Category Archives: Uncategorized

Authors: Ujwal Bhalgat, Swaraj Wetal, Ayush Shah, Prof. Pramod Jagdale

Abstract: This paper presents a comprehensive review of quantum communication using photons, based primarily on the foundational work of Krenn, Malik, Scheidl, Ursin, and Zeilinger. The review covers core quantum mechanical principles such as qubits, superposition, entanglement, and the no-cloning theorem, and explains how these principles underpin secure quantum communication. Key protocols including Quantum Key Distribution (QKD) and quantum teleportation are discussed. The paper further explores long-distance ground-based and space-based experiments, and examines the emerging role of high-dimensional quantum states using Orbital Angular Momentum (OAM) of photons. The aim is to provide a structured understanding of the current state and future potential of quantum communication technologies.

DOI: https://doi.org/10.5281/zenodo.19129375

Published by: vikaspatanker

Authors: Jagadeswara reddy, D. Karishma, G. Teja Sree, G. Harsha Vardhan, K. Abdul Rehaman

Abstract: This paper aims to establish a driven g style recognition m eth od that is highly accurate, fast and generalizable, considering the la ck o f d a ta types in driven style classification task a n d the lo w recognition accuracy of widely u sed u n supervised clustering algorithms and single convolutional neural network methods. First, we propose a method to collect the inform a t ion on drive r's operation time sequence in view of the imperfect driving data, a n d then extract the drive r's style features through convolutional n e u ra l network. Then, for the collected temporal data, the Lo n g S h ort T e rm Memory networks (L ST M) m od u le is added to encode and transform the driven features, to a chive the driven style classification. T h e results show that accuracy of driving style recognition reaches over 9 3 %, while the speed is improv ed significantly.

DOI: https://doi.org/10.5281/zenodo.19127173

Published by: vikaspatanker

Mr. Talari Manohar
Affiliation	Assistant Professor,  Anantha Lakshmi Institute of Technology & Sciences, Ananthapuramu
Email-Id:	talarimanohar1207@gmail.com
Educational Qualifications: M.Tech (Electrical Power Systems), S.K.D. Engineering college, Gooty, JNTUA, Ananthapuramu (2016), 74% B.Tech (Electrical and Electronics Engineering), Anantha Lakshmi Institute of Technology and Sciences, Ananthapuramu JNTUA, Ananthapuramu, (2012 ) 66.54 %

Published by: vikaspatanker

Authors: Thirumala Sri Venkata Charan, Arudra Sri Sai Vignesh, Dr. K. Sudha

Abstract: Freight transportation systems contribute significantly to operational inefficiencies and greenhouse gas emissions due to suboptimal routing and poor truck capacity utilization. Traditional logistics planning approaches primarily focus on minimizing distance without incorporating dynamic traffic conditions, fuel efficiency, and environmental constraints. This paper proposes LOADMIND, an Artificial Intelligence (AI)-driven platform designed to enhance truck utilization and reduce emissions through intelligent multi-objective route optimization. The system integrates real-time traffic prediction using machine learning models with a Genetic Algorithm-based optimization engine to determine fuel-efficient and emission-aware routes. A mathematical formulation incorporating distance, fuel consumption, and emission parameters is developed. Experimental evaluation using simulated logistics datasets demonstrates improvements of 18% in truck utilization, 15% reduction in fuel consumption, and 17% reduction in CO₂ emissions compared to conventional shortest-path routing. The results validate the effectiveness of AI-driven optimization for sustainable freight transportation.

DOI: https://doi.org/10.5281/zenodo.19125446

 

Published by: vikaspatanker

Publishing in journal without publication fee seems easy but it creates a big task to find a true journal which publishes paper for free in real. Scholars, PhD students, research professionals often seek to get these kinds of journals. So to make their searching easy to find, we will here mention that what are journals without publication fees and how they help you to publish for free.

Submit Your Paper  / Check Publication Charges

What is Journals without Publication Fees?

The journals which facilitate to publish your research papers, articles or paper works without taking any cost or in free. These journals are generally funded by research organizations, college and universities or government institutes which promote scholars to prepare research works and gain opportunities.

How These Journals Help You to Publish Paper for Free?

When you are writing a research paper, be conscious about journal paper’s standards of writing and publication, which helps you to prepare the best paper and increase chances of acceptance. For example you are researching in the field of science, technology or engineering, you can visit some journals which provide free access of reading pre-published articles for its relevant readers. This will help you to find more aspects and knowledge of the disciplined subject area. Write an honest paper which is not copied, result solves the issue and presents all the pros and cons of the topic, with a simple and easy to understand language.

 

However, paper publishing without publication fees is not always true, so check official website and assure that there is no any hidden or extra charge.

A free of cost publication is always depends on your paper quality. So write well, check the journals having these following traits and submit the paper:

• Guidelines for submission of paper and fee (when charge), maintaining transparency
• Peer review or double blind review process by subject experts
• High impact factor number and more citations
• Authorized, widely known and recognized
• Free reading access of already published articles
• Provide International Standard Serial Number and Digital Object Identifier (based on journal’s policy and depending on paper quality
• Fast publication capacity and copyright form to fill and submit  
• Digital certificate of publication and a proper chat system to clear points

Looking for these qualities submit manuscript with filling all the asked mandatory details. These journals which help scholars to publish for free prove to be very valuable for those who cannot pay a high publication charge. They help to provide them credibility focusing on paper quality, fee should not become the restriction on knowledge sharing.

 

 

Published by: Neeraj Mishra

Authors: Shikha Gupta

Abstract: Adolescence is a crucial stage of human development characterized by rapid physical, emotional, cognitive, and social changes. In the contemporary world, adolescents face numerous challenges such as academic stress, peer pressure, emotional instability, and uncertainty about the future. These challenges often hinder their overall development and well-being. Therefore, the development of essential competencies has become increasingly important. Essential competencies include self-awareness, emotional regulation, critical thinking, problem-solving, communication skills, and interpersonal abilities. The present study aims to examine the role of these competencies in promoting adolescent well-being, personal growth, and holistic development. The study is based on a descriptive and analytical review of existing literature. The findings highlight that competency-based education significantly contributes to emotional stability, academic achievement, and social adjustment. The paper concludes that integrating essential competencies into the educational system is necessary to prepare adolescents for a balanced and successful life.

DOI: https://doi.org/10.5281/zenodo.19110935

Published by: vikaspatanker

Authors: Venkata Nagamani Reddi, Charitha Pasumarthi, Mounika Mudavath, SriLaxmi Thurupu, Keerthana Vadagam

Abstract: The emergence of AI-generated voices has posed significant problems with the authenticity of media and their digital safety. False audio detection or fake audio has been critical in such areas as audio forensics and voice authentication. In this paper, a literature review of deep fake audio detection with deep learning is conducted. The system used currently works with Mel-frequency Cepstral Coefficients (MFCCs) as the input feature and a VGG16based Convolutional Neural Network (CNN) as transfer learning to classify the real and fake voices. VGG16 is an effective model that can capture spectral variations but it is not able to learn temporal dependencies. To overcome this hybrid CNN-LSTM models have been investigated, which combine both spatial and time based feature learning to make them more accurate and robust.

DOI: https://doi.org/10.5281/zenodo.19109733

Published by: vikaspatanker

Authors: Jitendra Kumar, Vinit Kumar Sharma

Abstract: Operations research is a general method used in the study and optimization of a system through modeling of the system. In the field of education, especially in education management, operations research has not been widely used. This paper gives idea about how operations research can be used for optimization the reliability/creditability of an academic institution.Reliability in academic institutions refers to the ability of the system to consistently deliver quality education, administrative efficiency, and infrastructure availability. Many educational institutions face operational challenges such as inefficient scheduling, resource underutilization, long service queues, and infrastructure failures. This study proposes the application of OR techniques including Linear Programming, Queuing Theory, Simulation, and Reliability Modeling to improve the operational efficiency of academic institutions. A dataset representing faculty utilization, service waiting time, and infrastructure reliability is analyzed. Results indicate that OR-based optimization can increase faculty utilization by 18%, reduce administrative waiting time by 40%, and improve system reliability significantly. The research demonstrates that systematic application of OR techniques can enhance institutional performance and ensure consistent educational service delivery.

 

 

Published by: vikaspatanker

Authors: Kemudeme Sunday Effiong, Hachimenum Nyebuchi Amadi, Biobele A. Wokoma, Richeal Chinaeche Ijeoma

Abstract: This study examines the overhead transmission line ampacity prediction performance of a supervised multiple linear regression machine learning algorithm integrated with the IEEE-738 heat balance equation, using ten years of historical data from the Nigerian Meteorological Agency (NiMet) and operational data from the Transmission Company of Nigeria (TCN) Afam network using a Python environment. Key meteorological factors included ambient temperature, wind velocity, solar radiation, and air pressure, while conductor properties such as emissivity and age were also considered. The aim was to evaluate the performance of supervised multiple regression algorithm to predict the dynamic amapcity of overhead transmission lines. This was achieved by first deriving the amapcity under different weather and line conditions, then deploying the algorithm for real-time dynamic line rating (DLR) prediction to determine its accuracy and speed based on the performance metrics. The IEEE-738 heat balance amapcity derivation results showed that the 450A-rated conductors had ampacitiy between 309A and 1406A (62% to 312% of the rated value) while the 630A-rated lines ranged from 380A to 1897A (60% to 301%), implying that depending on the weather conditions and other parameters, overhead transmission lines dynamic amapcity can increase up to 212% and decrease up to about 40% of the rated values of the lines’ conductors. On the other hand, the prediction results of the Multiple Regression Machine Learning Algorithm showed a coefficient of determination 0.8912, a Standard Deviation of 0.0021, Root Mean Squared Error (RMSE) of 56.03, Mean Square Error (MSE) of 3139.32, and Mean Absolute Error (MAE) of 39.64 within a computing time of 0.9 second. While the prediction speed is very good, it is recommended that other supervised machine learning algorithms should be deployed with the same data to compare their prediction accuracy.

DOI: https://doi.org/10.5281/zenodo.19109133

 

Published by: vikaspatanker

Authors: S. Vimala, Dr. M. Senthilkumar, Abishek Winston I, Santhosh Kumar T, Sivakumar P

Abstract: An AI-based Online E-Voting System is developed to provide a secure, transparent, and reliable digital voting mechanism by integrating face recognition techniques with Java and SQL-based processing. The system authenticates voters by capturing live facial images and comparing them with registered facial data using machine learning and computer vision methods to prevent impersonation and duplicate voting. It validates voter eligibility, enforces one-time voting through database constraints, and securely records votes to ensure data integrity and accuracy. Users interact with the system through a user-friendly interface where voter registration, authentication, and vote casting are performed seamlessly. The backend application processes voting requests, manages election data, and automates vote counting and result generation. By leveraging AI-driven facial authentication instead of traditional credential-based verification, the system enhances election security and minimizes manual intervention. The proposed framework improves the efficiency, trustworthiness, and scalability of online voting systems and supports fair and reliable elections in institutional and organizational environments.

DOI: https://doi.org/10.5281/zenodo.19107029

 

Published by: vikaspatanker