19c96fd517d854497e8-2943 20220211042040887 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 06 30 2021 10 8 Department of Mathematics, Integral University, Lucknow (U.P) India. Dr. Najmuddin Ahmad Balmukund Singh Research Scholar, Department of Mathematics, Integral University, Lucknow (U.P) India. In this paper, we discuss the numerical solution of Adomian decomposition method and Taylor’s expansion method in Volterra linear integral equation. And we apply modified Adomian decomposition method and Newton Raphson method in Volterra nonlinear integral equation with the help of example and estimated an error in MATLAB 13 versions. 06 30 2021 5 11 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9069.0610821 https://www.ijitee.org/portfolio-item/H90690610821/ Department of Computer Science and Engineering, SRM IST, Delhi NCR Campus Modinagar, Ghaziabad (U.P), India. Rakesh Kumar Yadav Abhay Pratap Mishra Department of Computer Science and Engineering, SRM IST, Delhi NCR Campus Modinagar, Ghaziabad (U.P), India. Aman Singh Department of Computer Science and Engineering, SRM IST, Delhi NCR Campus Modinagar, Ghaziabad (U.P), India. In the past few years, people’s life is affecting badly by the spread of coronavirus due to a lack of information about the spread of the virus and proper management to control it. The government is also looking for ways to get information that how beneficial is their preventive measures. So, that they can Know that whether their preventive measures need to be modified or not. The effect of coronavirus can be seen by the number of people affected, the number of people being treated, and the number of people dead. These are the data based on which our application will make a prediction. The goal of this paper is to make a model that will give us a good prediction based on other variables. In most cases, we use linear regression for data because linear regression gives good accuracy. This paper will be helpful for both people and the government, they will be able to predict the number of cases in the next month so that they can prepare themselves to face the problem and control it from further spreading. 06 30 2021 12 18 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9076.0610821 https://www.ijitee.org/portfolio-item/H90760610821/ Tesla Air Technologies, Pune (Maharashtra), India. Shubham Thakur Risha Shetty Mechatronics Engineering, Symbiosis Skills and Professional University, Pune (Maharashtra), India. Sanskruti Sawant Mechatronics Engineering, Symbiosis Skills and Professional University, Pune (Maharashtra), India. Mrunali Rajigare Mechatronics Engineering, Symbiosis Skills and Professional University, Pune (Maharashtra), India. Santosh Sonavane Director at school of Mechatronics Engineering, Symbiosis Skills and Professional University, Pune (Maharashtra), India. Washing our hands regularly is extremely important to keep up with sanitation and to prevent ourselves from sickness, and we follow this standard consistently in this period because of the current pandemic crisis. Accordingly, People all around the world have normalized the significance of sanitation and disinfecting surfaces and objects in the area. Sanitation does not usually erase microbes, but instead lessens their presence by removing them. The number of microbes lessened from a surface is quite dependent on type of material and product used to sanitize the area. Hence, we have come up with an object that is not only capable of wiping out the microbes completely but also it is cost effective. The corona virus is transmitted by people coming in contact with each other. This virus lives on variety of surfaces, but we can cleanse it by using various disinfecting and sterilizing products. It is therefore very important that people realize the necessity of sanitizing almost all the surfaces and objects in the environment around us. For example, people working in various sectors including dispensaries, hotels, shopping complexes, salons etc. to maintain hygienic environment. Keeping in mind, several devices have been designed for sanitizing hands and objects and increasing the need creating more such systems in affordable manner. Taking these areas into consideration, we planned to construct a sensor-based product which will play an essential role. Hence, we thought of a unique concept and worked on this latest technology using UV lamps for disinfecting the germs, viruses etc. This solution will not only be innovative but also conveyable so that it is ready to carry. 06 30 2021 19 22 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9114.0610821 https://www.ijitee.org/portfolio-item/H91140610821/ Professor & Research Director, Asia Technological School of Science and Arts Sta. Rosa, Laguna Philippines. Arman Bernard G. Santos Neil P. Balba Professor & Director, Center for Innovation and Development Lyceum of the Philippines University, Laguna, Corazon B. Rebong Professor & Vice President for Academics Colegio de San Juan de Letran-Calamba Calamba, Laguna Philippines. In this paper, researchers had provided definite solutions in order to check and validate student attendance with the use of computerized seat plans along with the information and image of each student. This study also discussed the inclusion of Optimization Query Algorithm in order to identify and monitor student’s punctuality as well as the analysis of the reasons why they fail to attend their class. Attendance patterns are formed early in life because it validates one of the components of student’s academic and scholastic performance. Regular attendance is vital part of the grading component necessary to attain some portion of the student’s academic progress. You are missing out on active learning experiences and class attendance. As a result, they are more likely to to fail which tends to affect their academic performances. Index Terms: Drag, Drop, Re-Arrange, Images, Reports, Schedule, Load, Computer-Based Systems. 06 30 2021 142 146 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9149.0610821 https://www.ijitee.org/portfolio-item/H91490610821/ Assistant Professor, Department of Computer Science, St. Xavier’s College (Autonomous), Palayamkottai, Tiruneveli, (Tamil Nadu), India. Dr. M. Venkatesh Ms. R. Rashia SubaShree Junior Analyst, G-VEN Group, Palayamkottai, Tiruneveli, (Tamil Nadu), India. The world has improving with lot of people utilities for living case. In this development technologies make the purpose of surviving easier. Internet of things is the inter-connecting technology used to pass the data to the required people via physical devices which are embedded with the software’s, sensors, electronics etc. IoT lift up smart cities, transportation, industries with new innovations for the development. The proposed system is done in transport sector to effectively manage the vacant seats particularly on travel buses. The vacant seats may happen due to last minute cancellation, the passengers who missed bus, or the passengers who doesn’t cancel their ticket even after they decide not to travel. In present situation, the seat allocation for the travelers is mostly done through online but when it comes to the vacant seats, the ticket checker has to allocate it manually. The system purpose is to verify whether all booked seats are occupied or not using sensors, and it automatically sends the signal to centralized server and make enable that particular seat for fresh booking. So that, the passengers who planned for travel by last minute can able to book ticket through online from the upcoming boarding stations. 06 30 2021 28 32 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9163.0610821 https://www.ijitee.org/portfolio-item/H91630610821/ Department of Electronics Engineering, Madhav Institute of Technology & Science, Gwalior (MP), India. Chandra Pal Kushwah Kuruna Markam Department of Electronics Engineering, Madhav Institute of Technology & Science, Gwalior (MP), India. Bidirectional in recent years, Deep learning performance in natural scene image processing has improved its use in remote sensing image analysis. In this paper, we used the semantic segmentation of remote sensing images for deep neural networks (DNN). To make it ideal for multi-target semantic segmentation of remote sensing image systems, we boost the Seg Net encoder-decoder CNN structures with index pooling & U-net. The findings reveal that the segmentation of various objects has its benefits and drawbacks for both models. Furthermore, we provide an integrated algorithm that incorporates two models. The test results indicate that the integrated algorithm proposed will take advantage of all multi-target segmentation models and obtain improved segmentation relative to two models. Keywords: A Satellite Image, Deep Neural Network, U-net, SigNet. 06 30 2021 33 37 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9186.0610821 https://www.ijitee.org/portfolio-item/H91860610821/ Pursuing, Department of Computer Engg., PCCOE, Pune (Maharashtra), India. Snehal Patil Yash Shah Pursuing, Department of Computer Engg., PCCOE, Pune (Maharashtra), India. Payal Narkhede Pursuing, Department of Computer Engg., PCCOE, Pune (Maharashtra), India. Abhinav Thakare Pursuing, Department of Computer Engg., PCCOE, Pune (Maharashtra), India. Rahul Pitale Assistant Professor, Department of Computer Engg., PCCOE, Pune (Maharashtra), India. Human communication plays a vital role; without communicating, day-to-day tasks seem difficult to complete. And the world has an almost 5% population that struggles with hearing or speaking disability, which contributes to 430 million people worldwide, and this will grow up to 900million just in the next 25 to 30 years. With the increasing noise pollution, hearing capacity degrades, leading to various hearing problems. The WHO statistics show that 32million kids are acoustically impaired. With disabilities, there are multiple issues these people face, such as lack of learning facilities, job opportunities, communication platforms, etc. These people need a cooperative environment to express, learn at their pace and level of understanding. This paper focuses on developing an application that bridges the gap between these acoustically disabled people and people unknown to their way of communication. The proposed research is an edge device application provides features like a gesture to text, speech to text, e-learning platform, and Alert mechanism. This paper majorly focuses on developing a friendly all in one platform for mute and deaf community for communication, learning and emergency alerts. The research was conducted with two approaches the traditional CNN and Tensorflow lite EfficientNet model to train the ASL (American Sign Language) dataset for the communication platform, where we obtained accuracy of 98.91% and 98.82% respectively. To overcome the computational barriers of traditional CNN approach, Tensorf low lite Efficient Net model was brought into the picture. The proposed methodology would help build a platform for the deaf and mute community to express themselves better and gain wider exposure to the world. 06 30 2021 38 42 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9204.0610821 https://www.ijitee.org/portfolio-item/H92040610821/