomposition is hierarchically structured: a higher-level decomposition among the computational nodes, and a lower-level one among the processors of each computational node. Several decomposition strategies are evaluated by means of the prediction model, with respect to the memory occupancy, the parallelization efficiency and the required programming effort. Such strategies have been implemented by integrating the high-level languages High Performance Fortran (at the inter-node stage and OpenMP (at the intra-node one. The details of these implementations are presented, and the experimental values of parallelization efficiency are compared with the predicted results.

Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry

International Nuclear Information System (INIS)

Lee, Choonsik; Lamart, Stephanie; Moroz, Brian E

2013-01-01

We developed models of lymphatic nodes for six pediatric and two adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right) and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in six lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for

A Hybrid Double-Layer Master-Slave Model For Multicore-Node Clusters

International Nuclear Information System (INIS)

Liu Gang; Schmider, Hartmut; Edgecombe, Kenneth E

2012-01-01

The Double-Layer Master-Slave Model (DMSM) is a suitable hybrid model for executing a workload that consists of multiple independent tasks of varying length on a cluster consisting of multicore nodes. In this model, groups of individual tasks are first deployed to the cluster nodes through an MPI based Master-Slave model. Then, each group is processed by multiple threads on the node through an OpenMP based All-Slave approach. The lack of thread safety of most MPI libraries has to be addressed by a judicious use of OpenMP critical regions and locks. The HPCVL DMSM Library implements this model in Fortran and C. It requires a minimum of user input to set up the framework for the model and to define the individual tasks. Optionally, it supports the dynamic distribution of task-related data and the collection of results at runtime. This library is freely available as source code. Here, we outline the working principles of the library and on a few examples demonstrate its capability to efficiently distribute a workload on a distributed-memory cluster with shared-memory nodes.

Biothermal conditions on Mt. Zlatibor based on thermophysiological indices

Directory of Open Access Journals (Sweden)

Pecelj Milica

2017-01-01

Full Text Available This paper presents part of the research in the field of human bioclimatology and refers to biothermal conditions in different geographical environments in Serbia: an urban area and a mountain of medium height. The goal of the paper was to show bioclimatic differences during the summer between the city of Belgrade (116 m a.s.l. and the mountain resort of Zlatibor (1498 m a.s.l.. The basic principle of bioclimatic analysis is the human heat balance between man and environment. This methodological approach is a combination of physiological and meteorological parameters that result in thermophysiological bioclimatic indices: heat load (HL in man and the Universal Thermal Climate Index (UTCI. For this analysis, weather data for July, as the warmest month, was obtained, using daily meteorological data for the decade from 2000 to 2010. Results for July indicate a considerable difference between the two abovementioned environments. HL in Belgrade was dominated by degrees of comfort “hot” and “extremely hot, with the highest value of 4.540, while for Zlatibor the dominant degree of comfort was “warm”. The UTCI in Belgrade has dominated by strong heat stress and moderate heat stress, compared to Zlatibor where the UTCI is dominated by moderate heat stress. In addition, a significant part of the monitored decade on Mt. Zlatibor was without heat stress, with the exception of 2006 and 2007, indicating favorable biothermal characteristics. Therefore, compared to Belgrade, with its considerably lower overall heat stress Zlatibor has the characteristics of a site with favorable bioclimatic qualities.

Target Control in Logical Models Using the Domain of Influence of Nodes.

Science.gov (United States)

Yang, Gang; Gómez Tejeda Zañudo, Jorge; Albert, Réka

2018-01-01

Dynamical models of biomolecular networks are successfully used to understand the mechanisms underlying complex diseases and to design therapeutic strategies. Network control and its special case of target control, is a promising avenue toward developing disease therapies. In target control it is assumed that a small subset of nodes is most relevant to the system's state and the goal is to drive the target nodes into their desired states. An example of target control would be driving a cell to commit to apoptosis (programmed cell death). From the experimental perspective, gene knockout, pharmacological inhibition of proteins, and providing sustained external signals are among practical intervention techniques. We identify methodologies to use the stabilizing effect of sustained interventions for target control in Boolean network models of biomolecular networks. Specifically, we define the domain of influence (DOI) of a node (in a certain state) to be the nodes (and their corresponding states) that will be ultimately stabilized by the sustained state of this node regardless of the initial state of the system. We also define the related concept of the logical domain of influence (LDOI) of a node, and develop an algorithm for its identification using an auxiliary network that incorporates the regulatory logic. This way a solution to the target control problem is a set of nodes whose DOI can cover the desired target node states. We perform greedy randomized adaptive search in node state space to find such solutions. We apply our strategy to in silico biological network models of real systems to demonstrate its effectiveness.

Multi-Source Energy Harvesting for Wireless Sensor Nodes.

OpenAIRE

Kang, Kai

2012-01-01

The past few years have seen an increasing interest in the development of wireless sensor networks. But the unsatisfactory or limited available energy source is one of the major bottlenecks which are limiting the wireless sensor technology from mass deployment. Ambient energy harvesting is the most promising solution towards autonomous sensor nodes by providing low cost, permanent, and maintenance-free energy source to wireless sensor nodes. In this paper, we first invested available energy s...

An algorithm for merging part nodes of JT models exported by FORAN

Directory of Open Access Journals (Sweden)

FANG Xiongbing

2017-05-01

Full Text Available Many cognominal parts exist in JT models exported by FORAN V70 R2.0 software, and this leads to an increase in time consumption and the space analysis results becoming hard to process when using clearance analysis software to perform distance computing for such JT models. Aiming at this problem, an algorithm for merging component nodes is put forward based on investigating the assembly configuration and inherent information (i.e. geometric and material information of JT models created by FORAN. The method is composed of four steps:coordinate transformation, model node renaming, node geometric data transferring and material attribute processing. Finally, the proposed method is implemented by C++ and JT Open Toolkit. The results show that the new JT models generated by the proposed method are comprised of only one assembly node, and they preserve the intrinsic information of the original JT models. Its validity is illustrated by a great deal of examples, and the content of the worked JT models are reduced by about 7% to 20%.

A mathematical prediction model incorporating molecular subtype for risk of non-sentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients: a retrospective analysis and nomogram development.

Science.gov (United States)

Wang, Na-Na; Yang, Zheng-Jun; Wang, Xue; Chen, Li-Xuan; Zhao, Hong-Meng; Cao, Wen-Feng; Zhang, Bin

2018-04-25

Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort. We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort. Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025-2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111-23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714-3.892; P model based on the results of multivariate analysis was established to predict the risk of non

Multi-attribute integrated measurement of node importance in complex networks.

Science.gov (United States)

Wang, Shibo; Zhao, Jinlou

2015-11-01

The measure of node importance in complex networks is very important to the research of networks stability and robustness; it also can ensure the security of the whole network. Most researchers have used a single indicator to measure the networks node importance, so that the obtained measurement results only reflect certain aspects of the networks with a loss of information. Meanwhile, because of the difference of networks topology, the nodes' importance should be described by combining the character of the networks topology. Most of the existing evaluation algorithms cannot completely reflect the circumstances of complex networks, so this paper takes into account the degree of centrality, the relative closeness centrality, clustering coefficient, and topology potential and raises an integrated measuring method to measure the nodes' importance. This method can reflect nodes' internal and outside attributes and eliminate the influence of network structure on the node importance. The experiments of karate network and dolphin network show that networks topology structure integrated measure has smaller range of metrical result than a single indicator and more universal. Experiments show that attacking the North American power grid and the Internet network with the method has a faster convergence speed than other methods.

Isotopic ordering in eggshells reflects body temperatures and suggests differing thermophysiology in two Cretaceous dinosaurs

Science.gov (United States)

Eagle, Robert A.; Enriquez, Marcus; Grellet-Tinner, Gerald; Pérez-Huerta, Alberto; Hu, David; Tütken, Thomas; Montanari, Shaena; Loyd, Sean J.; Ramirez, Pedro; Tripati, Aradhna K.; Kohn, Matthew J.; Cerling, Thure E.; Chiappe, Luis M.; Eiler, John M.

2015-10-01

Our understanding of the evolutionary transitions leading to the modern endothermic state of birds and mammals is incomplete, partly because tools available to study the thermophysiology of extinct vertebrates are limited. Here we show that clumped isotope analysis of eggshells can be used to determine body temperatures of females during periods of ovulation. Late Cretaceous titanosaurid eggshells yield temperatures similar to large modern endotherms. In contrast, oviraptorid eggshells yield temperatures lower than most modern endotherms but ~6 °C higher than co-occurring abiogenic carbonates, implying that this taxon did not have thermoregulation comparable to modern birds, but was able to elevate its body temperature above environmental temperatures. Therefore, we observe no strong evidence for end-member ectothermy or endothermy in the species examined. Body temperatures for these two species indicate that variable thermoregulation likely existed among the non-avian dinosaurs and that not all dinosaurs had body temperatures in the range of that seen in modern birds.

Isotopic ordering in eggshells reflects body temperatures and suggests differing thermophysiology in two Cretaceous dinosaurs.

Science.gov (United States)

Eagle, Robert A; Enriquez, Marcus; Grellet-Tinner, Gerald; Pérez-Huerta, Alberto; Hu, David; Tütken, Thomas; Montanari, Shaena; Loyd, Sean J; Ramirez, Pedro; Tripati, Aradhna K; Kohn, Matthew J; Cerling, Thure E; Chiappe, Luis M; Eiler, John M

2015-10-13

Our understanding of the evolutionary transitions leading to the modern endothermic state of birds and mammals is incomplete, partly because tools available to study the thermophysiology of extinct vertebrates are limited. Here we show that clumped isotope analysis of eggshells can be used to determine body temperatures of females during periods of ovulation. Late Cretaceous titanosaurid eggshells yield temperatures similar to large modern endotherms. In contrast, oviraptorid eggshells yield temperatures lower than most modern endotherms but ∼ 6 °C higher than co-occurring abiogenic carbonates, implying that this taxon did not have thermoregulation comparable to modern birds, but was able to elevate its body temperature above environmental temperatures. Therefore, we observe no strong evidence for end-member ectothermy or endothermy in the species examined. Body temperatures for these two species indicate that variable thermoregulation likely existed among the non-avian dinosaurs and that not all dinosaurs had body temperatures in the range of that seen in modern birds.

Immunolymphoscintigraphy for metastatic sentinel nodes: test of a model

DEFF Research Database (Denmark)

Chakera, A H; Nielsen, B S; Madsen, J

2011-01-01

Aim. To develop a method and obtain proof-of-principle for immunolymphoscintigraphy for identification of metastatic sentinel nodes. Methods. We selected one of four tumour-specific antibodies against human breast cancer and investigated (1), in immune-deficient (nude) mice with xenograft human b...... in healthy rabbits. Results and Conclusion. Our paper suggests the theoretical possibility of a model of dual isotope immuno-lymphoscintigraphy for noninvasive, preoperative, malignant sentinel node imaging....

Chimera states in multi-strain epidemic models with temporary immunity

Science.gov (United States)

Bauer, Larissa; Bassett, Jason; Hövel, Philipp; Kyrychko, Yuliya N.; Blyuss, Konstantin B.

2017-11-01

We investigate a time-delayed epidemic model for multi-strain diseases with temporary immunity. In the absence of cross-immunity between strains, dynamics of each individual strain exhibit emergence and annihilation of limit cycles due to a Hopf bifurcation of the endemic equilibrium, and a saddle-node bifurcation of limit cycles depending on the time delay associated with duration of temporary immunity. Effects of all-to-all and non-local coupling topologies are systematically investigated by means of numerical simulations, and they suggest that cross-immunity is able to induce a diverse range of complex dynamical behaviors and synchronization patterns, including discrete traveling waves, solitary states, and amplitude chimeras. Interestingly, chimera states are observed for narrower cross-immunity kernels, which can have profound implications for understanding the dynamics of multi-strain diseases.

Anomalous thermoelectric phenomena in lattice models of multi-Weyl semimetals

Science.gov (United States)

Gorbar, E. V.; Miransky, V. A.; Shovkovy, I. A.; Sukhachov, P. O.

2017-10-01

The thermoelectric transport coefficients are calculated in a generic lattice model of multi-Weyl semimetals with a broken time-reversal symmetry by using the Kubo's linear response theory. The contributions connected with the Berry curvature-induced electromagnetic orbital and heat magnetizations are systematically taken into account. It is shown that the thermoelectric transport is profoundly affected by the nontrivial topology of multi-Weyl semimetals. In particular, the calculation reveals a number of thermal coefficients of the topological origin which describe the anomalous Nernst and thermal Hall effects in the absence of background magnetic fields. Similarly to the anomalous Hall effect, all anomalous thermoelectric coefficients are proportional to the integer topological charge of the Weyl nodes. The dependence of the thermoelectric coefficients on the chemical potential and temperature is also studied.

High-resolution simulations of the thermophysiological effects of human exposure to 100 MHz RF energy

International Nuclear Information System (INIS)

Nelson, David A; Curran, Allen R; Nyberg, Hans A; Marttila, Eric A; Mason, Patrick A; Ziriax, John M

2013-01-01

Human exposure to radio frequency (RF) electromagnetic energy is known to result in tissue heating and can raise temperatures substantially in some situations. Standards for safe exposure to RF do not reflect bio-heat transfer considerations however. Thermoregulatory function (vasodilation, sweating) may mitigate RF heating effects in some environments and exposure scenarios. Conversely, a combination of an extreme environment (high temperature, high humidity), high activity levels and thermally insulating garments may exacerbate RF exposure and pose a risk of unsafe temperature elevation, even for power densities which might be acceptable in a normothermic environment. A high-resolution thermophysiological model, incorporating a heterogeneous tissue model of a seated adult has been developed and used to replicate a series of whole-body exposures at a frequency (100 MHz) which approximates that of human whole-body resonance. Exposures were simulated at three power densities (4, 6 and 8 mW cm −2 ) plus a sham exposure and at three different ambient temperatures (24, 28 and 31 °C). The maximum hypothalamic temperature increase over the course of a 45 min exposure was 0.28 °C and occurred in the most extreme conditions (T amb = 31 °C, PD = 8 mW cm −2 ). Skin temperature increases attributable to RF exposure were modest, with the exception of a ‘hot spot’ in the vicinity of the ankle where skin temperatures exceeded 39 °C. Temperature increases in internal organs and tissues were small, except for connective tissue and bone in the lower leg and foot. Temperature elevation also was noted in the spinal cord, consistent with a hot spot previously identified in the literature. (paper)

High performance MRI simulations of motion on multi-GPU systems.

Science.gov (United States)

Xanthis, Christos G; Venetis, Ioannis E; Aletras, Anthony H

2014-07-04

MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance multi-GPU environment. Three different motion models were introduced in the Magnetic Resonance Imaging SIMULator (MRISIMUL) of this study: cardiac motion, respiratory motion and flow. Simulation of a simple Gradient Echo pulse sequence and a CINE pulse sequence on the corresponding anatomical model was performed. Myocardial tagging was also investigated. In pulse sequence design, software crushers were introduced to accommodate the long execution times in order to avoid spurious echoes formation. The displacement of the anatomical model isochromats was calculated within the Graphics Processing Unit (GPU) kernel for every timestep of the pulse sequence. Experiments that would allow simulation of custom anatomical and motion models were also performed. Last, simulations of motion with MRISIMUL on single-node and multi-node multi-GPU systems were examined. Gradient Echo and CINE images of the three motion models were produced and motion-related artifacts were demonstrated. The temporal evolution of the contractility of the heart was presented through the application of myocardial tagging. Better simulation performance and image quality were presented through the introduction of software crushers without the need to further increase the computational load and GPU resources. Last, MRISIMUL demonstrated an almost linear scalable performance with the increasing number of available GPU cards, in both single-node and multi-node multi-GPU computer systems. MRISIMUL is the first MR physics simulator to have implemented motion with a 3D large computational load on a single computer multi-GPU configuration. The incorporation

Coexisting chaotic and multi-periodic dynamics in a model of cardiac alternans

Energy Technology Data Exchange (ETDEWEB)

Skardal, Per Sebastian, E-mail: skardals@gmail.com [Departament d' Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona (Spain); Restrepo, Juan G., E-mail: juanga@colorado.edu [Department of Applied Mathematics, University of Colorado, Boulder, Colorado 80309 (United States)

2014-12-15

The spatiotemporal dynamics of cardiac tissue is an active area of research for biologists, physicists, and mathematicians. Of particular interest is the study of period-doubling bifurcations and chaos due to their link with cardiac arrhythmogenesis. In this paper, we study the spatiotemporal dynamics of a recently developed model for calcium-driven alternans in a one dimensional cable of tissue. In particular, we observe in the cable coexistence of regions with chaotic and multi-periodic dynamics over wide ranges of parameters. We study these dynamics using global and local Lyapunov exponents and spatial trajectory correlations. Interestingly, near nodes—or phase reversals—low-periodic dynamics prevail, while away from the nodes, the dynamics tend to be higher-periodic and eventually chaotic. Finally, we show that similar coexisting multi-periodic and chaotic dynamics can also be observed in a detailed ionic model.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

Science.gov (United States)

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

The Universal Thermal Climate Index UTCI compared to ergonomics standards for assessing the thermal environment.

Science.gov (United States)

Bröde, Peter; Błazejczyk, Krzysztof; Fiala, Dusan; Havenith, George; Holmér, Ingvar; Jendritzky, Gerd; Kuklane, Kalev; Kampmann, Bernhard

2013-01-01

The growing need for valid assessment procedures of the outdoor thermal environment in the fields of public weather services, public health systems, urban planning, tourism & recreation and climate impact research raised the idea to develop the Universal Thermal Climate Index UTCI based on the most recent scientific progress both in thermo-physiology and in heat exchange theory. Following extensive validation of accessible models of human thermoregulation, the advanced multi-node 'Fiala' model was selected to form the basis of UTCI. This model was coupled with an adaptive clothing model which considers clothing habits by the general urban population and behavioral changes in clothing insulation related to actual environmental temperature. UTCI was developed conceptually as an equivalent temperature. Thus, for any combination of air temperature, wind, radiation, and humidity, UTCI is defined as the air temperature in the reference condition which would elicit the same dynamic response of the physiological model. This review analyses the sensitivity of UTCI to humidity and radiation in the heat and to wind in the cold and compares the results with observational studies and internationally standardized assessment procedures. The capabilities, restrictions and potential future extensions of UTCI are discussed.

A comprehensive multi-local-world model for complex networks

International Nuclear Information System (INIS)

Fan Zhengping; Chen Guanrong; Zhang Yunong

2009-01-01

The nodes in a community within a network are much more connected to each other than to the others outside the community in the same network. This phenomenon has been commonly observed from many real-world networks, ranging from social to biological even to technical networks. Meanwhile, the number of communities in some real-world networks, such as the Internet and most social networks, are evolving with time. To model this kind of networks, the present Letter proposes a multi-local-world (MLW) model to capture and describe their essential topological properties. Based on the mean-field theory, the degree distribution of this model is obtained analytically, showing that the generated network has a novel topological feature as being not completely random nor completely scale-free but behaving somewhere between them. As a typical application, the MLW model is applied to characterize the Internet against some other models such as the BA, GBA, Fitness and HOT models, demonstrating the superiority of the new model.

Algorithm for queueing networks with multi-rate traffic

DEFF Research Database (Denmark)

Iversen, Villy Bæk; Ko, King-Tim

2011-01-01

the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolution algorithm to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate......In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... of queueing networks in general, presumes that we have product form between the nodes. Otherwise, we have the state space explosion. Even so, the detailed state space of each node may become very large because there is no product form between chains inside a node. A prerequisite for product form...

Three essays on multi-level optimization models and applications

Science.gov (United States)

Rahdar, Mohammad

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation

Algorithm for queueing networks with multi-rate traffic

DEFF Research Database (Denmark)

Iversen, Villy Bæk; King-Tim, Ko

2011-01-01

the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolutions to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate the detailed......In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... of queueing networks in general presumes that we have product form between the nodes. Other ways we have the state space explosion. Even so the detailed state space of each node may easily become very large because there is no product form between chains inside a node. A prerequisite for product form...

phylo-node: A molecular phylogenetic toolkit using Node.js.

Science.gov (United States)

O'Halloran, Damien M

2017-01-01

Node.js is an open-source and cross-platform environment that provides a JavaScript codebase for back-end server-side applications. JavaScript has been used to develop very fast and user-friendly front-end tools for bioinformatic and phylogenetic analyses. However, no such toolkits are available using Node.js to conduct comprehensive molecular phylogenetic analysis. To address this problem, I have developed, phylo-node, which was developed using Node.js and provides a stable and scalable toolkit that allows the user to perform diverse molecular and phylogenetic tasks. phylo-node can execute the analysis and process the resulting outputs from a suite of software options that provides tools for read processing and genome alignment, sequence retrieval, multiple sequence alignment, primer design, evolutionary modeling, and phylogeny reconstruction. Furthermore, phylo-node enables the user to deploy server dependent applications, and also provides simple integration and interoperation with other Node modules and languages using Node inheritance patterns, and a customized piping module to support the production of diverse pipelines. phylo-node is open-source and freely available to all users without sign-up or login requirements. All source code and user guidelines are openly available at the GitHub repository: https://github.com/dohalloran/phylo-node.

Reliability evaluation of linear multi-state consecutively-connected systems constrained by m consecutive and n total gaps

International Nuclear Information System (INIS)

Yu, Huan; Yang, Jun; Peng, Rui; Zhao, Yu

2016-01-01

This paper extends the linear multi-state consecutively-connected system (LMCCS) to the case of LMCCS-MN, where MN denotes the dual constraints of m consecutive gaps and n total gaps. All the nodes are distributed along a line and form a sequence. The distances between the adjacent nodes are usually non-uniform. The nodes except the last one can contain statistically independent multi-state connection elements (MCEs). Each MCE can provide a connection between the node at which it is located and the next nodes along the sequence. The LMCCS-MN fails if it meets either of the two constraints. The universal generating function technique is adopted to evaluate the system reliability. The optimal allocations of LMCCS-MN with two different types of failures are solved by genetic algorithm. Finally, two examples are given for the demonstration of the proposed model. - Highlights: • A new model of multi-state consecutively-connected system (LMCCS-MN) is proposed. • The non-uniform distributed nodes are involved in the proposed LMCCS-MN model. • An algorithm for system reliability evaluation is provided by the UGF method. • The computational complexity of the proposed algorithm is discussed in detail. • Optimal element allocation problem is formulated and solved.

Node localization algorithm of wireless sensor networks for large electrical equipment monitoring application

DEFF Research Database (Denmark)

Chen, Qinyin; Hu, Y.; Chen, Zhe

2016-01-01

Node localization technology is an important technology for the Wireless Sensor Networks (WSNs) applications. An improved 3D node localization algorithm is proposed in this paper, which is based on a Multi-dimensional Scaling (MDS) node localization algorithm for large electrical equipment monito...

Neural node network and model, and method of teaching same

Science.gov (United States)

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

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.

Learning and inference in a nonequilibrium Ising model with hidden nodes.

Science.gov (United States)

Dunn, Benjamin; Roudi, Yasser

2013-02-01

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations of the hidden ones. This, as we show, can be represented as a path integral. Using this representation, we demonstrate that systematic approximate inference and learning rules can be derived using dynamical mean-field theory. Although naive mean-field theory leads to an unstable learning rule, taking into account Gaussian corrections allows learning the couplings involving hidden nodes. It also improves learning of the couplings between the observed nodes compared to when hidden nodes are ignored.

Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC

Directory of Open Access Journals (Sweden)

Xiangyu Li

2017-02-01

Full Text Available This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430, and that it can make a system do more valuable works and make more than 99.9% use of the power budget.

The vascularized groin lymph node flap (VGLN): Anatomical study and flap planning using multi-detector CT scanner. The golden triangle for flap harvesting.

Science.gov (United States)

Zeltzer, Assaf A; Anzarut, Alexander; Braeckmans, Delphine; Seidenstuecker, Katrin; Hendrickx, Benoit; Van Hedent, Eddy; Hamdi, Moustapha

2017-09-01

A growing number of surgeons perform lymph node transfers for the treatment of lymphedema. When harvesting a vascularized lymph node groin flap (VGLNF) one of the major concerns is the potential risk of iatrogenic lymphedema of the donor-site. This article helps understanding of the lymph node distribution of the groin in order to minimize this risk. Fifty consecutive patients undergoing abdominal mapping by multi-detector CT scanner were included and 100 groins analyzed. The groin was divided in three zones (of which zone II is the safe zone) and lymph nodes were counted and mapped with their distances to anatomic landmarks. Further node units were plotted and counted. The average age was 48 years. A mean number of nodes of 6.5/groin was found. In zone II, which is our zone of interest a mean of 3.1 nodes were counted with a mean size of 7.8 mm. In three patients no nodes were found in zone II. In five patients nodes were seen in zone II but were not sufficient in size or number to be considered a lymph node unit. On average the lymph node unit in zone II was found to be 48.3 mm from the pubic tubercle when projected on a line from the pubic tubercle to the anterior superior iliac spine, 16.0 mm caudal to this line, and 20.4 mm above the groin crease. On average the lymph node unit was a mean of 41.7 mm lateral to the SCIV-SIEV confluence. This study provides increased understanding of the lymphatic anatomy in zone II of the groin flap and suggests a refined technique for designing the VGLNF. As with any flap there is a degree of individual patient variability. However, having information on the most common anatomy and flap design is of great value. © 2017 Wiley Periodicals, Inc.

A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

Directory of Open Access Journals (Sweden)

Mohammad Mozumdar

2014-06-01

Full Text Available The Model Based Design (MBD approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL simulation.

Live and Dead Nodes

DEFF Research Database (Denmark)

Jørgensen, Sune Lehman; Jackson, A. D.

2005-01-01

In this paper, we explore the consequences of a distinction between `live' and `dead' network nodes; `live' nodes are able to acquire new links whereas `dead' nodes are static. We develop an analytically soluble growing network model incorporating this distinction and show that it can provide...

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-01-01

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive

Backoff-stage synchronization in three-hop string-topology wireless networks with hidden nodes

Science.gov (United States)

Sanada, Kosuke; Sekiya, Hiroo; Komuro, Nobuyoshi; Sakata, Shiro

In IEEE 802.11 wireless multi-hop networks, each node works individually and their individual operations generate entire network dynamics. It is important to clarify the network dynamics in wireless multi-hop networks for designing and constructing multi-hop communication networks. This paper presents the network-dynamics investigations for three-hop string-topology wireless network in detail. From the investigations, a “backoff-stage synchronization” phenomenon, which is mutuality between hidden nodes, is found. The mechanism of the backoff-stage synchronization is expressed and the sufficient conditions for the synchronization occurrence are given. This phenomenon gives some impacts on the IEEE 802.11 multi-hop-network communications.

Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

Energy Technology Data Exchange (ETDEWEB)

Wolfe, Noah; Carothers, Christopher; Mubarak, Misbah; Ross, Robert; Carns, Philip

2016-05-15

As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the model size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.

Model-based MPC enables curvilinear ILT using either VSB or multi-beam mask writers

Science.gov (United States)

Pang, Linyong; Takatsukasa, Yutetsu; Hara, Daisuke; Pomerantsev, Michael; Su, Bo; Fujimura, Aki

2017-07-01

Inverse Lithography Technology (ILT) is becoming the choice for Optical Proximity Correction (OPC) of advanced technology nodes in IC design and production. Multi-beam mask writers promise significant mask writing time reduction for complex ILT style masks. Before multi-beam mask writers become the main stream working tools in mask production, VSB writers will continue to be the tool of choice to write both curvilinear ILT and Manhattanized ILT masks. To enable VSB mask writers for complex ILT style masks, model-based mask process correction (MB-MPC) is required to do the following: 1). Make reasonable corrections for complex edges for those features that exhibit relatively large deviations from both curvilinear ILT and Manhattanized ILT designs. 2). Control and manage both Edge Placement Errors (EPE) and shot count. 3. Assist in easing the migration to future multi-beam mask writer and serve as an effective backup solution during the transition. In this paper, a solution meeting all those requirements, MB-MPC with GPU acceleration, will be presented. One model calibration per process allows accurate correction regardless of the target mask writer.

An IEEE 802.11 EDCA Model with Support for Analysing Networks with Misbehaving Nodes

Directory of Open Access Journals (Sweden)

Szott Szymon

2010-01-01

Full Text Available We present a novel model of IEEE 802.11 EDCA with support for analysing networks with misbehaving nodes. In particular, we consider backoff misbehaviour. Firstly, we verify the model by extensive simulation analysis and by comparing it to three other IEEE 802.11 models. The results show that our model behaves satisfactorily and outperforms other widely acknowledged models. Secondly, a comparison with simulation results in several scenarios with misbehaving nodes proves that our model performs correctly for these scenarios. The proposed model can, therefore, be considered as an original contribution to the area of EDCA models and backoff misbehaviour.

Tetrahedral node for Transmission-Line Modeling (TLM) applied to Bio-heat Transfer.

Science.gov (United States)

Milan, Hugo F M; Gebremedhin, Kifle G

2016-12-01

Transmission-Line Modeling (TLM) is a numerical method used to solve complex and time-domain bio-heat transfer problems. In TLM, parallelepipeds are used to discretize three-dimensional problems. The drawback in using parallelepiped shapes is that instead of refining only the domain of interest, a large additional domain would also have to be refined, which results in increased computational time and memory space. In this paper, we developed a tetrahedral node for TLM applied to bio-heat transfer that does not have the drawback associated with the parallelepiped node. The model includes heat source, blood perfusion, boundary conditions and initial conditions. The boundary conditions could be adiabatic, temperature, heat flux, or convection. The predicted temperature and heat flux were compared against results from an analytical solution and the results agreed within 2% for a mesh size of 69,941 nodes and a time step of 5ms. The method was further validated against published results of maximum skin-surface temperature difference in a breast with and without tumor and the results agreed within 6%. The published results were obtained from a model that used parallelepiped TLM node. An open source software, TLMBHT, was written using the theory developed herein and is available for download free-of-charge. Copyright © 2016 Elsevier Ltd. All rights reserved.

Subcarinal lymph node in upper lobe non-small cell lung cancer patients: is selective lymph node dissection valid?

Science.gov (United States)

Aokage, Keiju; Yoshida, Junji; Ishii, Genichiro; Hishida, Tomoyuki; Nishimura, Mitsuyo; Nagai, Kanji

2010-11-01

Little is known about selective lymph node dissection in non-small cell lung cancer (NSCLC) patients. We sought to gain insight into subcarinal node involvement for its frequency and impact on outcome to evaluate whether it is valid to omit subcarinal lymph node dissection in upper lobe NSCLC patients. We reviewed node metastases distribution according to node region, tumor location, and histology among 1099 patients with upper lobe NSCLC. We paid special attention to subcarinal metastases patients without superior mediastinal node metastases, because their pathological stages would have been underdiagnosed if subcarinal node dissection had been omitted. We also assessed the outcome and the pattern of failure among subcarinal metastases patients. To identify subcarinal node involvement predictors, we analyzed 7 clinical factors. Subcarinal node metastases were found in 20 patients and were least frequent among squamous cell carcinoma patients (0.5%). Two of them were free from superior mediastinal metastases but died of the disease at 1 month and due to an unknown cause at 18 months, respectively. Seventeen of the 20 patients developed multi-site recurrence within 37 months. The 5-year survival rate of the 20 patients with subcarinal metastases was 9.0%, which was significantly lower than 32.0% of patients with only superior mediastinal metastases. Clinical diagnosis of node metastases was significantly predictive of subcarinal metastases. Subcarinal node metastases from upper lobe NSCLC were rare and predicted an extremely poor outcome. It appears valid to omit subcarinal node dissection in upper lobe NSCLC patients, especially in clinical N0 squamous cell carcinoma patients. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Node-pair reliability of network systems with small distances between adjacent nodes

International Nuclear Information System (INIS)

Malinowski, Jacek

2007-01-01

A new method for computing the node-pair reliability of network systems modeled by random graphs with nodes arranged in sequence is presented. It is based on a recursive algorithm using the 'sliding window' technique, the window being composed of several consecutive nodes. In a single step, the connectivity probabilities for all nodes included in the window are found. Subsequently, the window is moved one node forward. This process is repeated until, in the last step, the window reaches the terminal node. The connectivity probabilities found at that point are used to compute the node-pair reliability of the network system considered. The algorithm is designed especially for graphs with small distances between adjacent nodes, where the distance between two nodes is defined as the absolute value of the difference between the nodes' numbers. The maximal distance between any two adjacent nodes is denoted by Γ(G), where G symbolizes a random graph. If Γ(G)=2 then the method can be applied for directed as well as undirected graphs whose nodes and edges are subject to failure. This is important in view of the fact that many algorithms computing network reliability are designed for graphs with failure-prone edges and reliable nodes. If Γ(G)=3 then the method's applicability is limited to undirected graphs with reliable nodes. The main asset of the presented algorithms is their low numerical complexity-O(n), where n denotes the number of nodes

Security for multi-hop wireless networks

CERN Document Server

Mahmoud, Mohamed M E A

2014-01-01

This Springer Brief discusses efficient security protocols and schemes for multi-hop wireless networks. It presents an overview of security requirements for these networks, explores challenges in securing networks and presents system models. The authors introduce mechanisms to reduce the overhead and identify malicious nodes that drop packets intentionally. Also included is a new, efficient cooperation incentive scheme to stimulate the selfish nodes to relay information packets and enforce fairness. Many examples are provided, along with predictions for future directions of the field. Security

Modeling Multi-Level Systems

CERN Document Server

Iordache, Octavian

2011-01-01

This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...

New Ghost-node method for linking different models with varied grid refinement

International Nuclear Information System (INIS)

Mehl, Steffen W.; Hill, Mary Catherine; James, Scott Carlton; Leake, Stanley A.; Zyvoloski, George A.; Dickinson, Jesse E.; Eddebbarh, Al A.

2006-01-01

A flexible, robust method for linking grids of locally refined models constructed with different numerical methods is needed to address a variety of hydrologic problems. This work outlines and tests a new ghost-node model-linking method for a refined 'child' model that is contained within a larger and coarser 'parent' model that is based on the iterative method of Mehl and Hill (2002, 2004). The method is applicable to steady-state solutions for ground-water flow. Tests are presented for a homogeneous two-dimensional system that has either matching grids (parent cells border an integer number of child cells; Figure 2a) or non-matching grids (parent cells border a non-integer number of child cells; Figure 2b). The coupled grids are simulated using the finite-difference and finite-element models MODFLOW and FEHM, respectively. The simulations require no alteration of the MODFLOW or FEHM models and are executed using a batch file on Windows operating systems. Results indicate that when the grids are matched spatially so that nodes and child cell boundaries are aligned, the new coupling technique has error nearly equal to that when coupling two MODFLOW models (Mehl and Hill, 2002). When the grids are non-matching, model accuracy is slightly increased over matching-grid cases. Overall, results indicate that the ghost-node technique is a viable means to accurately couple distinct models because the overall error is less than if only the regional model was used to simulate flow in the child model's domain

New ghost-node method for linking different models with varied grid refinement

Science.gov (United States)

James, S.C.; Dickinson, J.E.; Mehl, S.W.; Hill, M.C.; Leake, S.A.; Zyvoloski, G.A.; Eddebbarh, A.-A.

2006-01-01

A flexible, robust method for linking grids of locally refined ground-water flow models constructed with different numerical methods is needed to address a variety of hydrologic problems. This work outlines and tests a new ghost-node model-linking method for a refined "child" model that is contained within a larger and coarser "parent" model that is based on the iterative method of Steffen W. Mehl and Mary C. Hill (2002, Advances in Water Res., 25, p. 497-511; 2004, Advances in Water Res., 27, p. 899-912). The method is applicable to steady-state solutions for ground-water flow. Tests are presented for a homogeneous two-dimensional system that has matching grids (parent cells border an integer number of child cells) or nonmatching grids. The coupled grids are simulated by using the finite-difference and finite-element models MODFLOW and FEHM, respectively. The simulations require no alteration of the MODFLOW or FEHM models and are executed using a batch file on Windows operating systems. Results indicate that when the grids are matched spatially so that nodes and child-cell boundaries are aligned, the new coupling technique has error nearly equal to that when coupling two MODFLOW models. When the grids are nonmatching, model accuracy is slightly increased compared to that for matching-grid cases. Overall, results indicate that the ghost-node technique is a viable means to couple distinct models because the overall head and flow errors relative to the analytical solution are less than if only the regional coarse-grid model was used to simulate flow in the child model's domain.

Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models

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Matsumoto, Monica M. S.; Beig, Niha G.; Udupa, Jayaram K.; Archer, Steven; Torigian, Drew A.

2014-03-01

Lung cancer is associated with the highest cancer mortality rates among men and women in the United States. The accurate and precise identification of the lymph node stations on computed tomography (CT) images is important for staging disease and potentially for prognosticating outcome in patients with lung cancer, as well as for pretreatment planning and response assessment purposes. To facilitate a standard means of referring to lymph nodes, the International Association for the Study of Lung Cancer (IASLC) has recently proposed a definition of the different lymph node stations and zones in the thorax. However, nodal station identification is typically performed manually by visual assessment in clinical radiology. This approach leaves room for error due to the subjective and potentially ambiguous nature of visual interpretation, and is labor intensive. We present a method of automatically recognizing the mediastinal IASLC-defined lymph node stations by modifying a hierarchical fuzzy modeling approach previously developed for body-wide automatic anatomy recognition (AAR) in medical imagery. Our AAR-lymph node (AAR-LN) system follows the AAR methodology and consists of two steps. In the first step, the various lymph node stations are manually delineated on a set of CT images following the IASLC definitions. These delineations are then used to build a fuzzy hierarchical model of the nodal stations which are considered as 3D objects. In the second step, the stations are automatically located on any given CT image of the thorax by using the hierarchical fuzzy model and object recognition algorithms. Based on 23 data sets used for model building, 22 independent data sets for testing, and 10 lymph node stations, a mean localization accuracy of within 1-6 voxels has been achieved by the AAR-LN system.

Mathematical model of optimal empty rail car distribution at railway transport nodes

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Aleksandr RAKHMANGULOV

2014-09-01

Full Text Available At present there are two trends in the market of rail freight transportation in Russia: freight owners put forward higher demands to the transportation quality (promptness of delivery in an effort to reduce storage costs by means of reducing the size of freight shipment; the structure of railcar traffic volume of the railways of Russia is getting more complex due to the reduction of the average shipment size and due to the transfer of railcar fleet ownership to a large number of operating companies. These trends significantly complicate operational management supervision of railway stations and transport nodes. Application of typical data from the information system about the railcar location at the transportation node is not enough for the dispatchers to make the best decision concerning the car traffic management. The dispatcher traffic control service needs some software-based models of efficient railcar distribution. The article is concerned with the description and development of the mathematical model of empty railcar distribution for loading at the railway transport node; this model will take into account the requirements of railcar owners in terms of their cars application, the operating work level of railroad stations of the transportation node and the possibility of adding the groups of empty railcars to the transfer trains, clean-up trains and industrial railway trains operating on a tight schedule. The developed model and the software package were implemented in the information system of the industrial railway of the major metallurgical enterprise - OJSC «Magnitogorsk Metallurgical Works», which processes up to two thousand of railcars belonging to different owners. This model made it possible to reduce the labour intensity of dispatcher operation planning the empty railcar distribution for loading and reduce the total time the railcars spend in the enterprise railway system.

Distribution of shortest path lengths in a class of node duplication network models

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Steinbock, Chanania; Biham, Ofer; Katzav, Eytan

2017-09-01

We present analytical results for the distribution of shortest path lengths (DSPL) in a network growth model which evolves by node duplication (ND). The model captures essential properties of the structure and growth dynamics of social networks, acquaintance networks, and scientific citation networks, where duplication mechanisms play a major role. Starting from an initial seed network, at each time step a random node, referred to as a mother node, is selected for duplication. Its daughter node is added to the network, forming a link to the mother node, and with probability p to each one of its neighbors. The degree distribution of the resulting network turns out to follow a power-law distribution, thus the ND network is a scale-free network. To calculate the DSPL we derive a master equation for the time evolution of the probability Pt(L =ℓ ) , ℓ =1 ,2 ,⋯ , where L is the distance between a pair of nodes and t is the time. Finding an exact analytical solution of the master equation, we obtain a closed form expression for Pt(L =ℓ ) . The mean distance 〈L〉 t and the diameter Δt are found to scale like lnt , namely, the ND network is a small-world network. The variance of the DSPL is also found to scale like lnt . Interestingly, the mean distance and the diameter exhibit properties of a small-world network, rather than the ultrasmall-world network behavior observed in other scale-free networks, in which 〈L〉 t˜lnlnt .

Multi-Radio Mobile Device in Role of Hybrid Node Between WiFi and LTE networks

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Pavel Masek

2015-05-01

Full Text Available With the ubiquitous wireless network coverage, Machine-Type Communications (MTC is emerging to enable data transfers using devices/sensors without need for human interaction. In this paper we, we introduce a comprehensive simulation scenario for modeling and analysis for heterogeneous MTC. We demonstrate the most expected scenario of MTC communication using the IEEE 802.11 standard for direct communication between sensors and for transmitting data between individual sensor and Machine-Type Communication Gateway (MTCG. The MTCG represents the hybrid node serving as bridge between two heterogeneous networks (WiFi and LTE. Following the idea of hybrid node, two active interfaces must be implemented on this node together with mechanism for handling the incoming traffic (from WiFi network to LTE network. As a simulation tool, the Network Simulator 3 (NS-3 with implemented LTE/EPC Network Simulator (LENA framework was used. The major contribution of this paper therefore lies in the implementation of logic for interconnection of two heterogeneous networks in simulation environment NS-3.

Wireless Sensor Node for Autonomous Monitoring and Alerts in Remote Environments

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Monacos, Steve P. (Inventor); Panangadan, Anand V. (Inventor)

2015-01-01

A method, apparatus, system, and computer program products provides personal alert and tracking capabilities using one or more nodes. Each node includes radio transceiver chips operating at different frequency ranges, a power amplifier, sensors, a display, and embedded software. The chips enable the node to operate as either a mobile sensor node or a relay base station node while providing a long distance relay link between nodes. The power amplifier enables a line-of-sight communication between the one or more nodes. The sensors provide a GPS signal, temperature, and accelerometer information (used to trigger an alert condition). The embedded software captures and processes the sensor information, provides a multi-hop packet routing protocol to relay the sensor information to and receive alert information from a command center, and to display the alert information on the display.

Energy-Aware Topology Evolution Model with Link and Node Deletion in Wireless Sensor Networks

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Xiaojuan Luo

2012-01-01

Full Text Available Based on the complex network theory, a new topological evolving model is proposed. In the evolution of the topology of sensor networks, the energy-aware mechanism is taken into account, and the phenomenon of change of the link and node in the network is discussed. Theoretical analysis and numerical simulation are conducted to explore the topology characteristics and network performance with different node energy distribution. We find that node energy distribution has the weak effect on the degree distribution P(k that evolves into the scale-free state, nodes with more energy carry more connections, and degree correlation is nontrivial disassortative. Moreover, the results show that, when nodes energy is more heterogeneous, the network is better clustered and enjoys higher performance in terms of the network efficiency and the average path length for transmitting data.

Sentinel Node Biopsy Alone versus Completion Axillary Node Dissection in Node Positive Breast Cancer: Systematic Review and Meta-Analysis

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Rachna Ram

2014-01-01

Full Text Available Introduction. There has been recent interest in validity of completion axillary node dissection after a positive sentinel node. This systematic review aims to ascertain if sentinel lymph node dissection alone was noninferior to axillary lymph node dissection for breast cancer patients who have a positive sentinel node. Method. A systematic review of the electronic databases Embase, MEDLINE, and Cochrane Register of Controlled Trials was carried out. Only randomised trials that had patients with positive sentinel node as the study sample were included in the meta-analysis using the reported hazard ratios with a fixed effect model. Results. Three randomised controlled trials and five retrospective studies were identified. The pooled effect for overall survival was HR 0.94, 95% CI [0.79, 1.19], and for disease free survival was HR 0.83, 95% CI [0.60, 1.14]. The reported rates for locoregional recurrence were similar in both groups. The surgical morbidity was found to be significantly more in patients who had underwent axillary dissection. Conclusion. Amongst patients with micrometastasis in the sentinel node, no further axillary dissection is necessary. For patients with macrometastasis in the sentinel node, it is reasonable to consider omitting axillary dissection to avoid the morbidity of the procedure.

Tumor implantation model for rapid testing of lymphatic dye uptake from paw to node in small animals

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DSouza, Alisha V.; Elliott, Jonathan T.; Gunn, Jason R.; Barth, Richard J.; Samkoe, Kimberley S.; Tichauer, Kenneth M.; Pogue, Brian W.

2015-03-01

Morbidity and complexity involved in lymph node staging via surgical resection and biopsy calls for staging techniques that are less invasive. While visible blue dyes are commonly used in locating sentinel lymph nodes, since they follow tumor-draining lymphatic vessels, they do not provide a metric to evaluate presence of cancer. An area of active research is to use fluorescent dyes to assess tumor burden of sentinel and secondary lymph nodes. The goal of this work was to successfully deploy and test an intra-nodal cancer-cell injection model to enable planar fluorescence imaging of a clinically relevant blue dye, specifically methylene blue - used in the sentinel lymph node procedure - in normal and tumor-bearing animals, and subsequently segregate tumor-bearing from normal lymph nodes. This direct-injection based tumor model was employed in athymic rats (6 normal, 4 controls, 6 cancer-bearing), where luciferase-expressing breast cancer cells were injected into axillary lymph nodes. Tumor presence in nodes was confirmed by bioluminescence imaging before and after fluorescence imaging. Lymphatic uptake from the injection site (intradermal on forepaw) to lymph node was imaged at approximately 2 frames/minute. Large variability was observed within each cohort.

Support vector machine model for diagnosis of lymph node metastasis in gastric cancer with multidetector computed tomography: a preliminary study

International Nuclear Information System (INIS)

Zhang, Xiao-Peng; Wang, Zhi-Long; Tang, Lei; Sun, Ying-Shi; Cao, Kun; Gao, Yun

2011-01-01

Lymph node metastasis (LNM) of gastric cancer is an important prognostic factor regarding long-term survival. But several imaging techniques which are commonly used in stomach cannot satisfactorily assess the gastric cancer lymph node status. They can not achieve both high sensitivity and specificity. As a kind of machine-learning methods, Support Vector Machine has the potential to solve this complex issue. The institutional review board approved this retrospective study. 175 consecutive patients with gastric cancer who underwent MDCT before surgery were included. We evaluated the tumor and lymph node indicators on CT images including serosal invasion, tumor classification, tumor maximum diameter, number of lymph nodes, maximum lymph node size and lymph nodes station, which reflected the biological behavior of gastric cancer. Univariate analysis was used to analyze the relationship between the six image indicators with LNM. A SVM model was built with these indicators above as input index. The output index was that lymph node metastasis of the patient was positive or negative. It was confirmed by the surgery and histopathology. A standard machine-learning technique called k-fold cross-validation (5-fold in our study) was used to train and test SVM models. We evaluated the diagnostic capability of the SVM models in lymph node metastasis with the receiver operating characteristic (ROC) curves. And the radiologist classified the lymph node metastasis of patients by using maximum lymph node size on CT images as criterion. We compared the areas under ROC curves (AUC) of the radiologist and SVM models. In 175 cases, the cases of lymph node metastasis were 134 and 41 cases were not. The six image indicators all had statistically significant differences between the LNM negative and positive groups. The means of the sensitivity, specificity and AUC of SVM models with 5-fold cross-validation were 88.5%, 78.5% and 0.876, respectively. While the diagnostic power of the

Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

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Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

2016-11-01

A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

Physical Layer Multi-Core Prototyping A Dataflow-Based Approach for LTE eNodeB

CERN Document Server

Pelcat, Maxime; Piat, Jonathan; Nezan, Jean-François

2013-01-01

Base stations developed according to the 3GPP Long Term Evolution (LTE) standard require unprecedented processing power. 3GPP LTE enables data rates beyond hundreds of Mbits/s by using advanced technologies, necessitating a highly complex LTE physical layer. The operating power of base stations is a significant cost for operators, and is currently optimized using state-of-the-art hardware solutions, such as heterogeneous distributed systems. The traditional system design method of porting algorithms to heterogeneous distributed systems based on test-and-refine methods is a manual, thus time-expensive, task.   Physical Layer Multi-Core Prototyping: A Dataflow-Based Approach for LTE eNodeB provides a clear introduction to the 3GPP LTE physical layer and to dataflow-based prototyping and programming. The difficulties in the process of 3GPP LTE physical layer porting are outlined, with particular focus on automatic partitioning and scheduling, load balancing and computation latency reduction, specifically in sys...

High-Performance, Multi-Node File Copies and Checksums for Clustered File Systems

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Kolano, Paul Z.; Ciotti, Robert B.

2012-01-01

Modern parallel file systems achieve high performance using a variety of techniques, such as striping files across multiple disks to increase aggregate I/O bandwidth and spreading disks across multiple servers to increase aggregate interconnect bandwidth. To achieve peak performance from such systems, it is typically necessary to utilize multiple concurrent readers/writers from multiple systems to overcome various singlesystem limitations, such as number of processors and network bandwidth. The standard cp and md5sum tools of GNU coreutils found on every modern Unix/Linux system, however, utilize a single execution thread on a single CPU core of a single system, and hence cannot take full advantage of the increased performance of clustered file systems. Mcp and msum are drop-in replacements for the standard cp and md5sum programs that utilize multiple types of parallelism and other optimizations to achieve maximum copy and checksum performance on clustered file systems. Multi-threading is used to ensure that nodes are kept as busy as possible. Read/write parallelism allows individual operations of a single copy to be overlapped using asynchronous I/O. Multinode cooperation allows different nodes to take part in the same copy/checksum. Split-file processing allows multiple threads to operate concurrently on the same file. Finally, hash trees allow inherently serial checksums to be performed in parallel. Mcp and msum provide significant performance improvements over standard cp and md5sum using multiple types of parallelism and other optimizations. The total speed-ups from all improvements are significant. Mcp improves cp performance over 27x, msum improves md5sum performance almost 19x, and the combination of mcp and msum improves verified copies via cp and md5sum by almost 22x. These improvements come in the form of drop-in replacements for cp and md5sum, so are easily used and are available for download as open source software at http://mutil.sourceforge.net.

A local-world node deleting evolving network model

International Nuclear Information System (INIS)

Gu Yuying; Sun Jitao

2008-01-01

A new type network growth rule which comprises node addition with the concept of local-world connectivity and node deleting is studied. A series of theoretical analysis and numerical simulation to the LWD network are conducted in this Letter. Firstly, the degree distribution p(k) of this network changes no longer pure scale free but truncates by an exponential tail and the truncation in p(k) increases as p a decreases. Secondly, the connectivity is tighter, as the local-world size M increases. Thirdly, the average path length L increases and the clustering coefficient decreases as generally node deleting increases. Finally, trends up when the local-world size M increases, so as to k max . Hence, the expanding local-world can compensate the infection of the node deleting

A local-world node deleting evolving network model

Energy Technology Data Exchange (ETDEWEB)

Gu Yuying [Department of Mathematics, Tongji University, Shanghai 200092 (China); Sun Jitao [Department of Mathematics, Tongji University, Shanghai 200092 (China)], E-mail: sunjt@sh163.net

2008-06-16

A new type network growth rule which comprises node addition with the concept of local-world connectivity and node deleting is studied. A series of theoretical analysis and numerical simulation to the LWD network are conducted in this Letter. Firstly, the degree distribution p(k) of this network changes no longer pure scale free but truncates by an exponential tail and the truncation in p(k) increases as p{sub a} decreases. Secondly, the connectivity is tighter, as the local-world size M increases. Thirdly, the average path length L increases and the clustering coefficient decreases as generally node deleting increases. Finally, trends up when the local-world size M increases, so as to k{sub max}. Hence, the expanding local-world can compensate the infection of the node deleting.

Multi-Stratum Networks: toward a unified model of on-line identities

DEFF Research Database (Denmark)

Rossi, Luca; Magnani, Matteo

2012-01-01

One of the reasons behind the success of Social Network Analysis is its simple and general graph model made of nodes (representing individuals) and ties. However, when we focus on our daily on-line experience we must confront a more complex scenario: people inhabitate several on-line spaces...... interacting to several communities active on various technological infrastructures like Twitter, Facebook, YouTube or FourSquare and with distinct social objectives. This constitutes a complex network of interconnected networks where users' identities are spread and where information propagates navigating...... through different communities and social platforms. In this article we introduce a model for this layered scenario that we call multi-stratum network. Through a theoretical discussion and the analysis of real-world data we show how not only focusing on a single network may provide a very partial...

Multi-physics modeling of large ring motor for mining industry - Combining electromagnetism, fluid mechanics, mass and heat transfer in engineering design

DEFF Research Database (Denmark)

Andersen, Søren Bøgh; Santos, Ilmar F.; Fuerst, Axel

2015-01-01

This paper presents an improved completely interconnected procedure for estimating the losses, cooling flows, fluid characteristics and temperature distribution in a gearless mill drive using real life data. The presented model is part of a larger project building a multi-physics model combining...... iteratively according to the heat flux transferred to the fluid, is modeled as a lumped model with two nodes interconnected by 11 channels and one pump. The flow model is based on Bernoulli's energy equation and solved by Newton-Raphson method. All the results from the three physical areas have been verified...

Study on Multi-Depot Collaborative Transportation Problem of Milk-Run Pattern

Directory of Open Access Journals (Sweden)

Lou Zhenkai

2016-01-01

Full Text Available Analyze the relevance between Milk Run mode and collaborative transportation problem, put forward collaborative transportation problem of multiple-depot on Milk Run mode under the supply and demand separate nodes, consider the value of transport and transport costs, introduce the concept of node - arc flow, by comparing the size of traffic flow determine nodes collection, and then constructed multi-transport model of the problem. Considering one-way pickup and delivery closed, construct two-stage algorithm model, use dynamic programming recursive solution to determine the best route to pick up, and then solving delivery routing problem with different start and return point based on geometric method of Cosine. Finally use a numerical example illustrates the effectiveness of the algorithm and reasonable model.

Support vector machine model for diagnosis of lymph node metastasis in gastric cancer with multidetector computed tomography: a preliminary study

Directory of Open Access Journals (Sweden)

Gao Yun

2011-01-01

Full Text Available Abstract Background Lymph node metastasis (LNM of gastric cancer is an important prognostic factor regarding long-term survival. But several imaging techniques which are commonly used in stomach cannot satisfactorily assess the gastric cancer lymph node status. They can not achieve both high sensitivity and specificity. As a kind of machine-learning methods, Support Vector Machine has the potential to solve this complex issue. Methods The institutional review board approved this retrospective study. 175 consecutive patients with gastric cancer who underwent MDCT before surgery were included. We evaluated the tumor and lymph node indicators on CT images including serosal invasion, tumor classification, tumor maximum diameter, number of lymph nodes, maximum lymph node size and lymph nodes station, which reflected the biological behavior of gastric cancer. Univariate analysis was used to analyze the relationship between the six image indicators with LNM. A SVM model was built with these indicators above as input index. The output index was that lymph node metastasis of the patient was positive or negative. It was confirmed by the surgery and histopathology. A standard machine-learning technique called k-fold cross-validation (5-fold in our study was used to train and test SVM models. We evaluated the diagnostic capability of the SVM models in lymph node metastasis with the receiver operating characteristic (ROC curves. And the radiologist classified the lymph node metastasis of patients by using maximum lymph node size on CT images as criterion. We compared the areas under ROC curves (AUC of the radiologist and SVM models. Results In 175 cases, the cases of lymph node metastasis were 134 and 41 cases were not. The six image indicators all had statistically significant differences between the LNM negative and positive groups. The means of the sensitivity, specificity and AUC of SVM models with 5-fold cross-validation were 88.5%, 78.5% and 0

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

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Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Experiences Using Hybrid MPI/OpenMP in the Real World: Parallelization of a 3D CFD Solver for Multi-Core Node Clusters

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Gabriele Jost

2010-01-01

Full Text Available Today most systems in high-performance computing (HPC feature a hierarchical hardware design: shared-memory nodes with several multi-core CPUs are connected via a network infrastructure. When parallelizing an application for these architectures it seems natural to employ a hierarchical programming model such as combining MPI and OpenMP. Nevertheless, there is the general lore that pure MPI outperforms the hybrid MPI/OpenMP approach. In this paper, we describe the hybrid MPI/OpenMP parallelization of IR3D (Incompressible Realistic 3-D code, a full-scale real-world application, which simulates the environmental effects on the evolution of vortices trailing behind control surfaces of underwater vehicles. We discuss performance, scalability and limitations of the pure MPI version of the code on a variety of hardware platforms and show how the hybrid approach can help to overcome certain limitations.

A novel game theoretic approach for modeling competitive information diffusion in social networks with heterogeneous nodes

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Agha Mohammad Ali Kermani, Mehrdad; Fatemi Ardestani, Seyed Farshad; Aliahmadi, Alireza; Barzinpour, Farnaz

2017-01-01

Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes' sociability and initial tendency measures have an effect on the determination of the influential node in the network.

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

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Kaveh Khalili-Damghani

2017-07-01

Full Text Available In this paper a multi-period multi-product multi-objective aggregate production planning (APP model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.

The evaluation of multi-structure, multi-atlas pelvic anatomy features in a prostate MR lymphography CAD system

Science.gov (United States)

Meijs, M.; Debats, O.; Huisman, H.

2015-03-01

In prostate cancer, the detection of metastatic lymph nodes indicates progression from localized disease to metastasized cancer. The detection of positive lymph nodes is, however, a complex and time consuming task for experienced radiologists. Assistance of a two-stage Computer-Aided Detection (CAD) system in MR Lymphography (MRL) is not yet feasible due to the large number of false positives in the first stage of the system. By introducing a multi-structure, multi-atlas segmentation, using an affine transformation followed by a B-spline transformation for registration, the organ location is given by a mean density probability map. The atlas segmentation is semi-automatically drawn with ITK-SNAP, using Active Contour Segmentation. Each anatomic structure is identified by a label number. Registration is performed using Elastix, using Mutual Information and an Adaptive Stochastic Gradient optimization. The dataset consists of the MRL scans of ten patients, with lymph nodes manually annotated in consensus by two expert readers. The feature map of the CAD system consists of the Multi-Atlas and various other features (e.g. Normalized Intensity and multi-scale Blobness). The voxel-based Gentleboost classifier is evaluated using ROC analysis with cross validation. We show in a set of 10 studies that adding multi-structure, multi-atlas anatomical structure likelihood features improves the quality of the lymph node voxel likelihood map. Multiple structure anatomy maps may thus make MRL CAD more feasible.

New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients

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Johnson Denise L

2008-03-01

Full Text Available Abstract Background Current practice is to perform a completion axillary lymph node dissection (ALND for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs, although fewer than half will have non-sentinel node (NSLN metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model. Methods We constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC, boosted Classification and Regression Trees (CART, and multivariate logistic regression (MLR informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram in our dataset and an independent dataset from Northwestern University. Results 285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93% patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%. 101 (35% of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC was 0.83/0.85 for MLR (n = 213/n = 171 and 0.77 for Nomogram (n = 171. When applied to an independent dataset (n = 77, AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of

Endometrial Stromal Cells and Immune Cell Populations Within Lymph Nodes in a Nonhuman Primate Model of Endometriosis

Science.gov (United States)

Fazleabas, A. T.; Braundmeier, A. G.; Markham, R.; Fraser, I. S.; Berbic, M.

2011-01-01

Mounting evidence suggests that immunological responses may be altered in endometriosis. The baboon (Papio anubis) is generally considered the best model of endometriosis pathogenesis. The objective of the current study was to investigate for the first time immunological changes within uterine and peritoneal draining lymph nodes in a nonhuman primate baboon model of endometriosis. Paraffin-embedded femoral lymph nodes were obtained from 22 normally cycling female baboons (induced endometriosis n = 11; control n = 11). Immunohistochemical staining was performed with antibodies for endometrial stromal cells, T cells, immature and mature dendritic cells, and B cells. Lymph nodes were evaluated using an automated cellular imaging system. Endometrial stromal cells were significantly increased in lymph nodes from animals with induced endometriosis, compared to control animals (P = .033). In animals with induced endometriosis, some lymph node immune cell populations including T cells, dendritic cells and B cells were increased, suggesting an efficient early response or peritoneal drainage. PMID:21617251

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

Generalized modeling of multi-component vaporization/condensation phenomena for multi-phase-flow analysis

International Nuclear Information System (INIS)

Morita, K.; Fukuda, K.; Tobita, Y.; Kondo, Sa.; Suzuki, T.; Maschek, W.

2003-01-01

A new multi-component vaporization/condensation (V/C) model was developed to provide a generalized model for safety analysis codes of liquid metal cooled reactors (LMRs). These codes simulate thermal-hydraulic phenomena of multi-phase, multi-component flows, which is essential to investigate core disruptive accidents of LMRs such as fast breeder reactors and accelerator driven systems. The developed model characterizes the V/C processes associated with phase transition by employing heat transfer and mass-diffusion limited models for analyses of relatively short-time-scale multi-phase, multi-component hydraulic problems, among which vaporization and condensation, or simultaneous heat and mass transfer, play an important role. The heat transfer limited model describes the non-equilibrium phase transition processes occurring at interfaces, while the mass-diffusion limited model is employed to represent effects of non-condensable gases and multi-component mixture on V/C processes. Verification of the model and method employed in the multi-component V/C model of a multi-phase flow code was performed successfully by analyzing a series of multi-bubble condensation experiments. The applicability of the model to the accident analysis of LMRs is also discussed by comparison between steam and metallic vapor systems. (orig.)

Throughput analysis of point-to-multi-point hybric FSO/RF network

KAUST Repository

Rakia, Tamer

2017-07-31

This paper presents and analyzes a point-to-multi-point (P2MP) network that uses a number of free-space optical (FSO) links for data transmission from the central node to the different remote nodes. A common backup radio-frequency (RF) link is used by the central node for data transmission to any remote node in case of the failure of any one of FSO links. We develop a cross-layer Markov chain model to study the throughput from central node to a tagged remote node. Numerical examples are presented to compare the performance of the proposed P2MP hybrid FSO/RF network with that of a P2MP FSO-only network and show that the P2MP Hybrid FSO/RF network achieves considerable performance improvement over the P2MP FSO-only network.

Riemannian multi-manifold modeling and clustering in brain networks

Science.gov (United States)

Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

2017-08-01

This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.

Using high resolution X-ray computed tomography to create an image based model of a lymph node.

Science.gov (United States)

Cooper, L J; Zeller-Plumhoff, B; Clough, G F; Ganapathisubramani, B; Roose, T

2018-07-14

Lymph nodes are an important part of the immune system. They filter the lymphatic fluid as it is transported from the tissues before being returned to the blood stream. The fluid flow through the nodes influences the behaviour of the immune cells that gather within the nodes and the structure of the node itself. Measuring the fluid flow in lymph nodes experimentally is challenging due to their small size and fragility. In this paper, we present high resolution X-ray computed tomography images of a murine lymph node. The impact of the resulting visualized structures on fluid transport are investigated using an image based model. The high contrast between different structures within the lymph node provided by phase contrast X-ray computed tomography reconstruction results in images that, when related to the permeability of the lymph node tissue, suggest an increased fluid velocity through the interstitial channels in the lymph node tissue. Fluid taking a direct path from the afferent to the efferent lymphatic vessel, through the centre of the node, moved faster than the fluid that flowed around the periphery of the lymph node. This is a possible mechanism for particles being moved into the cortex. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiphysics and Thermal Response Models to Improve Accuracy of Local Temperature Estimation in Rat Cortex under Microwave Exposure

Science.gov (United States)

Kodera, Sachiko; Gomez-Tames, Jose; Hirata, Akimasa; Masuda, Hiroshi; Arima, Takuji; Watanabe, Soichi

2017-01-01

The rapid development of wireless technology has led to widespread concerns regarding adverse human health effects caused by exposure to electromagnetic fields. Temperature elevation in biological bodies is an important factor that can adversely affect health. A thermophysiological model is desired to quantify microwave (MW) induced temperature elevations. In this study, parameters related to thermophysiological responses for MW exposures were estimated using an electromagnetic-thermodynamics simulation technique. To the authors’ knowledge, this is the first study in which parameters related to regional cerebral blood flow in a rat model were extracted at a high degree of accuracy through experimental measurements for localized MW exposure at frequencies exceeding 6 GHz. The findings indicate that the improved modeling parameters yield computed results that match well with the measured quantities during and after exposure in rats. It is expected that the computational model will be helpful in estimating the temperature elevation in the rat brain at multiple observation points (that are difficult to measure simultaneously) and in explaining the physiological changes in the local cortex region. PMID:28358345

High risk of non-sentinel node metastases in a group of breast cancer patients with micrometastases in the sentinel node

DEFF Research Database (Denmark)

Tvedskov, Tove Filtenborg; Jensen, Maj-Britt; Lisse, Ida Marie

2012-01-01

Axillary lymph node dissection (ALND) in breast cancer patients with positive sentinel nodes is under debate. We aimed to establish two models to predict non-sentinel node (NSN) metastases in patients with micrometastases or isolated tumor cells (ITC) in sentinel nodes, to guide the decision for ...

Numerical modeling of macrodispersion in heterogeneous media: a comparison of multi-Gaussian and non-multi-Gaussian models

Science.gov (United States)

Wen, Xian-Huan; Gómez-Hernández, J. Jaime

1998-03-01

The macrodispersion of an inert solute in a 2-D heterogeneous porous media is estimated numerically in a series of fields of varying heterogeneity. Four different random function (RF) models are used to model log-transmissivity (ln T) spatial variability, and for each of these models, ln T variance is varied from 0.1 to 2.0. The four RF models share the same univariate Gaussian histogram and the same isotropic covariance, but differ from one another in terms of the spatial connectivity patterns at extreme transmissivity values. More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated. The other three models are non-multi-Gaussian: model B with high connectivity of high extreme values, model C with high connectivity of low extreme values, and model D with high connectivities of both high and low extreme values. Residence time distributions (RTDs) and macrodispersivities (longitudinal and transverse) are computed on ln T fields corresponding to the different RF models, for two different flow directions and at several scales. They are compared with each other, as well as with predicted values based on first-order analytical results. Numerically derived RTDs and macrodispersivities for the multi-Gaussian model are in good agreement with analytically derived values using first-order theories for log-transmissivity variance up to 2.0. The results from the non-multi-Gaussian models differ from each other and deviate largely from the multi-Gaussian results even when ln T variance is small. RTDs in non-multi-Gaussian realizations with high connectivity at high extreme values display earlier breakthrough than in multi-Gaussian realizations, whereas later breakthrough and longer tails are observed for RTDs from non-multi-Gaussian realizations with high connectivity at low extreme values. Longitudinal macrodispersivities in the non-multi-Gaussian realizations are, in general, larger than

The effects of node exclusion on the centrality measures in graph models of interacting economic agents

Science.gov (United States)

Caetano, Marco Antonio Leonel; Yoneyama, Takashi

2015-07-01

This work concerns the study of the effects felt by a network as a whole when a specific node is perturbed. Many real world systems can be described by network models in which the interactions of the various agents can be represented as an edge of a graph. With a graph model in hand, it is possible to evaluate the effect of deleting some of its edges on the architecture and values of nodes of the network. Eventually a node may end up isolated from the rest of the network and an interesting problem is to have a quantitative measure of the impact of such an event. For instance, in the field of finance, the network models are very popular and the proposed methodology allows to carry out "what if" tests in terms of weakening the links between the economic agents, represented as nodes. The two main concepts employed in the proposed methodology are (i) the vibrational IC-Information Centrality, which can provide a measure of the relative importance of a particular node in a network and (ii) autocatalytic networks that can indicate the evolutionary trends of the network. Although these concepts were originally proposed in the context of other fields of knowledge, they were also found to be useful in analyzing financial networks. In order to illustrate the applicability of the proposed methodology, a case of study using the actual data comprising stock market indices of 12 countries is presented.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

Node-Splitting Generalized Linear Mixed Models for Evaluation of Inconsistency in Network Meta-Analysis.

Science.gov (United States)

Yu-Kang, Tu

2016-12-01

Network meta-analysis for multiple treatment comparisons has been a major development in evidence synthesis methodology. The validity of a network meta-analysis, however, can be threatened by inconsistency in evidence within the network. One particular issue of inconsistency is how to directly evaluate the inconsistency between direct and indirect evidence with regard to the effects difference between two treatments. A Bayesian node-splitting model was first proposed and a similar frequentist side-splitting model has been put forward recently. Yet, assigning the inconsistency parameter to one or the other of the two treatments or splitting the parameter symmetrically between the two treatments can yield different results when multi-arm trials are involved in the evaluation. We aimed to show that a side-splitting model can be viewed as a special case of design-by-treatment interaction model, and different parameterizations correspond to different design-by-treatment interactions. We demonstrated how to evaluate the side-splitting model using the arm-based generalized linear mixed model, and an example data set was used to compare results from the arm-based models with those from the contrast-based models. The three parameterizations of side-splitting make slightly different assumptions: the symmetrical method assumes that both treatments in a treatment contrast contribute to inconsistency between direct and indirect evidence, whereas the other two parameterizations assume that only one of the two treatments contributes to this inconsistency. With this understanding in mind, meta-analysts can then make a choice about how to implement the side-splitting method for their analysis. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

High risk of non-sentinel node metastases in a group of breast cancer patients with micrometastases in the sentinel node.

Science.gov (United States)

Tvedskov, Tove Filtenborg; Jensen, Maj-Britt; Lisse, Ida Marie; Ejlertsen, Bent; Balslev, Eva; Kroman, Niels

2012-11-15

Axillary lymph node dissection (ALND) in breast cancer patients with positive sentinel nodes is under debate. We aimed to establish two models to predict non-sentinel node (NSN) metastases in patients with micrometastases or isolated tumor cells (ITC) in sentinel nodes, to guide the decision for ALND. A total of 1,577 breast cancer patients with micrometastases and 304 with ITC in sentinel nodes, treated by sentinel lymph node dissection and ALND in 2002-2008 were identified in the Danish Breast Cancer Cooperative Group database. Risk of NSN metastases was calculated according to clinicopathological variables in a logistic regression analysis. We identified tumor size, proportion of positive sentinel nodes, lymphovascular invasion, hormone receptor status and location of tumor in upper lateral quadrant of the breast as risk factors for NSN metastases in patients with micrometastases. A model based on these risk factors identified 5% of patients with a risk of NSN metastases on nearly 40%. The model was however unable to identify a subgroup of patients with a very low risk of NSN metastases. Among patients with ITC, we identified tumor size, age and proportion of positive sentinel nodes as risk factors. A model based on these risk factors identified 32% of patients with risk of NSN metastases on only 2%. Omission of ALND would be acceptable in this group of patients. In contrast, ALND may still be beneficial in the subgroup of patients with micrometastases and a high risk of NSN metastases. Copyright © 2012 UICC.

Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model

Directory of Open Access Journals (Sweden)

Takada Masahiro

2012-06-01

Full Text Available Abstract Background The aim of this study was to develop a new data-mining model to predict axillary lymph node (AxLN metastasis in primary breast cancer. To achieve this, we used a decision tree-based prediction method—the alternating decision tree (ADTree. Methods Clinical datasets for primary breast cancer patients who underwent sentinel lymph node biopsy or AxLN dissection without prior treatment were collected from three institutes (institute A, n = 148; institute B, n = 143; institute C, n = 174 and were used for variable selection, model training and external validation, respectively. The models were evaluated using area under the receiver operating characteristics (ROC curve analysis to discriminate node-positive patients from node-negative patients. Results The ADTree model selected 15 of 24 clinicopathological variables in the variable selection dataset. The resulting area under the ROC curve values were 0.770 [95% confidence interval (CI, 0.689–0.850] for the model training dataset and 0.772 (95% CI: 0.689–0.856 for the validation dataset, demonstrating high accuracy and generalization ability of the model. The bootstrap value of the validation dataset was 0.768 (95% CI: 0.763–0.774. Conclusions Our prediction model showed high accuracy for predicting nodal metastasis in patients with breast cancer using commonly recorded clinical variables. Therefore, our model might help oncologists in the decision-making process for primary breast cancer patients before starting treatment.

Annexin A7 suppresses lymph node metastasis of hepatocarcinoma cells in a mouse model

International Nuclear Information System (INIS)

Jin, Yanling; Wang, Shaoqing; Chen, Wenjing; Zhang, Jun; Wang, Bo; Guan, Hongwei; Tang, Jianwu

2013-01-01

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in China. This study investigated the effects of Annexin A7 (ANXA7) on the inhibition of HCC lymph node metastasis in a mouse model. The stable knockup and knockdown of Annexin A7-expressing HCC cells using Annexin A7 cDNA and shRNA vectors, respectively, were injected into a mouse footpad to establish primary and metastatic tumors in mice. On the 14th, 21st, and 28th days after HCC cells inoculation, the mice were sacrificed for inspection of primary and secondary tumors and immunohistochemistry of Annexin A7 expression. The lymph node metastasis rate of the F ANXA7-control group was 77%, and the lymph node metastasis rate of the F ANXA7-down group was 100% (p < 0.05). In contrast, the lymph node metastasis rate of the P ANXA7-up group was 0% and that of the P ANXA7-control group was 36% (p < 0.05). Furthermore, immunohistochemistry experiments revealed that the subcellular localization of Annexin A7 protein in both primary and lymph node-metastasized tumors was mainly in the cytosol. In addition, the expression of the 47 kDa and 51 kDa isoforms of Annexin A7 protein changed during tumor progression. This study indicated that Annexin A7 expression was able to inhibit HCC lymph node metastasis, whereas knockdown of Annexin A7 expression significantly induced HCC metastasis to local lymph nodes

Multi-population genomic prediction using a multi-task Bayesian learning model.

Science.gov (United States)

Chen, Liuhong; Li, Changxi; Miller, Stephen; Schenkel, Flavio

2014-05-03

Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n = 20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (ρ = 0.2), and up to 0.16 when QTL effects were highly correlated (ρ = 0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n = 200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an

Network structure exploration in networks with node attributes

Science.gov (United States)

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

2016-05-01

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

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

Directory of Open Access Journals (Sweden)

Youngmin Kim

2017-12-01

Full Text Available In wireless sensor networks (WSNs, sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods.

Multi-Model Ensemble Wake Vortex Prediction

Science.gov (United States)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Ratios of involved nodes in early breast cancer

International Nuclear Information System (INIS)

Vinh-Hung, Vincent; Royce, Melanie; Verschraegen, Claire; Promish, Donald I; Cserni, Gábor; Van de Steene, Jan; Tai, Patricia; Vlastos, Georges; Voordeckers, Mia; Storme, Guy

2004-01-01

The number of lymph nodes found to be involved in an axillary dissection is among the most powerful prognostic factors in breast cancer, but it is confounded by the number of lymph nodes that have been examined. We investigate an idea that has surfaced recently in the literature (since 1999), namely that the proportion of node-positive lymph nodes (or a function thereof) is a much better predictor of survival than the number of excised and node-positive lymph nodes, alone or together. The data were abstracted from 83,686 cases registered in the Surveillance, Epidemiology, and End Results (SEER) program of women diagnosed with nonmetastatic T1–T2 primary breast carcinoma between 1988 and 1997, in whom axillary node dissection was performed. The end-point was death from breast cancer. Cox models based on different expressions of nodal involvement were compared using the Nagelkerke R 2 index (R 2 N ). Ratios were modeled as percentage and as log odds of involved nodes. Log odds were estimated in a way that avoids singularities (zero values) by using the empirical logistic transform. In node-negative cases both the number of nodes excised and the log odds were significant, with hazard ratios of 0.991 (95% confidence interval 0.986–0.997) and 1.150 (1.058–1.249), respectively, but without improving R 2 N . In node-positive cases the hazard ratios were 1.003–1.088 for the number of involved nodes, 0.966–1.005 for the number of excised nodes, 1.015–1.017 for the percentage, and 1.344–1.381 for the log odds. R 2 N improved from 0.067 (no nodal covariate) to 0.102 (models based on counts only) and to 0.108 (models based on ratios). Ratios are simple optimal predictors, in that they provide at least the same prognostic value as the more traditional staging based on counting of involved nodes, without replacing them with a needlessly complicated alternative. They can be viewed as a per patient standardization in which the number of involved nodes is standardized

An improved power flow method based on extended chain-table storage structure for distribution network with PV nodes

DEFF Research Database (Denmark)

Chen, Shuheng; Wang, Xiongfei; Su, Chi

2014-01-01

with a reduced memory size. The voltage error of each PV node is adjusted by a reactive power adjusting strategy. The adjusting strategy is based on a multi-variable linear function with an accelerating factor. Finally, this new improved power flow method is realized by the software system developed in VC......Based on an extended chain-table storage structure, an improved power flow method is presented, which can be applied to a distribution network with multi PV nodes. The extended chain-table storage structure is designed on the basis of address-pointer technology describing the radial topology...... and the corresponding case study has been done. The experimental data and the further analysis have proved that this method can calculate the power flow of a distribution network with multi PV nodes precisely and fast. © 2014 IEEE....

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

Science.gov (United States)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Multi-petascale highly efficient parallel supercomputer

Science.gov (United States)

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.; Blumrich, Matthias A.; Boyle, Peter; Brunheroto, Jose R.; Chen, Dong; Cher, Chen -Yong; Chiu, George L.; Christ, Norman; Coteus, Paul W.; Davis, Kristan D.; Dozsa, Gabor J.; Eichenberger, Alexandre E.; Eisley, Noel A.; Ellavsky, Matthew R.; Evans, Kahn C.; Fleischer, Bruce M.; Fox, Thomas W.; Gara, Alan; Giampapa, Mark E.; Gooding, Thomas M.; Gschwind, Michael K.; Gunnels, John A.; Hall, Shawn A.; Haring, Rudolf A.; Heidelberger, Philip; Inglett, Todd A.; Knudson, Brant L.; Kopcsay, Gerard V.; Kumar, Sameer; Mamidala, Amith R.; Marcella, James A.; Megerian, Mark G.; Miller, Douglas R.; Miller, Samuel J.; Muff, Adam J.; Mundy, Michael B.; O'Brien, John K.; O'Brien, Kathryn M.; Ohmacht, Martin; Parker, Jeffrey J.; Poole, Ruth J.; Ratterman, Joseph D.; Salapura, Valentina; Satterfield, David L.; Senger, Robert M.; Smith, Brian; Steinmacher-Burow, Burkhard; Stockdell, William M.; Stunkel, Craig B.; Sugavanam, Krishnan; Sugawara, Yutaka; Takken, Todd E.; Trager, Barry M.; Van Oosten, James L.; Wait, Charles D.; Walkup, Robert E.; Watson, Alfred T.; Wisniewski, Robert W.; Wu, Peng

2015-07-14

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaOPS-scale computing, at decreased cost, power and footprint, and that allows for a maximum packaging density of processing nodes from an interconnect point of view. The Supercomputer exploits technological advances in VLSI that enables a computing model where many processors can be integrated into a single Application Specific Integrated Circuit (ASIC). Each ASIC computing node comprises a system-on-chip ASIC utilizing four or more processors integrated into one die, with each having full access to all system resources and enabling adaptive partitioning of the processors to functions such as compute or messaging I/O on an application by application basis, and preferably, enable adaptive partitioning of functions in accordance with various algorithmic phases within an application, or if I/O or other processors are underutilized, then can participate in computation or communication nodes are interconnected by a five dimensional torus network with DMA that optimally maximize the throughput of packet communications between nodes and minimize latency.

Combined dose and geometry correction (DMG) for low energy multi electron beam lithography (5kV): application to the 16nm node

Science.gov (United States)

Martin, Luc; Manakli, Serdar; Bayle, Sebastien; Belledent, Jérôme; Soulan, Sebastien; Wiedemann, Pablo; Farah, Abdi; Schiavone, Patrick

2012-03-01

Lithography faces today many challenges to meet the ITRS road-map. 193nm is still today the only existing industrial option to address high volume production for the 22nm node. Nevertheless to achieve such a resolution, double exposure is mandatory for critical level patterning. EUV lithography is still challenged by the availability of high power source and mask defectivity and suffers from a high cost of ownership perspective. Its introduction is now not foreseen before 2015. Parallel to these mask-based technologies, maskless lithography regularly makes significant progress in terms of potential and maturity. The massively parallel e-beam solution appears as a real candidate for high volume manufacturing. Several industrial projects are under development, one in the US, with the KLA REBL project and two in Europe driven by IMS Nanofabrication (Austria; MAPPER (The Netherlands). Among the developments to be performed to secure the takeoff of the multi-beam technology, the availability of a rapid and robust data treatment solution will be one of the major challenges. Within this data preparation flow, advanced proximity effect corrections must be implemented to address the 16nm node and below. This paper will detail this process and compare correction strategies in terms of robustness and accuracy. It will be based on results obtained using a MAPPER tool within the IMAGINE program driven by CEA-LETI, in Grenoble, France. All proximity effects corrections and the dithering step were performed using the software platform Inscale® from Aselta Nanographics. One important advantage of Inscale® is the ability to combine both model based dose and geometry adjustment to accurately pattern critical features. The paper will focus on the advantage of combining those two corrections at the 16nm node instead of using only geometry corrections. Thanks to the simulation capability of Inscale®, pattern fidelity and correction robustness will be evaluated and compared between

Multi-Domain Modeling Based on Modelica

Directory of Open Access Journals (Sweden)

Liu Jun

2016-01-01

Full Text Available With the application of simulation technology in large-scale and multi-field problems, multi-domain unified modeling become an effective way to solve these problems. This paper introduces several basic methods and advantages of the multidisciplinary model, and focuses on the simulation based on Modelica language. The Modelica/Mworks is a newly developed simulation software with features of an object-oriented and non-casual language for modeling of the large, multi-domain system, which makes the model easier to grasp, develop and maintain.It This article shows the single degree of freedom mechanical vibration system based on Modelica language special connection mechanism in Mworks. This method that multi-domain modeling has simple and feasible, high reusability. it closer to the physical system, and many other advantages.

Lymph Node Yield as a Predictor of Survival in Pathologically Node Negative Oral Cavity Carcinoma.

Science.gov (United States)

Lemieux, Aaron; Kedarisetty, Suraj; Raju, Sharat; Orosco, Ryan; Coffey, Charles

2016-03-01

Even after a pathologically node-negative (pN0) neck dissection for oral cavity squamous cell carcinoma (SCC), patients may develop regional recurrence. In this study, we (1) hypothesize that an increased number of lymph nodes removed (lymph node yield) in patients with pN0 oral SCC predicts improved survival and (2) explore predictors of survival in these patients using a multivariable model. Case series with chart review. Administrative database analysis. The SEER database was queried for patients diagnosed with all-stage oral cavity SCC between 1988 and 2009 who were determined to be pN0 after elective lymph node dissection. Demographic and treatment variables were extracted. The association of lymph node yield with 5-year all-cause survival was studied with multivariable survival analyses. A total of 4341 patients with pN0 oral SCC were included in this study. The 2 highest lymph node yield quartiles (representing >22 nodes removed) were found to be significant predictors of overall survival (22-35 nodes: hazard ratio [HR] = 0.854, P = .031; 36-98 nodes: HR = 0.827, P = .010). Each additional lymph node removed during neck dissection was associated with increased survival (HR = 0.995, P = .022). These data suggest that patients with oral SCC undergoing elective neck dissection may experience an overall survival benefit associated with greater lymph node yield. Mechanisms behind the demonstrated survival advantage are unknown. Larger nodal dissections may remove a greater burden of microscopic metastatic disease, diminishing the likelihood of recurrence. Lymph node yield may serve as an objective measure of the adequacy of lymphadenectomy. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

A cyber-anima-based model of material conscious information network

Directory of Open Access Journals (Sweden)

Jianping Shen

2017-03-01

Full Text Available Purpose – This paper aims to study the node modeling, multi-agent architecture and addressing method for the material conscious information network (MCIN, which is a large-scaled, open-styled, self-organized and ecological intelligent network of supply–demand relationships. Design/methodology/approach – This study models the MCIN by node model definition, multi-agent architecture design and addressing method presentation. Findings – The prototype of novel E-commerce platform based on the MCIN shows the effectiveness and soundness of the MCIN modeling. By comparing to current internet, the authors also find that the MCIN has the advantages of socialization, information integration, collective intelligence, traceability, high robustness, unification of producing and consuming, high scalability and decentralization. Research limitations/implications – Leveraging the dimensions of structure, character, knowledge and experience, a modeling approach of the basic information can fit all kinds of the MCIN nodes. With the double chain structure for both basic and supply–demand information, the MCIN nodes can be modeled comprehensively. The anima-desire-intention-based multi-agent architecture makes the federated agents of the MCIN nodes self-organized and intelligent. The MCIN nodes can be efficiently addressed by the supply–demand-oriented method. However, the implementation of the MCIN is still in process. Practical implications – This paper lays the theoretical foundation for the future networked system of supply–demand relationship and the novel E-commerce platform. Originality/value – The authors believe that the MCIN, first proposed in this paper, is a transformational innovation which facilitates the infrastructure of the future networked system of supply–demand relationship.

Multi-channel distributed coordinated function over single radio in wireless sensor networks.

Science.gov (United States)

Campbell, Carlene E-A; Loo, Kok-Keong Jonathan; Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

A multi-state reliability evaluation model for P2P networks

International Nuclear Information System (INIS)

Fan Hehong; Sun Xiaohan

2010-01-01

The appearance of new service types and the convergence tendency of the communication networks have endowed the networks more and more P2P (peer to peer) properties. These networks can be more robust and tolerant for a series of non-perfect operational states due to the non-deterministic server-client distributions. Thus a reliability model taking into account of the multi-state and non-deterministic server-client distribution properties is needed for appropriate evaluation of the networks. In this paper, two new performance measures are defined to quantify the overall and local states of the networks. A new time-evolving state-transition Monte Carlo (TEST-MC) simulation model is presented for the reliability analysis of P2P networks in multiple states. The results show that the model is not only valid for estimating the traditional binary-state network reliability parameters, but also adequate for acquiring the parameters in a series of non-perfect operational states, with good efficiencies, especially for highly reliable networks. Furthermore, the model is versatile for the reliability and maintainability analyses in that both the links and the nodes can be failure-prone with arbitrary life distributions, and various maintainability schemes can be applied.

Radiation-hardened MRAM-based LUT for non-volatile FPGA soft error mitigation with multi-node upset tolerance

Science.gov (United States)

Zand, Ramtin; DeMara, Ronald F.

2017-12-01

In this paper, we have developed a radiation-hardened non-volatile lookup table (LUT) circuit utilizing spin Hall effect (SHE)-magnetic random access memory (MRAM) devices. The design is motivated by modeling the effect of radiation particles striking hybrid complementary metal oxide semiconductor/spin based circuits, and the resistive behavior of SHE-MRAM devices via established and precise physics equations. The models developed are leveraged in the SPICE circuit simulator to verify the functionality of the proposed design. The proposed hardening technique is based on using feedback transistors, as well as increasing the radiation capacity of the sensitive nodes. Simulation results show that our proposed LUT circuit can achieve multiple node upset (MNU) tolerance with more than 38% and 60% power-delay product improvement as well as 26% and 50% reduction in device count compared to the previous energy-efficient radiation-hardened LUT designs. Finally, we have performed a process variation analysis showing that the MNU immunity of our proposed circuit is realized at the cost of increased susceptibility to transistor and MRAM variations compared to an unprotected LUT design.

Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

Science.gov (United States)

Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

2014-01-01

The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

Targeted Delivery of Immunomodulators to Lymph Nodes

Directory of Open Access Journals (Sweden)

Jamil Azzi

2016-05-01

Full Text Available Active-targeted delivery to lymph nodes represents a major advance toward more effective treatment of immune-mediated disease. The MECA79 antibody recognizes peripheral node addressin molecules expressed by high endothelial venules of lymph nodes. By mimicking lymphocyte trafficking to the lymph nodes, we have engineered MECA79-coated microparticles containing an immunosuppressive medication, tacrolimus. Following intravenous administration, MECA79-bearing particles showed marked accumulation in the draining lymph nodes of transplanted animals. Using an allograft heart transplant model, we show that targeted lymph node delivery of microparticles containing tacrolimus can prolong heart allograft survival with negligible changes in tacrolimus serum level. Using MECA79 conjugation, we have demonstrated targeted delivery of tacrolimus to the lymph nodes following systemic administration, with the capacity for immune modulation in vivo.

Research on Multi - Person Parallel Modeling Method Based on Integrated Model Persistent Storage

Science.gov (United States)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper mainly studies the multi-person parallel modeling method based on the integrated model persistence storage. The integrated model refers to a set of MDDT modeling graphics system, which can carry out multi-angle, multi-level and multi-stage description of aerospace general embedded software. Persistent storage refers to converting the data model in memory into a storage model and converting the storage model into a data model in memory, where the data model refers to the object model and the storage model is a binary stream. And multi-person parallel modeling refers to the need for multi-person collaboration, the role of separation, and even real-time remote synchronization modeling.

Adaptive Demand-Driven Multicast Routing in Multi-Hop Wireless Ad Hoc Networks

National Research Council Canada - National Science Library

Jetcheva, Jorjeta G

2004-01-01

...) nodes that wish to communicate. Each node in the ad hoc network acts as a router and forwards packets on behalf of other nodes, allowing nodes that are not within wireless range of each other to communicate over multi-hop paths...

Nomogram for prediction of level 2 axillary lymph node metastasis in proven level 1 node-positive breast cancer patients.

Science.gov (United States)

Jiang, Yanlin; Xu, Hong; Zhang, Hao; Ou, Xunyan; Xu, Zhen; Ai, Liping; Sun, Lisha; Liu, Caigang

2017-09-22

The current management of the axilla in level 1 node-positive breast cancer patients is axillary lymph node dissection regardless of the status of the level 2 axillary lymph nodes. The goal of this study was to develop a nomogram predicting the probability of level 2 axillary lymph node metastasis (L-2-ALNM) in patients with level 1 axillary node-positive breast cancer. We reviewed the records of 974 patients with pathology-confirmed level 1 node-positive breast cancer between 2010 and 2014 at the Liaoning Cancer Hospital and Institute. The patients were randomized 1:1 and divided into a modeling group and a validation group. Clinical and pathological features of the patients were assessed with uni- and multivariate logistic regression. A nomogram based on independent predictors for the L-2-ALNM identified by multivariate logistic regression was constructed. Independent predictors of L-2-ALNM by the multivariate logistic regression analysis included tumor size, Ki-67 status, histological grade, and number of positive level 1 axillary lymph nodes. The areas under the receiver operating characteristic curve of the modeling set and the validation set were 0.828 and 0.816, respectively. The false-negative rates of the L-2-ALNM nomogram were 1.82% and 7.41% for the predicted probability cut-off points of level 1 axillary lymph node metastasis. Patients with a low probability of L-2-ALNM could be spared level 2 axillary lymph node dissection, thereby reducing postoperative morbidity.

Study on the well-posedness, convergence and the stability of the semi-implicit upwind numerical solver for the multi-fluid model

International Nuclear Information System (INIS)

Lee, S. Y.; Park, C. E.; Hibiki, T.; Ishii, M.; Ransom, V. H.

2012-01-01

The well-posedness, convergence and the stability of the two-fluid code has been studied for a long time. Most of the investigations concern the semi-implicit upwind solution scheme for the six equation two-fluid model such as used in RELAP5 3 or TRACE 21. Since the system code, SPACE 2, adopts one more field, a droplet field, it consists of nine equations (3 mass, 3 momentum and 3 energy balance equations) and thus more involved investigations are necessary to confirm the stability and convergence. For this objective, the old issue of the well-posedness, convergence and the stability is revisited and some general guidelines to develop a well-posed numerical multi-fluid model are derived as follows; (1) Hyperbolicity of the corresponding system of partial differential equations is not a necessary condition for the development of a numerical model for multi-phase flow, but whether or not it is hyperbolic can provide guidance relative to initial conditions, boundary conditions, and expected high frequency behavior of the model. (2) A necessary condition for a well-posed numerical model is stability in the von Neumann sense, i.e. growth factor less than 1.0 for the shortest wave-length, 2Δx. (3) The smallest node size used for convergence studies should be of the order of the characteristic dimension of the average description, i.e. smaller nodes can be used so long as they do not result in unphysical growth of wave-lengths less than the characteristic dimension. The usual mathematical definition of convergence i.e. the behavior of the solution as the node size approaches zero, is not appropriate for the discrete averaged numerical model, since there is diminished physical meaning to behavior at wavelengths less than the characteristic dimension of the average description. Under these guidelines, dispersion analysis and von Neumann stability analysis are performed for the three field multi-fluid, semi-implicit, upwind numerical model to show that the necessary

Multi-stage crypto ransomware attacks: A new emerging cyber threat to critical infrastructure and industrial control systems

OpenAIRE

Aaron Zimba; Zhaoshun Wang; Hongsong Chen

2018-01-01

The inevitable integration of critical infrastructure to public networks has exposed the underlying industrial control systems to various attack vectors. In this paper, we model multi-stage crypto ransomware attacks, which are today an emerging cyber threat to critical infrastructure. We evaluate our modeling approach using multi-stage attacks by the infamous WannaCry ransomware. The static malware analysis results uncover the techniques employed by the ransomware to discover vulnerable nodes...

Statistical post-processing of seasonal multi-model forecasts: Why is it so hard to beat the multi-model mean?

Science.gov (United States)

Siegert, Stefan

2017-04-01

Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.

Wireless multi-hop networks with stealing : large buffer asymptotics

NARCIS (Netherlands)

Guillemin, F.; Knessl, C.; Leeuwaarden, van J.S.H.

2010-01-01

Wireless networks equipped with CSMA are scheduled in a fully distributed manner. A disadvantage of such distributed control in multi-hop networks is the hidden node problem that causes the effect of stealing, in which a downstream node steals the channel from an upstream node with probability p.

B220 analysis with the local lymph node assay: proposal for a more flexible prediction model.

Science.gov (United States)

Betts, Catherine J; Dearman, Rebecca J; Kimber, Ian; Ryan, Cindy A; Gerberick, G Frank; Lalko, Jon; Api, Anne Marie

2007-01-01

The mouse local lymph node assay (LLNA) has been developed and validated for the identification of chemicals that have the potential to induce skin sensitisation. In common with other predictive test methods the accuracy of the LLNA is not absolute and experience has revealed that a few chemicals, including for instance a minority of skin irritants, may elicit false-positive reactions in the assay. To improve further the performance of the LLNA, and to eliminate or reduce false-positives, there has been interest in an adjunct method in which the ability of chemicals to cause increases in the frequency of B220(+) lymphocytes in skin-draining lymph nodes is measured. Previous studies suggest that the use of B220 analyses aligned with the standard LLNA may serve to distinguish further between contact allergens and skin irritants. In the original predictive model, chemicals were regarded as being skin sensitisers if they were able to induce a 1.25-fold or greater increase in the percentage of B220(+) cells within lymph nodes compared with concurrent vehicle controls. Although this first prediction model has proven useful, in the light of more recent experience, and specifically as a consequence of some variability observed in the frequency of B220(+) lymphocytes in nodes taken from vehicle control-treated animals, it is timely now to reconsider and refine the model. As a result a new prediction model is proposed in which reliance on the use of absolute thresholds is reduced, and in which small changes in control values can be better accommodated. (c) 2007 John Wiley & Sons, Ltd.

UTCI—Why another thermal index?

Science.gov (United States)

Jendritzky, Gerd; de Dear, Richard; Havenith, George

2012-05-01

Existing procedures for the assessment of the thermal environment in the fields of public weather services, public health systems, precautionary planning, urban design, tourism and recreation and climate impact research exhibit significant shortcomings. This is most evident for simple (mostly two-parameter) indices, when comparing them to complete heat budget models developed since the 1960s. ISB Commission 6 took up the idea of developing a Universal Thermal Climate Index (UTCI) based on the most advanced multi-node model of thermoregulation representing progress in science within the last three to four decades, both in thermo-physiological and heat exchange theory. Creating the essential research synergies for the development of UTCI required pooling the resources of multidisciplinary experts in the fields of thermal physiology, mathematical modelling, occupational medicine, meteorological data handling (in particular radiation modelling) and application development in a network. It was possible to extend the expertise of ISB Commission 6 substantially by COST (a European programme promoting Cooperation in Science and Technology) Action 730 so that finally over 45 scientists from 23 countries (Australia, Canada, Israel, several Europe countries, New Zealand, and the United States) worked together. The work was performed under the umbrella of the WMO Commission on Climatology (CCl). After extensive evaluations, Fiala's multi-node human physiology and thermal comfort model (FPC) was adopted for this study. The model was validated extensively, applying as yet unused data from other research groups, and extended for the purposes of the project. This model was coupled with a state-of-the-art clothing model taking into consideration behavioural adaptation of clothing insulation by the general urban population in response to actual environmental temperature. UTCI was then derived conceptually as an equivalent temperature (ET). Thus, for any combination of air

ZONE BASED PATH ROUTING APPROACH FOR THE DETECTION AND PREVENTION OF MALICIOUS BEHAVIOUR OF THE NODE IN MANET

Directory of Open Access Journals (Sweden)

Akansha Shrivastava

2016-09-01

Full Text Available Mobile Ad-hoc Network (MANET is one of the important research areas. MANET is a cluster of movable nodes that communicate without any wired connection. It refers to a network of moving nodes communicating with other mobile nodes in a multi-hop fashion. Mobile nodes provide flexibility to this network. Thus this flexible network is prone to a variety of attacks. Wormhole attack is a major threat to this network. In this attack, a tunnel is created between two nodes. These nodes transmit all communication through this tunnel. Detecting such attack is a major task. This paper presents a zone-based approach that detects and prevents such attack.

Maximizing Lifetime of Wireless Sensor Networks with Mobile Sink Nodes

Directory of Open Access Journals (Sweden)

Yourong Chen

2014-01-01

Full Text Available In order to maximize network lifetime and balance energy consumption when sink nodes can move, maximizing lifetime of wireless sensor networks with mobile sink nodes (MLMS is researched. The movement path selection method of sink nodes is proposed. Modified subtractive clustering method, k-means method, and nearest neighbor interpolation method are used to obtain the movement paths. The lifetime optimization model is established under flow constraint, energy consumption constraint, link transmission constraint, and other constraints. The model is solved from the perspective of static and mobile data gathering of sink nodes. Subgradient method is used to solve the lifetime optimization model when one sink node stays at one anchor location. Geometric method is used to evaluate the amount of gathering data when sink nodes are moving. Finally, all sensor nodes transmit data according to the optimal data transmission scheme. Sink nodes gather the data along the shortest movement paths. Simulation results show that MLMS can prolong network lifetime, balance node energy consumption, and reduce data gathering latency under appropriate parameters. Under certain conditions, it outperforms Ratio_w, TPGF, RCC, and GRND.

Information spreading in Delay Tolerant Networks based on nodes' behaviors

Science.gov (United States)

Wu, Yahui; Deng, Su; Huang, Hongbin

2014-07-01

Information spreading in DTNs (Delay Tolerant Networks) adopts a store-carry-forward method, and nodes receive the message from others directly. However, it is hard to judge whether the information is safe in this communication mode. In this case, a node may observe other nodes' behaviors. At present, there is no theoretical model to describe the varying rule of the nodes' trusting level. In addition, due to the uncertainty of the connectivity in DTN, a node is hard to get the global state of the network. Therefore, a rational model about the node's trusting level should be a function of the node's own observing result. For example, if a node finds k nodes carrying a message, it may trust the information with probability p(k). This paper does not explore the real distribution of p(k), but instead presents a unifying theoretical framework to evaluate the performance of the information spreading in above case. This framework is an extension of the traditional SI (susceptible-infected) model, and is useful when p(k) conforms to any distribution. Simulations based on both synthetic and real motion traces show the accuracy of the framework. Finally, we explore the impact of the nodes' behaviors based on certain special distributions through numerical results.

Reliability-Aware Cooperative Node Sleeping and Clustering in Duty-Cycled Sensors Networks

Directory of Open Access Journals (Sweden)

Jeungeun Song

2018-01-01

Full Text Available Duty-cycled sensor networks provide a new perspective for improvement of energy efficiency and reliability assurance of multi-hop cooperative sensor networks. In this paper, we consider the energy-efficient cooperative node sleeping and clustering problems in cooperative sensor networks where clusters of relay nodes jointly transmit sensory data to the next hop. Our key idea for guaranteeing reliability is to exploit the on-demand number of cooperative nodes, facilitating the prediction of personalized end-to-end (ETE reliability. Namely, a novel reliability-aware cooperative routing (RCR scheme is proposed to select k-cooperative nodes at every hop (RCR-selection. After selecting k cooperative nodes at every hop, all of the non-cooperative nodes will go into sleep status. In order to solve the cooperative node clustering problem, we propose the RCR-based optimal relay assignment and cooperative data delivery (RCR-delivery scheme to provide a low-communication-overhead data transmission and an optimal duty cycle for a given number of cooperative nodes when the network is dynamic, which enables part of cooperative nodes to switch into idle status for further energy saving. Through the extensive OPNET-based simulations, we show that the proposed scheme significantly outperforms the existing geographic routing schemes and beaconless geographic routings in wireless sensor networks with a highly dynamic wireless channel and controls energy consumption, while ETE reliability is effectively guaranteed.

A bridge role metric model for nodes in software networks.

Directory of Open Access Journals (Sweden)

Bo Li

Full Text Available A bridge role metric model is put forward in this paper. Compared with previous metric models, our solution of a large-scale object-oriented software system as a complex network is inherently more realistic. To acquire nodes and links in an undirected network, a new model that presents the crucial connectivity of a module or the hub instead of only centrality as in previous metric models is presented. Two previous metric models are described for comparison. In addition, it is obvious that the fitting curve between the Bre results and degrees can well be fitted by a power law. The model represents many realistic characteristics of actual software structures, and a hydropower simulation system is taken as an example. This paper makes additional contributions to an accurate understanding of module design of software systems and is expected to be beneficial to software engineering practices.

Data driven CAN node reliability assessment for manufacturing system

Science.gov (United States)

Zhang, Leiming; Yuan, Yong; Lei, Yong

2017-01-01

The reliability of the Controller Area Network(CAN) is critical to the performance and safety of the system. However, direct bus-off time assessment tools are lacking in practice due to inaccessibility of the node information and the complexity of the node interactions upon errors. In order to measure the mean time to bus-off(MTTB) of all the nodes, a novel data driven node bus-off time assessment method for CAN network is proposed by directly using network error information. First, the corresponding network error event sequence for each node is constructed using multiple-layer network error information. Then, the generalized zero inflated Poisson process(GZIP) model is established for each node based on the error event sequence. Finally, the stochastic model is constructed to predict the MTTB of the node. The accelerated case studies with different error injection rates are conducted on a laboratory network to demonstrate the proposed method, where the network errors are generated by a computer controlled error injection system. Experiment results show that the MTTB of nodes predicted by the proposed method agree well with observations in the case studies. The proposed data driven node time to bus-off assessment method for CAN networks can successfully predict the MTTB of nodes by directly using network error event data.

Regression Nodes: Extending attack trees with data from social sciences

NARCIS (Netherlands)

Bullee, Jan-Willem; Montoya, L.; Pieters, Wolter; Junger, Marianne; Hartel, Pieter H.

In the field of security, attack trees are often used to assess security vulnerabilities probabilistically in relation to multi-step attacks. The nodes are usually connected via AND-gates, where all children must be executed, or via OR-gates, where only one action is necessary for the attack step to

Gene expression profiles in auricle skin as a possible additional endpoint for determination of sensitizers: A multi-endpoint evaluation of the local lymph node assay.

Science.gov (United States)

Tsuchiyama, Hiromi; Maeda, Akihisa; Nakajima, Mayumi; Kitsukawa, Mika; Takahashi, Kei; Miyoshi, Tomoya; Mutsuga, Mayu; Asaoka, Yoshiji; Miyamoto, Yohei; Oshida, Keiyu

2017-10-05

The murine local lymph node assay (LLNA) is widely used to test chemicals to induce skin sensitization. Exposure of mouse auricle skin to a sensitizer results in proliferation of local lymph node T cells, which has been measured by in vivo incorporation of H 3 -methyl thymidine or 5-bromo-2'-deoxyuridine (BrdU). The stimulation index (SI), the ratio of the mean proliferation in each treated group to that in the concurrent vehicle control group, is frequently used as a regulatory-authorized endpoint for LLNA. However, some non-sensitizing irritants, such as sodium dodecyl sulfate (SDS) or methyl salicylate (MS), have been reported as false-positives by this endpoint. In search of a potential endpoint to enhance the specificity of existing endpoints, we evaluated 3 contact sensitizers; (hexyl cinnamic aldehyde [HCA], oxazolone [OXA], and 2,4-dinitrochlorobenzene [DNCB]), 1 respiratory sensitizer (toluene 2,4-diisocyanate [TDI]), and 2 non-sensitizing irritants (MS and SDS) by several endpoints in LLNA. Each test substance was applied to both ears of female CBA/Ca mice daily for 3 consecutive days. The ears and auricle lymph node cells were analyzed on day 5 for endpoints including the SI value, lymph node cell count, cytokine release from lymph node cells, and histopathological changes and gene expression profiles in auricle skin. The SI values indicated that all the test substances induced significant proliferation of lymph node cells. The lymph node cell counts showed no significant changes by the non-sensitizers assessed. The inflammatory findings of histopathology were similar among the auricle skins treated by sensitizers and irritants. Gene expression profiles of cytokines IFN-γ, IL-4, and IL-17 in auricle skin were similar to the cytokine release profiles in draining lymph node cells. In addition, the gene expression of the chemokine CXCL1 and/or CXCL2 showed that it has the potential to discriminate sensitizers and non-sensitizing irritants. Our results

Secure message authentication system for node to node network

Science.gov (United States)

Sindhu, R.; Vanitha, M. M.; Norman, J.

2017-10-01

The Message verification remains some of the best actual methods for prevent the illegal and dis honored communication after presence progressed to WSNs (Wireless Sensor Networks). Intend for this purpose, several message verification systems must stand established, created on both symmetric key cryptography otherwise public key cryptosystems. Best of them will have some limits for great computational then statement above in count of deficiency of climb ability then flexibility in node settlement occurrence. In a polynomial based system was newly presented for these problems. Though, this system then situations delay will must the dimness of integral limitation firm in the point of polynomial: once the amount of message transferred remains the greater than the limitation then the opponent will completely improve the polynomial approaches. This paper suggests using ECC (Elliptic Curve Cryptography). Though using the node verification the technique in this paper permits some nodes to transfer a limitless amount of messages lacking misery in the limit problem. This system will have the message cause secrecy. Equally theoretic study then model effects show our planned system will be effective than the polynomial based method in positions of calculation then statement above in privacy points though message basis privacy.

Multi-model analysis in hydrological prediction

Science.gov (United States)

Lanthier, M.; Arsenault, R.; Brissette, F.

2017-12-01

Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

Node cookbook

CERN Document Server

Clements, David Mark

2014-01-01

In Node Cookbook Second Edition, each chapter focuses on a different aspect of working with Node. Following a Cookbook structure, the recipes are written in an easy-to-understand language. Readers will find it easier to grasp even the complex recipes which are backed by lots of illustrations, tips, and hints.If you have some knowledge of JavaScript and want to build fast, efficient, scalable client-server solutions, then Node Cookbook Second Edition is for you. Knowledge of Node will be an advantage but is not required. Experienced users of Node will be able to improve their skills.

Node-node correlations and transport properties in scale-free networks

Science.gov (United States)

Obregon, Bibiana; Guzman, Lev

2011-03-01

We study some transport properties of complex networks. We focus our attention on transport properties of scale-free and small-world networks and compare two types of transport: Electric and max-flow cases. In particular, we construct scale-free networks, with a given degree sequence, to estimate the distribution of conductances for different values of assortative/dissortative mixing. For the electric case we find that the distributions of conductances are affect ed by the assortative mixing of the network whereas for the max-flow case, the distributions almost do not show changes when node-node correlations are altered. Finally, we compare local and global transport in terms of the average conductance for the small-world (Watts-Strogatz) model

Integrated multi-scale modelling and simulation of nuclear fuels

International Nuclear Information System (INIS)

Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.

2015-01-01

This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)

Risk model in stage IB1-IIB cervical cancer with positive node after radical hysterectomy

Directory of Open Access Journals (Sweden)

Chen Z

2016-05-01

Full Text Available Zhilan Chen,1,2,* Kecheng Huang,1,* Zhiyong Lu,1,3 Song Deng,1,4 Jiaqiang Xiong,1 Jia Huang,1 Xiong Li,5 Fangxu Tang,1 Zhihao Wang,6 Haiying Sun,1 Lin Wang,1 Shasha Zhou,1 Xiaoli Wang,1 Yao Jia,1 Ting Hu,1 Juan Gui,7 Dongyi Wan,1 Ding Ma,1 Shuang Li,1 Shixuan Wang11Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Techonology, Wuhan, 2Department of Obstetrics and Gynecology, Wuhan General Hospital of Guangzhou Military Command, Wuhan, 3Hubei Key Laboratory of Embryonic Stem Cell Research, Tai-He Hospital, Hubei University of Medicine, Shiyan, Hubei, 4Department of Obstetrics and Gynecology, University Hospital of Hubei University for Nationalities, Enshi, Hubei, 5Department of Obstetrics and Gynecology, Wuhan Central Hospital, Wuhan, 6Department of Pathology and Pathophysiology, Key Laboratory of Ministry of Education of China for Neurological Disorders, Huazhong University of Science and Techonology, Wuhan, 7Department of Obstetrics and Gynecology, Renmin Hospital, Wuhan University, Wuhan, People’s Republic of China*These authors contributed equally to this workAbstract: The purpose of this study was to identify risk factors in patients with surgically treated node-positive IB1-IIB cervical cancer and to establish a risk model for disease-free survival (DFS and overall survival (OS. A total of 170 patients who underwent radical hysterectomy and bilateral pelvic lymphadenectomy as primary treatment for node-positive International Federation of Gynaecology and Obstetrics (FIGO stage IB1-IIB cervical cancer from January 2002 to December 2008 were retrospectively analyzed. Five published risk models were evaluated in this population. The variables, including common iliac lymph node metastasis and parametrial invasion, were independent predictors of outcome in a multivariate analysis using a Cox regression model. Three distinct prognostic groups (low, intermediate, and high risk

Routing protocol for wireless quantum multi-hop mesh backbone network based on partially entangled GHZ state

Science.gov (United States)

Xiong, Pei-Ying; Yu, Xu-Tao; Zhang, Zai-Chen; Zhan, Hai-Tao; Hua, Jing-Yu

2017-08-01

Quantum multi-hop teleportation is important in the field of quantum communication. In this study, we propose a quantum multi-hop communication model and a quantum routing protocol with multihop teleportation for wireless mesh backbone networks. Based on an analysis of quantum multi-hop protocols, a partially entangled Greenberger-Horne-Zeilinger (GHZ) state is selected as the quantum channel for the proposed protocol. Both quantum and classical wireless channels exist between two neighboring nodes along the route. With the proposed routing protocol, quantum information can be transmitted hop by hop from the source node to the destination node. Based on multi-hop teleportation based on the partially entangled GHZ state, a quantum route established with the minimum number of hops. The difference between our routing protocol and the classical one is that in the former, the processes used to find a quantum route and establish quantum channel entanglement occur simultaneously. The Bell state measurement results of each hop are piggybacked to quantum route finding information. This method reduces the total number of packets and the magnitude of air interface delay. The deduction of the establishment of a quantum channel between source and destination is also presented here. The final success probability of quantum multi-hop teleportation in wireless mesh backbone networks was simulated and analyzed. Our research shows that quantum multi-hop teleportation in wireless mesh backbone networks through a partially entangled GHZ state is feasible.

Multi-petascale highly efficient parallel supercomputer

Science.gov (United States)

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.; Blumrich, Matthias A.; Boyle, Peter; Brunheroto, Jose R.; Chen, Dong; Cher, Chen-Yong; Chiu, George L.; Christ, Norman; Coteus, Paul W.; Davis, Kristan D.; Dozsa, Gabor J.; Eichenberger, Alexandre E.; Eisley, Noel A.; Ellavsky, Matthew R.; Evans, Kahn C.; Fleischer, Bruce M.; Fox, Thomas W.; Gara, Alan; Giampapa, Mark E.; Gooding, Thomas M.; Gschwind, Michael K.; Gunnels, John A.; Hall, Shawn A.; Haring, Rudolf A.; Heidelberger, Philip; Inglett, Todd A.; Knudson, Brant L.; Kopcsay, Gerard V.; Kumar, Sameer; Mamidala, Amith R.; Marcella, James A.; Megerian, Mark G.; Miller, Douglas R.; Miller, Samuel J.; Muff, Adam J.; Mundy, Michael B.; O'Brien, John K.; O'Brien, Kathryn M.; Ohmacht, Martin; Parker, Jeffrey J.; Poole, Ruth J.; Ratterman, Joseph D.; Salapura, Valentina; Satterfield, David L.; Senger, Robert M.; Steinmacher-Burow, Burkhard; Stockdell, William M.; Stunkel, Craig B.; Sugavanam, Krishnan; Sugawara, Yutaka; Takken, Todd E.; Trager, Barry M.; Van Oosten, James L.; Wait, Charles D.; Walkup, Robert E.; Watson, Alfred T.; Wisniewski, Robert W.; Wu, Peng

2018-05-15

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time and supports DMA functionality allowing for parallel processing message-passing.

The Influence of Total Nodes Examined, Number of Positive Nodes, and Lymph Node Ratio on Survival After Surgical Resection and Adjuvant Chemoradiation for Pancreatic Cancer: A Secondary Analysis of RTOG 9704

Energy Technology Data Exchange (ETDEWEB)

Showalter, Timothy N. [Department of Radiation Oncology, Jefferson Medical College, Thomas Jefferson University, Philadelphia, PA (United States); Winter, Kathryn A. [Radiation Therapy Oncology Group, RTOG Statistical Center, Philadelphia, PA (United States); Berger, Adam C., E-mail: adam.berger@jefferson.edu [Department of Surgery, Jefferson Medical College, Thomas Jefferson University, Philadelphia, PA (United States); Regine, William F. [Department of Radiation Oncology, University of Maryland Medical Center, Baltimore, MD (United States); Abrams, Ross A. [Department of Radiation Oncology, Rush University Medical Center, Chicago, IL (United States); Safran, Howard [Department of Medicine, Miriam Hospital, Brown University Oncology Group, Providence, RI (United States); Hoffman, John P. [Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA (United States); Benson, Al B. [Division of Hematology-Oncology, Northwestern University, Chicago, IL (United States); MacDonald, John S. [St. Vincent' s Cancer Care Center, New York, NY (United States); Willett, Christopher G. [Department of Radiation Oncology, Duke University Medical Center, Durham, NC (United States)

2011-12-01

Purpose: Lymph node status is an important predictor of survival in pancreatic cancer. We performed a secondary analysis of Radiation Therapy Oncology Group (RTOG) 9704, an adjuvant chemotherapy and chemoradiation trial, to determine the influence of lymph node factors-number of positive nodes (NPN), total nodes examined (TNE), and lymph node ratio (LNR ratio of NPN to TNE)-on OS and disease-free survival (DFS). Patient and Methods: Eligible patients from RTOG 9704 form the basis of this secondary analysis of lymph node parameters. Actuarial estimates for OS and DFS were calculated using Kaplan-Meier methods. Cox proportional hazards models were performed to evaluate associations of NPN, TNE, and LNR with OS and DFS. Multivariate Cox proportional hazards models were also performed. Results: There were 538 patients enrolled in the RTOG 9704 trial. Of these, 445 patients were eligible with lymph nodes removed. Overall median NPN was 1 (min-max, 0-18). Increased NPN was associated with worse OS (HR = 1.06, p = 0.001) and DFS (HR = 1.05, p = 0.01). In multivariate analyses, both NPN and TNE were associated with OS and DFS. TNE > 12, and >15 were associated with increased OS for all patients, but not for node-negative patients (n = 142). Increased LNR was associated with worse OS (HR = 1.01, p < 0.0001) and DFS (HR = 1.006, p = 0.002). Conclusion: In patients who undergo surgical resection followed by adjuvant chemoradiation, TNE, NPN, and LNR are associated with OS and DFS. This secondary analysis of a prospective, cooperative group trial supports the influence of these lymph node parameters on outcomes after surgery and adjuvant therapy using contemporary techniques.

Suppressing epidemics on networks by exploiting observer nodes.

Science.gov (United States)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Suppressing epidemics on networks by exploiting observer nodes

Science.gov (United States)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Minimizing size of decision trees for multi-label decision tables

KAUST Repository

Azad, Mohammad

2014-09-29

We used decision tree as a model to discover the knowledge from multi-label decision tables where each row has a set of decisions attached to it and our goal is to find out one arbitrary decision from the set of decisions attached to a row. The size of the decision tree can be small as well as very large. We study here different greedy as well as dynamic programming algorithms to minimize the size of the decision trees. When we compare the optimal result from dynamic programming algorithm, we found some greedy algorithms produce results which are close to the optimal result for the minimization of number of nodes (at most 18.92% difference), number of nonterminal nodes (at most 20.76% difference), and number of terminal nodes (at most 18.71% difference).

Minimizing size of decision trees for multi-label decision tables

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2014-01-01

We used decision tree as a model to discover the knowledge from multi-label decision tables where each row has a set of decisions attached to it and our goal is to find out one arbitrary decision from the set of decisions attached to a row. The size of the decision tree can be small as well as very large. We study here different greedy as well as dynamic programming algorithms to minimize the size of the decision trees. When we compare the optimal result from dynamic programming algorithm, we found some greedy algorithms produce results which are close to the optimal result for the minimization of number of nodes (at most 18.92% difference), number of nonterminal nodes (at most 20.76% difference), and number of terminal nodes (at most 18.71% difference).

Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network.

Science.gov (United States)

Han, Changcai; Yang, Jinsheng

2017-10-30

The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes.

Microphysics in Multi-scale Modeling System with Unified Physics

Science.gov (United States)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Oology and the evolution of thermophysiology in saurischian dinosaurs: homeotherm and endotherm deinonychosaurians?

Directory of Open Access Journals (Sweden)

Gerald Grellet-Tinner

2006-01-01

Full Text Available The origin of avian endothermy is a long-held question the answer of which cannot be provided by first level observations. Oological and reproductive characters have collectively provided a new source of data useful for phylogenetic analyses and paleobiological inferences. In addition, the observations of reproductive and oological evolutionary trends in saurischian dinosaurs lead to the interpretation that not only, the thermophysiology of these dinosaurs progressively became more avian-like but after re-examination allows to infer that deinonychosaurians represented here by three troodontids and one dromaeosaurid might already have developed an avian-like endothermy, thus predating the rise of avians. These results based on reproductive traits are independently corroborated by the discoveries of troodontid dinosaurs 1 in high latitudes, 2 covered with feathers in Chinese Lagerstätten, and recently 3 fossilized in a death pose identical to an avian sleeping posture.A origem da endotermia nas aves é uma questão há muito discutida e sua resposta não pode ser encontrada através de observações superficiais. Caracteres oológicos e reprodutivos surgiram como uma nova fonte de dados relevantes tanto para análises filogenéticas quanto para inferências paleobiológicas dos dinossauros Saurischia. Além disso, as observações das tendências evolutivas reprodutivas e oológicas nos dinossauros Saurischia nos levam a inferir que não apenas, como anteriormente a termofisiologia deste grupo de dinossauros tornou-se progressivamente ornítica, mas um posterior reexame nos permitiu concluir que os deinonicossauros, representados aqui por dois troodontídeos e um dromeossaurídeo, provavelmente já haviam desenvolvido uma endotermia semelhante a das aves, anterior, portanto, ao seu surgimento. Estes resultados baseados em características reprodutivas são independentemente corroborados pela descoberta dos dinossauros troodontídeos 1 em altas

The Goddard multi-scale modeling system with unified physics

Directory of Open Access Journals (Sweden)

W.-K. Tao

2009-08-01

Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.

This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.

Allocating resources between network nodes for providing a network node function

NARCIS (Netherlands)

Strijkers, R.J.; Meulenhoff, P.J.

2014-01-01

The invention provides a method wherein a first network node advertises available resources that a second network node may use to offload network node functions transparently to the first network node. Examples of the first network node are a client device (e.g. PC, notebook, tablet, smart phone), a

Multi-sector thermophysiological head simulator for headgear research

OpenAIRE

Martínez Guillamón, Natividad

2016-01-01

[EN] Predicting thermal comfort perceived during wearing protective clothing is important especially for the head as it is one of the most sensitive body parts to heat. Since helmets typically induce an additional thermal insulation that impairs the heat dissipation from the head, a special attention should be drawn to a heat strain leading to a decrease of the cognitive performance and to adverse health effects. Thermal manikins allow systematic analysis of the heat and mass transfer prop...

Lymph node detection in IASLC-defined zones on PET/CT images

Science.gov (United States)

Song, Yihua; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2016-03-01

Lymph node detection is challenging due to the low contrast between lymph nodes as well as surrounding soft tissues and the variation in nodal size and shape. In this paper, we propose several novel ideas which are combined into a system to operate on positron emission tomography/ computed tomography (PET/CT) images to detect abnormal thoracic nodes. First, our previous Automatic Anatomy Recognition (AAR) approach is modified where lymph node zones predominantly following International Association for the Study of Lung Cancer (IASLC) specifications are modeled as objects arranged in a hierarchy along with key anatomic anchor objects. This fuzzy anatomy model built from diagnostic CT images is then deployed on PET/CT images for automatically recognizing the zones. A novel globular filter (g-filter) to detect blob-like objects over a specified range of sizes is designed to detect the most likely locations and sizes of diseased nodes. Abnormal nodes within each automatically localized zone are subsequently detected via combined use of different items of information at various scales: lymph node zone model poses found at recognition indicating the geographic layout at the global level of node clusters, g-filter response which hones in on and carefully selects node-like globular objects at the node level, and CT and PET gray value but within only the most plausible nodal regions for node presence at the voxel level. The models are built from 25 diagnostic CT scans and refined for an object hierarchy based on a separate set of 20 diagnostic CT scans. Node detection is tested on an additional set of 20 PET/CT scans. Our preliminary results indicate node detection sensitivity and specificity at around 90% and 85%, respectively.

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

Science.gov (United States)

Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

2014-01-27

(k)(i) values were used as inputs for different ANNs in order to discriminate correct node connectivity patterns from incorrect random patterns. The MIANN models obtained present good values of Sensitivity/Specificity (%): MRNs (78/78), IWDBNs (90/88), and SFLN (86/84). These preliminary results are very promising from the point of view of a first exploratory study and suggest that the use of these models could be extended to the high-throughput re-evaluation of connectivity in known complex networks (collation).

Assessment of body mapping sportswear using a manikin operated in constant temperature mode and thermoregulatory model control mode

Science.gov (United States)

Wang, Faming; Del Ferraro, Simona; Molinaro, Vincenzo; Morrissey, Matthew; Rossi, René

2014-09-01

Regional sweating patterns and body surface temperature differences exist between genders. Traditional sportswear made from one material and/or one fabric structure has a limited ability to provide athletes sufficient local wear comfort. Body mapping sportswear consists of one piece of multiple knit structure fabric or of different fabric pieces that may provide athletes better wear comfort. In this study, the `modular' body mapping sportswear was designed and subsequently assessed on a `Newton' type sweating manikin that operated in both constant temperature mode and thermophysiological model control mode. The performance of the modular body mapping sportswear kit and commercial products were also compared. The results demonstrated that such a modular body mapping sportswear kit can meet multiple wear/thermal comfort requirements in various environmental conditions. All body mapping clothing (BMC) presented limited global thermophysiological benefits for the wearers. Nevertheless, BMC showed evident improvements in adjusting local body heat exchanges and local thermal sensations.

A Multi-Hop Advertising Discovery and Delivering Protocol for Multi Administrative Domain MANET

Directory of Open Access Journals (Sweden)

Federico Mari

2013-01-01

Full Text Available A Mobile Ad-hoc NETwork (MANET is Multi Administrative Domain (MAD if each network node belongs to an independent authority, that is each node owns its resources and there is no central authority owning all network nodes. One of the main obstructions in designing Service Advertising, Discovery and Delivery (SADD protocol for MAD MANETs is the fact that, in an attempt to increase their own visibility, network nodes tend to flood the network with their advertisements. In this paper, we present a SADD protocol for MAD MANET, based on Bloom filters, that effectively prevents advertising floods due to such misbehaving nodes. Our results with the ns-2 simulator show that our SADD protocol is effective in counteracting advertising floods, it keeps low the collision rate as well as the energy consumption while ensuring that each peer receives all messages broadcasted by other peers.

Cross-Dependency Inference in Multi-Layered Networks: A Collaborative Filtering Perspective.

Science.gov (United States)

Chen, Chen; Tong, Hanghang; Xie, Lei; Ying, Lei; He, Qing

2017-08-01

The increasingly connected world has catalyzed the fusion of networks from different domains, which facilitates the emergence of a new network model-multi-layered networks. Examples of such kind of network systems include critical infrastructure networks, biological systems, organization-level collaborations, cross-platform e-commerce, and so forth. One crucial structure that distances multi-layered network from other network models is its cross-layer dependency, which describes the associations between the nodes from different layers. Needless to say, the cross-layer dependency in the network plays an essential role in many data mining applications like system robustness analysis and complex network control. However, it remains a daunting task to know the exact dependency relationships due to noise, limited accessibility, and so forth. In this article, we tackle the cross-layer dependency inference problem by modeling it as a collective collaborative filtering problem. Based on this idea, we propose an effective algorithm Fascinate that can reveal unobserved dependencies with linear complexity. Moreover, we derive Fascinate-ZERO, an online variant of Fascinate that can respond to a newly added node timely by checking its neighborhood dependencies. We perform extensive evaluations on real datasets to substantiate the superiority of our proposed approaches.

A random network based, node attraction facilitated network evolution method

Directory of Open Access Journals (Sweden)

WenJun Zhang

2016-03-01

Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

Two-Way Multi-Antenna Relaying with Simultaneous Wireless Information and Power Transfer

Directory of Open Access Journals (Sweden)

Thanaphat Srivantana

2017-03-01

Full Text Available In this paper, we propose various kinds of two-way multi-antenna relaying with simultaneous wireless information and power transfer (SWIPT and investigate their performance. Specifically, we first consider a two-way relay network where two single-antenna end nodes communicate with each other through a multi-antenna relay node that is energy constrained. This relay node harvests energy from the two end nodes and use the harvested energy for forwarding their information. Six relaying schemes that support the considered network then build on the power splitting-based relaying and time switching-based relaying protocols. The average bit error rates of these schemes are evaluated and compared by computer simulations considering several network parameters, including the number of relay antennas, power splitting ratio, and energy harvesting time. Such evaluation and comparison provide useful insights into the performance of SWIPT-based two-way multi-antenna relaying.

Triangular node for Transmission-Line Modeling (TLM) applied to bio-heat transfer.

Science.gov (United States)

Milan, Hugo F M; Gebremedhin, Kifle G

2016-12-01

Transmission-Line Modeling (TLM) is a numerical method used to solve complex and time-domain bio-heat transfer problems. In TLM, rectangles are used to discretize two-dimensional problems. The drawback in using rectangular shapes is that instead of refining only the domain of interest, a large additional domain will also be refined in the x and y axes, which results in increased computational time and memory space. In this paper, we developed a triangular node for TLM applied to bio-heat transfer that does not have the drawback associated with the rectangular nodes. The model includes heat source, blood perfusion (advection), boundary conditions and initial conditions. The boundary conditions could be adiabatic, temperature, heat flux, or convection. A matrix equation for TLM, which simplifies the solution of time-domain problems or solves steady-state problems, was also developed. The predicted results were compared against results obtained from the solution of a simplified two-dimensional problem, and they agreed within 1% for a mesh length of triangular faces of 59µm±9µm (mean±standard deviation) and a time step of 1ms. Copyright © 2016 Elsevier Ltd. All rights reserved.

A morphologically preserved multi-resolution TIN surface modeling and visualization method for virtual globes

Science.gov (United States)

Zheng, Xianwei; Xiong, Hanjiang; Gong, Jianya; Yue, Linwei

2017-07-01

Virtual globes play an important role in representing three-dimensional models of the Earth. To extend the functioning of a virtual globe beyond that of a "geobrowser", the accuracy of the geospatial data in the processing and representation should be of special concern for the scientific analysis and evaluation. In this study, we propose a method for the processing of large-scale terrain data for virtual globe visualization and analysis. The proposed method aims to construct a morphologically preserved multi-resolution triangulated irregular network (TIN) pyramid for virtual globes to accurately represent the landscape surface and simultaneously satisfy the demands of applications at different scales. By introducing cartographic principles, the TIN model in each layer is controlled with a data quality standard to formulize its level of detail generation. A point-additive algorithm is used to iteratively construct the multi-resolution TIN pyramid. The extracted landscape features are also incorporated to constrain the TIN structure, thus preserving the basic morphological shapes of the terrain surface at different levels. During the iterative construction process, the TIN in each layer is seamlessly partitioned based on a virtual node structure, and tiled with a global quadtree structure. Finally, an adaptive tessellation approach is adopted to eliminate terrain cracks in the real-time out-of-core spherical terrain rendering. The experiments undertaken in this study confirmed that the proposed method performs well in multi-resolution terrain representation, and produces high-quality underlying data that satisfy the demands of scientific analysis and evaluation.

Node-based measures of connectivity in genetic networks.

Science.gov (United States)

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

2016-01-01

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

Allocating resources between network nodes for providing a network node function

OpenAIRE

Strijkers, R.J.; Meulenhoff, P.J.

2014-01-01

The invention provides a method wherein a first network node advertises available resources that a second network node may use to offload network node functions transparently to the first network node. Examples of the first network node are a client device (e.g. PC, notebook, tablet, smart phone), a server (e.g. application server, a proxy server, cloud location, router). Examples of the second network node are an application server, a cloud location or a router. The available resources may b...

A multi-state model for the reliability assessment of a distributed generation system via universal generating function

International Nuclear Information System (INIS)

Li, Yan-Fu; Zio, Enrico

2012-01-01

The current and future developments of electric power systems are pushing the boundaries of reliability assessment to consider distribution networks with renewable generators. Given the stochastic features of these elements, most modeling approaches rely on Monte Carlo simulation. The computational costs associated to the simulation approach force to treating mostly small-sized systems, i.e. with a limited number of lumped components of a given renewable technology (e.g. wind or solar, etc.) whose behavior is described by a binary state, working or failed. In this paper, we propose an analytical multi-state modeling approach for the reliability assessment of distributed generation (DG). The approach allows looking to a number of diverse energy generation technologies distributed on the system. Multiple states are used to describe the randomness in the generation units, due to the stochastic nature of the generation sources and of the mechanical degradation/failure behavior of the generation systems. The universal generating function (UGF) technique is used for the individual component multi-state modeling. A multiplication-type composition operator is introduced to combine the UGFs for the mechanical degradation and renewable generation source states into the UGF of the renewable generator power output. The overall multi-state DG system UGF is then constructed and classical reliability indices (e.g. loss of load expectation (LOLE), expected energy not supplied (EENS)) are computed from the DG system generation and load UGFs. An application of the model is shown on a DG system adapted from the IEEE 34 nodes distribution test feeder.

Identifying Vulnerable Nodes of Complex Networks in Cascading Failures Induced by Node-Based Attacks

Directory of Open Access Journals (Sweden)

Shudong Li

2013-01-01

Full Text Available In the research on network security, distinguishing the vulnerable components of networks is very important for protecting infrastructures systems. Here, we probe how to identify the vulnerable nodes of complex networks in cascading failures, which was ignored before. Concerned with random attack (RA and highest load attack (HL on nodes, we model cascading dynamics of complex networks. Then, we introduce four kinds of weighting methods to characterize the nodes of networks including Barabási-Albert scale-free networks (SF, Watts-Strogatz small-world networks (WS, Erdos-Renyi random networks (ER, and two real-world networks. The simulations show that, for SF networks under HL attack, the nodes with small value of the fourth kind of weight are the most vulnerable and the ones with small value of the third weight are also vulnerable. Also, the real-world autonomous system with power-law distribution verifies these findings. Moreover, for WS and ER networks under both RA and HL attack, when the nodes have low tolerant ability, the ones with small value of the fourth kind of weight are more vulnerable and also the ones with high degree are easier to break down. The results give us important theoretical basis for digging the potential safety loophole and making protection strategy.

Immune networks: multi-tasking capabilities at medium load

Science.gov (United States)

Agliari, E.; Annibale, A.; Barra, A.; Coolen, A. C. C.; Tantari, D.

2013-08-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ˜ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ˜ Nδ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ frameworks are required to achieve effective retrieval.

Quality models for audiovisual streaming

Science.gov (United States)

Thang, Truong Cong; Kim, Young Suk; Kim, Cheon Seog; Ro, Yong Man

2006-01-01

Quality is an essential factor in multimedia communication, especially in compression and adaptation. Quality metrics can be divided into three categories: within-modality quality, cross-modality quality, and multi-modality quality. Most research has so far focused on within-modality quality. Moreover, quality is normally just considered from the perceptual perspective. In practice, content may be drastically adapted, even converted to another modality. In this case, we should consider the quality from semantic perspective as well. In this work, we investigate the multi-modality quality from the semantic perspective. To model the semantic quality, we apply the concept of "conceptual graph", which consists of semantic nodes and relations between the nodes. As an typical of multi-modality example, we focus on audiovisual streaming service. Specifically, we evaluate the amount of information conveyed by a audiovisual content where both video and audio channels may be strongly degraded, even audio are converted to text. In the experiments, we also consider the perceptual quality model of audiovisual content, so as to see the difference with semantic quality model.

Degrees-of-Freedom of the MIMO Three-Way Channel with Node-Intermittency

KAUST Repository

Neu, Joachim

2017-08-28

The characterization of fundamental performance bounds of many-to-many communication systems in which participating nodes are active in an intermittent way is one of the major challenges in communication theory. In order to address this issue, we introduce the multiple-input multiple-output (MIMO) three-way channel (3WC) with an intermittent node and study its degrees-of-freedom (DoF) region and sum-DoF. We devise a non-adaptive encoding scheme based on zero-forcing, interference alignment and erasure coding, and show its DoF region (and thus sum-DoF) optimality for non-intermittent 3WCs and its sum-DoF optimality for (node-)intermittent 3WCs. However, we show by example that in general some DoF tuples in the intermittent 3WC can only be achieved by adaptive schemes, such as multi-hop or decode-forward relaying. This shows that non-adaptive encoding is sufficient for the non-intermittent 3WC and for the sum-DoF of intermittent 3WCs, but adaptive encoding is necessary for the DoF region of intermittent 3WCs. Our work contributes to a better understanding of the fundamental limits of multi-way communication systems with intermittency and the impact of adaptation therein.

A Topology Evolution Model Based on Revised PageRank Algorithm and Node Importance for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Xiaogang Qi

2015-01-01

Full Text Available Wireless sensor network (WSN is a classical self-organizing communication network, and its topology evolution currently becomes one of the attractive issues in this research field. Accordingly, the problem is divided into two subproblems: one is to design a new preferential attachment method and the other is to analyze the dynamics of the network topology evolution. To solve the first subproblem, a revised PageRank algorithm, called Con-rank, is proposed to evaluate the node importance upon the existing node contraction, and then a novel preferential attachment is designed based on the node importance calculated by the proposed Con-rank algorithm. To solve the second one, we firstly analyze the network topology evolution dynamics in a theoretical way and then simulate the evolution process. Theoretical analysis proves that the network topology evolution of our model agrees with power-law distribution, and simulation results are well consistent with our conclusions obtained from the theoretical analysis and simultaneously show that our topology evolution model is superior to the classic BA model in the average path length and the clustering coefficient, and the network topology is more robust and can tolerate the random attacks.

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Low Power Multi-Hop Networking Analysis in Intelligent Environments.

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-05-19

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

Generalised linear models for correlated pseudo-observations, with applications to multi-state models

DEFF Research Database (Denmark)

Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne

2003-01-01

Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

International Nuclear Information System (INIS)

Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

2013-01-01

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network

Cluster synchronization induced by one-node clusters in networks with asymmetric negative couplings

Science.gov (United States)

Zhang, Jianbao; Ma, Zhongjun; Zhang, Gang

2013-12-01

This paper deals with the problem of cluster synchronization in networks with asymmetric negative couplings. By decomposing the coupling matrix into three matrices, and employing Lyapunov function method, sufficient conditions are derived for cluster synchronization. The conditions show that the couplings of multi-node clusters from one-node clusters have beneficial effects on cluster synchronization. Based on the effects of the one-node clusters, an effective and universal control scheme is put forward for the first time. The obtained results may help us better understand the relation between cluster synchronization and cluster structures of the networks. The validity of the control scheme is confirmed through two numerical simulations, in a network with no cluster structure and in a scale-free network.

Self-Organization Scheme for Balanced Routing in Large-Scale Multi-Hop Networks

DEFF Research Database (Denmark)

Badiu, Mihai Alin; Saad, David; Coon, Justin P.

2018-01-01

We propose a self-organization scheme for cost-effective and load-balanced routing in multi-hop networks. To avoid overloading nodes that provide favourable routing conditions, we assign each node with a cost function that penalizes high loads. Thus, finding routes to sink nodes is formulated...

Competitive dynamics of lexical innovations in multi-layer networks

Science.gov (United States)

Javarone, Marco Alberto

2014-04-01

We study the introduction of lexical innovations into a community of language users. Lexical innovations, i.e. new term added to people's vocabulary, plays an important role in the process of language evolution. Nowadays, information is spread through a variety of networks, including, among others, online and offline social networks and the World Wide Web. The entire system, comprising networks of different nature, can be represented as a multi-layer network. In this context, lexical innovations diffusion occurs in a peculiar fashion. In particular, a lexical innovation can undergo three different processes: its original meaning is accepted; its meaning can be changed or misunderstood (e.g. when not properly explained), hence more than one meaning can emerge in the population. Lastly, in the case of a loan word, it can be translated into the population language (i.e. defining a new lexical innovation or using a synonym) or into a dialect spoken by part of the population. Therefore, lexical innovations cannot be considered simply as information. We develop a model for analyzing this scenario using a multi-layer network comprising a social network and a media network. The latter represents the set of all information systems of a society, e.g. television, the World Wide Web and radio. Furthermore, we identify temporal directed edges between the nodes of these two networks. In particular, at each time-step, nodes of the media network can be connected to randomly chosen nodes of the social network and vice versa. In doing so, information spreads through the whole system and people can share a lexical innovation with their neighbors or, in the event they work as reporters, by using media nodes. Lastly, we use the concept of "linguistic sign" to model lexical innovations, showing its fundamental role in the study of these dynamics. Many numerical simulations have been performed to analyze the proposed model and its outcomes.

The sentinel lymph node spread determines quantitatively melanoma seeding to non-sentinel lymph nodes and survival.

Science.gov (United States)

Ulmer, Anja; Dietz, Klaus; Werner-Klein, Melanie; Häfner, Hans-Martin; Schulz, Claudia; Renner, Philipp; Weber, Florian; Breuninger, Helmut; Röcken, Martin; Garbe, Claus; Fierlbeck, Gerhard; Klein, Christoph A

2018-03-01

Complete lymph node dissection (CLND) after a positive sentinel node (SN) biopsy provides important prognostic information in melanoma patients but has been questioned for therapeutic use recently. We explored whether quantification of the tumour spread to SNs may replace histopathology of non-sentinel nodes (NSNs) for staging purposes. We quantified melanoma spread in SNs and NSNs in 128 patients undergoing CLND for a positive SN. In addition to routine histopathology, one-half of each of all 1496 SNs and NSNs was disaggregated into a single cell suspension and stained immunocytochemically to determine the number of melanoma cells per 10 6 lymph node cells, i.e. the disseminated cancer cell density (DCCD). We uncovered melanoma spread to NSNs in the majority of patients; however, the tumour load and the proportion of positive nodes were significantly lower in NSNs than in SNs. The relation between SN and NSN spread could be described by a mathematical function with DCCD NSN  = DCCD SN c /10 1 - c (c = 0.69; 95% confidence interval [CI]: 0.62-0.76). At a median follow-up of 67 months, multivariable Cox regression analyses revealed that DCCD SN (p = 0.02; HR 1.34, 95% CI: 1.05-1.71) and the total number of pathologically positive nodes (p = 0.02; HR 1.53, 95% CI: 1.07-2.22) were significant risk factors after controlling for age, gender, thickness of melanoma and ulceration status. A prognostic model based on DCCD SN and melanoma thickness predicted outcome as accurately as a model including pathological information of both SNs and NSNs. The assessment of DCCD SN renders CLND for staging purposes unnecessary. Copyright © 2017 Elsevier Ltd. All rights reserved.

Interactive Graph Layout of a Million Nodes

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Peng Mi

2016-12-01

Full Text Available Sensemaking of large graphs, specifically those with millions of nodes, is a crucial task in many fields. Automatic graph layout algorithms, augmented with real-time human-in-the-loop interaction, can potentially support sensemaking of large graphs. However, designing interactive algorithms to achieve this is challenging. In this paper, we tackle the scalability problem of interactive layout of large graphs, and contribute a new GPU-based force-directed layout algorithm that exploits graph topology. This algorithm can interactively layout graphs with millions of nodes, and support real-time interaction to explore alternative graph layouts. Users can directly manipulate the layout of vertices in a force-directed fashion. The complexity of traditional repulsive force computation is reduced by approximating calculations based on the hierarchical structure of multi-level clustered graphs. We evaluate the algorithm performance, and demonstrate human-in-the-loop layout in two sensemaking case studies. Moreover, we summarize lessons learned for designing interactive large graph layout algorithms on the GPU.

Research on centrality of urban transport network nodes

Science.gov (United States)

Wang, Kui; Fu, Xiufen

2017-05-01

Based on the actual data of urban transport in Guangzhou, 19,150 bus stations in Guangzhou (as of 2014) are selected as nodes. Based on the theory of complex network, the network model of Guangzhou urban transport is constructed. By analyzing the degree centrality index, betweenness centrality index and closeness centrality index of nodes in the network, the level of centrality of each node in the network is studied. From a different point of view to determine the hub node of Guangzhou urban transport network, corresponding to the city's key sites and major transfer sites. The reliability of the network is determined by the stability of some key nodes (transport hub station). The research of network node centralization can provide a theoretical basis for the rational allocation of urban transport network sites and public transport system planning.

Opinion formation driven by PageRank node influence on directed networks

Science.gov (United States)

Eom, Young-Ho; Shepelyansky, Dima L.

2015-10-01

We study a two states opinion formation model driven by PageRank node influence and report an extensive numerical study on how PageRank affects collective opinion formations in large-scale empirical directed networks. In our model the opinion of a node can be updated by the sum of its neighbor nodes' opinions weighted by the node influence of the neighbor nodes at each step. We consider PageRank probability and its sublinear power as node influence measures and investigate evolution of opinion under various conditions. First, we observe that all networks reach steady state opinion after a certain relaxation time. This time scale is decreasing with the heterogeneity of node influence in the networks. Second, we find that our model shows consensus and non-consensus behavior in steady state depending on types of networks: Web graph, citation network of physics articles, and LiveJournal social network show non-consensus behavior while Wikipedia article network shows consensus behavior. Third, we find that a more heterogeneous influence distribution leads to a more uniform opinion state in the cases of Web graph, Wikipedia, and Livejournal. However, the opposite behavior is observed in the citation network. Finally we identify that a small number of influential nodes can impose their own opinion on significant fraction of other nodes in all considered networks. Our study shows that the effects of heterogeneity of node influence on opinion formation can be significant and suggests further investigations on the interplay between node influence and collective opinion in networks.

Multi-Level Anomaly Detection on Time-Varying Graph Data

Energy Technology Data Exchange (ETDEWEB)

Bridges, Robert A [ORNL; Collins, John P [ORNL; Ferragut, Erik M [ORNL; Laska, Jason A [ORNL; Sullivan, Blair D [ORNL

2015-01-01

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

Multi-Agent Modeling in Managing Six Sigma Projects

Directory of Open Access Journals (Sweden)

K. Y. Chau

2009-10-01

Full Text Available In this paper, a multi-agent model is proposed for considering the human resources factor in decision making in relation to the six sigma project. The proposed multi-agent system is expected to increase the acccuracy of project prioritization and to stabilize the human resources service level. A simulation of the proposed multiagent model is conducted. The results show that a multi-agent model which takes into consideration human resources when making decisions about project selection and project team formation is important in enabling efficient and effective project management. The multi-agent modeling approach provides an alternative approach for improving communication and the autonomy of six sigma projects in business organizations.

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

Science.gov (United States)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

A new ghost-node method for linking different models and initial investigations of heterogeneity and nonmatching grids

Science.gov (United States)

Dickinson, J.E.; James, S.C.; Mehl, S.; Hill, M.C.; Leake, S.A.; Zyvoloski, G.A.; Faunt, C.C.; Eddebbarh, A.-A.

2007-01-01

A flexible, robust method for linking parent (regional-scale) and child (local-scale) grids of locally refined models that use different numerical methods is developed based on a new, iterative ghost-node method. Tests are presented for two-dimensional and three-dimensional pumped systems that are homogeneous or that have simple heterogeneity. The parent and child grids are simulated using the block-centered finite-difference MODFLOW and control-volume finite-element FEHM models, respectively. The models are solved iteratively through head-dependent (child model) and specified-flow (parent model) boundary conditions. Boundary conditions for models with nonmatching grids or zones of different hydraulic conductivity are derived and tested against heads and flows from analytical or globally-refined models. Results indicate that for homogeneous two- and three-dimensional models with matched grids (integer number of child cells per parent cell), the new method is nearly as accurate as the coupling of two MODFLOW models using the shared-node method and, surprisingly, errors are slightly lower for nonmatching grids (noninteger number of child cells per parent cell). For heterogeneous three-dimensional systems, this paper compares two methods for each of the two sets of boundary conditions: external heads at head-dependent boundary conditions for the child model are calculated using bilinear interpolation or a Darcy-weighted interpolation; specified-flow boundary conditions for the parent model are calculated using model-grid or hydrogeologic-unit hydraulic conductivities. Results suggest that significantly more accurate heads and flows are produced when both Darcy-weighted interpolation and hydrogeologic-unit hydraulic conductivities are used, while the other methods produce larger errors at the boundary between the regional and local models. The tests suggest that, if posed correctly, the ghost-node method performs well. Additional testing is needed for highly

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

Science.gov (United States)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

Multi-way Communications: An Information Theoretic Perspective

KAUST Repository

Chaaban, Anas

2015-09-15

Multi-way communication is a means to significantly improve the spectral efficiency of wireless networks. For instance, in a bi-directional (or two-way) communication channel, two users can simultaneously use the transmission medium to exchange information, thus achieving up to twice the rate that would be achieved had each user transmitted separately. Multi-way communications provides an overview on the developments in this research area since it has been initiated by Shannon. The basic two-way communication channel is considered first, followed by the two-way relay channel obtained by the deployment of an additional cooperative relay node to improve the overall communication performance. This basic setup is then extended to multi-user systems. For all these setups, fundamental limits on the achievable rates are reviewed, thereby making use of a linear high-SNR deterministic channel model to provide valuable insights which are helpful when discussing the coding schemes for Gaussian channel models in detail. Several tools and communication strategies are used in the process, including (but not limited to) computation, signal-space alignment, and nested-lattice codes. Finally, extensions of multi-way communication channels to multiple antenna settings are discussed. © 2015 A. Chaaban and A. Sezgin.

Multi-stage optimization of decision and inhibitory trees for decision tables with many-valued decisions

KAUST Repository

Azad, Mohammad

2017-06-16

We study problems of optimization of decision and inhibitory trees for decision tables with many-valued decisions. As cost functions, we consider depth, average depth, number of nodes, and number of terminal/nonterminal nodes in trees. Decision tables with many-valued decisions (multi-label decision tables) are often more accurate models for real-life data sets than usual decision tables with single-valued decisions. Inhibitory trees can sometimes capture more information from decision tables than decision trees. In this paper, we create dynamic programming algorithms for multi-stage optimization of trees relative to a sequence of cost functions. We apply these algorithms to prove the existence of totally optimal (simultaneously optimal relative to a number of cost functions) decision and inhibitory trees for some modified decision tables from the UCI Machine Learning Repository.

Multi-stage optimization of decision and inhibitory trees for decision tables with many-valued decisions

KAUST Repository

Azad, Mohammad; Moshkov, Mikhail

2017-01-01

We study problems of optimization of decision and inhibitory trees for decision tables with many-valued decisions. As cost functions, we consider depth, average depth, number of nodes, and number of terminal/nonterminal nodes in trees. Decision tables with many-valued decisions (multi-label decision tables) are often more accurate models for real-life data sets than usual decision tables with single-valued decisions. Inhibitory trees can sometimes capture more information from decision tables than decision trees. In this paper, we create dynamic programming algorithms for multi-stage optimization of trees relative to a sequence of cost functions. We apply these algorithms to prove the existence of totally optimal (simultaneously optimal relative to a number of cost functions) decision and inhibitory trees for some modified decision tables from the UCI Machine Learning Repository.

Symplectic multi-particle tracking on GPUs

Science.gov (United States)

Liu, Zhicong; Qiang, Ji

2018-05-01

A symplectic multi-particle tracking model is implemented on the Graphic Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) language. The symplectic tracking model can preserve phase space structure and reduce non-physical effects in long term simulation, which is important for beam property evaluation in particle accelerators. Though this model is computationally expensive, it is very suitable for parallelization and can be accelerated significantly by using GPUs. In this paper, we optimized the implementation of the symplectic tracking model on both single GPU and multiple GPUs. Using a single GPU processor, the code achieves a factor of 2-10 speedup for a range of problem sizes compared with the time on a single state-of-the-art Central Processing Unit (CPU) node with similar power consumption and semiconductor technology. It also shows good scalability on a multi-GPU cluster at Oak Ridge Leadership Computing Facility. In an application to beam dynamics simulation, the GPU implementation helps save more than a factor of two total computing time in comparison to the CPU implementation.

Graph Grammar-Based Multi-Frontal Parallel Direct Solver for Two-Dimensional Isogeometric Analysis

KAUST Repository

Kuźnik, Krzysztof

2012-06-02

This paper introduces the graph grammar based model for developing multi-thread multi-frontal parallel direct solver for two dimensional isogeometric finite element method. Execution of the solver algorithm has been expressed as the sequence of graph grammar productions. At the beginning productions construct the elimination tree with leaves corresponding to finite elements. Following sequence of graph grammar productions generates element frontal matri-ces at leaf nodes, merges matrices at parent nodes and eliminates rows corresponding to fully assembled degrees of freedom. Finally, there are graph grammar productions responsible for root problem solution and recursive backward substitutions. Expressing the solver algorithm by graph grammar productions allows us to explore the concurrency of the algorithm. The graph grammar productions are grouped into sets of independent tasks that can be executed concurrently. The resulting concurrent multi-frontal solver algorithm is implemented and tested on NVIDIA GPU, providing O(NlogN) execution time complexity where N is the number of degrees of freedom. We have confirmed this complexity by solving up to 1 million of degrees of freedom with 448 cores GPU.

Reference Models for Multi-Layer Tissue Structures

Science.gov (United States)

2016-09-01

function of multi-layer tissues (etiology and management of pressure ulcers ). What was the impact on other disciplines? As part of the project, a data...simplification to develop cost -effective models of surface manipulation of multi-layer tissues. Deliverables. Specimen- (or subject) and region-specific...simplification to develop cost -effective models of surgical manipulation. Deliverables. Specimen-specific surrogate models of upper legs confirmed against data

Prediction of Non-sentinel Node Status in Patients with Melanoma and Positive Sentinel Node Biopsy: An Italian Melanoma Intergroup (IMI) Study.

Science.gov (United States)

Rossi, Carlo Riccardo; Mocellin, Simone; Campana, Luca Giovanni; Borgognoni, Lorenzo; Sestini, Serena; Giudice, Giuseppe; Caracò, Corrado; Cordova, Adriana; Solari, Nicola; Piazzalunga, Dario; Carcoforo, Paolo; Quaglino, Pietro; Caliendo, Virginia; Ribero, Simone

2018-01-01

Approximately 20% of melanoma patients harbor metastases in non-sentinel nodes (NSNs) after a positive sentinel node biopsy (SNB), and recent evidence questions the therapeutic benefit of completion lymph node dissection (CLND). We built a nomogram for prediction of NSN status in melanoma patients with positive SNB. Data on anthropometric and clinicopathological features of patients with cutaneous melanoma who underwent CLND after a positive SNB were collected from nine Italian centers. Multivariate logistic regression was utilized to identify predictors of NSN status in a training set, while model efficiency was validated in a validation set. Data were available for 1220 patients treated from 2000 through 2016. In the training set (n = 810), the risk of NSN involvement was higher when (1) the primary melanoma is thicker or (2) sited in the trunk/head and neck; (3) fewer nodes are excised and (4) more nodes are involved; and (5) the lymph node metastasis is larger or (6) is deeply located. The model showed high discrimination (area under the receiver operating characteristic curve 0.74, 95% confidence interval [CI] 0.70-0.79) and calibration (Brier score 0.16, 95% CI 0.15-0.17) performance in the validation set (n = 410). The nomogram including these six clinicopathological variables performed significantly better than five other previously published models in terms of both discrimination and calibration. Our nomogram could be useful for follow-up personalization in clinical practice, and for patient risk stratification while conducting clinical trials or analyzing their results.

Data Fusion Based on Node Trust Evaluation in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhou Jianming

2014-01-01

Full Text Available Abnormal behavior detection and trust evaluation mode of traditional sensor node have a single function without considering all the factors, and the trust value algorithm is relatively complicated. To avoid these above disadvantages, a trust evaluation model based on the autonomous behavior of sensor node is proposed in this paper. Each sensor node has the monitoring privilege and obligation. Neighboring sensor nodes can monitor each other. Their direct and indirect trust values can be achieved by using a relatively simple calculation method, the synthesis trust value of which could be got according to the composition rule of D-S evidence theory. Firstly, the cluster head assigns different weighted value for the data from each sensor node, then the weight vector is set according to the synthesis trust value, the data fusion processing is executed, and finally the cluster head sensor node transmits the fused result to the base station. Simulation experiment results demonstrate that the trust evaluation model can rapidly, exactly, and effectively recognize malicious sensor node and avoid malicious sensor node becoming cluster head sensor node. The proposed algorithm can greatly increase the safety and accuracy of data fusion, improve communication efficiency, save energy of sensor node, suit different application fields, and deploy environments.

An activity recognition model using inertial sensor nodes in a wireless sensor network for frozen shoulder rehabilitation exercises.

Science.gov (United States)

Lin, Hsueh-Chun; Chiang, Shu-Yin; Lee, Kai; Kan, Yao-Chiang

2015-01-19

This paper proposes a model for recognizing motions performed during rehabilitation exercises for frozen shoulder conditions. The model consists of wearable wireless sensor network (WSN) inertial sensor nodes, which were developed for this study, and enables the ubiquitous measurement of bodily motions. The model employs the back propagation neural network (BPNN) algorithm to compute motion data that are formed in the WSN packets; herein, six types of rehabilitation exercises were recognized. The packets sent by each node are converted into six components of acceleration and angular velocity according to three axes. Motor features such as basic acceleration, angular velocity, and derivative tilt angle were input into the training procedure of the BPNN algorithm. In measurements of thirteen volunteers, the accelerations and included angles of nodes were adopted from possible features to demonstrate the procedure. Five exercises involving simple swinging and stretching movements were recognized with an accuracy of 85%-95%; however, the accuracy with which exercises entailing spiral rotations were recognized approximately 60%. Thus, a characteristic space and enveloped spectrum improving derivative features were suggested to enable identifying customized parameters. Finally, a real-time monitoring interface was developed for practical implementation. The proposed model can be applied in ubiquitous healthcare self-management to recognize rehabilitation exercises.

An Activity Recognition Model Using Inertial Sensor Nodes in a Wireless Sensor Network for Frozen Shoulder Rehabilitation Exercises

Directory of Open Access Journals (Sweden)

Hsueh-Chun Lin

2015-01-01

Full Text Available This paper proposes a model for recognizing motions performed during rehabilitation exercises for frozen shoulder conditions. The model consists of wearable wireless sensor network (WSN inertial sensor nodes, which were developed for this study, and enables the ubiquitous measurement of bodily motions. The model employs the back propagation neural network (BPNN algorithm to compute motion data that are formed in the WSN packets; herein, six types of rehabilitation exercises were recognized. The packets sent by each node are converted into six components of acceleration and angular velocity according to three axes. Motor features such as basic acceleration, angular velocity, and derivative tilt angle were input into the training procedure of the BPNN algorithm. In measurements of thirteen volunteers, the accelerations and included angles of nodes were adopted from possible features to demonstrate the procedure. Five exercises involving simple swinging and stretching movements were recognized with an accuracy of 85%–95%; however, the accuracy with which exercises entailing spiral rotations were recognized approximately 60%. Thus, a characteristic space and enveloped spectrum improving derivative features were suggested to enable identifying customized parameters. Finally, a real-time monitoring interface was developed for practical implementation. The proposed model can be applied in ubiquitous healthcare self-management to recognize rehabilitation exercises.

A VIRTUAL GLOBE-BASED MULTI-RESOLUTION TIN SURFACE MODELING AND VISUALIZETION METHOD

Directory of Open Access Journals (Sweden)

X. Zheng

2016-06-01

Full Text Available The integration and visualization of geospatial data on a virtual globe play an significant role in understanding and analysis of the Earth surface processes. However, the current virtual globes always sacrifice the accuracy to ensure the efficiency for global data processing and visualization, which devalue their functionality for scientific applications. In this article, we propose a high-accuracy multi-resolution TIN pyramid construction and visualization method for virtual globe. Firstly, we introduce the cartographic principles to formulize the level of detail (LOD generation so that the TIN model in each layer is controlled with a data quality standard. A maximum z-tolerance algorithm is then used to iteratively construct the multi-resolution TIN pyramid. Moreover, the extracted landscape features are incorporated into each-layer TIN, thus preserving the topological structure of terrain surface at different levels. In the proposed framework, a virtual node (VN-based approach is developed to seamlessly partition and discretize each triangulation layer into tiles, which can be organized and stored with a global quad-tree index. Finally, the real time out-of-core spherical terrain rendering is realized on a virtual globe system VirtualWorld1.0. The experimental results showed that the proposed method can achieve an high-fidelity terrain representation, while produce a high quality underlying data that satisfies the demand for scientific analysis.

Modular sensor network node

Science.gov (United States)

Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

2008-06-10

A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

A Multi-Model Approach for System Diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur

2007-01-01

A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....

Evolutionary optimization and game strategies for advanced multi-disciplinary design applications to aeronautics and UAV design

CERN Document Server

Periaux, Jacques; Lee, Dong Seop Chris

2015-01-01

Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with c...

Final report for the mobile node authentication LDRD project.

Energy Technology Data Exchange (ETDEWEB)

Michalski, John T.; Lanzone, Andrew J.

2005-09-01

In hostile ad hoc wireless communication environments, such as battlefield networks, end-node authentication is critical. In a wired infrastructure, this authentication service is typically facilitated by a centrally-located ''authentication certificate generator'' such as a Certificate Authority (CA) server. This centralized approach is ill-suited to meet the needs of mobile ad hoc networks, such as those required by military systems, because of the unpredictable connectivity and dynamic routing. There is a need for a secure and robust approach to mobile node authentication. Current mechanisms either assign a pre-shared key (shared by all participating parties) or require that each node retain a collection of individual keys that are used to communicate with other individual nodes. Both of these approaches have scalability issues and allow a single compromised node to jeopardize the entire mobile node community. In this report, we propose replacing the centralized CA with a distributed CA whose responsibilities are shared between a set of select network nodes. To that end, we develop a protocol that relies on threshold cryptography to perform the fundamental CA duties in a distributed fashion. The protocol is meticulously defined and is implemented it in a series of detailed models. Using these models, mobile wireless scenarios were created on a communication simulator to test the protocol in an operational environment and to gather statistics on its scalability and performance.

Floating Node Method and Virtual Crack Closure Technique for Modeling Matrix Cracking-Delamination Migration

Science.gov (United States)

DeCarvalho, Nelson V.; Chen, B. Y.; Pinho, Silvestre T.; Baiz, P. M.; Ratcliffe, James G.; Tay, T. E.

2013-01-01

A novel approach is proposed for high-fidelity modeling of progressive damage and failure in composite materials that combines the Floating Node Method (FNM) and the Virtual Crack Closure Technique (VCCT) to represent multiple interacting failure mechanisms in a mesh-independent fashion. In this study, the approach is applied to the modeling of delamination migration in cross-ply tape laminates. Delamination, matrix cracking, and migration are all modeled using fracture mechanics based failure and migration criteria. The methodology proposed shows very good qualitative and quantitative agreement with experiments.

A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering

CERN Document Server

Parasuraman, Ramviyas; Molinari, Luca; Kershaw, Keith; Di Castro, Mario; Masi, Alessandro; Ferre, Manuel

2014-01-01

The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide red...

Multi-Objective Planning of Multi-Type Distributed Generation Considering Timing Characteristics and Environmental Benefits

Directory of Open Access Journals (Sweden)

Yajing Gao

2014-09-01

Full Text Available This paper presents a novel approach to multi-type distributed generation (DG planning based on the analysis of investment and income brought by grid-connected DG. Firstly, the timing characteristics of loads and DG outputs, as well as the environmental benefits of DG are analyzed. Then, on the basis of the classification of daily load sequences, the typical daily load sequence and the typical daily output sequence of DG per unit capacity can be computed. The proposed planning model takes the location, capacity and types of DG into account as optimization variables. An improved adaptive genetic algorithm is proposed to solve the model. Case studies have been carried out on the IEEE 14-node distribution system to verify the feasibility and effectiveness of the proposed method and model.

The role of driver nodes in managing epileptic seizures: Application of Kuramoto model.

Science.gov (United States)

Mohseni, Ali; Gharibzadeh, Shahriar; Bakouie, Fatemeh

2017-04-21

Synchronization is an important global phenomenon which could be found in a wide range of complex systems such as brain or electronic devices. However, in some circumstances the synchronized states are not desirable for the system and should be suppressed. For example, excessively synchronized activities in the brain network could be the root of neuronal disorders like epileptic seizures. According to the controllability theory of the complex networks, a minimum set of driver nodes has the ability to control the entire system. In this study, we examine the role of driver nodes in suppressing the excessive synchronization in a generalized Kuramoto model, which consists of two types of oscillators: contrarian and regular ones. We used two different structural topologies: Barabási-Albert scale-free (BASF) network and Caenorhabditis elegans (C.elegans) neuronal network. Our results show that contrarian driver nodes have the sufficient ability to break the synchronized level of the systems. In this case, the system coherency level is not fully suppressed that is avoiding dysfunctions of normal brain functions which require the neuronal synchronized activities. Moreover, in this case, the oscillators grouped in two distinct synchronized clusters that could be an indication of chaotic behavior of the system known as resting-state activity of the brain. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clinical and pathologic factors affecting lymph node yields in colorectal cancer.

Directory of Open Access Journals (Sweden)

Ta-Wen Hsu

Full Text Available OBJECTIVE: Lymph node yield is recommended as a benchmark of quality care in colorectal cancer. The objective of this study was to evaluate the impact of various factors upon lymph node yield and to identify independent factors associated with lymph node harvest. MATERIALS AND METHODS: The records of 162 patients with Stage I to Stage III colorectal cancers seen in one institution were reviewed. These patients underwent radical surgery as definitive therapy; high-risk patients then received adjuvant treatment. Pathologic and demographic data were recorded and analyzed. The subgroup analysis of lymph node yields was determined using a t-test and analysis of variants. Linear regression model and multivariable analysis were used to perform potential confounding and predicting variables. RESULTS: Five variables had significant association with lymph node yield after adjustment for other factors in a multiple linear regression model. These variables were: tumor size, surgical method, specimen length, and individual surgeon and pathologist. The model with these five significant variables interpreted 44.4% of the variation. CONCLUSIONS: Patients, tumor characteristics and surgical variables all influence the number of lymph nodes retrieved. Physicians are the main gatekeepers. Adequate training and optimized guidelines could greatly improve the quality of lymph node yields.

Multi-time, multi-scale correlation functions in turbulence and in turbulent models

NARCIS (Netherlands)

Biferale, L.; Boffetta, G.; Celani, A.; Toschi, F.

1999-01-01

A multifractal-like representation for multi-time, multi-scale velocity correlation in turbulence and dynamical turbulent models is proposed. The importance of subleading contributions to time correlations is highlighted. The fulfillment of the dynamical constraints due to the equations of motion is

Controlling data transfers from an origin compute node to a target compute node

Science.gov (United States)

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Ratterman, Joseph D [Rochester, MN; Smith, Brian E [Rochester, MN

2011-06-21

Methods, apparatus, and products are disclosed for controlling data transfers from an origin compute node to a target compute node that include: receiving, by an application messaging module on the target compute node, an indication of a data transfer from an origin compute node to the target compute node; and administering, by the application messaging module on the target compute node, the data transfer using one or more messaging primitives of a system messaging module in dependence upon the indication.

Protocol for multiple node network

Science.gov (United States)

Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs an antibody recognition message termination process performed by all remote nodes and a remote node polling process performed by other nodes which are master units controlling remote nodes in respective zones of the network assigned to respective master nodes. Each remote node repeats only those messages originated in the local zone, to provide isolation among the master nodes.

Sentinel node biopsy before neoadjuvant chemotherapy spares breast cancer patients axillary lymph node dissection.

Science.gov (United States)

van Rijk, Maartje C; Nieweg, Omgo E; Rutgers, Emiel J T; Oldenburg, Hester S A; Olmos, Renato Valdés; Hoefnagel, Cornelis A; Kroon, Bin B R

2006-04-01

Neoadjuvant chemotherapy in breast cancer patients is a valuable method to determine the efficacy of chemotherapy and potentially downsize the primary tumor, which facilitates breast-conserving therapy. In 18 studies published about sentinel node biopsy after neoadjuvant chemotherapy, the sentinel node was identified in on average 89%, and the false-negative rate was on average 10%. Because of these mediocre results, no author dares to omit axillary clearance just yet. In our institute, sentinel lymph node biopsy is performed before neoadjuvant chemotherapy. The aim of this study was to evaluate our experience with this approach. Sentinel node biopsy was performed before neoadjuvant chemotherapy in 25 T2N0 patients by using lymphoscintigraphy, a gamma ray detection probe, and patent blue dye. Axillary lymph node dissection was performed after chemotherapy if the sentinel node contained metastases. Ten patients had a tumor-positive axillary sentinel node, and one patient had an involved lateral intramammary node. Four patients had additional involved nodes in the completion lymph node dissection specimen. The other 14 patients (56%) had a tumor-negative sentinel node and did not undergo axillary lymph node dissection. No recurrences have been observed after a median follow-up of 18 months. Fourteen (56%) of the 25 patients were spared axillary lymph node dissection when the sentinel node was found to be disease free. Performing sentinel node biopsy before neoadjuvant chemotherapy seems successful and reliable in patients with T2N0 breast cancer.

Unified Modeling Language description of the object-oriented multi-scale adaptive finite element method for Step-and-Flash Imprint Lithography Simulations

International Nuclear Information System (INIS)

Paszynski, Maciej; Gurgul, Piotr; Sieniek, Marcin; Pardo, David

2010-01-01

In the first part of the paper we present the multi-scale simulation of the Step-and-Flash Imprint Lithography (SFIL), a modern patterning process. The simulation utilizes the hp adaptive Finite Element Method (hp-FEM) coupled with Molecular Statics (MS) model. Thus, we consider the multi-scale problem, with molecular statics applied in the areas of the mesh where the highest accuracy is required, and the continuous linear elasticity with thermal expansion coefficient applied in the remaining part of the domain. The degrees of freedom from macro-scale element's nodes located on the macro-scale side of the interface have been identified with particles from nano-scale elements located on the nano-scale side of the interface. In the second part of the paper we present Unified Modeling Language (UML) description of the resulting multi-scale application (hp-FEM coupled with MS). We investigated classical, procedural codes from the point of view of the object-oriented (O-O) programming paradigm. The discovered hierarchical structure of classes and algorithms makes the UML project as independent on the spatial dimension of the problem as possible. The O-O UML project was defined at an abstract level, independent on the programming language used.

Multi-Level Model

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

Full Text Available Is an original paper, which contains a hierarchical model with three levels, for determining the linearized non-homogeneous and homogeneous credibility premiums at company level, at sector level and at contract level, founded on the relevant covariance relations between the risk premium, the observations and the weighted averages. We give a rather explicit description of the input data for the multi- level hierarchical model used, only to show that in practical situations, there will always be enough data to apply credibility theory to a real insurance portfolio.

Multi-scale analysis of the European airspace using network community detection.

Directory of Open Access Journals (Sweden)

Gérald Gurtner

Full Text Available We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspace and improve it by guiding the design of new ones. Specifically, we compare the performance of several community detection algorithms, both with fixed and variable resolution, and also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.

Analysis of route availability in inter-working multi-hop wireless networks

CSIR Research Space (South Africa)

Salami, O

2009-07-01

Full Text Available In order to link a source-destination node pair in inter-working multi-hop wireless networks, links or routes must first be available. It is only after establishing the availability of links and routes between nodes that factors which affect...

Objective Function and Learning Algorithm for the General Node Fault Situation.

Science.gov (United States)

Xiao, Yi; Feng, Rui-Bin; Leung, Chi-Sing; Sum, John

2016-04-01

Fault tolerance is one interesting property of artificial neural networks. However, the existing fault models are able to describe limited node fault situations only, such as stuck-at-zero and stuck-at-one. There is no general model that is able to describe a large class of node fault situations. This paper studies the performance of faulty radial basis function (RBF) networks for the general node fault situation. We first propose a general node fault model that is able to describe a large class of node fault situations, such as stuck-at-zero, stuck-at-one, and the stuck-at level being with arbitrary distribution. Afterward, we derive an expression to describe the performance of faulty RBF networks. An objective function is then identified from the formula. With the objective function, a training algorithm for the general node situation is developed. Finally, a mean prediction error (MPE) formula that is able to estimate the test set error of faulty networks is derived. The application of the MPE formula in the selection of basis width is elucidated. Simulation experiments are then performed to demonstrate the effectiveness of the proposed method.

Mathematical model comparing of the multi-level economics systems

Science.gov (United States)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

Hop-by-HopWorm Propagation with Carryover Epidemic Model in Mobile Sensor Networks

Directory of Open Access Journals (Sweden)

Jun-Won Ho

2015-10-01

Full Text Available In the internet, a worm is usually propagated in a random multi-hop contact manner. However, the attacker will not likely select this random multi-hop propagation approach in a mobile sensor network. This is because multi-hop worm route paths to random vulnerable targets can be often breached due to node mobility, leading to failure of fast worm spread under this strategy. Therefore, an appropriate propagation strategy is needed for mobile sensor worms. To meet this need, we discuss a hop-by-hop worm propagation model in mobile sensor networks. In a hop-by-hop worm propagation model, benign nodes are infected by worm in neighbor-to-neighbor spread manner. Since worm infection occurs in hop-by-hop contact, it is not substantially affected by a route breach incurred by node mobility. We also propose the carryover epidemic model to deal with the worm infection quota deficiency that might occur when employing an epidemic model in a mobile sensor network. We analyze worm infection capability under the carryover epidemic model. Moreover, we simulate hop-by-hop worm propagation with carryover epidemic model by using an ns-2 simulator. The simulation results demonstrate that infection quota carryovers are seldom observed where a node’s maximum speed is no less than 20 m/s.

Loop equations for multi-cut matrix models

International Nuclear Information System (INIS)

Akemann, G.

1995-03-01

The loop equation for the complex one-matrix model with a multi-cut structure is derived and solved in the planar limit. An iterative scheme for higher genus contributions to the free energy and the multi-loop correlators is presented for the two-cut model, where explicit results are given up to and including genus two. The double-scaling limit is analyzed and the relation to the one-cut solution of the hermitian and complex one-matrix model is discussed. (orig.)

Throughput analysis of point-to-multi-point hybric FSO/RF network

KAUST Repository

Rakia, Tamer; Gebali, Fayez; Yang, Hong-Chuan; Alouini, Mohamed-Slim

2017-01-01

This paper presents and analyzes a point-to-multi-point (P2MP) network that uses a number of free-space optical (FSO) links for data transmission from the central node to the different remote nodes. A common backup radio-frequency (RF) link is used

Multi-level decision making models, methods and applications

CERN Document Server

Zhang, Guangquan; Gao, Ya

2015-01-01

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

Robust multi-model predictive control of multi-zone thermal plate system

Directory of Open Access Journals (Sweden)

Poom Jatunitanon

2018-02-01

Full Text Available A modern controller was designed by using the mathematical model of a multi–zone thermal plate system. An important requirement for this type of controller is that it must be able to keep the temperature set-point of each thermal zone. The mathematical model used in the design was determined through a system identification process. The results showed that when the operating condition is changed, the performance of the controller may be reduced as a result of the system parameter uncertainties. This paper proposes a weighting technique of combining the robust model predictive controller for each operating condition into a single robust multi-model predictive control. Simulation and experimental results showed that the proposed method performed better than the conventional multi-model predictive control in rise time of transient response, when used in a system designed to work over a wide range of operating conditions.

Pattern of Colon Cancer Lymph Node Metastases in Patients Undergoing Central Mesocolic Lymph Node Excision

DEFF Research Database (Denmark)

Bertelsen, Claus A; Kirkegaard-Klitbo, Anders; Nielsen, Mingyuan

2016-01-01

BACKGROUND: Extended mesocolic lymph node dissection in colon cancer surgery seems to improve oncological outcome. A possible reason might be related to metastases in the central mesocolic lymph nodes. OBJECTIVE: The purpose of this study was to describe the pattern of mesocolic lymph node...... metastases, particularly in central lymph nodes, and the risk of skip, aberrant, and gastrocolic ligament metastases as the argument for performing extended lymph node dissection. DATA SOURCES: EMBASE and PubMed were searched using the terms colon or colorectal with sentinel node, lymph node mapping, or skip...... node; lymph node resection colon; and complete or total and mesocolic excision. STUDY SELECTION: Studies describing the risk of metastases in central, skip, aberrant, and gastrocolic ligament lymph node metastases from colon adenocarcinomas in 10 or more patients were included. No languages were...

Multi baryons with flavors in the Skyrme model

Energy Technology Data Exchange (ETDEWEB)

Schat, Carlos L. [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil); Scoccola, Norberto N. [Comision Nacional de Energia Atomica, Buenos Aires (Argentina). Dept. of Physics

1999-07-01

We investigate the possible existence of multi baryons with heavy flavor quantum numbers using the bound state approach to the topological soliton model and the recently proposed approximation for multi skyrmion fields based on rational maps. We use an effective interaction Lagrangian which consistently incorporates both chiral symmetry and the heavy quark symmetry including the corrections up to order {omicron}(1/m{sub Q}). The model predicts some narrow heavy flavored multi baryon states with baryon number four and seven. (author)

Multi baryons with flavors in the Skyrme model

International Nuclear Information System (INIS)

Schat, Carlos L.; Scoccola, Norberto N.

1999-07-01

We investigate the possible existence of multi baryons with heavy flavor quantum numbers using the bound state approach to the topological soliton model and the recently proposed approximation for multi skyrmion fields based on rational maps. We use an effective interaction Lagrangian which consistently incorporates both chiral symmetry and the heavy quark symmetry including the corrections up to order ο(1/m Q ). The model predicts some narrow heavy flavored multi baryon states with baryon number four and seven. (author)

Partial axillary lymph node dissection inferior to the intercostobrachial nerves complements sentinel node biopsy in patients with clinically node-negative breast cancer.

Science.gov (United States)

Li, Jianyi; Jia, Shi; Zhang, Wenhai; Qiu, Fang; Zhang, Yang; Gu, Xi; Xue, Jinqi

2015-06-30

The practice of breast cancer diagnosis and treatment in China varies to that in western developed countries. With the unavailability of radioactive tracer technique for sentinel lymph nodes biopsy (SLNB), using blue dye alone has been the only option in China. Also, the diagnosis of breast malignant tumor in most Chinese centres heavily relies on intraoperative instant frozen histology which is normally followed by sentinel lymph nodes mapping, SLNB and the potential breast and axillary operations in one consecutive session. This practice appears to cause a high false negative rate (FNR) for SLNB. The present study aimed to investigate the impact of the current practice in China on the accuracy of SLNB, and whether partial axillary lymph node dissection (PALND), dissection of lymph nodes inferior to the intercostobrachial nerve (ICBN), was a good complementary procedure following SLNB using blue dye. 289 patients with clinically node-negative breast cancer were identified and recruited. Tumorectomy, intraoperative instant frozen histological diagnosis, SLNB using methylene blue dye, and PALND or complete axillary node dissection (ALND) were performed in one consecutive operative session. The choice of SLNB only, SLNB followed by PALND or by ALND was based on the pre-determined protocol and preoperative choice by the patient. Clinical parameters were analyzed and survival analysis was performed. 37% patients with clinically negative nodes were found nodes positive. 59 patients with positive SLN underwent ALND, including 47 patients with up to two positive nodes which were all located inferior to the ICBN. 9 patients had failed SLNB and underwent PALND. Among them, 3 (33.3%) patients were found to have one metastatic node. 149 patients showed negative SLNB but chose PALND. Among them, 30 (20.1%), 14 (9.4) and 1 (0.7%) patients were found to have one, two and three metastatic node(s), respectively. PALND detected 48 (30.4%) patients who had either failed SLNB or

Empirical Research of Micro-blog Information Transmission Range by Guard nodes

Science.gov (United States)

Chen, Shan; Ji, Ling; Li, Guang

2018-03-01

The prediction and evaluation of information transmission in online social networks is a challenge. It is significant to solve this issue for monitoring public option and advertisement communication. First, the prediction process is described by a set language. Then with Sina Microblog system as used as the case object, the relationship between node influence and coverage rate is analyzed by using the topology structure of information nodes. A nonlinear model is built by a statistic method in a specific, bounded and controlled Microblog network. It can predict the message coverage rate by guard nodes. The experimental results show that the prediction model has higher accuracy to the source nodes which have lower influence in social network and practical application.

Beamforming-Based Physical Layer Network Coding for Non-Regenerative Multi-Way Relaying

Directory of Open Access Journals (Sweden)

Klein Anja

2010-01-01

Full Text Available We propose non-regenerative multi-way relaying where a half-duplex multi-antenna relay station (RS assists multiple single-antenna nodes to communicate with each other. The required number of communication phases is equal to the number of the nodes, N. There are only one multiple-access phase, where the nodes transmit simultaneously to the RS, and broadcast (BC phases. Two transmission methods for the BC phases are proposed, namely, multiplexing transmission and analog network coded transmission. The latter is a cooperation method between the RS and the nodes to manage the interference in the network. Assuming that perfect channel state information is available, the RS performs transceive beamforming to the received signals and transmits simultaneously to all nodes in each BC phase. We address the optimum transceive beamforming maximising the sum rate of non-regenerative multi-way relaying. Due to the nonconvexity of the optimization problem, we propose suboptimum but practical signal processing schemes. For multiplexing transmission, we propose suboptimum schemes based on zero forcing, minimising the mean square error, and maximising the signal to noise ratio. For analog network coded transmission, we propose suboptimum schemes based on matched filtering and semidefinite relaxation of maximising the minimum signal to noise ratio. It is shown that analog network coded transmission outperforms multiplexing transmission.

Multi-model-based Access Control in Construction Projects

Directory of Open Access Journals (Sweden)

Frank Hilbert

2012-04-01

Full Text Available During the execution of large scale construction projects performed by Virtual Organizations (VO, relatively complex technical models have to be exchanged between the VO members. For linking the trade and transfer of these models, a so-called multi-model container format was developed. Considering the different skills and tasks of the involved partners, it is not necessary for them to know all the models in every technical detailing. Furthermore, the model size can lead to a delay in communication. In this paper an approach is presented for defining model cut-outs according to the current project context. Dynamic dependencies to the project context as well as static dependencies on the organizational structure are mapped in a context-sensitive rule. As a result, an approach for dynamic filtering of multi-models is obtained which ensures, together with a filtering service, that the involved VO members get a simplified view of complex multi-models as well as sufficient permissions depending on their tasks.

Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

Science.gov (United States)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

Multi-compartment Fire Modeling for Switchgear Room using CFAST

International Nuclear Information System (INIS)

Han, Kiyoon; Kang, Dae Il; Lim, Ho Gon

2015-01-01

In this study, multi-compartment fire modeling for fire propagation scenario from SWGR A to SWGR B is performed using CFAST. New fire PSA method (NUREG/CR-6850) requires that the severity factor is to be calculated by fire modeling. If fire modeling is not performed, the severity factor should be estimated as one conservatively. Also, the possibility of the damages of components and cables located at adjacent compartments should be considered. Detailed fire modeling of multi-compartment fires refers to the evaluation of fire-generated conditions in one compartment that spread to adjacent ones. In general, the severity factor for multi-compartment fire scenario is smaller than that of single compartment scenario. Preliminary quantification of Hanul Unit 3 fire PSA was performed without fire modeling. As a result of quantification, multi-compartment scenario, fire propagation scenario from switchgear room (SWGR) A to SWGR B, is one of significant contributor to the CDF. In this study, fire modeling of multi-compartment was performed by Consolidated Fire Growth and Smoke Transport (CFAST) to identify the possibility of fire propagation. As a result of fire simulation, it is identified that fire propagation has little influences

Multi-compartment Fire Modeling for Switchgear Room using CFAST

Energy Technology Data Exchange (ETDEWEB)

Han, Kiyoon; Kang, Dae Il; Lim, Ho Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-10-15

In this study, multi-compartment fire modeling for fire propagation scenario from SWGR A to SWGR B is performed using CFAST. New fire PSA method (NUREG/CR-6850) requires that the severity factor is to be calculated by fire modeling. If fire modeling is not performed, the severity factor should be estimated as one conservatively. Also, the possibility of the damages of components and cables located at adjacent compartments should be considered. Detailed fire modeling of multi-compartment fires refers to the evaluation of fire-generated conditions in one compartment that spread to adjacent ones. In general, the severity factor for multi-compartment fire scenario is smaller than that of single compartment scenario. Preliminary quantification of Hanul Unit 3 fire PSA was performed without fire modeling. As a result of quantification, multi-compartment scenario, fire propagation scenario from switchgear room (SWGR) A to SWGR B, is one of significant contributor to the CDF. In this study, fire modeling of multi-compartment was performed by Consolidated Fire Growth and Smoke Transport (CFAST) to identify the possibility of fire propagation. As a result of fire simulation, it is identified that fire propagation has little influences.

Improvement of sweating model in 2-Node Model and its application to thermal safety for hot environments

Energy Technology Data Exchange (ETDEWEB)

Ooka, Ryozo [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba Meguro-ku, Tokyo 153 8505 (Japan); Minami, Yuriko [Tokyo Electric Power Company, Tokyo (Japan); Sakoi, Tomonori [International Young Researchers Empowerment Center, Shinshu University, Nagano (Japan); Tsuzuki, Kazuyo [National Institute of Advanced Industrial Science and Technology, Tsukuba (Japan); Rijal, H.B. [Integrated Research System for Sustainability Science, The University of Tokyo, Tokyo (Japan)

2010-07-15

Recently, due to global warming and the heat-island effect, more and more people are exposed to the dangers of heat disorders. A hot thermal environment can be evaluated using various indices, such as new Standard Effective Temperature (SET{sup *}) using the 2-Node Model (2 NM), Wet Bulb Globe Temperature (WBGT), Predicted Heat Strain (PHS) model, and so on. The authors aim to develop a safety evaluation approach for hot environments. Subject experiments are performed in a laboratory to comprehend the physiological response of the human body. The results are compared with the computed values from the 2 NM and PHS models, and improved the sweating model in 2 NM in order to take into account the relationship with metabolic rate. A demonstration is provided of using the new sweating model for evaluating thermal safety in a hot environment. (author)

Air launch wireless sensor nodes (ALSN) for battle damage assessment (BDA)

Science.gov (United States)

Back, Jason M.; Beck, Steven D.; Frank, Mark A.; Hoenes, Eric

2006-05-01

This paper summarizes the Defense Threat Reduction Agency (DTRA) sponsored development and demonstration of an Air Launched Sensor Node (ALSN) system designed to fill DTRA's immediate need to support the Global Strike requirement of weapon-borne deliverable sensors for Battle Damage Assessment (BDA). Unattended ground sensors were integrated into a CBU-103 Tactical Munitions Dispenser (TMD), and flight test demonstrated with the 46 th Test Wing at Eglin AFB, FL. The objectives of the ALSN program were to repackage an existing multi-sensor node system to conform to the payload envelope and deployment configuration design; to integrate this payload into the CBU-103 TMD; and to conduct a combined payload flight test demonstration. The final sensor node included multiple sensors a microphone, a geophone, and multiple directional Passive Infrared (PIR) detectors with processing electronics, a low power wireless communications 802.15.4 mesh network, GPS (Global Positioning System), and power integrated into a form-fit BLU-97 munitions deployable package. This paper will present and discuss the flight test, results, and ALSN performance.

Macroscopic description of complex adaptive networks coevolving with dynamic node states

Science.gov (United States)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Slip-flow in complex porous media as determined by a multi-relaxation-time lattice Boltzmann model

Science.gov (United States)

Landry, C. J.; Prodanovic, M.; Eichhubl, P.

2014-12-01

The pores and throats of shales and mudrocks are predominantly found within a range of 1-100 nm, within this size range the flow of gas at reservoir conditions will fall within the slip-flow and low transition-flow regime (0.001 clays). Molecular dynamics (MD) simulations can be used to predict slip-flow in complex geometries, but due to prohibitive computational demand are generally limited to small volumes (one to several pores). Here we present a multi-relaxation-time lattice Boltzmann model (LBM) parameterized for slip-flow (Guo et al. 2008) and adapted here to complex geometries. LBMs are inherently parallelizable, such that flow in complex geometries of significant (near REV-scale) volumes can be readily simulated at a fraction of the computational cost of MD simulations. At the macroscopic-scale the LBM is parameterized with local effective viscosities at each node to capture the variance of the mean-free-path of gas molecules in a bounded system. The corrected mean-free-path for each lattice node is determined using the mean distance of the node to the pore-wall and Stop's correction for mean-free-paths in an infinite parallel-plate geometry. At the microscopic-scale, a combined bounce-back specular-reflection boundary condition is applied to the pore-wall nodes to capture Maxwellian-slip. The LBM simulation results are first validated in simple tube and channel geometries, where good agreement is found for Knudsen numbers below 0.1, and fair agreement is found for Knudsen numbers between 0.1 and 0.5. More complex geometries are then examined including triangular-ducts and ellipsoid-ducts, both with constant and tapering/expanding cross-sections, as well as a clay pore-network imaged from a hydrocarbon producing shale by sequential focused ion-beam scanning electron microscopy. These results are analyzed to determine grid-independent resolutions, and used to explore the relationship between effective permeability and Knudsen number in complex geometries.

Contraindications of sentinel lymph node biopsy: Áre there any really?

Directory of Open Access Journals (Sweden)

Zografos George

2007-01-01

Full Text Available Abstract Background One of the most exciting and talked about new surgical techniques in breast cancer surgery is the sentinel lymph node biopsy. It is an alternative procedure to standard axillary lymph node dissection, which makes possible less invasive surgery and side effects for patients with early breast cancer that wouldn't benefit further from axillary lymph node clearance. Sentinel lymph node biopsy helps to accurately evaluate the status of the axilla and the extent of disease, but also determines appropriate adjuvant treatment and long-term follow-up. However, like all surgical procedures, the sentinel lymph node biopsy is not appropriate for each and every patient. Methods In this article we review the absolute and relative contraindications of the procedure in respect to clinically positive axilla, neoadjuvant therapy, tumor size, multicentric and multifocal disease, in situ carcinoma, pregnancy, age, body-mass index, allergies to dye and/or radio colloid and prior breast and/or axillary surgery. Results Certain conditions involving host factors and tumor biologic characteristics may have a negative impact on the success rate and accuracy of the procedure. The overall fraction of patients unsuitable or with multiple risk factors that may compromise the success of the sentinel lymph node biopsy, is very small. Nevertheless, these patients need to be successfully identified, appropriately advised and cautioned, and so do the surgeons that perform the procedure. Conclusion When performed by an experienced multi-disciplinary team, the SLNB is a highly effective and accurate alternative to standard level I and II axillary clearance in the vast majority of patients with early breast cancer.

Design of node record for fast active reflector

International Nuclear Information System (INIS)

Wu Wenqing; Luo Mingcheng; Tang Pengyi; Liu Jiajing; Wang Jian

2014-01-01

Active Reflector is the one of the innovations of Five hundred meter Aperture Spherical Telescope (FAST) whose performance touches on that of the overall telescope. Therefore a real time control system is needed by the Active Reflector System. In this paper, a new record type-node record is designed for EPICS-based active reflector control system of FAST, according to more than 2000 controlled node, which will be convenient for node management of IOC and prove the reusage of IOC codes. The record type is used in design of active reflector control system of FAST Miyun model. (authors)

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

Science.gov (United States)

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment. PMID:22163678

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

Directory of Open Access Journals (Sweden)

JangMook Kang

2010-09-01

Full Text Available In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

Automated construction of node software using attributes in a ubiquitous sensor network environment.

Science.gov (United States)

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric-the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

Multi-cut solutions in Chern-Simons matrix models

Science.gov (United States)

Morita, Takeshi; Sugiyama, Kento

2018-04-01

We elaborate the Chern-Simons (CS) matrix models at large N. The saddle point equations of these matrix models have a curious structure which cannot be seen in the ordinary one matrix models. Thanks to this structure, an infinite number of multi-cut solutions exist in the CS matrix models. Particularly we exactly derive the two-cut solutions at finite 't Hooft coupling in the pure CS matrix model. In the ABJM matrix model, we argue that some of multi-cut solutions might be interpreted as a condensation of the D2-brane instantons.

A Multi-Actor Dynamic Integrated Assessment Model (MADIAM)

OpenAIRE

Weber, Michael

2004-01-01

The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...

Real-time advanced nuclear reactor core model

International Nuclear Information System (INIS)

Koclas, J.; Friedman, F.; Paquette, C.; Vivier, P.

1990-01-01

The paper describes a multi-nodal advanced nuclear reactor core model. The model is based on application of modern equivalence theory to the solution of neutron diffusion equation in real time employing the finite differences method. The use of equivalence theory allows the application of the finite differences method to cores divided into hundreds of nodes, as opposed to the much finer divisions (in the order of ten thousands of nodes) where the unmodified method is currently applied. As a result the model can be used for modelling of the core kinetics for real time full scope training simulators. Results of benchmarks, validate the basic assumptions of the model and its applicability to real-time simulation. (orig./HP)

CFD simulation of flow through single and multi vane spiral pump for low pressure application using moving node unsteady computation

International Nuclear Information System (INIS)

Banerjee, I.; Mahendra, A.K.; Chandresh, B.G.; Srikanthan, M.R.; Bera, T.K.

2010-01-01

A spiral pump uses two interleaved spirals (it can be involutes of a circle, involutes of a square, hybrid wraps, Archimedean spiral, logarithmic spirals and so on). Interleaved spiral orbits eccentrically without rotation around a fixed scroll, thereby trapping and compressing pockets of fluids between the spirals. Another method of providing the compression motion is by virtue of co-rotating the spirals synchronously with an offset in centers of rotation thereby providing relative motion similar to orbiting. Recently spiral pumps for low-pressure application have become popular. Since spiral pumps contain gas volumes, whose shapes and size change continuously, the flow fields inside the pumps is time dependent. The unsteadiness controls the mechanisms responsible for the behavior of the spiral pump components. To improve the spiral pump design for better performance as per our process requirement and reliability, information is required to understand the detailed physics of the unsteady flows inside the spiral pumps. The unsteady flows in a pump are studied numerically. The system simulated includes one side gap between fixed and moving spirals as the other side lies just in the reverse symmetry of the one side. Heavy molecular weight, condensable gas is used as the moving fluid. The mesh free Least Square Kinetic Upwind Method (LSKUM) for moving node is applied for numerical analysis of wobbling spiral. Nodes and boundaries change their positions, for every real time step hence at every iteration nodes take new coordinates. Our work consists of identifying various spiral dimensions and geometry, geometric modeling of suction process, identifying the eccentric orbiting motion of the moving spiral, formation of variable velocity moving nodes. Flow analysis of the spiral pump is done with a view to design and develop new pump as per our requirement. Experimental data from an existing spiral pump is used to carryout validation of the code. (author)

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

International Nuclear Information System (INIS)

Bin Abas, Faizulsalihin; Takayama, Shigeru

2015-01-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and ''Cloud'' System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

Science.gov (United States)

Abas, Faizulsalihin bin; Takayama, Shigeru

2015-02-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems.

Science.gov (United States)

Indiveri, Giacomo

2008-09-03

Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

Directory of Open Access Journals (Sweden)

Giacomo Indiveri

2008-09-01

Full Text Available Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

Multiscale Modeling of the Early CD8 T-Cell Immune Response in Lymph Nodes: An Integrative Study

Directory of Open Access Journals (Sweden)

Sotiris A. Prokopiou

2014-09-01

Full Text Available CD8 T-cells are critical  in controlling infection by intracellular  pathogens. Upon encountering antigen presenting cells, T-cell receptor activation promotes the differentiation of naïve CD8 T-cells into strongly proliferating  activated and effector stages. We propose a 2D-multiscale computational model to study the maturation of CD8 T-cells in a lymph node controlled by their molecular profile. A novel molecular pathway is presented and converted into an ordinary differential  equation model, coupled with a cellular Potts model to describe cell-cell interactions. Key molecular  players such as activated IL2 receptor and Tbet levels  control the differentiation  from naïve into activated and effector stages, respectively,  while caspases and Fas-Fas ligand interactions control cell apoptosis.  Coupling  this molecular model to the cellular scale successfully  reproduces  qualitatively the evolution of total CD8 T-cell counts observed in mice lymph node, between Day 3 and 5.5 post-infection. Furthermore, this model allows us to make testable predictions  of the evolution of the different CD8 T-cell stages.

Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

Science.gov (United States)

Li, Zhiqiang; Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

2018-04-01

This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit.

Adaptive filtering for hidden node detection and tracking in networks.

Science.gov (United States)

Hamilton, Franz; Setzer, Beverly; Chavez, Sergio; Tran, Hien; Lloyd, Alun L

2017-07-01

The identification of network connectivity from noisy time series is of great interest in the study of network dynamics. This connectivity estimation problem becomes more complicated when we consider the possibility of hidden nodes within the network. These hidden nodes act as unknown drivers on our network and their presence can lead to the identification of false connections, resulting in incorrect network inference. Detecting the parts of the network they are acting on is thus critical. Here, we propose a novel method for hidden node detection based on an adaptive filtering framework with specific application to neuronal networks. We consider the hidden node as a problem of missing variables when model fitting and show that the estimated system noise covariance provided by the adaptive filter can be used to localize the influence of the hidden nodes and distinguish the effects of different hidden nodes. Additionally, we show that the sequential nature of our algorithm allows for tracking changes in the hidden node influence over time.

Dynamically reassigning a connected node to a block of compute nodes for re-launching a failed job

Science.gov (United States)

Budnik, Thomas A [Rochester, MN; Knudson, Brant L [Rochester, MN; Megerian, Mark G [Rochester, MN; Miller, Samuel J [Rochester, MN; Stockdell, William M [Byron, MN

2012-03-20

Methods, systems, and products for dynamically reassigning a connected node to a block of compute nodes for re-launching a failed job that include: identifying that a job failed to execute on the block of compute nodes because connectivity failed between a compute node assigned as at least one of the connected nodes for the block of compute nodes and its supporting I/O node; and re-launching the job, including selecting an alternative connected node that is actively coupled for data communications with an active I/O node; and assigning the alternative connected node as the connected node for the block of compute nodes running the re-launched job.

A Brief Review on the Baer-Nunziato type Multi-pressure Multi-fluid Models

International Nuclear Information System (INIS)

Lee, Sang Yong; Park, Chan Eok; Lee, Gyu Cheon

2010-01-01

Single pressure two-fluid flow equations have complex characteristics. This causes ill-posedness problem. Even though some authors show that the numerical solutions are well behaved if the number of mesh points is sufficiently small, the stability of the solution is always challenged. There have been several attempts to overcome these problems. Multi-pressure multi-fluid models are one of them. Among them, Baer and Nunziato (BN) derived an interesting two-fluid model. BN model has independent phase pressures. It is closed by inserting volume fraction evolution equation. In this paper, several aspects of the BN type model will be reviewed and some suggestion for the future study will be made

Value of irradiation of neck nodes metastases. Pt. 1. Treatment of palpable nodes

International Nuclear Information System (INIS)

Bujko, K.

1993-01-01

Medical records of 222 patients with neck nodes metastases from squamous cell carcinoma of supraglottic larynx, tonsil and base of tongue were analyzed. All cases were treated with definitive irradiation. 110 patients were treated with orthovoltage technique with total doses of 5000-6000 rads, 150-10 rads per fraction; 112 patients with Co-60 with total doses 6000-7000 rads, 180-230 rads per fraction. Local-regional control was achieved in 28% of cases. Failures in the neck nodes with primary tumor controlled, were recorded in 10% of patients. Failures in a primary tumor alone were observed in 26% of patients, in primary tumor and neck nodes in 36%. Radiocurability of primary tumor and involved neck nodes was similar. In cases with primary tumor controlled, the probability of eradication of neck nodes metastases is high, even in N3 stage patients. Residual neck nodes palpable 1 to 3 months after irradiation were unfavorable prognostic factor indicated 50% risk of neck recurrence. In patients with complete regression of primary and nodal disease, failure in neck nodes was recorded in 5% of cases. The role of surgery following irradiation in patients with cervical nodes metastases is discussed. (author)

On Throughput Improvement of Wireless Ad Hoc Networks with Hidden Nodes

Science.gov (United States)

Choi, Hong-Seok; Lim, Jong-Tae

In this letter, we present the throughput analysis of the wireless ad hoc networks based on the IEEE 802.11 MAC (Medium Access Control). Especially, our analysis includes the case with the hidden node problem so that it can be applied to the multi-hop networks. In addition, we suggest a new channel access control algorithm to maximize the network throughput and show the usefulness of the proposed algorithm through simulations.

The design of multi-core DSP parallel model based on message passing and multi-level pipeline

Science.gov (United States)

Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong

2017-10-01

Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.

Wave Model Development in Multi-Ion Plasmas

Directory of Open Access Journals (Sweden)

Sung-Hee Song

1999-06-01

Full Text Available Near-earth space is composed of plasmas which embed a number of plasma waves. Space plasmas consist of electrons and multi-ion that determine local wave propagation characteristics. In multi-ion plasmas, it is di cult to find out analytic solution from the dispersion relation in general. In this work, we have developed a model with an arbitrary magnetic field and density as well as multi-ion plasmas. This model allows us to investigate how plasma waves behave when they propagate along realistic magnetic field lines, which are assumed by IGRF(International Geomagnetic Reference Field. The results are found to be useful for the analysis of the in situ observational data in space. For instance, if waves are assumed to propagate into the polar region, from the equatorial region, our model quantitatively shows how polarization is altered along earth travel path.

Exotic Homoclinic Surface of a Saddle-Node Limit Cycle in a Leech Neuron Model

Science.gov (United States)

Yooer, Chi-Feng; Wei, Fang; Xu, Jian-Xue; Zhang, Xin-Hua

2011-03-01

We carry out numerical and theoretical investigations on the global unstable invariant set (manifold) of a saddle-node limit cycle in a leech heart interneuron model. The corresponding global bifurcation is accompanied by an explosion of secondary bifurcations of limit cycles and the emergence of loop-shaped bifurcation structures. The dynamical behaviors of the trajectories of the invariant set are very complicated and can only be partially explained by existing theories.

Non sentinel node involvement prediction for sentinel node micrometastases in breast cancer: nomogram validation and comparison with other models.

Science.gov (United States)

Houvenaeghel, Gilles; Bannier, Marie; Nos, Claude; Giard, Sylvia; Mignotte, Herve; Jacquemier, Jocelyne; Martino, Marc; Esterni, Benjamin; Belichard, Catherine; Classe, Jean-Marc; Tunon de Lara, Christine; Cohen, Monique; Payan, Raoul; Blanchot, Jerome; Rouanet, Philippe; Penault-Llorca, Frederique; Bonnier, Pascal; Fournet, Sandrine; Agostini, Aubert; Marchal, Frederique; Garbay, Jean-Remi

2012-04-01

The risk of non sentinel node (NSN) involvement varies in function of the characteristics of sentinel nodes (SN) and primary tumor. Our aim was to determine and validate a statistical tool (a nomogram) able to predict the risk of NSN involvement in case of SN micro or sub-micrometastasis of breast cancer. We have compared this monogram with other models described in the literature. We have collected data on 905 patients, then 484 other patients, to build and validate the nomogram and compare it with other published scores and nomograms. Multivariate analysis conducted on the data of the first cohort allowed us to define a nomogram based on 5 criteria: the method of SN detection (immunohistochemistry or by standard coloration with HES); the ratio of positive SN out of total removed SN; the pathologic size of the tumor; the histological type; and the presence (or not) of lympho-vascular invasion. The nomogram developed here is the only one dedicated to micrometastasis and developed on the basis of two large cohorts. The results of this statistical tool in the calculation of the risk of NSN involvement is similar to those of the MSKCC (the similarly more effective nomogram according to the literature), with a lower rate of false negatives. this nomogram is dedicated specifically to cases of SN involvement by metastasis lower or equal to 2 mm. It could be used in clinical practice in the way to omit ALND when the risk of NSN involvement is low. Copyright © 2011 Elsevier Ltd. All rights reserved.

Experimental verification of a novel MEMS multi-modal vibration energy harvester for ultra-low power remote sensing nodes

Science.gov (United States)

Iannacci, J.; Sordo, G.; Serra, E.; Kucera, M.; Schmid, U.

2015-05-01

In this work, we discuss the verification and preliminary experimental characterization of a MEMS-based vibration Energy Harvester (EH) design. The device, named Four-Leaf Clover (FLC), is based on a circular-shaped mechanical resonator with four petal-like mass-spring cascaded systems. This solution introduces several mechanical Degrees of Freedom (DOFs), and therefore enables multiple resonant modes and deformation shapes in the vibrations frequency range of interest. The target is to realize a wideband multi-modal EH-MEMS device, that overcomes the typical narrowband working characteristics of standard cantilevered EHs, by ensuring flexible and adaptable power source to ultra-low power electronics for integrated remote sensing nodes (e.g. Wireless Sensor Networks - WSNs) in the Internet of Things (IoT) scenario, aiming to self-powered and energy autonomous smart systems. Finite Element Method simulations of the FLC EH-MEMS show the presence of several resonant modes for vibrations up to 4-5 kHz, and level of converted power up to a few μW at resonance and in closed-loop conditions (i.e. with resistive load). On the other hand, the first experimental tests of FLC fabricated samples, conducted with a Laser Doppler Vibrometer (LDV), proved the presence of several resonant modes, and allowed to validate the accuracy of the FEM modeling method. Such a good accordance holds validity for what concerns the coupled field behavior of the FLC EH-MEMS, as well. Both measurements and simulations performed at 190 Hz (i.e. out of resonance) showed the generation of power in the range of nW (Root Mean Square - RMS values). Further steps of this work will include the experimental characterization in a full range of vibrations, aiming to prove the whole functionality of the FLC EH-MEMS proposed design concept.

Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection.

Directory of Open Access Journals (Sweden)

Mark N Read

2016-09-01

Full Text Available The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto

Using multi-state markov models to identify credit card risk

Directory of Open Access Journals (Sweden)

Daniel Evangelista Régis

2016-06-01

Full Text Available Abstract The main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We also used logistic regression models to compare the results with those obtained using multi-state Markov models. The models were applied to an actual database of a Brazilian financial institution. In this application, multi-state Markov models performed better than logistic regression models in predicting default risk, and logistic regression models performed better in predicting cancellation risk.

Sentinel nodes outside lymph node basins in patients with melanoma

NARCIS (Netherlands)

Roozendaal, GK; de Vries, JDH; van Poll, D; Jansen, L; Nieweg, OE; Kroon, BBR; Schraffordt Koops, H.

Background: Lymphoscintigraphy occasionally reveals hot spots outside lymph node basins in patients with melanoma. The aim of this study was to evaluate such abnormally located hot spots. Methods: Sentinel node biopsy was studied prospectively in 379 patients with clinically localized cutaneous

Comparative analysis of multi-slice spiral CT and positron emission tomography-CT in evaluation of axillary lymph nodes in breast cancer patients

International Nuclear Information System (INIS)

Sun Xianchang; Zhang Ruyi; Liu Qingwei; Zhao Suhong; Zu Degui; Li Xin

2008-01-01

Objective: To evaluate and compare spiral CT and positron emission tomography-CT (PET-CT) in characterization of of axillary lymph nodes in breast cancer patients. Methods: Forty patients with pathologically proven breast cancer underwent contrast-enhanced spiral CT of the breast and axilla, 13 of them also underwent PET-CT examination. One hundred and fifty-eight axillary lymph nodes were found in the 40 patients through contrast enhanced spiral CT, while 57 lymph nodes were found in the 13 patients through PET-CT. Three radiologists rated the lymph nodes found in CT images on a five-point scale. If the score was equal to or greater than 3, it was defined as positive (metastatic), otherwise negative. Visual observation and semiquantitative analysis were used to classify lymph nodes in PET-CT images. The results of spiral CT observation and PET-CT observation of lymph nodes were compared with pathological results. The relative value of CT and PET-CT was analyzed. Exact probability statistics were employed. Results: One hundred and fifty eight lymph nodes of 40 patients were detected by spiral CT, 91 of them were diagnosed as positive and 67 as negative Among the lymph nodes found in spiral CT, 99 were positive and 59 were negative pathologicall. A total of 57 lymph nodes were found by PET-CT. Thirty-nine of them were defined as positive and 18 as negative. Among the lymph nodes found in PET-CT, 39 were positive and 18 were negative pathologically. The sensitivity, specificity, accuracy, positive and negative predictive values in CT prediction in axillary lymph nodes metastases were 88.89%, 94.91%, 91.14%, 96.70%, and 83.58%, respectively. The sensitivity, specificity, accuracy, positive and negative predictive values in PET-CT prediction in axillary lymph nodes metastases were 97.44%, 94.44%, 96.49%, 97.44%, and 94.44%, respectively. PET-CT had no significant difference with spiral CT in sensitivity, accuracy, positive and negative predictive values for detection

Multi-state modeling of biomolecules.

Directory of Open Access Journals (Sweden)

Melanie I Stefan

2014-09-01

Full Text Available Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the "specification problem" and the problem of how to use a computer to simulate the progress of the system over time (the "computation problem". To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus, BioNetGen, the Allosteric Network Compiler, and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim, DYNSTOC, RuleMonkey, and the Network-Free Stochastic Simulator (NFSim, and spatial simulators, including Meredys, SRSim, and MCell. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.

Cellular Automaton Modeling of Dendritic Growth Using a Multi-grid Method

International Nuclear Information System (INIS)

Natsume, Y; Ohsasa, K

2015-01-01

A two-dimensional cellular automaton model with a multi-grid method was developed to simulate dendritic growth. In the present model, we used a triple-grid system for temperature, solute concentration and solid fraction fields as a new approach of the multi-grid method. In order to evaluate the validity of the present model, we carried out simulations of single dendritic growth, secondary dendrite arm growth, multi-columnar dendritic growth and multi-equiaxed dendritic growth. From the results of the grid dependency from the simulation of single dendritic growth, we confirmed that the larger grid can be used in the simulation and that the computational time can be reduced dramatically. In the simulation of secondary dendrite arm growth, the results from the present model were in good agreement with the experimental data and the simulated results from a phase-field model. Thus, the present model can quantitatively simulate dendritic growth. From the simulated results of multi-columnar and multi-equiaxed dendrites, we confirmed that the present model can perform simulations under practical solidification conditions. (paper)

Competitive energy consumption under transmission constraints in a multi-supplier power grid system

Science.gov (United States)

Popov, Ivan; Krylatov, Alexander; Zakharov, Victor; Ivanov, Dmitry

2017-04-01

Power grid architectures need to be revised in order to manage the increasing number of producers and, more generally, the decentralisation of energy production and distribution. In this work, we describe a multi-supplier multi-consumer congestion model of a power grid, where the costs of consumers depend on the congestion in nodes and arcs of the power supply network. The consumer goal is both to meet their energy demand and to minimise the costs. We show that the methods of non-atomic routing can be applied in this model in order to describe current distribution in the network. We formulate a consumer cost minimisation game for this setting, and discuss the challenges arising in equilibrium search for this game.

A Compact Energy Harvesting System for Outdoor Wireless Sensor Nodes Based on a Low-Cost In Situ Photovoltaic Panel Characterization-Modelling Unit.

Science.gov (United States)

Antolín, Diego; Medrano, Nicolás; Calvo, Belén; Martínez, Pedro A

2017-08-04

This paper presents a low-cost high-efficiency solar energy harvesting system to power outdoor wireless sensor nodes. It is based on a Voltage Open Circuit (VOC) algorithm that estimates the open-circuit voltage by means of a multilayer perceptron neural network model trained using local experimental characterization data, which are acquired through a novel low cost characterization system incorporated into the deployed node. Both units-characterization and modelling-are controlled by the same low-cost microcontroller, providing a complete solution which can be understood as a virtual pilot cell, with identical characteristics to those of the specific small solar cell installed on the sensor node, that besides allows an easy adaptation to changes in the actual environmental conditions, panel aging, etc. Experimental comparison to a classical pilot panel based VOC algorithm show better efficiency under the same tested conditions.

A multi-species multi-fleet bioeconomic simulation model for the English Channel artisanal fisheries

DEFF Research Database (Denmark)

Ulrich, Clara; Le Gallic, B.; Dunn, M.R.

2002-01-01

Considering the large number of technical interactions between various fishing activities, the English Channel (ICES divisions VIId and VIIe) fisheries may be regarded as one large and diverse multi-country, multi-gear and multi-species artisanal fishery, although rarely studied as such. A whole...... of the model is to study the long-term consequences of various management alternatives on the economic situation of the English and French fleets fishing in the area and on exploited resources. The model describes this feature through the links between three entities on the one hand (stocks, fleets...... and "metiers", i.e. gear x target species x fishing area), and three modules on the other hand (activity, biological production and economics). The model is described and some simulation results are presented. An example simulating a decrease of one fleet segment effort illustrates these technical interactions...

Computationally Efficient Transient Stability Modeling of multi-terminal VSC-HVDC

DEFF Research Database (Denmark)

van der Meer, Arjen A; Rueda-Torres, José; Silva, Filipe Miguel Faria da

2016-01-01

This paper studies the inclusion of averaged VSC-based grid interfaces and HVDC networks into stability type simulations, and compares the accuracy and speed of three multi-terminal DC dynamic models: 1) a state-space based model, 2) a multi-rate improved model, and 3) a reduced-order model...

Related Drupal Nodes Block

NARCIS (Netherlands)

Van der Vegt, Wim

2010-01-01

Related Drupal Nodes Block This module exposes a block that uses Latent Semantic Analysis (Lsa) internally to suggest three nodes that are relevant to the node a user is viewing. This module performs three tasks. 1) It periodically indexes a Drupal site and generates a Lsa Term Document Matrix.

Critical nodes in signalling pathways

DEFF Research Database (Denmark)

Taniguchi, Cullen M; Emanuelli, Brice; Kahn, C Ronald

2006-01-01

Physiologically important cell-signalling networks are complex, and contain several points of regulation, signal divergence and crosstalk with other signalling cascades. Here, we use the concept of 'critical nodes' to define the important junctions in these pathways and illustrate their unique role...... using insulin signalling as a model system....

Discrimination of malignant versus benign mediastinal lymph nodes using diffusion MRI with an IVIM model

Energy Technology Data Exchange (ETDEWEB)

Qi, Li-Ping [Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Department of Radiology, Beijing (China); University of Illinois at Chicago, Center for MR Research, and Department of Radiology, Chicago, IL (United States); Yan, Wan-Pu; Chen, Ke-Neng [Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Department of Thoracic Oncosurgery, Beijing (China); Zhong, Zheng [University of Illinois at Chicago, Center for MR Research, and Department of Radiology, Chicago, IL (United States); University of Illinois, Department of Bioengineering, Chicago, IL (United States); Li, Xiao-Ting; Sun, Ying-Shi [Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Department of Radiology, Beijing (China); Cai, Kejia [University of Illinois at Chicago, Center for MR Research, and Department of Radiology, Chicago, IL (United States); University of Illinois, Department of Bioengineering, Chicago, IL (United States); University of Illinois, Department of Radiology, Chicago, IL (United States); Zhou, Xiaohong Joe [University of Illinois at Chicago, Center for MR Research, and Department of Radiology, Chicago, IL (United States); University of Illinois, Department of Bioengineering, Chicago, IL (United States); University of Illinois, Department of Radiology, Chicago, IL (United States); University of Illinois, Department of Neurosurgery, Chicago, IL (United States)

2018-03-15

To investigate the value of an intravoxel incoherent motion (IVIM) diffusion model for discriminating malignant versus benign mediastinal lymph nodes (MLN). Thirty-five subjects with enlarged MLN were scanned at 1.5 Tesla. Diffusion-weighted imaging was performed with eight b-values. IVIM parameters D, D*, and f, as well as apparent diffusion coefficient (ADC) from a mono-exponential model were obtained. 91 nodes (49 malignant and 42 benign) were analysed with pathologic (n=90) or radiologic (n=1) confirmations. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance. The mean values of D, ADC, and f for the malignant group were significantly lower than those for the benign group (p<0.001), while D* showed no significant difference (p=0.281). In the ROC analysis, the combination of D and f produced the largest area under the curve (0.953) compared to ADC or other individual IVIM parameters, leading to the best specificity (92.9%) and diagnostic accuracy (90.1%). This study demonstrates that the combination of IVIM parameters can improve differentiation between malignant and benign MLN as compared to using ADC alone. (orig.)

A Loader for Executing Multi-Binary Applications on the Thinking Machines CM-5: It's Not Just for SPMD Anymore

Science.gov (United States)

Becker, Jeffrey C.

1995-01-01

The Thinking Machines CM-5 platform was designed to run single program, multiple data (SPMD) applications, i.e., to run a single binary across all nodes of a partition, with each node possibly operating on different data. Certain classes of applications, such as multi-disciplinary computational fluid dynamics codes, are facilitated by the ability to have subsets of the partition nodes running different binaries. In order to extend the CM-5 system software to permit such applications, a multi-program loader was developed. This system is based on the dld loader which was originally developed for workstations. This paper provides a high level description of dld, and describes how it was ported to the CM-5 to provide support for multi-binary applications. Finally, it elaborates how the loader has been used to implement the CM-5 version of MPIRUN, a portable facility for running multi-disciplinary/multi-zonal MPI (Message-Passing Interface Standard) codes.

Summary of multi-core hardware and programming model investigations

Energy Technology Data Exchange (ETDEWEB)

Kelly, Suzanne Marie; Pedretti, Kevin Thomas Tauke; Levenhagen, Michael J.

2008-05-01

This report summarizes our investigations into multi-core processors and programming models for parallel scientific applications. The motivation for this study was to better understand the landscape of multi-core hardware, future trends, and the implications on system software for capability supercomputers. The results of this study are being used as input into the design of a new open-source light-weight kernel operating system being targeted at future capability supercomputers made up of multi-core processors. A goal of this effort is to create an agile system that is able to adapt to and efficiently support whatever multi-core hardware and programming models gain acceptance by the community.

Identification of hybrid node and link communities in complex networks.

Science.gov (United States)

He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

2015-03-02

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

Identification of hybrid node and link communities in complex networks

Science.gov (United States)

He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

2015-03-01

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility

Directory of Open Access Journals (Sweden)

Klaus Moessner

2013-10-01

Full Text Available This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines.

MCBT: Multi-Hop Cluster Based Stable Backbone Trees for Data Collection and Dissemination in WSNs

Directory of Open Access Journals (Sweden)

Tae-Jin Lee

2009-07-01

Full Text Available We propose a stable backbone tree construction algorithm using multi-hop clusters for wireless sensor networks (WSNs. The hierarchical cluster structure has advantages in data fusion and aggregation. Energy consumption can be decreased by managing nodes with cluster heads. Backbone nodes, which are responsible for performing and managing multi-hop communication, can reduce the communication overhead such as control traffic and minimize the number of active nodes. Previous backbone construction algorithms, such as Hierarchical Cluster-based Data Dissemination (HCDD and Multicluster, Mobile, Multimedia radio network (MMM, consume energy quickly. They are designed without regard to appropriate factors such as residual energy and degree (the number of connections or edges to other nodes of a node for WSNs. Thus, the network is quickly disconnected or has to reconstruct a backbone. We propose a distributed algorithm to create a stable backbone by selecting the nodes with higher energy or degree as the cluster heads. This increases the overall network lifetime. Moreover, the proposed method balances energy consumption by distributing the traffic load among nodes around the cluster head. In the simulation, the proposed scheme outperforms previous clustering schemes in terms of the average and the standard deviation of residual energy or degree of backbone nodes, the average residual energy of backbone nodes after disseminating the sensed data, and the network lifetime.

Hop-distance relationship analysis with quasi-UDG model for node localization in wireless sensor networks

Directory of Open Access Journals (Sweden)

Chen Ping

2011-01-01

Full Text Available Abstract In wireless sensor networks (WSNs, location information plays an important role in many fundamental services which includes geographic routing, target tracking, location-based coverage, topology control, and others. One promising approach in sensor network localization is the determination of location based on hop counts. A critical priori of this approach that directly influences the accuracy of location estimation is the hop-distance relationship. However, most of the related works on the hop-distance relationship assume the unit-disk graph (UDG model that is unrealistic in a practical scenario. In this paper, we formulate the hop-distance relationship for quasi-UDG model in WSNs where sensor nodes are randomly and independently deployed in a circular region based on a Poisson point process. Different from the UDG model, quasi-UDG model has the non-uniformity property for connectivity. We derive an approximated recursive expression for the probability of the hop count with a given geographic distance. The border effect and dependence problem are also taken into consideration. Furthermore, we give the expressions describing the distribution of distance with known hop counts for inner nodes and those suffered from the border effect where we discover the insignificance of the border effect. The analytical results are validated by simulations showing the accuracy of the employed approximation. Besides, we demonstrate the localization application of the formulated relationship and show the accuracy improvement in the WSN localization.

Computational modelling of multi-cell migration in a multi-signalling substrate

International Nuclear Information System (INIS)

Mousavi, Seyed Jamaleddin; Doblaré, Manuel; Doweidar, Mohamed Hamdy

2014-01-01

Cell migration is a vital process in many biological phenomena ranging from wound healing to tissue regeneration. Over the past few years, it has been proven that in addition to cell–cell and cell-substrate mechanical interactions (mechanotaxis), cells can be driven by thermal, chemical and/or electrical stimuli. A numerical model was recently presented by the authors to analyse single cell migration in a multi-signalling substrate. That work is here extended to include multi-cell migration due to cell–cell interaction in a multi-signalling substrate under different conditions. This model is based on balancing the forces that act on the cell population in the presence of different guiding cues. Several numerical experiments are presented to illustrate the effect of different stimuli on the trajectory and final location of the cell population within a 3D heterogeneous multi-signalling substrate. Our findings indicate that although multi-cell migration is relatively similar to single cell migration in some aspects, the associated behaviour is very different. For instance, cell–cell interaction may delay single cell migration towards effective cues while increasing the magnitude of the average net cell traction force as well as the local velocity. Besides, the random movement of a cell within a cell population is slightly greater than that of single cell migration. Moreover, higher electrical field strength causes the cell slug to flatten near the cathode. On the other hand, as with single cell migration, the existence of electrotaxis dominates mechanotaxis, moving the cells to the cathode or anode pole located at the free surface. The numerical results here obtained are qualitatively consistent with related experimental works. (paper)

Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes.

Science.gov (United States)

Ahmed, Faisal; Tamberg, Gert; Le Moullec, Yannick; Annus, Paul

2018-04-05

In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90-94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models.

Analytic model for the long-term evolution of circular Earth satellite orbits including lunar node regression

Science.gov (United States)

Zhu, Ting-Lei; Zhao, Chang-Yin; Zhang, Ming-Jiang

2017-04-01

This paper aims to obtain an analytic approximation to the evolution of circular orbits governed by the Earth's J2 and the luni-solar gravitational perturbations. Assuming that the lunar orbital plane coincides with the ecliptic plane, Allan and Cook (Proc. R. Soc. A, Math. Phys. Eng. Sci. 280(1380):97, 1964) derived an analytic solution to the orbital plane evolution of circular orbits. Using their result as an intermediate solution, we establish an approximate analytic model with lunar orbital inclination and its node regression be taken into account. Finally, an approximate analytic expression is derived, which is accurate compared to the numerical results except for the resonant cases when the period of the reference orbit approximately equals the integer multiples (especially 1 or 2 times) of lunar node regression period.

Predictive modeling of coupled multi-physics systems: I. Theory

International Nuclear Information System (INIS)

Cacuci, Dan Gabriel

2014-01-01

Highlights: • We developed “predictive modeling of coupled multi-physics systems (PMCMPS)”. • PMCMPS reduces predicted uncertainties in predicted model responses and parameters. • PMCMPS treats efficiently very large coupled systems. - Abstract: This work presents an innovative mathematical methodology for “predictive modeling of coupled multi-physics systems (PMCMPS).” This methodology takes into account fully the coupling terms between the systems but requires only the computational resources that would be needed to perform predictive modeling on each system separately. The PMCMPS methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution based on a priori known mean values and uncertainties characterizing the parameters and responses for both multi-physics models. This “maximum entropy”-approximate a priori distribution is combined, using Bayes’ theorem, with the “likelihood” provided by the multi-physics simulation models. Subsequently, the posterior distribution thus obtained is evaluated using the saddle-point method to obtain analytical expressions for the optimally predicted values for the multi-physics models parameters and responses along with corresponding reduced uncertainties. Noteworthy, the predictive modeling methodology for the coupled systems is constructed such that the systems can be considered sequentially rather than simultaneously, while preserving exactly the same results as if the systems were treated simultaneously. Consequently, very large coupled systems, which could perhaps exceed available computational resources if treated simultaneously, can be treated with the PMCMPS methodology presented in this work sequentially and without any loss of generality or information, requiring just the resources that would be needed if the systems were treated sequentially

Isolated perifacial lymph node metastasis in oral squamous cell carcinoma with clinically node-negative neck.

Science.gov (United States)

Agarwal, Sangeet Kumar; Arora, Sowrabh Kumar; Kumar, Gopal; Sarin, Deepak

2016-10-01

The incidence of occult perifacial nodal disease in oral cavity squamous cell carcinoma is not well reported. The purpose of this study was to evaluate the incidence of isolated perifacial lymph node metastasis in patients with oral squamous cell carcinoma with a clinically node-negative neck. The study will shed light on current controversies and will provide valuable clinical and pathological information in the practice of routine comprehensive removal of these lymph node pads in selective neck dissection in the node-negative neck. Prospective analysis. This study was started in August 2011 when intraoperatively we routinely separated the lymph node levels from the main specimen for evaluation of the metastatic rate to different lymph node levels in 231 patients of oral squamous cell cancer with a clinically node-negative neck. The current study demonstrated that 19 (8.22%) out of 231 patients showed ipsilateral isolated perifacial lymph node involvement. The incidence of isolated perifacial nodes did not differ significantly between the oral tongue (7.14%) and buccal mucosa (7.75%). Incidence was statistically significant in cases with lower age group (oral squamous cell carcinoma with a clinically node-negative neck. The incidence of isolated perifacial involvement is high in cases of buccal mucosal and tongue cancers. A meticulous dissection of the perifacial nodes seems prudent when treating the neck in oral cavity squamous cell carcinoma. 4 Laryngoscope, 126:2252-2256, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Bi-dimension decomposed hidden Markov models for multi-person activity recognition

Institute of Scientific and Technical Information of China (English)

Wei-dong ZHANG; Feng CHEN; Wen-li XU

2009-01-01

We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named 'decomposed hidden Markov model' (DHMM), combines spatial decomposition and hierarchical abstraction to capture multi-modal, long-term dependent and multi-scale characteristics of activities. Decomposition in space and time offers conceptual advantages of compaction and clarity, and greatly reduces the size of state space as well as the number of parameters.DHMMs are efficient even when the number of persons is variable. We also introduce an efficient approximation algorithm for inference and parameter estimation. Experiments on multi-person activities and multi-modal individual activities demonstrate that DHMMs are more efficient and reliable than familiar models, such as coupled HMMs, hierarchical HMMs, and multi-observation HMMs.

Information loss method to measure node similarity in networks

Science.gov (United States)

Li, Yongli; Luo, Peng; Wu, Chong

2014-09-01

Similarity measurement for the network node has been paid increasing attention in the field of statistical physics. In this paper, we propose an entropy-based information loss method to measure the node similarity. The whole model is established based on this idea that less information loss is caused by seeing two more similar nodes as the same. The proposed new method has relatively low algorithm complexity, making it less time-consuming and more efficient to deal with the large scale real-world network. In order to clarify its availability and accuracy, this new approach was compared with some other selected approaches on two artificial examples and synthetic networks. Furthermore, the proposed method is also successfully applied to predict the network evolution and predict the unknown nodes' attributions in the two application examples.

Evaluation of mobile ad hoc network reliability using propagation-based link reliability model

International Nuclear Information System (INIS)

Padmavathy, N.; Chaturvedi, Sanjay K.

2013-01-01

A wireless mobile ad hoc network (MANET) is a collection of solely independent nodes (that can move randomly around the area of deployment) making the topology highly dynamic; nodes communicate with each other by forming a single hop/multi-hop network and maintain connectivity in decentralized manner. MANET is modelled using geometric random graphs rather than random graphs because the link existence in MANET is a function of the geometric distance between the nodes and the transmission range of the nodes. Among many factors that contribute to the MANET reliability, the reliability of these networks also depends on the robustness of the link between the mobile nodes of the network. Recently, the reliability of such networks has been evaluated for imperfect nodes (transceivers) with binary model of communication links based on the transmission range of the mobile nodes and the distance between them. However, in reality, the probability of successful communication decreases as the signal strength deteriorates due to noise, fading or interference effects even up to the nodes' transmission range. Hence, in this paper, using a propagation-based link reliability model rather than a binary-model with nodes following a known failure distribution to evaluate the network reliability (2TR m , ATR m and AoTR m ) of MANET through Monte Carlo Simulation is proposed. The method is illustrated with an application and some imperative results are also presented

A new approach using the Pierce two-node model for different body parts.

Science.gov (United States)

Foda, Ehab; Sirén, Kai

2011-07-01

This paper presents a new approach, in applying the Pierce two-node model, to predict local skin temperatures of individual body parts with good accuracy. In this study, local skin temperature measurements at 24 sites on the bodies of 11 human subjects were carried out in a controlled environment under three different indoor conditions (i.e. neutral, warm and cold). The neutral condition measurements were used to adjust the local skin set-points in the model for each body part. Additional modifications to the calculation algorithm were introduced corresponding to different body parts. The local core set-points were then calculated, using a line search method, as the input values that allow the model to predict the skin temperatures with maximum deviation of ±0.1°C for the neutral condition. The model predictability was verified for the other two indoor conditions, and the results show that the modified model predicts local skin temperatures with average deviation of ±0.3°C.

Multi-scale climate modelling over Southern Africa using a variable-resolution global model

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

Node Discovery and Interpretation in Unstructured Resource-Constrained Environments

DEFF Research Database (Denmark)

Gechev, Miroslav; Kasabova, Slavyana; Mihovska, Albena D.

2014-01-01

for the discovery, linking and interpretation of nodes in unstructured and resource-constrained network environments and their interrelated and collective use for the delivery of smart services. The model is based on a basic mathematical approach, which describes and predicts the success of human interactions...... in the context of long-term relationships and identifies several key variables in the context of communications in resource-constrained environments. The general theoretical model is described and several algorithms are proposed as part of the node discovery, identification, and linking processes in relation...

A multi-band, multi-level, multi-electron model for efficient FDTD simulations of electromagnetic interactions with semiconductor quantum wells

Science.gov (United States)

Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

2015-08-01

We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.

Sentinel node concept in breast cancer

Energy Technology Data Exchange (ETDEWEB)

Kiricuta, I.C. [St. Vincenz-Hospital, Limburg (Germany). Inst. for Radiation Oncology

2000-07-01

Background/purpose: It seems that there exists a specific lymph node center called sentinel node (SN) which appears to be the primary site of metastases. The sentinel node concept (SNC) is fundamentally based on the orderly progression of tumor cells within the lymphatic system. It is the most important new concept in surgical and radiation oncology. The purpose is to present the biological significance, the diagnostic and clinical basis of the sentinel node concept in breast cancer patients. Material and methods: Lymphoscintigraphy and gamma probe biopsy is necessary to show predictable lymph flow to the regional sentinel node, to multiple sentinel nodes or unpredictable lymph flow to extra-regional sentinel nodes and for performing sentinel node procedure. The standard protocol for the evaluation of the sentinel node metastases consists of extensive histopathological investigation including step Hematoxylin and Eosin (H and E) stained sections and immunohistochemistry. Results: A high rate of success of the identification of the sentinel node for breast cancer was reported. The presence or absence of metastasis in this node is a very accurate predictor of overall nodal status. The temptation to examine the sentinel node with the greatest possible degree of accuracy highlights one of the major problems related to sentinel node biopsy. The success of the sentinel node procedure depends primarily on the adequate functional capacity necessary for sufficient uptake to ensure the accurate identification. In negative sentinel-node patients a complete axillary lymph node dissection is avoidable. In sentinel-node positive patients and clinically negative patients a postoperative radiotherapy would permit an adequate tumor control. The last 2-procedures permit a low morbidity. In the actual TNM classification it was recently introduced a definition of a 'pN0' patient based on sentinel node biopsy. New target volumes are defined for adjuvant radiotherapy or

A framework for multi-object tracking over distributed wireless camera networks

Science.gov (United States)

Gau, Victor; Hwang, Jenq-Neng

2010-07-01

In this paper, we propose a unified framework targeting at two important issues in a distributed wireless camera network, i.e., object tracking and network communication, to achieve reliable multi-object tracking over distributed wireless camera networks. In the object tracking part, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping field of views without initial training. To effectively exchange the tracking information among the distributed cameras, we proposed an idle probability based broadcasting method, iPro, which adaptively adjusts the broadcast probability to improve the broadcast effectiveness in a dense saturated camera network. Experimental results for the multi-object tracking demonstrate the promising performance of our approach on real video sequences for cameras with overlapping and non-overlapping views. The modeling and ns-2 simulation results show that iPro almost approaches the theoretical performance upper bound if cameras are within each other's transmission range. In more general scenarios, e.g., in case of hidden node problems, the simulation results show that iPro significantly outperforms standard IEEE 802.11, especially when the number of competing nodes increases.

Deployment of check-in nodes in complex networks

Science.gov (United States)

Jiang, Zhong-Yuan; Ma, Jian-Feng

2017-01-01

In many real complex networks such as the city road networks and highway networks, vehicles often have to pass through some specially functioned nodes to receive check-in like services such as gas supplement at gas stations. Based on existing network structures, to guarantee every shortest path including at least a check-in node, the location selection of all check-in nodes is very essential and important to make vehicles to easily visit these check-in nodes, and it is still remains an open problem in complex network studies. In this work, we aim to find possible solutions for this problem. We first convert it into a set cover problem which is NP-complete and propose to employ the greedy algorithm to achieve an approximate result. Inspired by heuristic information of network structure, we discuss other four check-in node location deployment methods including high betweenness first (HBF), high degree first (HDF), random and low degree first (LDF). Finally, we compose extensive simulations in classical scale-free networks, random networks and real network models, and the results can well confirm the effectiveness of the greedy algorithm. This work has potential applications into many real networks.

Sentinel node concept in breast cancer

International Nuclear Information System (INIS)

Kiricuta, I.C.

2000-01-01

Background/purpose: It seems that there exists a specific lymph node center called sentinel node (SN) which appears to be the primary site of metastases. The sentinel node concept (SNC) is fundamentally based on the orderly progression of tumor cells within the lymphatic system. It is the most important new concept in surgical and radiation oncology. The purpose is to present the biological significance, the diagnostic and clinical basis of the sentinel node concept in breast cancer patients. Material and methods: Lymphoscintigraphy and gamma probe biopsy is necessary to show predictable lymph flow to the regional sentinel node, to multiple sentinel nodes or unpredictable lymph flow to extra-regional sentinel nodes and for performing sentinel node procedure. The standard protocol for the evaluation of the sentinel node metastases consists of extensive histopathological investigation including step Hematoxylin and Eosin (H and E) stained sections and immunohistochemistry. Results: A high rate of success of the identification of the sentinel node for breast cancer was reported. The presence or absence of metastasis in this node is a very accurate predictor of overall nodal status. The temptation to examine the sentinel node with the greatest possible degree of accuracy highlights one of the major problems related to sentinel node biopsy. The success of the sentinel node procedure depends primarily on the adequate functional capacity necessary for sufficient uptake to ensure the accurate identification. In negative sentinel-node patients a complete axillary lymph node dissection is avoidable. In sentinel-node positive patients and clinically negative patients a postoperative radiotherapy would permit an adequate tumor control. The last 2-procedures permit a low morbidity. In the actual TNM classification it was recently introduced a definition of a 'pN0' patient based on sentinel node biopsy. New target volumes are defined for adjuvant radiotherapy or lymphatic basins

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

Science.gov (United States)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Chemical shift effect predicting lymph node status in rectal cancer using high-resolution MR imaging with node-for-node matched histopathological validation

Energy Technology Data Exchange (ETDEWEB)

Zhang, Hongmei; Zhang, Chongda; Ye, Feng; Liu, Yuan; Zhou, Chunwu [Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, ChaoYang District, Beijing (China); Zheng, Zhaoxu [Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Colorectal Oncology, National Cancer Center/Cancer Hospital, ChaoYang District, Beijing (China); Zou, Shuangmei [Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Pathology, National Cancer Center/Cancer Hospital, ChaoYang District, Beijing (China)

2017-09-15

To evaluate the value of the chemical shift effect (CSE) as well as other criteria for the prediction of lymph node status. Twenty-nine patients who underwent radical surgery of rectal cancers were studied with pre- and postoperative specimen MRI. Lymph nodes were harvested from transverse whole-mount specimens and compared with in vivo and ex vivo images to obtain a precise slice-for-section match. Preoperative MR characteristics including CSE, as well as other predictors, were evaluated by two readers independently between benign and metastatic nodes. A total of 255 benign and 35 metastatic nodes were obtained; 71.4% and 69.4% of benign nodes were detected with regular CSE for two readers, whereas 80.0% and 74.3% of metastatic nodes with absence of CSE. The CSE rendered areas under the ROC curve (AUC) of 0.879 and 0.845 for predicting nodal status for two readers. The criteria of nodal location, border, signal intensity and minimum distance to the rectal wall were also useful but with AUCs (0.629-0.743) lower than those of CSE. CSE is a reliable predictor for differentiating benign from metastatic nodes. Additional criteria should be taken into account when it is difficult to determine the nodal status by using only a single predictor. (orig.)

Multi-Level Marketing as a business model

Directory of Open Access Journals (Sweden)

Bogdan Gregor

2013-03-01

Full Text Available Multi Level Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (carries a very low risk ways of conducting a business activity. The knowledge about functioning of this business model, both among theoreticians (scanty literature on the subject and practitioners, is still insufficient in Poland. Thus, the presented paper has been prepared as — in the Authors' opinion — it, at least infinitesimally, bridges the gap in the recognition of Multi Level Marketing issues. The aim of the study was, first of all, to describe Multi Level Marketing, to indicate practical benefits of this business model as well as to present basic systems of calculating a commission, which are used in marketing plans of companies. The discussion was based on the study of literature and the knowledge gained in the course of free-form interviews with the leaders of the sector.

Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras

Science.gov (United States)

Andrade, Jefferson O.; Kameyama, Yukiyoshi

Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In this paper, we propose a novel, efficient algorithm for multi-valued bounded model checking. A notable feature of our algorithm is that it is not based on reduction of multi-values into two-values; instead, it generates a single formula which represents multi-valuedness by a suitable encoding, and asks a standard SAT solver to check its satisfiability. Our experimental results show a significant improvement in the number of variables and clauses and also in execution time compared with the reduction-based one.

Improvement of the SEP protocol based on community structure of node degree

Science.gov (United States)

Li, Donglin; Wei, Suyuan

2017-05-01

Analyzing the Stable election protocol (SEP) in wireless sensor networks and aiming at the problem of inhomogeneous cluster-heads distribution and unreasonable cluster-heads selectivity and single hop transmission in the SEP, a SEP Protocol based on community structure of node degree (SEP-CSND) is proposed. In this algorithm, network node deployed by using grid deployment model, and the connection between nodes established by setting up the communication threshold. The community structure constructed by node degree, then cluster head is elected in the community structure. On the basis of SEP, the node's residual energy and node degree is added in cluster-heads election. The information is transmitted with mode of multiple hops between network nodes. The simulation experiments showed that compared to the classical LEACH and SEP, this algorithm balances the energy consumption of the entire network and significantly prolongs network lifetime.

Algorithm for Financial Derivatives Evaluation in a Generalized Multi-Heston Model

Directory of Open Access Journals (Sweden)

Dan Negura

2013-02-01

Full Text Available In this paper we show how could a financial derivative be estimated based on an assumed Multi-Heston model support.Keywords: Euler Maruyama discretization method, Monte Carlo simulation, Heston model, Double-Heston model, Multi-Heston model

Network Design with Node Degree Balance Constraints

DEFF Research Database (Denmark)

Pedersen, Michael Berliner; Crainic, Teodor Gabriel

This presentation discusses an extension to the network design model where there in addition to the flow conservation constraints also are constraints that require design conservation. This means that the number of arcs entering and leaving a node must be the same. As will be shown the model has ...

Reliability-oriented multi-resource allocation in a stochastic-flow network

International Nuclear Information System (INIS)

Hsieh, C.-C.; Lin, M.-H.

2003-01-01

A stochastic-flow network consists of a set of nodes, including source nodes which supply various resources and sink nodes at which resource demands take place, and a collection of arcs whose capacities have multiple operational states. The network reliability of such a stochastic-flow network is the probability that resources can be successfully transmitted from source nodes through multi-capacitated arcs to sink nodes. Although the evaluation schemes of network reliability in stochastic-flow networks have been extensively studied in the literature, how to allocate various resources at source nodes in a reliable means remains unanswered. In this study, a resource allocation problem in a stochastic-flow network is formulated that aims to determine the optimal resource allocation policy at source nodes subject to given resource demands at sink nodes such that the network reliability of the stochastic-flow network is maximized, and an algorithm for computing the optimal resource allocation is proposed that incorporates the principle of minimal path vectors. A numerical example is given to illustrate the proposed algorithm

Assessment of multi class kinematic wave models

NARCIS (Netherlands)

Van Wageningen-Kessels, F.L.M.; Van Lint, J.W.C.; Vuik, C.; Hoogendoorn, S.P.

2012-01-01

In the last decade many multi class kinematic wave (MCKW) traffic ow models have been proposed. MCKW models introduce heterogeneity among vehicles and drivers. For example, they take into account differences in (maximum) velocities and driving style. Nevertheless, the models are macroscopic and the

MULTI: a shared memory approach to cooperative molecular modeling.

Science.gov (United States)

Darden, T; Johnson, P; Smith, H

1991-03-01

A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.

Lymph Node Micrometastases are Associated with Worse Survival in Patients with Otherwise Node-Negative Hilar Cholangiocarcinoma.

Science.gov (United States)

Mantel, Hendrik T J; Wiggers, Jim K; Verheij, Joanne; Doff, Jan J; Sieders, Egbert; van Gulik, Thomas M; Gouw, Annette S H; Porte, Robert J

2015-12-01

Lymph node metastases on routine histology are a strong negative predictor for survival after resection of hilar cholangiocarcinoma. Additional immunohistochemistry can detect lymph node micrometastases in patients who are otherwise node negative, but the prognostic value is unsure. The objective of this study was to assess the effect on survival of immunohistochemically detected lymph node micrometastases in patients with node-negative (pN0) hilar cholangiocarcinoma on routine histology. Between 1990 and 2010, a total of 146 patients underwent curative-intent resection of hilar cholangiocarcinoma with regional lymphadenectomy at two university medical centers in the Netherlands. Ninety-one patients (62 %) without lymph node metastases at routine histology were included. Micrometastases were identified by multiple sectioning of all lymph nodes and additional immunostaining with an antibody against cytokeratin 19 (K19). The association with overall survival was assessed in univariable and multivariable analysis. Median follow-up was 48 months. Micrometastases were identified in 16 (5 %) of 324 lymph nodes, corresponding to 11 (12 %) of 91 patients. There were no differences in clinical variables between K19 lymph node-positive and -negative patients. Five-year survival rates in patients with lymph node micrometastases were significantly lower compared to patients without micrometastases (27 vs. 54 %, P = 0.01). Multivariable analysis confirmed micrometastases as an independent prognostic factor for survival (adjusted Hazard ratio 2.4, P = 0.02). Lymph node micrometastases are associated with worse survival after resection of hilar cholangiocarcinoma. Immunohistochemical detection of lymph node micrometastases leads to better staging of patients who were initially diagnosed with node-negative (pN0) hilar cholangiocarcinoma on routine histology.

Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras

OpenAIRE

Andrade, Jefferson O.; Kameyama, Yukiyoshi

2012-01-01

Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In thi...

Exploring the evolution of node neighborhoods in Dynamic Networks

Science.gov (United States)

Orman, Günce Keziban; Labatut, Vincent; Naskali, Ahmet Teoman

2017-09-01

Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, and the number of available tools is consequently much smaller than for static networks. In this work, we propose a method specifically designed to take advantage of the longitudinal nature of dynamic networks. It characterizes each individual node by studying the evolution of its direct neighborhood, based on the assumption that the way this neighborhood changes reflects the role and position of the node in the whole network. For this purpose, we define the concept of neighborhood event, which corresponds to the various transformations such groups of nodes can undergo, and describe an algorithm for detecting such events. We demonstrate the interest of our method on three real-world networks: DBLP, LastFM and Enron. We apply frequent pattern mining to extract meaningful information from temporal sequences of neighborhood events. This results in the identification of behavioral trends emerging in the whole network, as well as the individual characterization of specific nodes. We also perform a cluster analysis, which reveals that, in all three networks, one can distinguish two types of nodes exhibiting different behaviors: a very small group of active nodes, whose neighborhood undergo diverse and frequent events, and a very large group of stable nodes.

Quantifying credit portfolio losses under multi-factor models

NARCIS (Netherlands)

G. Colldeforns-Papiol (Gemma); L. Ortiz Gracia (Luis); C.W. Oosterlee (Kees)

2018-01-01

textabstractIn this work, we investigate the challenging problem of estimating credit risk measures of portfolios with exposure concentration under the multi-factor Gaussian and multi-factor t-copula models. It is well-known that Monte Carlo (MC) methods are highly demanding from the computational

Multi-model approach to characterize human handwriting motion.

Science.gov (United States)

Chihi, I; Abdelkrim, A; Benrejeb, M

2016-02-01

This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.

Power/Energy Estimator for Designing WSN Nodes with Ambient Energy Harvesting Feature

Directory of Open Access Journals (Sweden)

Jutel Dominique

2011-01-01

Full Text Available Abstract Wireless Sensor Networks (WSNs consist of spatially distributed autonomous sensors to cooperatively monitor physical conditions. Thus, the node battery autonomy is critical. To outperform it, most WSNs rely on the harvesting capability. As nodes can recharge whenever energy is available, the problem is to determine at design time the node autonomy. For our project, we solve it by creating a power/energy estimator that simulates business scenarios to predict node autonomy; the estimation concerns both power and energy features. Based on node architecture configuration, its Dynamic Power Management (DPM policy, and environmental conditions, we present a simulator that helps identify power consumption hot spots and make critical choices during the system design. It also helps to scale the energy storage system as well as the energy harvesters correctly. The hardware part is modelled using the FLPA methodology to develop different node component models with a variable accuracy. For the logical part, we developped a specific DPM by integrating meteorology and weather forecast behaviours. The novelty comes from the ability to simulate the WSN harvesting capability and to estimate at runtime the remaining duration of each service.

Reinforcement learning for dpm of embedded visual sensor nodes

International Nuclear Information System (INIS)

Khani, U.; Sadhayo, I. H.

2014-01-01

This paper proposes a RL (Reinforcement Learning) based DPM (Dynamic Power Management) technique to learn time out policies during a visual sensor node's operation which has multiple power/performance states. As opposed to the widely used static time out policies, our proposed DPM policy which is also referred to as OLTP (Online Learning of Time out Policies), learns to dynamically change the time out decisions in the different node states including the non-operational states. The selection of time out values in different power/performance states of a visual sensing platform is based on the workload estimates derived from a ML-ANN (Multi-Layer Artificial Neural Network) and an objective function given by weighted performance and power parameters. The DPM approach is also able to dynamically adjust the power-performance weights online to satisfy a given constraint of either power consumption or performance. Results show that the proposed learning algorithm explores the power-performance tradeoff with non-stationary workload and outperforms other DPM policies. It also performs the online adjustment of the tradeoff parameters in order to meet a user-specified constraint. (author)

Deploying Node.js

CERN Document Server

Pasquali, Sandro

2015-01-01

If you are an intermediate or advanced developer deploying your Node.js applications, then this book is for you. If you have already built a Node application or module and want to take your knowledge to the next level, this book will help you find your way.

Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset.

Science.gov (United States)

Ha, Richard; Chang, Peter; Karcich, Jenika; Mutasa, Simukayi; Fardanesh, Reza; Wynn, Ralph T; Liu, Michael Z; Jambawalikar, Sachin

2018-04-25

The aim of this study is to evaluate the role of convolutional neural network (CNN) in predicting axillary lymph node metastasis, using a breast MRI dataset. An institutional review board (IRB)-approved retrospective review of our database from 1/2013 to 6/2016 identified 275 axillary lymph nodes for this study. Biopsy-proven 133 metastatic axillary lymph nodes and 142 negative control lymph nodes were identified based on benign biopsies (100) and from healthy MRI screening patients (42) with at least 3 years of negative follow-up. For each breast MRI, axillary lymph node was identified on first T1 post contrast dynamic images and underwent 3D segmentation using an open source software platform 3D Slicer. A 32 × 32 patch was then extracted from the center slice of the segmented tumor data. A CNN was designed for lymph node prediction based on each of these cropped images. The CNN consisted of seven convolutional layers and max-pooling layers with 50% dropout applied in the linear layer. In addition, data augmentation and L2 regularization were performed to limit overfitting. Training was implemented using the Adam optimizer, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments. Code for this study was written in Python using the TensorFlow module (1.0.0). Experiments and CNN training were done on a Linux workstation with NVIDIA GTX 1070 Pascal GPU. Two class axillary lymph node metastasis prediction models were evaluated. For each lymph node, a final softmax score threshold of 0.5 was used for classification. Based on this, CNN achieved a mean five-fold cross-validation accuracy of 84.3%. It is feasible for current deep CNN architectures to be trained to predict likelihood of axillary lymph node metastasis. Larger dataset will likely improve our prediction model and can potentially be a non-invasive alternative to core needle biopsy and even sentinel lymph node

Sentinel node biopsy in penile cancer

DEFF Research Database (Denmark)

Jakobsen, J. K.; Krarup, K. P.; Sommer, P.

2015-01-01

INTRODUCTION & OBJECTIVES: Nodal involvement is a strong prognosticator in penile cancer and lymph node staging is crucial. Sentinel node biopsy (SNB) has proven a useful staging tool with few complications, but evidence rely mostly on single institution publications with a short follow-up. In th......INTRODUCTION & OBJECTIVES: Nodal involvement is a strong prognosticator in penile cancer and lymph node staging is crucial. Sentinel node biopsy (SNB) has proven a useful staging tool with few complications, but evidence rely mostly on single institution publications with a short follow...... died from complications. CONCLUSIONS: To our knowledge, this is the first complete national study on sentinel node biopsy. Penile cancer sentinel node biopsy with a close follow-up is a reliable lymph node staging and has few complications in a national multicentre setting. Inguinal lymph node...

Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

Directory of Open Access Journals (Sweden)

Zili Zhang

Full Text Available Bi-objective Traveling Salesman Problem (bTSP is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM. PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

Coupling effect of nodes popularity and similarity on social network persistence.

Science.gov (United States)

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-21

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes' popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Uncertain and multi-objective programming models for crop planting structure optimization

Directory of Open Access Journals (Sweden)

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

2016-03-01

Full Text Available Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP model and an inexact fuzzy linear programming (IFLP model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods

Immune networks: multi-tasking capabilities at medium load

International Nuclear Information System (INIS)

Agliari, E; Annibale, A; Barra, A; Coolen, A C C; Tantari, D

2013-01-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ∼ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ∼ N δ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ < 1 the existence of large regions in the phase diagram where the network can retrieve all stored patterns simultaneously. Finally, in the high-load regime δ = 1 we find that the system behaves as a spin-glass, suggesting that finite-connectivity frameworks are required to achieve effective retrieval. (paper)

A real-time prediction model for post-irradiation malignant cervical lymph nodes.

Science.gov (United States)

Lo, W-C; Cheng, P-W; Shueng, P-W; Hsieh, C-H; Chang, Y-L; Liao, L-J

2018-04-01

To establish a real-time predictive scoring model based on sonographic characteristics for identifying malignant cervical lymph nodes (LNs) in cancer patients after neck irradiation. One-hundred forty-four irradiation-treated patients underwent ultrasonography and ultrasound-guided fine-needle aspirations (USgFNAs), and the resultant data were used to construct a real-time and computerised predictive scoring model. This scoring system was further compared with our previously proposed prediction model. A predictive scoring model, 1.35 × (L axis) + 2.03 × (S axis) + 2.27 × (margin) + 1.48 × (echogenic hilum) + 3.7, was generated by stepwise multivariate logistic regression analysis. Neck LNs were considered to be malignant when the score was ≥ 7, corresponding to a sensitivity of 85.5%, specificity of 79.4%, positive predictive value (PPV) of 82.3%, negative predictive value (NPV) of 83.1%, and overall accuracy of 82.6%. When this new model and the original model were compared, the areas under the receiver operating characteristic curve (c-statistic) were 0.89 and 0.81, respectively (P real-time sonographic predictive scoring model was constructed to provide prompt and reliable guidance for USgFNA biopsies to manage cervical LNs after neck irradiation. © 2017 John Wiley & Sons Ltd.

A Bayesian alternative for multi-objective ecohydrological model specification

Science.gov (United States)

Tang, Yating; Marshall, Lucy; Sharma, Ashish; Ajami, Hoori

2018-01-01

Recent studies have identified the importance of vegetation processes in terrestrial hydrologic systems. Process-based ecohydrological models combine hydrological, physical, biochemical and ecological processes of the catchments, and as such are generally more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov chain Monte Carlo (MCMC) techniques. The Bayesian approach offers an appealing alternative to traditional multi-objective hydrologic model calibrations by defining proper prior distributions that can be considered analogous to the ad-hoc weighting often prescribed in multi-objective calibration. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique. In our study, a Pareto-based multi-objective optimization and a formal Bayesian framework are implemented in a conceptual ecohydrological model that combines a hydrological model (HYMOD) and a modified Bucket Grassland Model (BGM). Simulations focused on one objective (streamflow/LAI) and multiple objectives (streamflow and LAI) with different emphasis defined via the prior distribution of the model error parameters. Results show more reliable outputs for both predicted streamflow and LAI using Bayesian multi-objective calibration with specified prior distributions for error parameters based on results from the Pareto front in the ecohydrological modeling. The methodology implemented here provides insight into the usefulness of multiobjective Bayesian calibration for ecohydrologic systems and the importance of appropriate prior

The Network Completion Problem: Inferring Missing Nodes and Edges in Networks

Energy Technology Data Exchange (ETDEWEB)

Kim, M; Leskovec, J

2011-11-14

Network structures, such as social networks, web graphs and networks from systems biology, play important roles in many areas of science and our everyday lives. In order to study the networks one needs to first collect reliable large scale network data. While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomplete with nodes and edges missing. Commonly, only a part of the network can be observed and we would like to infer the unobserved part of the network. We address this issue by studying the Network Completion Problem: Given a network with missing nodes and edges, can we complete the missing part? We cast the problem in the Expectation Maximization (EM) framework where we use the observed part of the network to fit a model of network structure, and then we estimate the missing part of the network using the model, re-estimate the parameters and so on. We combine the EM with the Kronecker graphs model and design a scalable Metropolized Gibbs sampling approach that allows for the estimation of the model parameters as well as the inference about missing nodes and edges of the network. Experiments on synthetic and several real-world networks show that our approach can effectively recover the network even when about half of the nodes in the network are missing. Our algorithm outperforms not only classical link-prediction approaches but also the state of the art Stochastic block modeling approach. Furthermore, our algorithm easily scales to networks with tens of thousands of nodes.

Distributed ESO based cooperative tracking control for high-order nonlinear multiagent systems with lumped disturbance and application in multi flight simulators systems.

Science.gov (United States)

Cong, Zhang

2018-03-01

Based on extended state observer, a novel and practical design method is developed to solve the distributed cooperative tracking problem of higher-order nonlinear multiagent systems with lumped disturbance in a fixed communication topology directed graph. The proposed method is designed to guarantee all the follower nodes ultimately and uniformly converge to the leader node with bounded residual errors. The leader node, modeled as a higher-order non-autonomous nonlinear system, acts as a command generator giving commands only to a small portion of the networked follower nodes. Extended state observer is used to estimate the local states and lumped disturbance of each follower node. Moreover, each distributed controller can work independently only requiring the relative states and/or the estimated relative states information between itself and its neighbors. Finally an engineering application of multi flight simulators systems is demonstrated to test and verify the effectiveness of the proposed algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Model-Checking of Linear-Time Properties in Multi-Valued Systems

OpenAIRE

Li, Yongming; Droste, Manfred; Lei, Lihui

2012-01-01

In this paper, we study model-checking of linear-time properties in multi-valued systems. Safety property, invariant property, liveness property, persistence and dual-persistence properties in multi-valued logic systems are introduced. Some algorithms related to the above multi-valued linear-time properties are discussed. The verification of multi-valued regular safety properties and multi-valued $\\omega$-regular properties using lattice-valued automata are thoroughly studied. Since the law o...

Sleep/wake scheduling scheme for minimizing end-to-end delay in multi-hop wireless sensor networks

OpenAIRE

Madani Sajjad; Nazir Babar; Hasbullah Halabi

2011-01-01

Abstract We present a sleep/wake schedule protocol for minimizing end-to-end delay for event driven multi-hop wireless sensor networks. In contrast to generic sleep/wake scheduling schemes, our proposed algorithm performs scheduling that is dependent on traffic loads. Nodes adapt their sleep/wake schedule based on traffic loads in response to three important factors, (a) the distance of the node from the sink node, (b) the importance of the node's location from connectivity's perspective, and...

Quantitative analysis and prediction of regional lymph node status in rectal cancer based on computed tomography imaging

Energy Technology Data Exchange (ETDEWEB)

Cui, Chunyan; Liu, Lizhi; Li, Li [Sun Yat-sen University, State Key Laboratory of Oncology in Southern China, Imaging Diagnosis and Interventional Center, Cancer Center, Guangzhou, Guangdong (China); Cai, Hongmin; Tian, Haiying [Sun Yat-Sen University, Department of Automation, School of Science Information and Technology, Guangzhou (China); Li, Liren [Sun Yat-sen University, State Key Laboratory of Oncology in Southern China, Department of Abdominal (colon and rectal) Surgery, Cancer Center, Guangzhou (China)

2011-11-15

To quantitatively evaluate regional lymph nodes in rectal cancer patients by using an automated, computer-aided approach, and to assess the accuracy of this approach in differentiating benign and malignant lymph nodes. Patients (228) with newly diagnosed rectal cancer, confirmed by biopsy, underwent enhanced computed tomography (CT). Patients were assigned to the benign node or malignant node group according to histopathological analysis of node samples. All CT-detected lymph nodes were segmented using the edge detection method, and seven quantitative parameters of each node were measured. To increase the prediction accuracy, a hierarchical model combining the merits of the support and relevance vector machines was proposed to achieve higher performance. Of the 220 lymph nodes evaluated, 125 were positive and 95 were negative for metastases. Fractal dimension obtained by the Minkowski box-counting approach was higher in malignant nodes than in benign nodes, and there was a significant difference in heterogeneity between metastatic and non-metastatic lymph nodes. The overall performance of the proposed model is shown to have accuracy as high as 88% using morphological characterisation of lymph nodes. Computer-aided quantitative analysis can improve the prediction of node status in rectal cancer. (orig.)

Multi-stage crypto ransomware attacks: A new emerging cyber threat to critical infrastructure and industrial control systems

Directory of Open Access Journals (Sweden)

Aaron Zimba

2018-03-01

Full Text Available The inevitable integration of critical infrastructure to public networks has exposed the underlying industrial control systems to various attack vectors. In this paper, we model multi-stage crypto ransomware attacks, which are today an emerging cyber threat to critical infrastructure. We evaluate our modeling approach using multi-stage attacks by the infamous WannaCry ransomware. The static malware analysis results uncover the techniques employed by the ransomware to discover vulnerable nodes in different SCADA and production subnets, and for the subsequent network propagation. Based on the uncovered artifacts, we recommend a cascaded network segmentation approach, which prioritizes the security of production network devices. Keywords: Critical infrastructure, Cyber-attack, Industrial control system, Crypto ransomware, Vulnerability

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

Science.gov (United States)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration

Science.gov (United States)

Walker, A. P.; De Kauwe, M. G.; Lu, D.; Medlyn, B.; Norby, R. J.; Ricciuto, D. M.; Rogers, A.; Serbin, S.; Weston, D. J.; Ye, M.; Zaehle, S.

2017-12-01

Large uncertainty is often inherent in model predictions due to imperfect knowledge of how to describe the mechanistic processes (hypotheses) that a model is intended to represent. Yet this model hypothesis uncertainty (MHU) is often overlooked or informally evaluated, as methods to quantify and evaluate MHU are limited. MHU is increased as models become more complex because each additional processes added to a model comes with inherent MHU as well as parametric unceratinty. With the current trend of adding more processes to Earth System Models (ESMs), we are adding uncertainty, which can be quantified for parameters but not MHU. Model inter-comparison projects do allow for some consideration of hypothesis uncertainty but in an ad hoc and non-independent fashion. This has stymied efforts to evaluate ecosystem models against data and intepret the results mechanistically because it is not simple to interpret exactly why a model is producing the results it does and identify which model assumptions are key as they combine models of many sub-systems and processes, each of which may be conceptualised and represented mathematically in various ways. We present a novel modelling framework—the multi-assumption architecture and testbed (MAAT)—that automates the combination, generation, and execution of a model ensemble built with different representations of process. We will present the argument that multi-hypothesis modelling needs to be considered in conjunction with other capabilities (e.g. the Predictive Ecosystem Analyser; PecAn) and statistical methods (e.g. sensitivity anaylsis, data assimilation) to aid efforts in robust data model integration to enhance our predictive understanding of biological systems.

Optimal Node Placement in Underwater Acoustic Sensor Network

KAUST Repository

Felemban, Muhamad

2011-10-01

Almost 70% of planet Earth is covered by water. A large percentage of underwater environment is unexplored. In the past two decades, there has been an increase in the interest of exploring and monitoring underwater life among scientists and in industry. Underwater operations are extremely difficult due to the lack of cheap and efficient means. Recently, Wireless Sensor Networks have been introduced in underwater environment applications. However, underwater communication via acoustic waves is subject to several performance limitations, which makes the relevant research issues very different from those on land. In this thesis, we investigate node placement for building an initial Underwater Wireless Sensor Network infrastructure. Firstly, we formulated the problem into a nonlinear mathematic program with objectives of minimizing the total transmission loss under a given number of sensor nodes and targeted volume. We conducted experiments to verify the proposed formulation, which is solved using Matlab optimization tool. We represented each node with a truncated octahedron to fill out the 3D space. The truncated octahedrons are tiled in the 3D space with each node in the center where locations of the nodes are given using 3D coordinates. Results are supported using ns-3 simulator. Results from simulation are consistent with the obtained results from mathematical model with less than 10% error.

A Longitudinal Comparison of Arm Morbidity in Stage I-II Breast Cancer Patients Treated with Sentinel Lymph Node Biopsy, Sentinel Lymph Node Biopsy Followed by Completion Lymph Node Dissection, or Axillary Lymph Node Dissection

NARCIS (Netherlands)

Kootstra, Jan J.; Hoekstra-Weebers, Josette E. H. M.; Rietman, Johan S.; de Vries, Jakob; Baas, Peter C.; Geertzen, Jan H. B.; Hoekstra, Harald J.

Background. Long-term shoulder and arm function following sentinel lymph node biopsy (SLNB) may surpass that following complete axillary lymph node dissection (CLND) or axillary lymph node dissection (ALND). We objectively examined the morbidity and compared outcomes after SLNB, SLNB + CLND, and

A longitudinal comparison of arm morbidity in stage I-II breast cancer patients treated with sentinel lymph node biopsy, sentinel lymph node biopsy followed by completion lymph node dissection, or axillary lymph node dissection

NARCIS (Netherlands)

Kootstra, Jan J.; Hoekstra-Weebers, Josette E.; Rietman, Johan Swanik; de Vries, Jakob; Baas, Peter C.; Geertzen, Jan H.B.; Hoekstra, Harald J.

2010-01-01

Background: Long-term shoulder and arm function following sentinel lymph node biopsy (SLNB) may surpass that following complete axillary lymph node dissection (CLND) or axillary lymph node dissection (ALND). We objectively examined the morbidity and compared outcomes after SLNB, SLNB + CLND, and

Penile Cancer: Contemporary Lymph Node Management.

Science.gov (United States)

O'Brien, Jonathan S; Perera, Marlon; Manning, Todd; Bozin, Mike; Cabarkapa, Sonja; Chen, Emily; Lawrentschuk, Nathan

2017-06-01

In penile cancer, the optimal diagnostics and management of metastatic lymph nodes are not clear. Advances in minimally invasive staging, including dynamic sentinel lymph node biopsy, have widened the diagnostic repertoire of the urologist. We aimed to provide an objective update of the recent trends in the management of penile squamous cell carcinoma, and inguinal and pelvic lymph node metastases. We systematically reviewed several medical databases, including the Web of Science® (with MEDLINE®), Embase® and Cochrane databases, according to PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) guidelines. The search terms used were penile cancer, lymph node, sentinel node, minimally invasive, surgery and outcomes, alone and in combination. Articles pertaining to the management of lymph nodes in penile cancer were reviewed, including original research, reviews and clinical guidelines published between 1980 and 2016. Accurate and minimally invasive lymph node staging is of the utmost importance in the surgical management of penile squamous cell carcinoma. In patients with clinically node negative disease, a growing body of evidence supports the use of sentinel lymph node biopsies. Dynamic sentinel lymph node biopsy exposes the patient to minimal risk, and results in superior sensitivity and specificity profiles compared to alternate nodal staging techniques. In the presence of locoregional disease, improvements in inguinal or pelvic lymphadenectomy have reduced morbidity and improved oncologic outcomes. A multimodal approach of chemotherapy and surgery has demonstrated a survival benefit for patients with advanced disease. Recent developments in lymph node management have occurred in penile cancer, such as minimally invasive lymph node diagnosis and intervention strategies. These advances have been met with a degree of controversy in the contemporary literature. Current data suggest that dynamic sentinel lymph node biopsy provides excellent

Multi area and multistage expansion-planning of electricity supply with sustainable energy development criteria: a multi objective model

Energy Technology Data Exchange (ETDEWEB)

Unsihuay-Vila, Clodomiro; Marangon-Lima, J.W.; Souza, A.C Zambroni de [Universidade Federal de Itajuba (UNIFEI), MG (Brazil)], emails: clodomirounsihuayvila @gmail.com, marangon@unifei.edu.br, zambroni@unifei.edu.br; Perez-Arriaga, I.J. [Universidad Pontificia Comillas, Madrid (Spain)], email: ipa@mit.edu

2010-07-01

A novel multi objective, multi area and multistage model to long-term expansion-planning of integrated generation and transmission corridors incorporating sustainable energy developing is presented in this paper. The proposed MESEDES model is a multi-regional multi-objective and 'bottom-up' energy model which considers the electricity generation/transmission value-chain, i.e., power generation alternatives including renewable, nuclear and traditional thermal generation along with transmission corridors. The model decides the optimal location and timing of the electricity generation/transmission abroad the multistage planning horizon. The MESEDES model considers three objectives belonging to sustainable energy development criteria such as: a) the minimization of investments and operation costs of : power generation, transmission corridors, energy efficiency (demand side management (DSM) programs) considering CO2 capture technologies; b) minimization of Life Cycle Greenhouse Gas Emissions (LC GHG); c) maximization of the diversification of electricity generation mix. The proposed model consider aspects of the carbon abatement policy under the CDM - Clean Development Mechanism or European Union Greenhouse Gas Emission Trading Scheme. A case study is used to illustrate the proposed framework. (author)

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

Science.gov (United States)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2016-04-01

Networks with nodes embedded in a metric space have gained increasing interest in recent years. The effects of spatial embedding on the networks' structural characteristics, however, are rarely taken into account when studying their macroscopic properties. Here, we propose a hierarchy of null models to generate random surrogates from a given spatially embedded network that can preserve certain global and local statistics associated with the nodes' embedding in a metric space. Comparing the original network's and the resulting surrogates' global characteristics allows one to quantify to what extent these characteristics are already predetermined by the spatial embedding of the nodes and links. We apply our framework to various real-world spatial networks and show that the proposed models capture macroscopic properties of the networks under study much better than standard random network models that do not account for the nodes' spatial embedding. Depending on the actual performance of the proposed null models, the networks are categorized into different classes. Since many real-world complex networks are in fact spatial networks, the proposed approach is relevant for disentangling the underlying complex system structure from spatial embedding of nodes in many fields, ranging from social systems over infrastructure and neurophysiology to climatology.

Agent-based modeling of the energy network for hybrid cars

International Nuclear Information System (INIS)

Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

2015-01-01

Highlights: • An approach to represent and calculate multicarrier energy networks has been developed. • It provides a modeling method based on agents, for multicarrier energy networks. • It allows the system representation on a single sheet. • Energy flows circulating in the system can be observed dynamically during simulation. • The method is technology independent. - Abstract: Studies in complex energy networks devoted to the modeling of electrical power grids, were extended in previous work, where a computational multi-layered ontology, implemented using agent-based methods, was adopted. This structure is compatible with recently introduced Multiplex Networks which using Multi-linear Algebra generalize some of classical results for single-layer networks, to multilayer networks in steady state. Static results do not assist overly in understanding dynamic networks in which the values of the variables in the nodes and edges can change suddenly, driven by events, and even where new nodes or edges may appear or disappear, also because of other events. To address this gap, a computational agent-based model is developed to extend the multi-layer and multiplex approaches. In order to demonstrate the benefits of a dynamical extension, a model of the energy network in a hybrid car is presented as a case study

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

Science.gov (United States)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

A Model for Generating Multi-hazard Scenarios

Science.gov (United States)

Lo Jacomo, A.; Han, D.; Champneys, A.

2017-12-01

Communities in mountain areas are often subject to risk from multiple hazards, such as earthquakes, landslides, and floods. Each hazard has its own different rate of onset, duration, and return period. Multiple hazards tend to complicate the combined risk due to their interactions. Prioritising interventions for minimising risk in this context is challenging. We developed a probabilistic multi-hazard model to help inform decision making in multi-hazard areas. The model is applied to a case study region in the Sichuan province in China, using information from satellite imagery and in-situ data. The model is not intended as a predictive model, but rather as a tool which takes stakeholder input and can be used to explore plausible hazard scenarios over time. By using a Monte Carlo framework and varrying uncertain parameters for each of the hazards, the model can be used to explore the effect of different mitigation interventions aimed at reducing the disaster risk within an uncertain hazard context.

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

Directory of Open Access Journals (Sweden)

Fonseca Carlos M

2010-10-01

Full Text Available Abstract Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the

On the sub-model errors of a generalized one-way coupling scheme for linking models at different scales

Science.gov (United States)

Zeng, Jicai; Zha, Yuanyuan; Zhang, Yonggen; Shi, Liangsheng; Zhu, Yan; Yang, Jinzhong

2017-11-01

Multi-scale modeling of the localized groundwater flow problems in a large-scale aquifer has been extensively investigated under the context of cost-benefit controversy. An alternative is to couple the parent and child models with different spatial and temporal scales, which may result in non-trivial sub-model errors in the local areas of interest. Basically, such errors in the child models originate from the deficiency in the coupling methods, as well as from the inadequacy in the spatial and temporal discretizations of the parent and child models. In this study, we investigate the sub-model errors within a generalized one-way coupling scheme given its numerical stability and efficiency, which enables more flexibility in choosing sub-models. To couple the models at different scales, the head solution at parent scale is delivered downward onto the child boundary nodes by means of the spatial and temporal head interpolation approaches. The efficiency of the coupling model is improved either by refining the grid or time step size in the parent and child models, or by carefully locating the sub-model boundary nodes. The temporal truncation errors in the sub-models can be significantly reduced by the adaptive local time-stepping scheme. The generalized one-way coupling scheme is promising to handle the multi-scale groundwater flow problems with complex stresses and heterogeneity.

IMHRP: Improved Multi-Hop Routing Protocol for Wireless Sensor Networks

Science.gov (United States)

Huang, Jianhua; Ruan, Danwei; Hong, Yadong; Zhao, Ziming; Zheng, Hong

2017-10-01

Wireless sensor network (WSN) is a self-organizing system formed by a large number of low-cost sensor nodes through wireless communication. Sensor nodes collect environmental information and transmit it to the base station (BS). Sensor nodes usually have very limited battery energy. The batteries cannot be charged or replaced. Therefore, it is necessary to design an energy efficient routing protocol to maximize the network lifetime. This paper presents an improved multi-hop routing protocol (IMHRP) for homogeneous networks. In the IMHRP protocol, based on the distances to the BS, the CH nodes are divided into internal CH nodes and external CH nodes. The set-up phase of the protocol is based on the LEACH protocol and the minimum distance between CH nodes are limited to a special constant distance, so a more uniform distribution of CH nodes is achieved. In the steady-state phase, the routes of different CH nodes are created on the basis of the distances between the CH nodes. The energy efficiency of communication can be maximized. The simulation results show that the proposed algorithm can more effectively reduce the energy consumption of each round and prolong the network lifetime compared with LEACH protocol and MHT protocol.

Status of lymph node staging

NARCIS (Netherlands)

Nieweg, O. E.; Estourgie, S. H.; Deurloo, E. E.; Rutgers, E. J. Th; Kroon, B. B. R.

2002-01-01

Sentinel node biopsy has the potential to provide more accurate staging information than axillary node dissection. Given the considerable morbidity of axillary node dissection this less invasive approach is attractive. However, there are a number of issues to be resolved before the best technique of

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

Science.gov (United States)

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.

Science.gov (United States)

Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael

2018-01-01

An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

Identifying Nodes of Transmission in Disease Diffusion Through Social Media

Science.gov (United States)

Lamb, David Sebastian

The spread of infectious diseases can be described in terms of three interrelated components: interaction, movement, and scale. Transmission between individuals requires some form of interaction, which is dependent on the pathogen, to occur. Diseases spread through the movement of their hosts; they spread across many spatial scales from local neighborhoods to countries, or temporal scales from days to years, or periodic intervals. Prior research into the spread of disease have examined diffusion processes retrospectively at regional or country levels, or developed differential equation or simulation models of the dynamics of disease transmission. While some of the more recent models incorporate all three components, they are limited in the way they understand where interactions occur. The focus has been on home or work, including contact with family or coworkers. The models reflect a lack of knowledge about how transmissions are made at specific locations in time, so-called nodes of transmission. That is, how individuals' intersections in time and space function in disease transmission. This project sought to use the three factors of interaction, movement, and scale to better understand the spread of disease in terms of the place of interaction called the node of transmission. The overarching objective of this research was: how can nodes of transmission be identified through individual activity spaces incorporating the three factors of infectious disease spread: interaction, movement, and scale?. This objective fed into three main sub-objectives: defining nodes of transmission, developing an appropriate methodology to identifying nodes of transmission, and applying it using geotagged social media data from Twitter. To develop an appropriate framework, this research relied on time geography, and traditional disease. This particularly relied on the idea of bundling to create the nodes, and a nesting effect that integrated scale. The data source used to identify nodes

Modeling multi-lateral wells

Energy Technology Data Exchange (ETDEWEB)

Su, H. J.; Fong, W. S. [Chevron Petroleum Technology Company (United States)

1998-12-31

A method for modeling multi-lateral wells by using a computational scheme embedded in a general-purpose, finite difference simulator was described. The calculation of wellbore pressure profile for each lateral included the frictional pressure drop along the wellbore and proper fluid mixing at lateral connection points. To obtain a good production profile the Beggs and Brill correlation, a homogenous flow model, and the model proposed by Ouyang et al, which includes an acceleration term and accounts for the lubrication effect due to radial influx, were implemented. Well performance prediction results were compared using the three models. The impact of different tubing sizes on the well performance and the prediction contribution from each lateral were also studied. Results of the study in the hypothetical example and under normal field operating conditions were reviewed. 7 refs., 10 tabs., 3 figs.

Multi-Gateway-Based Energy Holes Avoidance Routing Protocol for WSN

Directory of Open Access Journals (Sweden)

Rohini Sharma

2016-04-01

Full Text Available In wireless sensor networks (WSNs, efficient energy conservation is required to prolong the lifetime of the network. In this work, we have given emphasis on balanced energy consumption and energy holes avoidance. This paper proposes a multi-gateway-based approach to reduce the transmission distance between the sender and the sink node. The area to be monitored is divided into regions and gateway nodes are deployed at optimal positions. We have designed a transmission scheme, in which sensors in the sink region communicate directly to the sink, sensors in the gateway region communicate directly to the gateway, and sensors in the cluster region transmit their data directly to their respective cluster head which transmits data to the gateway in its region. If the distance between a cluster head and the sink is less than the distance between the cluster head and the gateway node, the cluster head transmits data to the sink instead of the gateway node. We have compared the proposed protocol with Low-Energy Adaptive Clustering Hierarchy (LEACH, Gateway Based Energy Aware Multi-Hop Routing (M-GEAR, and Gateway Based Stable Election Protocol (GSEP protocols. The protocol performs better than other protocols in terms of throughput, stability period, lifetime, residual energy, and the packet transmitted to the sink.