B. Karthikeyan, P. Nishmitha, B. Poojasree, S. Asha
{"title":"Authentication of Secret Message using Rabin-Karp in Image Steganography","authors":"B. Karthikeyan, P. Nishmitha, B. Poojasree, S. Asha","doi":"10.1109/ICCS45141.2019.9065849","DOIUrl":"https://doi.org/10.1109/ICCS45141.2019.9065849","url":null,"abstract":"This paper explicitly gives an inventive way to transfer the data without getting disrupted by using the methodologies of Steganography and Cryptography. Applying the strategies of Rabin-Karp, which is used to find the hash code for the message to be encrypted and Rotor Machine, which encrypts the message helps to protect the data from attackers. The coding has been implemented in MATLAB. After the implementation of the code, it is verified using the parameters called PSNR and MSE and obtained the clear results.","PeriodicalId":112413,"journal":{"name":"International Conference Intelligent Computing and Control Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123914500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Online State and Parameter Estimation of Ultracapacitor Using Marginalized Kalman Filter","authors":"S. Madhumitha, P. Sudheesh, P. AnitaJ","doi":"10.1109/ICCS45141.2019.9065304","DOIUrl":"https://doi.org/10.1109/ICCS45141.2019.9065304","url":null,"abstract":"Recent adoption to the usage of renewable resources has emerged as a consequence of the threats posed by the decreasing amount of fossil fuels and the increase in the level of greenhouse gases (GHG) in the atmosphere. This harnessed renewable energy needs to be stored in an energy storage device. One amongst the most prominently used energy storage devices is the ultracapacitor (UC). To ensure proper deployment and safer long-term operation, the dynamic behavior of the UC has to be observed carefully which is done by estimating the parameters of the UC online, which can be further used in the deduction of the state of health (SOH) and the state of charge (SOC) of the UC. The equivalent circuit model used for the purpose of estimation is demonstrated. Then the parameter estimation is done using the marginalized Kalman filter technique. This technique is implemented in MATLAB and the results are attached. The effectiveness of the method is validated by comparing the acquired results with the results that are obtained by employing other online parameter estimation techniques.","PeriodicalId":112413,"journal":{"name":"International Conference Intelligent Computing and Control Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121344265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Amrita-CEN-SentiDB: Twitter Dataset for Sentimental Analysis and Application of Classical Machine Learning and Deep Learning","authors":"K. Naveenkumar, R. Vinayakumar, K. Soman","doi":"10.1109/ICCS45141.2019.9065337","DOIUrl":"https://doi.org/10.1109/ICCS45141.2019.9065337","url":null,"abstract":"Social media is a platform in which the data is generated each and every day in an abundance manner. The data is so large that cannot be easily understood, so this has paved a path to a new field in the information technology which is natural language processing. In this paper, we use the text data for classification of tweets that determines the state of the person according of the sentiments which is positive, negative and neutral. Emotions are common between humans which has a way to express it that decides the person’s feelings which has a high influence on the decision making tasks. Here we have proposed the text representation, Term Frequency Inverse Document Frequency (tfidf), Keras embedding along with the machine learning and deep learning algorithms for classification of the sentiments, out of which Logistics Regression machine learning based methods out performs well when the features is taken in the limited amount as the features increases Support Vector Machine (SVM) that belongs to machine learning algorithm out performs well making a benchmark accuracy for this dataset as the 75.8%. The dataset is made publically available for research purpose.","PeriodicalId":112413,"journal":{"name":"International Conference Intelligent Computing and Control Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125864996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}