A study on various optimization algorithms for task scheduling in cloud computing
The prompt development of storage technologies, processing, and the internet’s success has made the computing resources more available, more influential, and cheaper than before. This drift in the technological field has paved way for the realization of a new computational model which is Cloud Computing. One of the most challenging problems faced in cloud computing is task scheduling, where the clients want their tasks to be finished as per the deadline within the shortest time possible. Task scheduling in the cloud is done based on various parameters such as priority, cost, time, bandwidth, resource utilization, performance, etc. The current work focuses on providing a detailed review of various optimization algorithms for scheduling in the cloud. This study is useful in understanding various optimization algorithms that are used for task scheduling, the way they behave and function. The algorithms presented here are mainly focused to minimize the computational cost and execution time thereby increasing the overall efficiency.
Published by: Gujjala Sai Lakshmi Namitha, Bindu Madhavi Siraparapu
Author: Gujjala Sai Lakshmi Namitha
Paper ID: V7I4-1414
Paper Status: published
Published: July 21, 2021
Adaptive traffic management system using traffic API
Traffic congestion is rising in cities around the world. Contributing factors include expanding urban population, aging infrastructure, inefficient and uncoordinated traffic signal timings. According to researchers, Signal Timer issues (like out-of-sync timers) are at the top causing factors of traffic congestion along with a disproportionate number of vehicles and road-work/accidents. The purpose of this article is to illustrate one of the possible solutions to increase the efficiency of existing traffic signals by optimizing signal timings with the help of real-time traffic data using a traffic API. The proposed solution is bolstered by a mathematical equation that follows the principle of equity.
Published by: Soham Bhure, Ritvik Patil, Sanket Umredkar
Author: Soham Bhure
Paper ID: V7I4-1365
Paper Status: published
Published: July 20, 2021
A study to assess the effectiveness of structured teaching program on knowledge regarding revised immunization schedule among mothers of under-five age children in selected hospital at the selected city.
A study to assess the effectiveness of structured teaching programme on knowledge regarding revised immunization schedule among mothers of under five age children in selected hospital at selected city.”Objectives: To assess the existing knowledge of mothers regarding revised immunization schedule and to evaluate effectiveness of structured teaching programme on knowledge regarding revised immunization schedule. And To find out the association between pre-test knowledge score with selected demographic variables. Methodology: quantitative research approach was used with quasi experimental one group pre-test and post- test design. Population50 Mothers of under Five Age Children, Purposive Sampling Technique was used for data collection. Result: In the pre-test- 6 (12%) had inadequate knowledge, maximum 44 (88%) had moderately adequate knowledge and no one mothers of under five age children had adequate knowledge regarding revised immunization schedule. In post-test- maximum 47 (94%) Mothers of under-five age children were having adequate knowledge and no one mothers of under-five age children were having inadequate knowledge and remaining 3 (6%) Of mothers of under-five age children were having moderately adequate knowledge regarding revised immunization schedule.
Published by: Fulwanti Natwar Padvi, Sandhya Bhimrao Wagh
Author: Fulwanti Natwar Padvi
Paper ID: V7I4-1406
Paper Status: published
Published: July 20, 2021
Remote administration of speed of an induction motor
Induction motors are widely used in many industries and domestic applications. They are used commonly in many open-loop control applications due to their cost, size, efficiency, less maintenance, simplicity and easy manufacture. In the past traditional speed control methods were used to control the speed of the DC motors, But DC motors have commutator and brushes which require more maintenance and are hazardous. So Induction motors are more preferred in these fields. Since most of the industries use Induction motors , controlling of it plays a major role. This project deals with controlling the speed of Induction Motor using Android phone remotely through Bluetooth Technology. We are using android application which uses Bluetooth to connect to the Bluetooth modem of the control circuit. Bluetooth modem is interfaced with the AVR Microcontroller. The Bluetooth slave receives the commands from the Android phone, then The Bluetooth module sends the signal to the Microcontroller. It decodes the signal and generates the pulse width signals which activates its circuit and gives the change in speed of induction motor with respect to the change in firing angle of TRAIC. This way speed can be easily varied and maintained as per the required values. We are not only controlling the speed of the induction motor, we can also detect the temperature and voltage of it which can be displayed on the android phone. Therefore, this project will be helpful in households, commercial use, industries etc
Published by: S. Bala Sai, G. Sharath Kumar, L. Sai Vivek, Baira Raviteja
Author: S. Bala Sai
Paper ID: V7I4-1448
Paper Status: published
Published: July 20, 2021
Automatic classification of diabetic retinopathy using Convolution Neural Network
Diabetic eye disease is a complexity that affects people having diabetes for a longer time. By affecting the blood vessels it can cause blurry vision or even blindness to the patients. Thus, detecting eye disease at an early stage can help many diabetic patients to get the required treatment and intern increases the survival rate. In the proposed system, the CNN algorithm of machine learning is used to detect diabetic eye disease by using thermal images. These images are pre-processed by converting them from RGB to GRAY based on which the required features are extracted. To detect diabetic retinopathy, here the Convolutional Neural Network is used to classify 5 stages of the diseased eye.
Published by: Pooja Pimpalshende, Rahul Bhandekar
Author: Pooja Pimpalshende
Paper ID: V7I4-1445
Paper Status: published
Published: July 20, 2021
Automatic solar tracking and cleaning system
Solar energy is the most abundant source of energy for all the forms of life on the planet Earth. But the solar technology has not developed to the extent of the conventional sources of energy. It faces lots of challenges such as high cost, erratic and unpredictable in nature, need for storage and low efficiency. This project aims at increasing the efficiency of solar panel which leads to increase in overall plant efficiency. This is the purposes to develop the “Solar Tracking and Cleaning System”. The Solar Tracking System is a power generating method from sunlight. This method of power generation is simple and is taken from natural resource. This needs only maximum sunlight to generate power. This project helps for power generation by setting the equipment to get maximum sunlight automatically. This system is tracking for maximum intensity of light. When there is decrease in intensity of light, this system automatically changes its direction to get maximum intensity of light. The cleaning system is using to remove the accumulated dust on its surface on a regular basis and maintain the solar panel output the system is robotic system which could have the nozzle from which the water is sprinkle on the panel and thus the panel get clean. This project also aims to reduce human involvement in the process of solar panel rotating and cleaning.
Published by: Rishikesh Sahebrao Dawange, Pavan Rajendra Shelar, Hemant Shamnath Khare, Vishal Kisan Deore
Author: Rishikesh Sahebrao Dawange
Paper ID: V7I4-1411
Paper Status: published
Published: July 19, 2021
