A study on network intrusion detection system
In this study, we have tried to survey the methods to detect network intrusions. The Intrusion detection system is important in computer networks for protecting the data. There are several algorithms using neural networks, deep learning, and machine learning to detect intrusion detection in the system. There are many methods for detecting intrusions by ensemble methods, classifiers, anomaly detection giving accuracy according to the methods. The goal of the study is to give a comparison of the methods for an accuracy rate of low rate false alarm and high detection rate. Also, the data sets used in the methods.
Published by: Vasumathi A. K., V. Banupriya
Author: Vasumathi A. K.
Paper ID: V7I3-1760
Paper Status: published
Published: June 10, 2021
Improvement of Rigid Pavement with Geogrid Material
We have seen the non uniformity, non consistency, loose soil, unstable soil while construction of roads. We have experimentally examined that geogrid can be added as an additional reinforcement. The benefit of Geogrid is that the geogrid increases the bearing ability of construction and reduces the spreading of gravels and soil. The Geogrid is also economical so the cost of construction can be reduced. Geogrid gives strength to the construction and increases life span of construction. Geogrid reinforcement is a method used in permanent paved roadways in two major application areas. They are: base reinforcement and subgrade stabilization. The strength and life of pavement is greatly affecting the type of sub- grade, sub base and base course materials. But in India most of the flexible pavements are mainly constructed over weak and problematic sub-grade. In base reinforcement, the geogrids are placed at the bottom of unbound layers of a flexible pavement system and improve the load-carrying capacity of the pavement under repeated traffic. In subgrade stabilization applications, the geogrid is used to build construction platform over weak subgrade to carry equipment and facilitate the construction of the pavement system without over deformations of the subgrade.
Published by: Samata Devanand Thakare, Ankita Kanhaiya Pailkar, Shradha Sanjay Sanap, Utkarsh Rajesh Andhere, Sarvesh Sudhakar Palkar, Vivek Sahadev Ubhare, Vaibhav Vinod Bhoir, Dr. S. R. Bhagat, P. P. Mahajan
Author: Samata Devanand Thakare
Paper ID: V7I3-1777
Paper Status: published
Published: June 10, 2021
Work Efficiency Prediction Analysis and Optimal Path Finding Algorithm
A correct prediction of a contractor’s work can lead to many important things like keeping corruption in check, determining whether that particular is fit for the job or not. Frequently, it is brought that prediction is chaotic rather than random, which means it can be predicted by carefully analysing the history of respective contractor. Machine learning is an efficient way to represent such processes. It predicts a value close to the tangible value, thereby increasing the accuracy. The vital part of machine learning is the dataset used. The dataset should be as concrete as possible because a little change in the data can perpetuate massive changes in the outcome. It consists of variables like name of contactors, previous projects that he worked on, budget of that project, estimated lifespan of the project and actual life of the project. Due to the serious problem of bad road construction and maintenance, the real-time road situation and the possibility of road conditions in the next time period should be taken into accounts through the vehicle navigation system, in order to provide the optimal routing plans for vehicles in routing optimization. To solve the ignoring of real-time travel information and historical travel information in the existing navigation systems during routing optimization, this paper compares the existing navigation system to a prototype system which considers the conditions of the roadways as one of the factor in the recommendation and optimization system of the path finding and navigation process.
Published by: Rohit Pillai, Vipul Bhangale, Bishal Anand, Adarsh Kumar
Author: Rohit Pillai
Paper ID: V7I3-1766
Paper Status: published
Published: June 10, 2021
RICA: Real-Time Image Captioning Application
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing. Image caption generator is a task that involves computer vision and natural language processing concepts to recognize the context of an image and describe them in a natural language like English. The recent advances in Deep Learning-based Machine Translation and Computer Vision have led to excellent Image Captioning models using advanced techniques like Deep Reinforcement Learning. While these models are very accurate, these often rely on the use of expensive computation hardware making it difficult to apply these models in real-time scenarios, where their actual applications can be realized. In this paper, we carefully follow some of the core concepts of Image Captioning and its common approaches and present our simplistic encoder and decoder-based implementation with significant modifications and optimizations which enable us to run these models on low-end hardware of hand-held devices. We also compare our results evaluated using various metrics with state-of-the-art models and analyze why and where our model trained on the MSCOCO dataset lacks due to the trade-off between computation speed and quality. Using the state-of-the-art TensorFlow framework by Google, we also implement a first-of-its-kind Android application to demonstrate the real-time applicability and optimizations of our approach.
Published by: Suraj Dahake, Aditya Ohekar, Shubham Ilag, Aasim Shah
Author: Suraj Dahake
Paper ID: V7I3-1729
Paper Status: published
Published: June 10, 2021
Design of a Micro-controller based programmable voltage source for process automation
Automated control of processes are emerging in all spheres as it saves time and energy by providing a significant improvement in productivity and accuracy when compared to the manual methods of controlling processes which require constant human intervention. This paper presents a design of a voltage source that can be programmed using a micro-controller board to control the voltage that needs to be generated. The design is achieved by interfacing the electronic components required along with necessary software tools as a part of an embedded system consisting of the input/output peripherals and a microcontroller. There are two approaches of design, the first approach is based on a Digital to Analog converter and an Operational amplifier, the second approach is based on a MOSFET driver circuit. The circuits are constructed based on the design methodology which is developed with all the components chosen according to desired requirements. The circuits are simulated in Proteus in order to evaluate their performance and the readings are tabulated. The accuracy of both the approaches are computed and it is found that both the approaches have high levels of accuracy.
Published by: Rahul Desingh S., Sindhu Rajendran
Author: Rahul Desingh S.
Paper ID: V7I3-1774
Paper Status: published
Published: June 10, 2021
Self-wound analysis using Machine Learning and Image Processing
The significance of powerful surgical wound care can never be underestimated. Poorly managing surgical wounds may reason many critical complications. As a result, it increases. The necessity to broaden a patient-friendly self-care device which can assist both sufferers and clinical specialists to ensure the Nation of the surgical wounds without any unique medical equipment. On this paper, a surgical wound evaluation gadget for Self-care is proposed. The proposed machine is designed to allow patients seize surgical wound pictures of themselves with the aid of the usage of a cellular tool and add these pix for evaluation. Combining Image-processing and gadget-gaining knowledge of strategies, the proposed approach consists of four levels. First, photos are segmented into superpixels wherein each superpixel carries the pixels within the comparable shade distribution. 2nd, these superpixels corresponding to the pores and skin are recognized and the area of related skin Superpixels is derived. 1/3, surgical wounds can be extracted from this place primarily based on the statement of the texture distinction between skin and wounds. Ultimately, country and signs and symptoms of surgical Wound may be assessed. Full-size experimental effects are Conducted. With the proposed method, greater than 90% of country evaluation consequences are correct, and greater than ninety one% of symptom evaluation results consistent with the real analysis. Furthermore, case studies are furnished to show the benefit and trouble of this machine. Those results display that this device should perform
Published by: Varun Ganesh, U. Nomesh
Author: Varun Ganesh
Paper ID: V7I3-1767
Paper Status: published
Published: June 10, 2021
