Investigating Neural Activation Effects on Deep Belief Echo-State Networks for Prediction Toward Smart Ocean Environment Monitoring

2021 ◽  
Author(s):  
Zhigang Li ◽  
Jialin Wang ◽  
Difei Cao ◽  
Yingqi Li ◽  
Xiaochuan Sun ◽  
...  
Keyword(s):  
Neural Activation ◽  
Environment Monitoring ◽  
Echo State Networks ◽  
Ocean Environment

Ship Surveillance by Integration of Space-borne SAR and AIS – Review of Current Research

2013 ◽  
Vol 67 (1) ◽  
pp. 177-189 ◽  
Author(s):  
Zhi Zhao ◽  
Kefeng Ji ◽  
Xiangwei Xing ◽  
Huanxin Zou ◽  
Shilin Zhou
Keyword(s):  
State Of The Art ◽  
Rapid Development ◽  
Automatic Identification ◽  
Identification System ◽  
Environment Monitoring ◽  
Ship Detection ◽  
Maritime Surveillance ◽  
Satisfactory Performance ◽  
Detection And Identification ◽  
Ocean Environment

Ship surveillance is important for maritime security and safety. It plays important roles in many applications including ocean environment monitoring, search and rescue, anti-piracy and military reconnaissance. Among various sensors used for maritime surveillance, space-borne Synthetic Aperture Radar (SAR) is valued for its high resolution over wide swaths and all-weather working capabilities. However, the state-of-the-art algorithms for ship detection and identification do not always achieve a satisfactory performance. With the rapid development of space-borne Automatic Identification System (AIS), near real-time and global surveillance has become feasible. However, not all ships are equipped with or operate AIS. Space-borne SAR and AIS are considered to be complementary, and ship surveillance using an integrated combination has attracted much attention. In order to summarize the achievements and present references for further research, this paper attempts to explicitly review the developments in previous research as the basis of a brief introduction to space-borne SAR and AIS.

scholarly journals Reservoir computing on the hypersphere

2017 ◽  
Vol 28 (07) ◽  
pp. 1750095 ◽  
Author(s):  
M. Andrecut
Keyword(s):  
Sequence Learning ◽  
Time Series Prediction ◽  
Activation Function ◽  
Neural Activation ◽  
Reservoir Computing ◽  
Symmetric Cryptography ◽  
Learning Problem ◽  
Echo State Networks ◽  
Fixed Weight ◽  
Unit Hypersphere

Reservoir Computing (RC) refers to a Recurrent Neural Network (RNNs) framework, frequently used for sequence learning and time series prediction. The RC system consists of a random fixed-weight RNN (the input-hidden reservoir layer) and a classifier (the hidden-output readout layer). Here, we focus on the sequence learning problem, and we explore a different approach to RC. More specifically, we remove the nonlinear neural activation function, and we consider an orthogonal reservoir acting on normalized states on the unit hypersphere. Surprisingly, our numerical results show that the system’s memory capacity exceeds the dimensionality of the reservoir, which is the upper bound for the typical RC approach based on Echo State Networks (ESNs). We also show how the proposed system can be applied to symmetric cryptography problems, and we include a numerical implementation.

scholarly journals Oscillation Reduction Control for Ocean Environment Monitoring Buoys

2010 ◽  
Vol 43 (20) ◽  
pp. 277-282 ◽  
Author(s):  
Yuji Tomizawa ◽  
Masayoshi Toda
Keyword(s):  
Environment Monitoring ◽  
Ocean Environment

Accurate Ulva prolifera regions extraction of UAV images with superpixel and CNNs for ocean environment monitoring

2019 ◽  
Vol 348 ◽  
pp. 158-168 ◽  
Author(s):  
Shengke Wang ◽  
Lu Liu ◽  
Liang Qu ◽  
Changyin Yu ◽  
Yujuan Sun ◽  
...  
Keyword(s):  
Ulva Prolifera ◽  
Environment Monitoring ◽  
Ocean Environment ◽  
Uav Images

Neural activation in mothers of preterm and full-term infants: Preliminary findings from a 3T fMRI study

2012 ◽  
Author(s):  
R. Montirosso ◽  
S. Moriconi ◽  
B. Riccardi ◽  
G. Reni ◽  
F. Arrigoni ◽  
...  
Keyword(s):  
Full Term ◽  
Neural Activation ◽  
Term Infants ◽  
Fmri Study

Economic models of Environment monitoring under imperfect information and high Costs

2014 ◽  
pp. 99-122
Author(s):  
M. Levin ◽  
K. Matrosova
Keyword(s):  
Environmental Monitoring ◽  
Environmental Regulation ◽  
Environmental Economics ◽  
Imperfect Information ◽  
Central Element ◽  
Economic Models ◽  
Environment Monitoring ◽  
Nature Protection ◽  
Protection Measures ◽  
Effective System

The paper considers monitoring of environmental change as the central element of environmental regulation. Monitoring, as each kind of principalagent relations, easily gives rise to corruptive behavior. In the paper we analyze economic models of environmental monitoring with high costs, incomplete information and corruption. These models should be the elements of environmental economics and are needed to create an effective system of nature protection measures.

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