Objective: The antinuclear antibodies (ANA) that present in the human serum have a link with various autoimmune diseases. Human Epithelial type-2 (HEp-2) cells acts as a substance in the Indirect Immuno fluorescence (IIF) test for diagnosing these autoimmune diseases. In recent times, the computer-aided diagnosis of autoimmune diseases by the HEp-2 cell classification has drawn more interest. Though, they often pose limitations like large intra-class and small inter-class variations. Hence, various efforts have been performed to automate the procedure of HEp-2 cell classification. To overcome these problems, this research work intends to propose a new HEp-2 classification process. Materials and Methods: This is regulated by integrating two processes, namely, segmentation and classification. Initially, the segmentation of the HEp-2 cells is carried out by deploying the morphological operations. In this paper, two morphology operations are deployed called opening and closing. Further, the classification process is exploited by proposing a modified Convolutional Neural Network (CNN). The main objective is to classify the HEp-2 cells effectively (Centromere, Golgi, Homogeneous, Nucleolar, NuMem, and Speckled) and is made by exploiting the optimization concept. This is implanted by developing a new algorithm called Distance Sorting Lion Algorithm (DSLA), which selects the optimal convolutional layer in CNN. Results: Through the performance analysis, the performance of the proposed model for test case 1 at learning percentage 60 is 3.84%, 1.79%, 6.22%, 1.69%, and 5.53% better than PSO, FF, GWO, WOA, and LA, respectively. At 80, the performance of the proposed model is 5.77%, 6.46%, 3.95%, 3.24%, and 5.55% better from PSO, FF, GWO, WOA, and LA, respectively. Hence, the performance of the proposed work is proved over other models under different measures. Conclusion: Finally, the performance is evaluated by comparing it with the other conventional algorithms in terms of accuracy, sensitivity, specificity, precision, FPR, FNR, NPV, MCC, F1-Score and FDR, and proves the efficacy of the proposed model.

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Net Neutrality is all about the neutrality in the web space. This means, no special favour to be shown to any data in the internet for whatsoever reasons.. Internet's most powerful tool, the Social media has become an essential component of our daily life. Social media helps people, who had never been heard, heard. Anyone can freely express his/her mind without feeling intimidated. This paper deals with data from one of the most popular social media, Twitter, for understanding public perceptions and misperceptions of net neutrality. A Sentimental analysis on tweets related to net neutrality is done country wise and overall during the period 2016-2017. The classification is done using machine learning technique. Processing of tweets data is done to find sentiments of people and polarity of their tweets which helps us to determine the attitude of the people around the world. Keywords-Sentimental Analysis; Net Neutrality; Naive Bayes Classifie;rLexicons;Polarity I. INTRODUCTION Sentimental Analysis can be defined as a contextual understanding of a sentence expressed in a social media or opinion mentioned by a person in form of a text. It is a part of Natural Language processing and detection of attitude of people or a society on a particular issue. It is a part of subjectivity analysis which includes review mining, opinion mining, appraisal extraction. The sentimental analysis can be in sentence level, document level and future level.[1] Feedback is a mechanism of expression of our views or attitude of people whatever thing that is happening in and around us. It will be there in a launch of new product, new policy decisions of the Government, new events by tweets, Face books or Instagrams. We can say these as opinion retrieval system in social media.[2][3] Net neutrality is a government mandated policy for all internet service providers to take all information in the internet to all users without any discrimination in terms of platform, website, content, equipment. No special favour to be shown to any data in the internet for whatsoever reasons. A predominant opinion about net neutrality is that an extremely popular device like internet, if remains neutral, can be the most useful device that human race has ever invented. The practice of certain internet service providers allowing certain data free of cost and slowing down some data or selling some data for a price are all considered to be against net neutrality. In the face of tough competition between ISPs, many have resorted to such practices to attract more customers. Though to some extend it helps certain section of the customers, to the larger extend, major part of the customers stand to lose.21st century's 17 years saw revolutionary changes in the way humans live. Internet played a big role in these developments. Unbridled availability of data across any kind of network was the key to the success of internet and it helped people bring the world to their finger tips. With the advent of competition among the internet service providers, to gain upper hand over or...

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