scholarly journals The exploration of an automatic detection method for the wind-storage and combined power generation monitoring system

2019 ◽  
Author(s):  
Jinxiong Zhao ◽  
Bo Zhao ◽  
Yanbin Zhang ◽  
Zhiru Li ◽  
Hui Yuan ◽  
...  
Keyword(s):  
Power Generation ◽  
Monitoring System ◽  
Detection Method ◽  
Automatic Detection

Single Channel EEG signal for Automatic Detection of Absence Seizure using Convolutional Neural Network

2019 ◽  
Vol 13 ◽  
Author(s):  
Niha Kamal Basha ◽  
Aisha Banu Wahab
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Convolutional Neural Network ◽  
Monitoring System ◽  
Single Channel ◽  
Confusion Matrix ◽  
Sudden Change ◽  
Automatic Detection ◽  
Support Vector ◽  
Absence Seizure

: Absence seizure is a type of brain disorder in which subject get into sudden lapses in attention. Which means sudden change in brain stimulation. Most of this type of disorder is widely found in children’s (5-18 years). These Electroencephalogram (EEG) signals are captured with long term monitoring system and are analyzed individually. In this paper, a Convolutional Neural Network to extract single channel EEG seizure features like Power, log sum of wavelet transform, cross correlation, and mean phase variance of each frame in a windows are extracted after pre-processing and classify them into normal or absence seizure class, is proposed as an empowerment of monitoring system by automatic detection of absence seizure. The training data is collected from the normal and absence seizure subjects in the form of Electroencephalogram. The objective is to perform automatic detection of absence seizure using single channel electroencephalogram signal as input. Here the data is used to train the proposed Convolutional Neural Network to extract and classify absence seizure. The Convolutional Neural Network consist of three layers 1] convolutional layer – which extract the features in the form of vector 2] Pooling layer – the dimensionality of output from convolutional layer is reduced and 3] Fully connected layer–the activation function called soft-max is used to find the probability distribution of output class. This paper goes through the automatic detection of absence seizure in detail and provide the comparative analysis of classification between Support Vector Machine and Convolutional Neural Network. The proposed approach outperforms the performance of Support Vector Machine by 80% in automatic detection of absence seizure and validated using confusion matrix.

An automatic detection method of spinal deformity from moire topographic images employing asymmetric degree of shoulder and waistline

2007 ◽  
Author(s):  
Toyoaki Tanoue ◽  
Satoshi Nakano ◽  
Hyoungseop Kim ◽  
Joo kooi Tan ◽  
Seiji Ishikawa ◽  
...  
Keyword(s):  
Spinal Deformity ◽  
Detection Method ◽  
Automatic Detection

Design of Solar-Wind Complementary Grid-Connected Power Generation Monitoring System for Teaching

2011 ◽  
Vol 383-390 ◽  
pp. 3628-3632
Author(s):  
Rong Xia Sun ◽  
Jian Li Wang ◽  
Pan Pan Huang ◽  
Jian Kang ◽  
Xiao Feng Chen ◽  
...  
Keyword(s):  
Power Generation ◽  
Solar Wind ◽  
Monitoring System ◽  
Experimental Teaching ◽  
Hardware System ◽  
New Energy ◽  
Power Enterprise ◽  
Field Device ◽  
And Control ◽  
Monitoring Application

With the development of new energy industry, the technicians in the area of solar-wind complementary grid-connected power generation are urgently needed. For this reason, the monitoring system of 10kW solar-wind complementary grid-connected power generation was designed. Hardware system includes field device, communication network and monitoring host. Software design includes operation monitoring, application analysis, video surveillance, information issuing. It realizes functions of supervise and control, equipment events and alarm, report forms and print, energy management and forecasting, remote monitoring and so on. This research can be used to demonstrate experimental teaching in high shool and train power enterprise technicians.

scholarly journals Amplitude Distribution of Calcium Sparks in Confocal Images: Theory and Studies with an Automatic Detection Method

1999 ◽  
Vol 76 (2) ◽  
pp. 606-617 ◽  
Author(s):  
Heping Cheng ◽  
Long-Sheng Song ◽  
Natalia Shirokova ◽  
Adom González ◽  
Edward G. Lakatta ◽  
...  
Keyword(s):  
Detection Method ◽  
Automatic Detection ◽  
Amplitude Distribution ◽  
Calcium Sparks ◽  
Confocal Images

Automatic detection method of lung cancers including ground-glass opacities from chest x-ray CT images

2002 ◽  
Author(s):  
Toshiharu Ezoe ◽  
Hotaka Takizawa ◽  
Shinji Yamamoto ◽  
Akinobu Shimizu ◽  
Tohru Matsumoto ◽  
...  
Keyword(s):  
Detection Method ◽  
Automatic Detection ◽  
Ct Images ◽  
Ground Glass ◽  
Lung Cancers ◽  
X Ray ◽  
Chest X Ray

A Rapid In Situ Monitoring System for the Determination of Total Phosphorus in Waters

2013 ◽  
Vol 779-780 ◽  
pp. 1526-1531
Author(s):  
Kang Lin Wei ◽  
Ming Chen ◽  
Fei Wang ◽  
Qiong Fang
Keyword(s):  
Monitoring System ◽  
Total Phosphorus ◽  
Detection Method ◽  
Automatic Monitoring ◽  
In Situ Monitoring ◽  
National Standard ◽  
Detection Methods ◽  
Water Quality Parameter ◽  
Automatic Monitoring System

Total phosphorus is an much important key water quality parameter . In view of the technical defects of existing detection methods and instruments for in situ monitoring total phosphorus, a new detection method based on ultrasonic assisted sample digestion and spectrum analysis was put forward in this paper, and the automatic monitoring system prototype based on such detection method had been developed. Aiming at wastewater treatment, the spot experiment had been carried out to contrast prototype with Chinas national standard analysis method for on line measuring total phosphorus in the water, and the results of the comparative experiment showed that the automatic monitoring instrument prototypes had good repeatability (10%) and high accuracy (±10%), which met the technical qualifications of Chinas environmental protection industry standards.

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