Category Archives: Uncategorized

A Deep Learning Structure for Forecasting Cyclone Intensity
Authors:-Assistant Professor Kavitha, Abhineet Raj, Tanmay Tiwari, Ayush Madurwar

Abstract-In a world where cyclone frequency and intensity pose major risks to people living along the shore, there has never been a more urgent need for accurate and early forecast. The paper “Cyclone Intensity Prediction,” aims to advance forecasting techniques by developing and implementing a novel approach. This research, which embraces cutting-edge technologies, uses advanced modelling approaches, machine learning algorithms, and meteorological data analytics to establish a solid foundation for predicting cyclone intensity with previously unheard-of accuracy. The combination of these elements enables a thorough comprehension of the intricate dynamics affecting the development and evolution of cyclones. The research attempts to find patterns and connections in historical cyclone data that were previously missed by performing in-depth data analysis and feature engineering. Modern deep learning algorithms make it possible to extract insightful information that helps build a predictive model that can predict cyclone intensity more accurately and with more advance warning. Furthermore, the paper focuses on real-time data integration to guarantee that the prediction model adapts dynamically to changing meteorological conditions. The integration of satellite imaging, oceanic data, and atmospheric factors increases forecast abilities, resulting in a more complete and nuanced knowledge of cyclone dynamics. This study not only advances the scientific community’s understanding of cyclone dynamics, but it also has far-reaching societal ramifications. Improved cyclone intensity forecasts can empower disaster response organizations, governments, and vulnerable communities by allowing them to take proactive measures to reduce potential damage and save lives.

DOI: 10.61137/ijsret.vol.10.issue2.155

Published by: Kajal Tripathi

Smart Hire – An Intelligent Hiring Platform
Authors:-Nikhil Kumar Thakur, Aakriti Chowdhary, Ujjwal Bhattarai, Professor Geetha Rani K, Dr. Shivakumar C

Abstract-In the rapidly evolving landscape of human resources and talent acquisition, traditional methods of hiring are proving increasingly inadequate in meeting the demands of modern organizations and job seekers. The inefficiencies inherent in manual resume screening, subjective evaluations, and disjointed recruitment processes contribute to extended timelines, suboptimal candidate selections, and diminished candidate experiences. Recognizing these challenges, this research endeavors to introduce a paradigm shift in recruitment practices by harnessing the power of micro-service architecture. Through the development of a sophisticated web application, this study aims to revolutionize the hiring process by integrating cutting- edge technologies such as Natural Language Processing (NLP) for resume screening, examination management, and interview scheduling. By adopting a modular micro- service architecture, the system promises to streamline recruitment workflows, enhance decision-making accuracy, and elevate the overall candidate experience. The primary objective of this research is to create a comprehensive solution that not only addresses the immediate pain points of recruiters and job seekers but also lays the foundation for a more agile and responsive recruitment ecosystem. By automating repetitive tasks, minimizing bias in candidate evaluation, and facilitating transparent communication between stakeholders, the proposed system seeks to transform recruitment into a strategic advantage for organizations. Furthermore, this research explores the potential benefits of the micro- service based approach, including improved efficiency, enhanced accuracy, better candidate experiences, and greater scalability. Through meticulous design and rigorous testing, the system aims to deliver tangible outcomes that align with the evolving needs of the talent market and contribute to organizational success in an increasingly competitive landscape.

DOI: 10.61137/ijsret.vol.10.issue2.154

Published by: Kajal Tripathi

Solar Based Green Hydrogen Production with Header and Riser Tube Arrangements
Authors:-Mr. E.Sivaprakash., Mohammed Imthiyas.A, MukesVarma.K, Kesavan. N

Abstract- The growing demand for sustainable energy solutions has spurred research into solar-based green hydrogen production systems. This study proposes an innovative approach integrating solar photovoltaic (PV) panels with paraffin wax-enhanced copper tubes to facilitate efficient hydrogen generation through electrolysis. The system design incorporates header and riser tube arrangements to optimize water flow and heat transfer. Paraffin wax, when spattered on the surface of the copper tubes, acts as a phase change material, enhancing heat absorption and retention. The hot water generated by the solar- heated copper tubes is directed to an electrolyzer where hydrogen and oxygen are separated. To ensure accurate measurement of hydrogen output, specific equipment tailored for hydrogen quantification is employed. This comprehensive system not only harnesses renewable solar energy but also capitalizes on the thermal properties of paraffin wax to achieve higher energy efficiency and greener hydrogen production. The findings of this study contribute to the advancement of sustainable energy technologies, paving the way for a cleaner and more sustainable future.

DOI: 10.61137/ijsret.vol.9.issue4.343

Published by: Kajal Tripathi

Deep Learning Approaches in Genomic Analysis: A Review of DNA Sequence Classification Techniques
Authors:- Vishakha Nerkar, Dr. Vinod Kimbahune

Abstract-In bioinformatics, DNA sequence classification poses many challenges due to its inherent complexity and volatility. In this paper, the difficulties in applying deep learning techniques to DNA sequence classification are examined. Variable sequence lengths, complex data representation, and the requirement for efficient feature extraction are all highlighted by the analysis. Moreover, when developing a model, factors like uneven data distributions, interpretability issues, and the possibility of overfitting must be carefully considered. Deep learning in genomic analysis has tremendous potential, but there are still many unanswered questions. Using transfer learning and genomics domain expertise can help overcome some of these obstacles. Despite these challenges, applying deep learning methods could greatly improve our comprehension of genetic data and how it relates to health and illness. Researchers can move the field toward transformative work by taking on these obstacles. Discoveries in genomic medicine and beyond.

DOI: 10.61137/ijsret.vol.10.issue2.153

Published by: vikaspatanker

Breast Cancer Detection Using Texture Analysis and Convolutional Neural Network
Authors:- Ashutosh Gupta, Surbhi Goria, Pallavi Awasare

Abstract-Breast cancer is a big problem for women all over the world and it can make them very sick. Researchers have worked hard to improve how we diagnose and detect this disease accurately. It remains one of the most life-threatening illnesses, affecting about one in eight women. The unclear causes make it challenging to manage, and prevention is difficult. So, early detection becomes crucial. This paper wants to explain a clear way to find breast cancer early by using computer tools to analyze images. It will explain the steps involved, such as image enhancement, segmentation, and feature extraction, utilizing a Convolutional Neural Network (CNN).

DOI: 10.61137/ijsret.vol.10.issue2.152

Published by: vikaspatanker

Age and Gender Prediction from Facial Images Using Deep Learning Approach
Authors:-Associate Professor Dr. A. Selva Reegan, Adan C Benedict, Jeevithan S, Hari B L, Raghul Babu J

Abstract- significant attention due to its wide range of applications in various facial investigations. This research paper presents a comprehensive approach utilizing convolutional neural networks (CNN) and deep learning methodologies to develop a gender and age detection system. The paper explores the underlying algorithms and techniques employed in CNN models for gender classification and age estimation, highlighting their synergy and integration. The primary objective of this study is to leverage deep learning techniques to create an accurate gende and age detector capable of providing approximate predictions for human faces in images. Additionally, the paper discusses the significance of this technology and its potential impact on improving everyday lives. Further- more, the research paper emphasizes the diverse range of applications where such technology can be effectively utilized. These applications span across various domains, including intelligence agencies, CCTV cameras, policing, and matrimony websites. The potential benefits and implications of implementing gender and age detection systems in these areas are explored. Overall, this research paper provides insights into the development of a gender and age detection system using deep learning and highlights its potential applications in different sectors, showcasing the value and impact it can have on society .]Automatic age and gender prediction from facial images has gained significant attention due to its wide range of applications in various facial investigations. This research paper presents a comprehensive approach utilizing convolutional neural networks (CNN) and deep learning methodologies to develop a gender and age detection system. The paper explores the underlying algorithms and techniques employed in CNN models for gender classification and age estimation, highlighting their synergy and integration. The primary objective of this study is to leverage deep learning techniques to create an accurate gender and age detector capable of providing approximate predictions for human faces in images. Additionally, the paper discusses the significance of this technology and its potential impact on improving everyday lives. Further- more, the research paper emphasizes the diverse range of applications where such technology can be effectively utilized. These applications span across various domains, including intelligence agencies, CCTV cameras, policing, and matrimony websites. The potential benefits and implications of implementing gender and age detection systems in these areas are explored. Overall, this research paper provides insights into the development of a gender and age detection system using deep learning and highlights its potential applications in different sectors, showcasing the value and impact it can have on society .

DOI: 10.61137/ijsret.vol.10.issue2.312

Published by: Kajal Tripathi

A Blockchain-based Approach for Drug Traceability in Healthcare Supply Chain
Authors:-Assistant Professor Mrs.J.Sunanthini, Ashina.R, Priskila.B, Pushpa Lincy.J, Sanju.P

Abstract- Counterfeit drugs are an immense threat for the pharmaceutical industry worldwide due to limitations of supply chain. Our proposed solution can overcome many challenges as it will trace and track the drugs while in transit, give transparency along with robust security and will ensure legitimacy across the supply chain. It provides a reliable certification process as well. Fabric architecture is permissioned and private. Hyperledger is a preferred framework over Ethereum because it makes use of features like modular design, high efficiency, quality code and open-source which makes it more suitable for B2B applications with no requirement of cryptocurrency in Hyperledger Fabric. QR generation and scanning are provided as a functionality in the application instead of bar code for its easy accessibility to make it more secure and reliable. The objective of our solution is to provide substantial solutions to the supply chain stakeholders in record maintenance, drug transit monitoring and vendor side verification.

DOI: 10.61137/ijsret.vol.10.issue2.311

Published by: Kajal Tripathi

Stabilization of Black Soil Using Lime and Jute Fibre
Authors:-P.Prabhu, S.Kamaleshwaran, B.Yogeshvaran, R.Ajith

Abstract- Black cotton soil is a type of expansive soil that exhibits high swelling and shrinking behavior due to changes in moisture content, causing damages to structures built on it. This study aims to improve the engineering properties of black cotton soil by stabilizing it with lime and jute fibre, which are natural and eco-friendly materials. The soil samples were prepared with different proportions of lime (10%, 20%, and 30%) and jute fibre (10%, 20%, and 30%) and tested for shrinkage limit, unconfined compressive strength, and California bearing ratio. The results showed that the addition of lime and jute fibre reduced the shrinkage limit, increased the unconfined compressive strength and the California bearing ratio of the soil, indicating an improvement in the soil stability and bearing capacity. Soil is a base of structure, which actually supports the structure from beneath and distributes the load effectively. If the stability of the soil is not adequate then failure of structure occurs in form of settlement, cracks etc. Expansive soil also known as black cotton soil is more responsible for such situations and this is due to presence of montmorillonite mineral in it, which has ability to undergo large swelling and shrinkage. To overcome this, properties of soil must be improved by artificial means. Soil reinforcement technique is one of the most popular techniques used for improvement of poor soils. Metal strips, synthetic geotextiles, geogrid sheets, natural geotextiles, randomly distributed, synthetic and natural fibres are being used as reinforcing materials to soil. The study concluded that lime and jute fibre can be effectively used as soil stabilizers for black cotton soil.

DOI: 10.61137/ijsret.vol.10.issue2.306

Published by: Kajal Tripathi

Scholars and other academic research individuals seek free research paper publication sites to publish their research paper and articles they have written so that other researchers or knowledge seekers around the world can be aware of the research findings and outcomes. Writing a research paper in itself is a tough job. Research in any area requires lots of effort and hardwork. Doing so first of all researchers advises to seek previously published research papers in their research domain. It helps them in developing better understanding of the research area along with requirements for future development.

Submit Your Paper  / Check Publication Charges

It is known to everyone that nothing is free in this world. Although some journals provide free publication which helps authors to highlight their research work among audiences sharing similar interests. But the approach used by them to share research work is not upto the mark. This blog will help scholars in finding the free research paper publication sites.

How to find free research paper publication sites

The internet world is full of numerous websites that show free research paper publication sites on their platform. Most of the sites lack genuine information and others run paid subscriptions to show the authentic and valid information. Due to the given condition how a student or scholar new to their respective fields would get their hands on trending and innovative research publications or get to know the platforms that assist them in getting their work present to the world of researchers.

No reviewer support – Many free publication sites do not have reviewers in all the domains. Sometimes authors have to suggest reviewers

Less chances of article indexing- Article indexing helps authors in reaching towards the targeted audiences fast as compared to other sources. Free publishing journals usually won’t work for indexing of their journals on different platforms. So there will be less chances of article indexing.

Limited reach – most of the journal with free publication has limited reach so publishing in this kind of journal has no benefit. It would be wise to check the presence of the journal at different portals so that articles can be reached to the targeted audiences.

Published by: Neeraj Mishra

Design and Performance Analysis of Electrochemical Micro Machining on GI Sheet
Authors:-M. Maniyarasan, A. Premkumar, S. Vigneshwaran, S. Surya

Abstract-Galvanized iron is manufactured and used for wide variety of purposes but its primary use is for sheet metal roofing and other building materials, such as metal framing studs, metal roof shingles and fencing. It may be used in future as micro level applications on the field of science and Nano technology. The current techniques for micro manufacturing mostly are silicon based. These manufacturing techniques are not suitable for use in demanding applications like aerospace and biomedical industries. Electrochemical micromachining (ECMM) can machine hard metals and alloys at micrometer scale. So, we developed a cost efficient electrochemical micromachining with feed control setup and conduct a performance analysis of electrochemical micromachining on GI sheet to find out the efficient parameters value required for GI sheet to perform a micro hole in electrochemical micromachining.

DOI: 10.61137/ijsret.vol.10.issue2.299

Published by: Kajal Tripathi