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Research Paper

Real Estate Solution driven by Blockchain Technology

The notion of Blockchain was first propositioned by Stuart Haber and Scott Stornetta in 1991 with an aim to develop a secure system where data and timestamps cannot be vandalizing. Within the established period of Blockchain, there have been a many momentous data breaches. As per the data breaches reports by MIT [1], cryptocurrency amount of almost $2 billion has been stolen since 2017. Forthwith, attacks on different data systems become frequent around the clock at all possible levels. These potential breaches indicate the necessity of a fortified architecture backed with distributed database and comprehensive risk management and allayed security systems. Our paper reconnoitres the types, algorithm, cyber-attacks with their core ideas, the ways to evade the threats by stating various security solutions, with the ongoing and future technologies to make blockchain, the safest system to protect the data as real-estate blockchain architecture in which an entirely new verified mechanism is introduced in order to reduce the fraudulent activities in the sector.

Published by: Akash Tyagi, Yatin Kalra

Author: Akash Tyagi

Paper ID: V8I3-1339

Paper Status: published

Published: May 23, 2022

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Research Paper

Early-Stage Dementia Detection by Optimize Feature Weights with Ensemble Learning

Dementia has developed into a significant health problem for many over the age of 50. Numerous kinds of dementia develop gradually and incrementally. Previous researchers have received reports from persons of various ages who have had memory loss and subsequent recall from long-term memory loss as a result of this neurodegenerative illness. Memory loss that is both gradual and irreversible characterises the disorder known as dementia. Although it is more common in the elderly, an increase in cases among the younger population has raised experts' eyes and encouraged them to explore the neuro-disorder, which causes memory loss and a barrier in recalling information from memory. Dementia can slow down to some extent if diagnosed early enough. Optimize learning and an additional tree classifier are used to extract information from brain MRI images and classify dementia at an early stage. In order to discover various patterns of dementia risk, hyper-parameters resulting from XGboost were obtained and assessed. Gradient boosting is commonly used to do variable extractions from independent to dependent variables, and the resulting derived variables are the result of this process

Published by: Tanvi Mahajan, Dr. Jyoti Srivastava

Author: Tanvi Mahajan

Paper ID: V8I3-1338

Paper Status: retracted

Submitted: May 23, 2022

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Research Paper

Power Loss and Voltage Profile in Distribution System by Neural Network

The objective of power system operation is to meet the demand at all the locations within the power network as economically and reliably as possible. The traditional electric power generation systems utilize the conventional energy resources, such as fossil fuels, hydro, nuclear etc. for electricity generation. The operation of such traditional generation systems is based on centralized control utility generators, delivering power through an extensive transmission and distribution system, to meet the given demands of widely dispersed users. Nowadays, the justification for the large central-station plants is weakening due to depleting conventional resources, increased transmission and distribution costs, deregulation trends, heightened environmental concerns, and technological advancements. location and size of the DGs before and after radial network reconfiguration are determined using a multi-objective particle swarm optimization technique. In an active distribution network, an ideal network layout with DG coordination eliminates power losses, elevates voltage profiles, and enhances system stability, reliability, and efficiency.

Published by: Sandeep Kaur, Tejpal Singh

Author: Sandeep Kaur

Paper ID: V8I3-1337

Paper Status: published

Published: May 23, 2022

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Research Paper

Accident detection system

In this project, we detect the accident between two vehicles. For the purpose of detection, we use certain algorithms such as YOLO and CNN (Convolutional Neural Networks). This project is mainly built upon the combination of Object Detection and Tracking System (which is also abbreviated as ODTS) and RCNN algorithms which are mainly used for detecting purposes. In this project, a video is given as input where the coded algorithm completely separates the video into frames and analyzes the-each frame and detects the crash in the frames, and gives those frames as an output. In addition to accident detection, YOLO also detects the surroundings such as persons, cars, trucks, etc. The main point of using YOLO is to detect the surroundings and the crash (with the help of CNN).

Published by: Manideep Pallerla, Anusha Nallamalla

Author: Manideep Pallerla

Paper ID: V8I3-1335

Paper Status: published

Published: May 23, 2022

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Research Paper

Annotations on files

Real-time collaborative editing allows multiple users to edit a shared document at once. It has received a lot of attention from both industry and education and gained popularity due to the wide availability of free services like Google Docs. Although these shared editing programs were originally used in situations that included only a small set of users such as writing a research article, these days we are seeing a change in scale from fewer users to user communities. [2] Annotation can be an important function when trying to understand new information. The methodology can be used to create a ‘summary’ version of real information for later review and to add additional information to an existing document. The growth in web-based learning materials and information sources has created a requirement for systems that allow annotations to be attached to these new sources and, potentially, shared with other learners.[3]

Published by: Vipul Shinde, Siddhant Rathi, Mansi Parmar, Darshana Kumbhakarna, Deepa Sapkal

Author: Vipul Shinde

Paper ID: V8I3-1314

Paper Status: published

Published: May 20, 2022

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Research Paper

Caption generator for random images using CNN & LSTM

With the rapid growth of artificial intelligence in recent years, picture caption has steadily grabbed the attention of many artificial intelligence researchers and has become an important study topic. alluring and arduous task. Image captioning and spontaneously generating natural human language captions according to the content observed in the above-captured image is an important part of scene understanding, which requires the knowledge of computer vision and natural language processing. The operation of the image caption generator is far-reaching and eloquent, for instance, the realization of human-computer interactions. This paper encapsulates methods and focuses on the attention mechanism, which plays a vital role in computer vision and is recently used in image caption generation tasks.

Published by: Ranga Prasad, B.Satyanarayana, Shaik Shahid

Author: Ranga Prasad

Paper ID: V8I3-1313

Paper Status: published

Published: May 20, 2022

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