Using spatial correlation of ocean current for velocity estimate of underwater drifting nodes

Author(s):  
Roee Diamant ◽  
Lars Michael Wolff ◽  
Lutz Lampe
2002 ◽  
Vol 7 (1) ◽  
pp. 31-42
Author(s):  
J. Šaltytė ◽  
K. Dučinskas

The Bayesian classification rule used for the classification of the observations of the (second-order) stationary Gaussian random fields with different means and common factorised covariance matrices is investigated. The influence of the observed data augmentation to the Bayesian risk is examined for three different nonlinear widely applicable spatial correlation models. The explicit expression of the Bayesian risk for the classification of augmented data is derived. Numerical comparison of these models by the variability of Bayesian risk in case of the first-order neighbourhood scheme is performed.


Author(s):  
Indah Kurniawati ◽  
Gamantyo Hendrantoro ◽  
Wirawan Wirawan ◽  
Muhammad Taufik

Author(s):  
Satya Ranjan Biswal ◽  
Santosh Kumar Swain

: Security is one of the important concern in both types of the network. The network may be wired or wireless. In case of wireless network security provisioning is more difficult in comparison to wired network. Wireless Sensor Network (WSN) is also a type of wireless network. And due to resource constraints WSN is vulnerable against malware attacks. Initially, the malware (virus, worm, malicious code, etc.) targets a single node of WSN for attack. When a node of WSN gets infected then automatically start to spread in the network. If nodes are strongly correlated the malware spreads quickly in the network. On the other hand, if nodes are weakly correlated the speed of malware spread is slow. A mathematical model is proposed for the study of malware propagation dynamics in WSN with combination of spatial correlation and epidemic theory. This model is based on epidemic theory with spatial correlation. The proposed model is Susceptible-Exposed-Infectious-Recover-Dead (SEIRD) with spatial correlation. We deduced the expression of basic reproduction number. It helps in the study of malware propagation dynamics in WSN. The stability analysis of the network has been investigated through proposed model. This model also helps in reduction of redundant information and saving of sensor nodes’ energy in WSN. The theoretical investigation verified by simulation results. A spatial correlation based epidemic model has been formulated for the study of dynamic behaviour of malware attacks in WSN.


1999 ◽  
Vol 87 (1) ◽  
pp. 132-141 ◽  
Author(s):  
Steven Deem ◽  
Richard G. Hedges ◽  
Steven McKinney ◽  
Nayak L. Polissar ◽  
Michael K. Alberts ◽  
...  

Severe anemia is associated with remarkable stability of pulmonary gas exchange (S. Deem, M. K. Alberts, M. J. Bishop, A. Bidani, and E. R. Swenson. J. Appl. Physiol. 83: 240–246, 1997), although the factors that contribute to this stability have not been studied in detail. In the present study, 10 Flemish Giant rabbits were anesthetized, paralyzed, and mechanically ventilated at a fixed minute ventilation. Serial hemodilution was performed in five rabbits by simultaneous withdrawal of blood and infusion of an equal volume of 6% hetastarch; five rabbits were followed over a comparable time. Ventilation-perfusion (V˙a/Q˙) relationships were studied by using the multiple inert-gas-elimination technique, and pulmonary blood flow distribution was assessed by using fluorescent microspheres. Expired nitric oxide (NO) was measured by chemiluminescence. Hemodilution resulted in a linear fall in hematocrit over time, from 30 ± 1.6 to 11 ± 1%. Anemia was associated with an increase in arterial [Formula: see text] in comparison with controls ( P < 0.01 between groups). The improvement in O2 exchange was associated with reducedV˙a/Q˙heterogeneity, a reduction in the fractal dimension of pulmonary blood flow ( P = 0.04), and a relative increase in the spatial correlation of pulmonary blood flow ( P = 0.04). Expired NO increased with anemia, whereas it remained stable in control animals ( P < 0.0001 between groups). Anemia results in improved gas exchange in the normal lung as a result of an improvement in overallV˙a/Q˙matching. In turn, this may be a result of favorable changes in pulmonary blood flow distribution, as assessed by the fractal dimension and spatial correlation of blood flow and as a result of increased NO availability.


NeuroImage ◽  
2001 ◽  
Vol 13 (6) ◽  
pp. 224
Author(s):  
Nader Pouratian ◽  
Susan Y. Bookheimer ◽  
Neil A. Martin ◽  
David E. Rex ◽  
Andrew F. Cannestra ◽  
...  

2013 ◽  
Vol 340 ◽  
pp. 642-646
Author(s):  
Li Song Tian ◽  
Wei Xuan Chen

The partial discharge (PD) detection systems are often vulnerable to strong external interferences, and sometimes the PD signals are submerged in noises (white noise for example) completely. So the signals acquired must be preprocessed to obtain the reliable PD information. While there are many methods for white noise denoising, mostly are not very suitable for partial discharge. The wavelet transform (WT) coefficient of PD and white noises have different spread characteristics in different WT scales. Based on the Information Theory, The Minimum Information Description Length (MDL) criterion is a optimization strategy, a small amount of signal parameter is requried to the PD signals representation, the paper proposes a wavelet spatial correlation algorithm to partial discharge denoising based on MDL criterion: optimal wavelet function is selected based on MDL, then have the white noise reduced in WT, the algorithm has wonderful virtues such as free from any parameters estimation about noise, free from presetting threshhold and threshold chooseing behavior, so the algorithm is highly adaptive. Large amount of experimental results illustrate that the method presented in this paper are efficient and feasible and outperforms other general method of PD noise reduction.


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