Category Archives: Uncategorized

Authors: Sharath Chandra Kodtihyala, Riddhi kinnera, Shashikiran Sangisetti, Praveem Kumar, Prasanthrao A

Abstract: This study presents Polyglot, a deep learning-based language translation system that utilizes Transformer, LSTM, Attention, and Seq2Seq models to enhance context-aware translation. While well-known systems like Google Translate provide reliable translations, Polyglot offers improved contextual understanding through a hybrid approach that balances accuracy and efficiency. The study evaluates Polyglot’s performance using BLEU scores and user satisfaction, demonstrating its effectiveness. It includes a detailed discussion on the dataset, model architecture, training process, and evaluation criteria. The results indicate a significant improvement in translation quality compared to baseline models. Future work will focus on real-time improvements and customization to further enhance translation accuracy and user experience

DOI: https://doi.org/10.5281/zenodo.16418885

Published by: vikaspatanker

Authors: Deepti Ram Gangurde, Arun Mishra, Shantanu Singh

Abstract: This research proposes a decentralized courier tracking system using blockchain technol- ogy and smart contracts, aimed at enhancing transparency, trust, and security in logistics. The solution is implemented on the Volta blockchain and integrates MetaMask[3] to facilitate se- cure interactions between participants without relying on centralized intermediaries. The sys- tem automates shipment updates, maintains immutable tracking records, and protects sensitive data through cryptographic mechanisms. The implementation demonstrates improved trace- ability, operational efficiency, and stakeholder accountability. Performance evaluation indi- cates significant enhancements in security, cost-effectiveness, and scalability when compared to conventional courier tracking methods. The proposed system offers a robust alternative for modern supply chain management[6].

DOI: https://doi.org/10.5281/zenodo.16418691

Published by: vikaspatanker

Authors: Yassine Dahbi, Hamza Naciri, Hamza Zaouri, Ouahib Alaoui

 

Abstract: This study examines the use of GradientBoostingRegressor, StackingRegressor, and Gradient Boosting Regression with HistGradientBoosting in developing models that predict the compressive strength (fcu) and splitting tensile strength (fsp) of steel fiber-reinforced recycled aggregate concrete (SFR-RAC). The information comprises 465 compressive strength and 339 splitting tensile strength data of concrete mixes with varied ratios. Training and model testing were performed using 80/20 split with PSO for the hyperparameter optimization. The performance of the model was measured with four statistical metrics: coefficient of determination (R²), mean absolute error (MAE), root mean squared error (RMSE), and mean absolute percentage error (MAPE). Out of the models, Gradient Boosting Regression with HistGradientBoosting performed better in terms of prediction, with StackingRegressor taking the second rank. SHapley Additive exPlanations (SHAP) and feature importance were employed to determine the influence of input parameters on model predictions. From the results obtained, it was evident that the water content, cement content, and fiber ratio influence considerably the strength of SFR-RAC. The models give good insights regarding SFR-RAC mixture behavior, which is helpful in the production of environmentally friendly concrete with greater enhanced strength. Future research can enhance the data and use other predictor variables to further support these models.

DOI: https://doi.org/10.5281/zenodo.16420152

 

Published by: vikaspatanker

Authors: Saba Zaidi, Thakur Nikhil, Tripti Goyal, Veersavarkar

Abstract: To meet the need of productivity concerns, project timelines, and changing needs, this research explores the interesting realm of web service development. The overall purpose of this research is to develop an easy-to-use and effective development system based on the Django framework. This provides programmers with the facility to simply develop web services that are efficient, effective, and reliable. Utilizing the Model-View-Template (MVT) design pattern is important, as it is compatible with list management systems. The overall effectiveness and efficiency of the system are improved by web page creation being automated using HTML, CSS, and Python modules; protocols for data sharing are standardized, system users are decentralized, and user login and registration processes are accelerated are all prioritized at their best. My SQL maintains the data base efficiently, and Django manages the smooth data interaction to provide an integrated and efficient user experience. Another central area of focus in this research is the development of a web application that provides secure, real-time user interactions while encrypting data to preserve its confidentiality and integrity. Django REST framework is employed to create a stable service that integrates with the front-end seamlessly through REST APIs. This allows HTML/CSS and JavaScript to drive a dynamic and interactive user interface. The research points out the key features of Django, including its administrative capabilities, Object-Relational Mapping (ORM), comprehensive documentation, secure and rapid development features, and REST API support. A deeper understanding of this dynamic subject attempts to shed light on the development, importance, challenges, and modern solutions in web technology and web service development. Following our research, the goal is to use Django to develop are liable, effective, and secure online application. Our goal is to use all of its characteristics to streamline the development process. Django's solid frame work promises the assurance of scalability and reliability .Our aim is to utilize its benefits for an extensive, modern, and efficient web service creation, ensuring a successful outcome meeting the increasing demands for efficient web services. In today’s digital world, websites and web applications play a very important role in how we communicate, do business, and share information. To build these websites, developers use tools called web frameworks. One of the most popular frameworks is Django, which is written in the Python programming language. This research paper explains how Django helps developers create websites faster and more efficiently. Django follows a structure called MVC (Model-View-Controller), or in Django’s case, MTV (Model-Template-View). This helps keep the code organized and easy to manage. Django also comes with many built-in features like user authentication, database management, security, and admin interface, which save time and effort for developers. The paper highlights Django’s advantages like its security features, scalability, and reusability of code. It also compares Django with other popular frameworks to show where Django performs better and where it might not be the best choice. In short, Django is a powerful tool that allows both beginners and professional developers to build high-quality web applications quickly and securely. This research explores Django’s role in modern web development and why it is a preferred choice for many developers and companies .The research by Idris et al. emphasizes Django's comprehensive nature, highlighting its suitability for developers seeking a full-featured framework that handles various aspects of web development out-of-the-box. This contrasts with frameworks like Flask, which offer more flexibility but require additional setup for features that Django provides by default. Moreover, Django's emphasis on security is notable. It includes protections against common web vulnerabilities like cross-site scripting (XSS), cross-site request forgery (CSRF), and SQL injection, ensuring that applications built with Django are robust and secure.

DOI: https://doi.org/10.5281/zenodo.16418373

Published by: vikaspatanker

Authors: Himanshu Shahoo, GautamYadav, ChinmayeeTripathy, Padmaja Panda

Abstract: Flower identification is a crucial aspect of plant classification and ecological research, playing a significant role in understanding biodiversity and ecosystem dynamics. This research paper presents a new approach to flower identification using advanced deep learning techniques. The proposed system used folding networks (CNNs) to automatically extract hierarchical features from high-resolution images of flowers, allowing for more accurate and efficient classification. The procedure is implemented as a multi-stage process, beginning with data preprocessing to enhance image quality and remove noise. Using another data record, educated CNN models such as modified reset 50, VGG16, or Google are then fine-tuned with commented flower images. Furthermore, transfer learning is used to properly use knowledge from large data records and improve the ability of models to generalize different types of flowers.. In the end, our approach achieved an accuracy of 82.04% using VGG16, the highest compared to other algorithms.

DOI: http://doi.org/10.5281/zenodo.16610684

Published by: vikaspatanker

Authors: Yajat Singh, Ms. Gurpreet Kaur, Barun Singh Bisht, Pushpam Kumar

Abstract: Underwater Sensor Networks USNs play a critical role in environmental monitoring marine exploration and defense applications. However traditional cloudbased data processing introduces significant latency and energy consumption making realtime decisionmaking challenging in extreme underwater environments. This paper proposes a novel edge computing architecture tailored for USNs enabling localized realtime data processing and anomaly detection. The architecture integrates a CNNLSTM deep learning model optimized for lowpower edge devices significantly reducing the need for cloudbased processing. Our experimental evaluation demonstrates a 39 reduction in latency and a 36 improvement in energy efficiency compared to cloudbased solutions. Additionally we present performance benchmarks showing a higher packet delivery ratio and improved data throughput. The proposed approach enhances the autonomy and efficiency of underwater sensor networks making it a viable solution for realtime applications in extreme environments.

DOI: https://doi.org/10.5281/zenodo.16610646

 

Published by: vikaspatanker

Authors: Dr Vinit Kumar Sharma,, Anjali Goyal, 3Kushagra Sharma, Kushagra Sharma

Abstract: In this paper, we have discussed application of various methods ([9],[10]) for solving the problem of a game as Dominance method, Graphical method, Algebraic method, Simplex method etc. Each method has its limitations and benefits, which depends upon the nature of problem. Students may learn about the uses of various methods by study this paper.

Published by: vikaspatanker

Authors: Er. Rajdeep Saharawat,, Muskan,, Dr. Vinit Kumar Sharma,, Ms. Meenal Maan

Abstract: Proteins must fold into specific three-dimensional structures to function correctly. Errors in protein folding—misfolding—can lead to aggregation and are associated with several degenerative diseases, including Alzheimer’s, Parkinson’s, and Huntington’s. This review explores the molecular mechanisms of protein folding and misfolding, the cellular quality control systems managing these processes, and the pathogenesis of misfolding-related disorders. We also discuss therapeutic approaches aimed at correcting misfolding or enhancing proteostasis

Published by: vikaspatanker

Authors: Usha Dhankar, Nikeeta, Sompriya N Tiwary, Suhani Singh, Pooja Sharma, AS Susanna Grace

Abstract: Solar photovoltaic (PV) panels were a broadly implemented renewable energy source but their efficiency was substantially influenced by dust accumulation which hindered sunlight absorption and reduced power output Regular cleaning and monitoring were essential to sustain their performance Traditional cleaning mechanisms such as manual or semiautomatic cleaning were often inefficient labor-intensive and costly which demanded the development of automated solutions This research introduced an IoTbased cleaning and monitoring system designed to enhance the efficiency of solar PV panels The system combined realtime data acquisition through IoT sensors to detect dust accumulation and environmental conditions activating an automated cleaning mechanism when necessary Additionally machine learning algorithms analyzed historical data to optimize cleaning schedules maintaining minimal energy loss and improved reliability A review of prevalent dust removal techniques such as passive coatings electrostatic cleaning and robotic solutions revealed that many methods were either highmaintenance or not costeffective for largescale deployment IoTbased solutions when integrated with predictive analytics provided a potential substitute by enabling realtime monitoring and analytical decisionmaking for panel maintenance The outlined methodology enhanced energy output while reducing operational costs and minimizing manual intervention making solar energy systems more efficient and sustainable This innovation contributed to the prolonged effectiveness of solar power by addressing one of its key operational challenges thereby fostering a cleaner and more reliable renewable energy future.

DOI: https://doi.org/10.5281/zenodo.16410228

 

Published by: vikaspatanker

Authors: Kushagra Sharma, Dr Vinit Kumar Sharma, Anjali Goyal

Abstract: In this paper, we have discussed application of various methods ([9],[10]) for solving the problem of a game as Dominance method, Graphical method, Algebraic method, Simplex method etc. Each method has its limitations and benefits, which depends upon the nature of problem. Students may learn about the uses of various methods by study this paper.

Published by: vikaspatanker