Enhanced LSB Algorithm For Stegano Communication

Steganography is outlined because the study of invisible communication that typically deals with the ways that of concealing the existence of the communicated message. Usually, information embedding is achieved in communication, image, text, voice or transmission content for copyright, military communication, authentication and plenty of alternative functions. In image Steganography, secret communication is achieved to infix a message into cowl image and generate a stego image. The goal of steganography is to cover the existence of the message from unauthorized party. The fashionable secure image steganography presents a task of transferring the embedded data to the destination while not being detected by the attacker. Several different image file formats will be used, however, digital pictures area unit the foremost widespread owing to their frequency on the web. Image steganography takes cover object as image. Generally, in this technique pixel intensities are used to hide the information. The concept of steganography known as ‘Enhanced LSB Algorithm’ is employed to hide an image in an image, which has negligent distortion as compared to the Least Significant Bit Algorithm

Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/

Effect of Parameters Behavior of Simarouba Methyl Ester Operated Diesel Engine

Being an energy source of another origin, the compression ignition (CI) engine’s typical design parameters might not suit Simarouba oil methyl ester (SuOME). Present experimental investigation targets are determining the effects of engine design parameters, including fuel injection pressure and nozzle geometry, on the engine, concerning performance and emissions such as carbon monoxide (CO), unburnt hydrocarbon (HC), oxides of nitrogen (NOx), and smoke opacity, with SuOME as fuel. Comparisons of brake thermal efficiency (BTE) and different emissions from the engine tailpipe were performed for different fuel injection pressures and a number of injector holes and diameter of orifices were opened in the injector to find the optimum combination to run the engine with SuOME. It was observed that the combined effect of an increase in injection pressure of 240 bar from 205 bar, and increasing number of injector holes from three to six with reduced injector hole diameters from 0.2 to 0.3 mm, recorded higher brake thermal efficiency with reduced emission levels for the SuOME mode of operation compared to the baseline standard operation with SuOME. For 240 bar compared to 205 bar of injection pressure (IP) for SuOME, the BTE increased by 2.35% and smoke opacity reduced by 1.45%. For six-hole fuel injectors compared to three-hole injectors, the BTE increased by 3.19%, HC reduced by 9.5%, and CO reduced by 14.7%. At 240 bar IP, with the six-hole injector having a 0.2 mm hole diameter compared to the 0.3 mm hole diameter, the BTE increased by 5%, HC reduced by 5.26%, CO reduced by 25.61%, smoke reduced by 10%, while NOx increased marginally by 0.27%. Hence, the six-hole FI, 240 IP, 0.2 mm FI diameter holes are suitable for diesel engine operation fueled by Simarouba biodiesel

Book of Abstracts of the 2nd International Conference on Applied Mathematics and Computational Sciences (ICAMCS-2022)

It is a great privilege for us to present the abstract book of ICAMCS-2022 to the authors and the delegates of the event. We hope that you will find it useful, valuable, aspiring, and inspiring. This book is a record of abstracts of the keynote talks, invited talks, and papers presented by the participants, which indicates the progress and state of development in research at the time of writing the research article. It is an invaluable asset to all researchers. The book provides a permanent record of this asset. Conference Title: 2nd International Conference on Applied Mathematics and Computational SciencesConference Acronym: ICAMCS-2022Conference Date: 12-14 October 2022Conference Organizers: DIT University, Dehradun, IndiaConference Mode: Online (Virtual