Arrhythmia Classification Based on Bi-Directional Long Short-Term Memory and Multi-Task Group Method Shaik Munawar, Geetha Angappan, Srinivas Konda International Journal of E Collaboration, 2023 Early and accurate classification of arrhythmia helps the experts to select the treatment for the patient to increase the recovery rate. The deep learning method of convolution neural network (CNN) is used for classification, and this has an overfitting problem. In this research, the multi-task group bi-directional long short term memory (MTGBi-LSTM) method is proposed to increases the performance of arrhythmia classification. The multi-task learning technique learns two ECG signals in shared representation for effective learning. The global and intra LSTM method selects the relevant feature and easily escapes from local optima. The MTGBi-LSTM model learns the unique features in shared representation that helps to overcome overfitting problem and increases the learning rate of the model. The MTGBi-LSTM model in arrhythmia classification is evaluated on MIT-BIH dataset. The MTGBi-LSTM model has 96.48% accuracy, 97.73% sensitivity, existing AFibNet has 96.36% accuracy, and 93.65% sensitivity for arrhythmia classification in CPSC 2018 dataset.
Narrow Band Internet of Things (NB-IoT) for Wireless Communication and Network Optimization Smita Khond, Kanegonda Ravi Chythanya, Shaik Munawar, Manjusha Mandava, Kruthika C G 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques Easct 2023, 2023 This research presents an all-encompassing method for improving Narrow Band Internet of Things (NB-IoT) network performance by including network design, interference management, power control techniques, and security measures. Planning your network ahead of time is essential, and will involve decisions like network design, base station placement, and channel allocation. The second stage, interference control, seeks to reduce background noise emanating from various sources. The third and last stage is to use transmission power management algorithms for NB-IoT devices. In real-time, these algorithms optimize power levels for the channel and the task at hand. In the last stage, we apply security measures including authentication, encryption, and other types of network access control. According to the data, the suggested approach would have cost a total of $500,000, but more conventional approaches would have cost between $700,000 and $900,000. Also, the suggested method had an average delay of 1.5 seconds.
SQUIRREL SEARCH-BASED OPTIMAL FEATURE EXTRACTION WITH BI-LSTM FOR THE ARRHYTHMIA CLASSIFICATION USING ECG Journal of Theoretical and Applied Information Technology, 2022
Data mining for cyber-physical systems M. Varaprasad Rao, D. Anji Reddy, Anusha Ampavathi, Shaik Munawar Data Mining and Machine Learning Applications, 2022
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