Authors: Janaki Ramarao Kasa, Dr. Chitra Gupta

Abstract: Due to their straightforwardness in synthesis, controllable electronic properties, high coordination abilities, and extensive biological importance, Schiff base derivatives concentrate greater importance and expertise in the research of organic and medicinal chemistry. The present study article surveys literature up to January 2016 so as to examine the impact of trends in functionalization on the chemical behaviour and medical uses of Schiff base antecedents. The research design used in the study is structured secondary research with the 60 peer-reviewed references published up to the beginning of the year 2016. The coding of these articles was by year of publication, structural classification, functional group modification, the ability to form metal-complex, biological use, and profile of activity reported. This was to identify the dominant research themes, gauge the major research treatment and interpretive uses, and to determine whether structural functionalization and metal coordination accepted superior performance. It has been disclosed that since 2010 and 2015, there was an increase in the number of studies published on Schiff bases, along with the most widespread types of use in the field were antimicrobial, anticancer, antioxidant, enzyme inhibitory, and chemosensing purposes. Schiff bases based on heteroaryl, quinoline, quinazoline, isatin, triazole and coumarin were particularly noticeable. Metal-complexed Schiff bases were found to be more commonly linked with DNA interaction, cytotoxicity and redox-based activity whereas metal free versions were more common in antimicrobial and enzyme-inhibition studies. Electron-withdrawing groups, incorporation of heterocyclic rings and the use of donor atoms like nitrogen and oxygen were always used to enhance reactivity and biological potential. The paper concludes that functionalized Schiff base derivatives were widely used as molecular platforms with twist before 2016 in selecting synthetic organic chemistry and coordination chemistry and medicinal chemistry, and the development of multifunctional therapeutics, molecular probes and catalytic systems used after 2016 builds off their earlier development.

Published by: vikaspatanker

Authors: Dr. R. Indra, Ms . Akshaya

Abstract: With the rapid advancement of digital technology, mobile banking has become an important tool for financial inclusion, especially in rural areas. This study focuses on analysing the buying behaviour of rural people towards mobile banking services. It examines the level of awareness, usage patterns, factors influencing adoption, and challenges faced by rural consumers. The study highlights that convenience, time-saving, and ease of use are the major factors encouraging adoption, while issues such as poor network connectivity, lack of digital literacy, and security concerns act as barriers. The findings reveal that most rural users have a positive attitude towards mobile banking, but there is still a need for awareness and improvement in infrastructure. The study concludes that mobile banking has strong potential to enhance financial inclusion in rural areas.

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Published by: vikaspatanker

Authors: Bhakti Pokale

Abstract: Phishing attacks have become one of the most serious cybersecurity threats worldwide, causing identity theft, financial loss, and data breaches. Attackers use fake websites, emails, and malicious links to trick users into revealing sensitive information. Traditional security mechanisms such as antivirus software and browser filters are often unable to detect newly generated phishing URLs, making users vulnerable to attacks. To address this issue, this project proposes a Real-Time Automatic Phishing Detection System that identifies and blocks phishing links instantly. The system uses Machine Learning techniques, specifically the Random Forest Classifier, to analyze URL features such as length, domain age, and special characters. It operates silently in the background without requiring user intervention, ensuring continuous and seamless protection. The system is developed using Python, Java, JavaScript, Node.js, MongoDB, HTML, and CSS to support multi-platform functionality. It provides real-time alerts and maintains logs of detected threats for further analysis. The proposed solution aims to enhance cybersecurity by offering proactive protection and ensuring a safer digital environment for individuals and organizations.

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Published by: vikaspatanker

Authors: Jyothsna M, Srinika Kontham, Sharanya Balachandran, Meghana Danta, Sindhu Naine

Abstract: The SignVoice system is based on artificial intel- ligence technology that offers a bidirectional communication system for deaf, mute, and visually impaired persons to com- municate smoothly with normal persons. The SignVoice system is based on machine learning, deep learning, and computer vision technologies to offer different types of communication such as sign language, speech, text, and image-based communication. The hand gestures are recorded through the webcam and processed through MediaPipe to identify the landmark and classify the image through machine learning to produce text output. The input is converted into text through Whisper for speech input, and the text output is generated through an artificial intelligence- based chatbot and then converted into audio through text- to-speech technology. The SignVoice system is based on the hybrid approach to process the gestures through client-side processing and computationally intensive operations such as speech recognition through cloud-based services. In addition to this, the chatbot can perform image input, text output, and speech output that can be helpful for visually impaired persons. The proposed SignVoice system can communicate efficiently and accurately for impaired persons through gesture, speech, and intelligent text-based responses.

DOI: https://doi.org/10.5281/zenodo.19326545

 

Published by: vikaspatanker

Authors: P.Sreesudha, CV.Kiranmaiee, P.Santhoshini, Nadia Shareen, Megha Chandana, Harini Vadla

Abstract: Real-time object detection and environmental awareness are essential components in assistive technologies for visually impaired individuals. Traditional mobility aids provide limited information about surrounding objects and their proximity, making independent navigation difficult in complex environments. In this work, an AI-based assistive vision system is proposed that integrates the YOLOv8 deep learning model for real-time object detection, distance estimation techniques for proximity awareness, and text-to-speech output for auditory feedback. The system captures input from a camera, detects and classifies multiple objects in the environment, estimates their distance from the user, and converts the detected object labels along with distance information into speech output. This enables visually impaired users to understand nearby obstacles and objects more effectively while moving in indoor and outdoor environments. The proposed approach offers a practical, low-cost, and efficient assistive solution by combining computer vision and artificial intelligence to enhance user safety, independence, and confidence. Experimental observations indicate that the system performs effectively for common object categories and provides meaningful audio guidance in real time

DOI: https://doi.org/10.5281/zenodo.19280231

 

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Authors: Souvik Shil

Abstract: Rapid urbanization and land surface transformations significantly influence local thermal environments, leading to the intensification of Urban Heat Island (UHI) effects. This study analyses the spatio-temporal relationship between vegetation dynamics and Land Surface Temperature (LST) in English Bazar Municipality (EBM), West Bengal, over the period 2001–2025 using multi-temporal satellite data. The results indicate a consistent decline in vegetation cover, accompanied by a substantial increase in surface temperature. The mean LST increased from approximately 30.43°C in 2001 to 40.41°C in 2025, reflecting pronounced thermal intensification. A strong inverse relationship between NDVI and LST is observed, with low vegetation areas corresponding to higher temperatures. High-temperature zones have expanded notably in the central and eastern parts of the municipality, indicating the growth of UHI hotspots. The study demonstrates that vegetation loss and urban expansion are key drivers of rising surface temperature and UHI intensification, highlighting the need for climate-responsive urban planning and increased green cover to mitigate future thermal stress.

Published by: vikaspatanker

Authors: Siddhi Suryakant Shigwan, Charulata Manohar Talele, Prajakta Vilasrao Wankhade, Ms. A. P. Deshmukh

Abstract: This study focuses on the design and development of a digital platform that enhances the monitoring and management of female reproductive and overall health. The purpose of the study is to analyze how modern digital technologies and data-driven approaches can be utilized to develop an intelligent health tracking system that goes beyond traditional menstrual tracking applications. Conventional period tracking systems mainly record menstrual cycle dates and provide basic predictions for upcoming cycles. However, these systems often fail to consider the broader physiological, psychological, and lifestyle factors that influence women’s health.

DOI: https://doi.org/10.5281/zenodo.19279759

 

Published by: vikaspatanker

Authors: Ajay Sonawane, Pranav Babrekar, Aditya Pandagale, Himanshu Saindlya

Abstract: Brain tumours are life-threatening conditions that demand early and precise diagnosis to improve patient outcomes. While deep learning has significantly advanced automated medical imaging, conventional convolutional neural network (CNN) models often require large annotated datasets and intensive computation, limiting their applicability in clinical settings. In experiments, the quantum-augmented models achieved notable performance gains. The hybrid MobileNetV2 model achieved the highest validation accuracy of 95.79%, outperforming traditional CNN baselines while offering faster inference and reduced computational overhead. These results suggest that integrating quantum layers enhances feature representation and model robustness.

DOI: https://doi.org/10.5281/zenodo.19279172

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Authors: R.L Aarthi, Dr. S. Selvi

Abstract: The Vedic Multiplier, derived from the ancient Urdhva-Tiryakbhyam sutra, provides an efficient and structured approach to perform high-speed multiplication, which is a fundamental operation in digital signal processing, image processing, embedded systems, and VLSI applications. Conventional multipliers such as array or Wallace tree multipliers, although accurate, often require large hardware resources and suffer from increased delay due to complex carry propagation paths, limiting their suitability for low-power and small-scale designs. In this project, a Vedic multiplier is designed and implemented in Verilog HDL, incorporating Ripple Carry Adder (RCA) optimization for the accumulation stage to reduce design complexity and ensure consistent performance. The design process covers the implementation of basic modules including AND, OR, Half Adder (HA), Full Adder (FA), and Ripple Carry Adder (RCA), which are then combined to form 2-bit and 4- bit Vedic multipliers. By leveraging the RCA for final addition, the architecture minimizes hardware overhead while maintaining reliable accuracy across test cases. Simulation and functional verification were carried out using industry-standard EDA tools, and results validate the correctness of multiplication operations for various inputs with low area utilization and moderate delay. The optimized Vedic multiplier demonstrates efficient trade-offs in terms of area and delay, establishing it as a simple yet effective solution for arithmetic-intensive applications in energy-constrained embedded systems and FPGA-based platforms, with scalability potential for higher bit-width multipliers. Furthermore, the simplicity of the RCA- based approach makes the proposed architecture highly adaptable for classroom learning, research, and prototyping environments where clarity and resource efficiency are essential. While advanced adders such as Carry Lookahead or Carry Save adders may provide lower propagation delay in large-scale multipliers, the Ripple Carry Adder offers a favourable balance of low power consumption, reduced complexity, and straightforward implementation, making it especially effective for small-to-medium bit-width operations. This highlights the practicality of the proposed design as a baseline for further optimization, with the potential to extend towards pipelined or parallel Vedic multiplier architectures suitable for real-time signal processing and embedded computing applications.

DOI: https://doi.org/10.5281/zenodo.19276670

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Authors: Mr. Anne Murali Krishna, Dr. M. A. Rasheed, Dr. N.Y. Raju

Abstract: Healthcare and pharmaceutical organizations depend on robust and efficient supply chains to ensure continuous access to essential medicines and medical products. Recent global disruptions have exposed critical vulnerabilities in conventional supply chain structures, underscoring the urgent need for strategic transformation. This study investigates the influence of supply chain resilience, risk management practices, and collaborative strategies on operational efficiency within healthcare and pharmaceutical organizations. A quantitative research approach was employed, with primary data collected from 180 supply chain professionals; this sample also served as a pilot study to validate the research instrument. Reliability and validity were established through appropriate statistical tests. Data were analyzed using descriptive statistics, correlation analysis, and multiple regression techniques. The findings reveal that resilience-focused supply chain strategies have a significant positive impact on operational efficiency and overall performance. The study offers empirical evidence and practical insights to support the development of more resilient healthcare and pharmaceutical supply chains in increasingly uncertain and dynamic environments.

DOI: https://doi.org/10.5281/zenodo.19276170

Published by: vikaspatanker