Manuscripts

Recent Papers

Others

Cloud storage scheme based on computational intelligence in fog computing

Traditional privacy protection schemes are usually based on cipher technology, but these kinds of methods cannot effectively resist attacks from the inside of a cloud server. In order to achieve the goal problem, the motive of a three-layer storage framework supported fog computing. The future framework can both take full advantage of cloud storage and protect the privacy of knowledge. The hash-Solomon code algorithm is meant to cleave data into different parts. Then, this can add a small part of data in the local machine and fog server in order to protect privacy. With the explosive growth of disorderly data, cloud storage technology gets more attention and better development. However, in Education, Financial, and Healthcare storage schema, users’ data is totally stored in cloud servers.

Published by: G. Thanuja Reddy, Dr. Vanitha Kakollu

Author: G. Thanuja Reddy

Paper ID: V8I3-1260

Paper Status: published

Published: May 16, 2022

Full Details
Review Paper

NeoLacta Lifesciences – Ensuring an Exclusive Human Milk Diet for Pre-term Infants through Donor Human Milk-Derived Nutrition

Each year 15 million premature babies are born globally of which ~ 1.1 million don’t survive beyond a few weeks. Almost 3.5 million babies are born prematurely in India alone, the highest globally for any nation. For such prematurely born babies, the mother’s own milk is the best source of nutrition. Human breast milk provides optimal nutrition, reduces the risk of NEC and Sepsis, builds immunity, strengthens the gut flora, and supports neurocognitive development. Numerous clinical trials have proven the value of human milk and products derived from human milk, especially for the sick and vulnerable premature population. Screened and pasteurized human milk has been the recommended option by healthcare bodies globally when a mother’s own milk is unavailable. Donation of surplus milk from healthy nursing mothers can make a world of difference by proving to be a lifesaver for premature babies and their families. Donating milk also brings a sense of satisfaction to the donor mother since her milk will benefit many other babies along with her own. Besides, it also promotes the well-being of the donor mother by reducing the risk of conditions such as engorgement and mastitis. A healthy nursing mother with excess breast milk should consider donating it to the sick and premature babies thereby contributing to building a healthier next generation. The endeavor is to draw the attention of the reader toward the importance of human milk donation and its impact on the health and well-being of premature babies. Through this white paper, NeoLacta Lifesciences would also like to highlight the safety, robustness, and ethicality of its operations. Our objective is to create a resilient framework by bringing together all stakeholders – healthcare professionals, parents, family, community, and policymakers towards destigmatizing this noble initiative of human milk donation.

Published by: Dr. Vikram Reddy K.

Author: Dr. Vikram Reddy K.

Paper ID: V8I3-1255

Paper Status: withdrawn

Submitted: May 16, 2022

Full Details Track Status
Research Paper

A comparative analysis of Machine Learning Algorithms on malicious URL prediction

Phishing is a type of deception in which a person or entity poses as a legitimate user. Phishing is a technique for fooling consumers that have grown more prevalent in cyberspace. The majority of phishing texts are cryptic. Many strategies and plan has now been intended to deal with the phishing problem in the literature. There is currently no solid remedy in place to prevent such assaults. This article proposes a To detect phishing assaults, a human has to learn forecasting engine is used taking this into account. Logical regression beats the other methods in both precision and failure rate, according to the experimental investigation. With logistic regression, you can predict URLs with accuracy.

Published by: B. Naveen Kumar, S. Viswa Teja Reddy, A. Yashwanth Sai, G. Umesh Kumar, M. Srikanth

Author: B. Naveen Kumar

Paper ID: V8I3-1275

Paper Status: published

Published: May 16, 2022

Full Details
Review Paper

Planning, estimation and designing of G+1 House Plan

Our project focuses on planning designing of estimating of G+ 1 house plan. In this exclusive civil project, the bone will get some vital information on how to develop the perfect house plan for any G+1 house. The main objective of our project is to know the various design aspects like planning and estimate We have planned to design a house consisting of two floors (G+1). The planning is done as per the requirements Project begins with starts the start of the Layout of the house or structure followed by the Design and Analysis of the structure which is succeeded by cost estimation and planning for the said project . This project involves the layout, design, analysis, planning, and cost estimation of a G+1 house The layout of the proposed G+1 house is based on a plot of size15.40m x 11.75m. The shape of the house is rectangular in plan. The house consists of the ground floor and first floor. The staircase is provided with enough safe. National Building Code (NBC). All the drafting was done using AutoCAD. Also, these drawings made on AutoCAD also served as a base for the transfer of the structure for analysis and design. The cost estimate for the project has been calculated using Centre Line Method.

Published by: Ehsan Ansari, Muskan Sharma, Ajmal Shaikh, Nikita Sawant, Sagar Mungase

Author: Ehsan Ansari

Paper ID: V8I3-1265

Paper Status: published

Published: May 16, 2022

Full Details
Research Paper

Analysis and Design of RCC T-Beam Bridge Superstructure by using Different Codes and Load Combinations for Performance Assessment

Abstract: This study summarized the comparative design and analysis of the RCC T-Beam Bridge superstructure for Different Codes i.e., Indian Road Congress (IRC) codes and American Association of State Highway Transportation Officials (AASHTO) Specification Load Combinations for varying span lengths. Several codes are used to design the bridges. IRC 21-2000 was used for designing bridges by working stress method (WSM), also IRC: 112-2011 introduced by Indian Road Congress for RCC and Pre- Stressed bridges by limit state method (LSM). Both the codes have different guidelines and procedures for the design of bridges. This study based on IRC 112-2011 (LSM) and IRC: 6- 2017 is used for load considerations. This analysis depends on the analytical modeling by Finite Element Method (FEM) in STAAD-Pro software and compares the structural parameter Bending moment, Shear Force, Deflection, and Area of Reinforcement for different girder span lengths 16M, 20M, 24M as per the IRC and AASHTO code. Class A & Class 70R consider from IRC 6-2017 and HS93 is the vehicular loading considered from AASHTO. Form the analysis understanding suitability design technique and the behavior of two-lane carriageway width of T- Beam bridge superstructure under different loading conditions and by using different code and comparing the result, conclusions will be made that up to what extent similarities between both standards.

Published by: Tanmay Farsule, Girish Sawai

Author: Tanmay Farsule

Paper ID: V8I3-1284

Paper Status: published

Published: May 16, 2022

Full Details
Research Paper

Stock price prediction

With the advent of technological marvels such as digitalization around the world, stock market predictions have entered a more technologically advanced era, reviving the old trading model. With the steady growth of market capitalization, stock trading has become an investment hub for many financial investors. Many analysts and researchers have developed tools and techniques that predict stock price movements and assist investors in making sound decisions. Advanced trading models enable researchers to predict the market using non-traditional text data from social media platforms. The use of advanced machine learning methods such as textual data analysis and compilation methods has greatly increased the accuracy of prediction. Meanwhile, stock market analysis and forecasting continue to be one of the most challenging research areas due to volatile, volatile, and volatile data. This study describes the design of machine-based learning strategies for predicting the stock market based on the use of a standard framework. In addition, a comprehensive comparative analysis was performed to obtain an indicator of significance. This research can be useful to emerge researchers to understand the basics and developments of this emerging environment, thus continuing further research in promising ways.

Published by: Kartik Bhatnagar, Arya Tomar, Teena Verma

Author: Kartik Bhatnagar

Paper ID: V8I3-1267

Paper Status: published

Published: May 16, 2022

Full Details
Request a Call
If someone in your research area is available then we will connect you both or our counsellor will get in touch with you.

    [honeypot honeypot-378]

    X
    Journal's Support Form
    For any query, please fill up the short form below. Try to explain your query in detail so that our counsellor can guide you. All fields are mandatory.

      X
       Enquiry Form
      Contact Board Member

        Member Name

        [honeypot honeypot-527]

        X
        Contact Editorial Board

          X

            [honeypot honeypot-310]

            X