Membrane proteins are encoded in the genome and functionally important in the living organisms. Information on subcellular localiza-tion of cellular proteins has a significant role in the function of cell organelles. Discovery of drug target and system biology between localization and biological function are highly correlated. Therefore, we are predicting the localization of protein using various machine learning approaches. The prediction system based on the integration of the outcome of five sequence based sub-classifiers. The subcellu-lar localization prediction of the final result is based on protein profile vector, which is a result of the sub-classifiers.

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In the existing methods the epilepsy was analysed using the PPG, EEG, ECG. The output obtained from the two different signals were analysed and found that the signal obtained while using ECG wearable sensor was more accurate and reliable when compared to the result obtained while using PPG. The main drawback while using EEG signal is the placement of wet scalp electrodes. Hence heart rate is used to analyse epilepsy in the proposed methodin order to obtain accurate and reliable result. In this method analysing the heart rate signal of the patient and epilepsy death rate prediction are two main goals of the project. The biomedical sensors and wearable sensors currently available in the market was studied. Sensors like EEG, ECG, PPG characteristics, and their working were studied completely. In this paper, we have not used any biomedical sensors or wearable sensors. For the heart rate signal, the dataset from the “fitbase” website was collected. Heart rate data collection per minute average heartbeat of the person. heart rate signal data length was 12,000 But only 90 samples were used for ensemble averaging. Not only the heart rate of the signal the epilepsy was also focussed. The epilepsy death rate data from the Statista. Epilepsy data contains year and death for future prediction; a linear regression algorithm was used.

Abstract-Visible Light is regarded as a reliable mode of communication in comparison with Radio Frequency communication. It has a great scope in 5G networks. But this visible light communication is prone to security issues like eavesdropping due to its visual nature. This paper deals with the light encryption scheme using Light Emitting Diode. Keywords: Security, Visual Cryptography, Otsu, Halftone, Lifi I.INTRODUCTION As the technology rules the world currently, security plays a very vital role in data transfer. This can be provided by means of Network security. Cryptography is a study of mathematical technique that relates the aspects of security issues like Data confidentiality, Data Integrity and Data Availability which is referred to as CIA triangle. Visual Cryptography is a new technique of providing information security using simple user algorithms. Complex, computationally intensive algorithm is not used in this technique as used in the traditional cryptographic techniques. As images are more attractive than text, they are more prone to hacking nowadays. The security should be provided for Visible Light Communication of image transmission. As far as now the security for image transmission in VLC was provided by an Otsu algorithm which has enhanced Bit Error Rate but has a limitation on computational time and image sharing scheme. This can be overcome by an Image security algorithm called halftone algorithm. The proposed idea will overcome the limitations that were mentioned above. Figure1 represents the light encryption system using laptops. The VLC signal from a LED can be received by a light encrypting device like mobile or laptops, which could be any device that has a optical receiver such as photodiode or an camera image sensor, and also having a visible LED for optical transmitter. After the visible light signal from LED is received by the light encrypted device, the image data can be encrypted by applying halftone algorithm followed by an XOR cipher. This ensures double encrypted security for the data to be sent. The above implementation could be made possible for the future VLC medium.