Our brain is our body’s control centre and is essential for proper functioning of the body. Alzheimer’s disease is a chronic neurodegenerative disease that affects the cerebral cortex of the brain and causes memory loss and loss of cognitive thinking. EEG (Electroencephalography) is a method of recording neurological electrical activity with electrodes. It was chosen as it is a simple, painless procedure. This paper suggests an automated and accurate algorithm for the detection of Alzheimer's Disease using EEG signals with a combination of Signal processing and Deep Learning Methods. Concepts like Butterworth filters, DWT, statistical parameters, Data Augmentation and CNN were used in order to achieve a classification algorithm with high accuracy. A total highest system accuracy of 97.61% was achieved.
Options trading is a process of speculating the strike price of an underlying security or index on the expiration date. To finalize the options contract, a trader pays a small percentage as premium. This paper is to maximmize the profits of trader and minimize their loses which is generally manual based process, but this research paper helps integrates finance with technology. It fills the gap between the implementation of deep learning and algorithm trading, with option trading. We have named this model as Option Trading Prediction Model (OTP). This paper can be referred to develop an option trading tool or platform. The paper contains the information in the following manner, Introduction, describes an overview of Model Features, followed by an overview of Evaluation which includes data collection and preprocessing. Later on, discusses Model training and about the modelling and prediction.
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