Encryption by Heart (EbH) for Secured Data Transmission and CNN Based EKG Signal Classification of Arrhythmia with Normal Data

2019 ◽  
pp. 290-299
Author(s):  
Tarun Kumar D ◽  
Ramya Lakshmi Srinivasan ◽  
Raajan N R
Keyword(s):  
Data Transmission ◽  
Signal Classification ◽  
Secured Data

scholarly journals fNIRS Signal Classification Based on Deep Learning in Rock-Paper-Scissors Imagery Task

2021 ◽  
Vol 11 (11) ◽  
pp. 4922
Author(s):  
Tengfei Ma ◽  
Wentian Chen ◽  
Xin Li ◽  
Yuting Xia ◽  
Xinhua Zhu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Total Duration ◽  
Signal Classification ◽  
Imagery Task ◽  
Neural Activities ◽  
Computer Interfaces ◽  
Acquisition Device ◽  
The Time Domain ◽  
The Brain

To explore whether the brain contains pattern differences in the rock–paper–scissors (RPS) imagery task, this paper attempts to classify this task using fNIRS and deep learning. In this study, we designed an RPS task with a total duration of 25 min and 40 s, and recruited 22 volunteers for the experiment. We used the fNIRS acquisition device (FOIRE-3000) to record the cerebral neural activities of these participants in the RPS task. The time series classification (TSC) algorithm was introduced into the time-domain fNIRS signal classification. Experiments show that CNN-based TSC methods can achieve 97% accuracy in RPS classification. CNN-based TSC method is suitable for the classification of fNIRS signals in RPS motor imagery tasks, and may find new application directions for the development of brain–computer interfaces (BCI).

Research of Trusted Network Security Technology

2011 ◽  
Vol 52-54 ◽  
pp. 713-716
Author(s):  
Xiao Ying Gan ◽  
Bin Liu
Keyword(s):  
Data Transmission ◽  
Network Access ◽  
End User ◽  
Security Technology ◽  
Resources Management ◽  
Integrity Verification ◽  
Reliable Model ◽  
User Data ◽  
Repair Techniques

Based on the TNC architecture, using a trusted network of repair techniques in the trusted network access scenario does not meet the requirements of integrity verification solution for end users. Put forward a credible fix the overall network design, reliable model restoration and repair services, network workflow. The system is in need of restoration to provide safe and reliable repair end-user data transmission, providing a humane, reasonable repair services to ensure the credibility of fixed network and the isolation effect of the terminal to be repaired and strengthened the security of fixed server. Realized the classification of various types of repair resources management, restoration of resources in ensuring the transfer of fast, reliable, based on the performance with a certain extension.

Human Action Recognition Using CNN-SVM Model

2021 ◽  
Vol 105 ◽  
pp. 282-290
Author(s):  
Vijay Anant Athavale ◽  
Suresh Chand Gupta ◽  
Deepak Kumar ◽  
Savita
Keyword(s):  
Human Action Recognition ◽  
Human Action ◽  
Signal Classification ◽  
Svm Classifier ◽  
Life Activity ◽  
Accelerometer Sensor ◽  
Svm Model ◽  
Fully Connected ◽  
Evaluation Parameters

In this paper, a pre-trained CNN model VGG16 with the SVM classifier is presented for the HAR task. The deep features are learned via the VGG16 pre-trained CNN model. The VGG 16 network is previously used for the image classification task. We used VGG16 for the signal classification of human activity, which is recorded by the accelerometer sensor of the mobile phone. The UniMiB dataset contains the 11771 samples of the daily life activity of humans. A Smartphone records these samples through the accelerometer sensor. The features are learned via the fifth max-pooling layer of the VGG16 CNN model and feed to the SVM classifier. The SVM classifier replaced the fully connected layer of the VGG16 model. The proposed VGG16-SVM model achieves effective and efficient results. The proposed method of VGG16-SVM is compared with the previously used schemes. The classification accuracy and F-Score are the evaluation parameters, and the proposed method provided 79.55% accuracy and 71.63% F-Score.

Encryption and Decryption of Image for Secured Data Transmission

2021 ◽  
pp. 145-155
Author(s):  
C. Thirumarai Selvi ◽  
R. S. Sankarasubramanian ◽  
M. MuthuKrishnan
Keyword(s):  
Data Transmission ◽  
Encryption And Decryption ◽  
Secured Data
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