Authors: Nikhil Kumar, Shekhar Kumar Purbe, Dr. Jyoti Gautam

Abstract: Phishing attacks are now considered to be the greatest cyber security threats in online banking, mobile wallet, and other online financial systems. Attackers launch such attacks not only exploit the vulnerabilities in systems but also exploit human factors to steal sensitive financial information and cause huge monetary losses and destroy users’ credibility. Current defense strategies are blacklist based URL filtering and static rules based detection, which are unable to cope with modern phishing attacks. Modern phishing attacks are carried out by employing advanced techniques such as domain spoofing, adversary-in-the-middle (AiTM) attacks, and dynamic web contents . This paper proposes a multi-layered intelligent phishing detection architecture to defend online banking platforms. The proposed system uses URL analysis, content inspection, and transaction behavior analysis to protect online banking systems from different angles. The system uses machine learning algorithms such as Random Forest, Support Vector Machine, and Logistic Regression to classify phishing attacks based on the features extracted from URL, web pages, and user transactions. Unlike previous approaches which only use single layer detection, this paper proposes a hybrid system architecture with real-time detection and behavioral analysis to detect phishing attacks. The system is trained with datasets collected from multiple repositories which are publicly available phishing repositories. The experimental results show that the model trained by the proposed method achieves an accuracy of 96.5% with high precision and recall and low latency to be applied in real-time systems. The system also provides an alert and response mechanism to notify users and stop fraudulent transactions as soon as possible.

DOI: https://doi.org/10.5281/zenodo.19762735

Published by: vikaspatanker

Authors: Sarwesh kumar, Keshav Kumar

Abstract: With the increase in the adoption of digital education and online certifications, there is a remarkable need for certificate verification systems that are secure and reliable. Certificate issuance and validation are traditionally conducted through a manual process relying on centralized databases that is easily forged, manipulated, and fails in the occurrence of an accidental data loss. A big cause of concern for educational institutions, employers and government agencies is fake certificates. To alleviate such problems, a tamper-proof and distributed certificate verification mechanism is proposed on the basis of block chain technology. The blockchain technology offers a decentralized and unchangeable ledger, like cannot change the data once stored in that ledger. The new system stores the verified certificates into a blockchain network securely after being issued by institutions. It assigns a unique cryptographic hash value for each certificate to ensure its authenticity and integrity.

DOI: https://doi.org/10.5281/zenodo.19761949

Published by: vikaspatanker

Authors: Bejini Chidananda Krishna, Naveen KR, D.Ravi

Abstract: This study examines how a diesel engine behaves when ethanol and butanol are mixed with regular diesel fuel in different proportions. The aim is to determine whether these cleaner, renewable fuels can partially replace diesel without compromising engine performance while reducing harmful emissions. To do this, several fuel blends were prepared and tested in a diesel engine under different load conditions and ratios (D85E7.5B7.5, D80E10B10, D75E12.5B12.5). During the experiments, important performance factors such as fuel efficiency, fuel consumption, and exhaust temperature were recorded. At the same time, emissions such as carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and smoke levels were measured to assess the environmental friendliness of each blend. The results show that adding ethanol and butanol improves the combustion process because these fuels contain oxygen, which helps the fuel burn more completely. This leads to lower emissions of pollutants like CO, HC, and smoke, making the engine cleaner compared to using pure diesel. However, when the proportion of ethanol and butanol is increased too much, the engine may consume more fuel and show a slight drop in efficiency, mainly because these fuels have lower energy content than diesel. In some cases, higher blends can also affect how smoothly the engine runs. Overall, the study suggests that using an optimal mix of ethanol and butanol with diesel can provide a good balance between performance and emission reduction, making it a practical and eco-friendly alternative for diesel engines.

DOI: https://doi.org/10.5281/zenodo.19761417

Published by: vikaspatanker

Authors: Pruthvik k c, Khushboo Khanum, Vinay Kumar, Aaditha, Prajwal, Dr Saumya patel

Abstract: The growing trend of the fitness culture and preventive nutrition has led to the demand of organized and evidence-based systems of meal-preparations. Nutrition based kitchens respond to this demand offering calorie controlled, macro based and goal oriented food that promotes muscle building, fat loss as well as athletic performance. The studies have always indicated that, when people are fed on professionally prepared, nutritionally optimized food, their level of dietary adherence, metabolic response, and training outcomes are better than when people prepare the food on their own. Also the ready-made healthy food assists in coping with the most widespread limitations, including time, decision fatigue, and irregular nutrient consumption. Research on personalized and sports nutrition points out the fact that diets that are consistent with individual fitness objectives enhance energy balance, body make-up and post- workout management. Protein rich and nutrient-dense functional diets also increase satiety, enhance muscle protein synthesis, and overall diet quality especially in individuals with a high physical activity. Nutrition-oriented kitchens use such principles as dietitian regulation, exact portion- control, and calculated macro- distribution in relation to clinical and sports nutrition practices. In contemporary nutrition services, technology is an important ingredient. The digital platform and mobile applications that focus on the user allow customization of the meal, tracking progress, and motivation of behaviour. Properly designed UI/UX systems have a great positive influence on engagement, compliance, and user satisfaction. In addition, meal-preparation services paired with app-observation proved to reinforce the long-term adherence and health outcomes. Generally, studies have indicated that nutrition-prep kitchens could be used as a remedy to modern dietary issues because they combine the element of convenience and scientifically tested nutritional habits. They fill the disconnect between individualized dieting planning and the actual practice, and assist athletes, gym-goers and common consumers to attain long-term health and fitness objectives. The paper assesses the operational model, digital integration, user experience, and nutritional efficiency of Nutri-Fit Kitchen by making it a revolutionary system in the contemporary health- conscious food-oriented business.

Published by: vikaspatanker

Authors: Pooja KR

Abstract: Zero Liquid Discharge (ZLD) systems are increasingly adopted to minimise industrial wastewater discharge; however, they generate concentrated brine streams rich in dissolved minerals. This study focuses on the recovery of magnesium hydroxide from ZLD wastewater using a controlled precipitation method and optimisation of key process parameters. The influence of pH (9–12), temperature (25–60°C), and reaction time (30–120 min) on recovery efficiency was systematically evaluated. Maximum recovery efficiency of approximately 91% was achieved at pH 11, 45°C, and 90 minutes reaction time. The recovered magnesium hydroxide exhibited satisfactory purity and demonstrated effective performance in neutralisation and contaminant removal tests. These findings are consistent with earlier studies on magnesium recovery from brine systems (Almousa et al., 2024; Yong et al., 2024).

DOI: https://doi.org/10.5281/zenodo.19757760

Published by: vikaspatanker

Authors: Santhosh Babu K C, Chirakshitha S, Eashanya K R, Eashanya K R, Ganavi A S, Gowthami G

Abstract: Efficient digital filtering is critical for modern signal processing applications. This work presents an Adaptive Distributed Arithmetic (ADA)-based FIR filter designed for single-channel and scalable multi-channel configurations on FPGA. The proposed design incorporates error- controlled approximation and optimized computation to reduce LUT usage, power consumption, and processing delay. Implementation using the Xilinx Vivado environment demonstrates improved area efficiency and speed while maintaining acceptable signal quality. The results indicate that the ADA approach is well- suited for low-power, high-throughput FPGA-based DSP applications.

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Published by: vikaspatanker

Authors: Veena Vanamane, S Zuha Afsheen, Thrisha M, Preksha Malipatil, Chirasvi S N

Abstract: In many industrial applications, maintaining a steady water level in tank systems is crucial. The design and analysis of proportional (P), proportional-integral (PI), and proportional-integral-derivative (PID) controllers for a single-tank water level control system are presented in this study. MATLAB/Simulink is used to create and construct a mathematical simulation model. Rise time, settling time, overshoot, and steady-state error are used to assess the controllers. The P controller has steady-state error, the PI controller decreases error but increases overshoot, and the PID controller offers ideal performance with better stability and quicker reaction, making it appropriate for efficient water level control, according to the results.

Published by: vikaspatanker

Authors: Dr. A Senthilkumar, Dr. Tintu George, Dr. Ginne M James

Abstract: Achromatopsia is a rare inherited retinal disorder characterized by the absence of cone photoreceptor function, resulting in color blindness, photophobia, nystagmus, and reduced visual acuity. Recent advances in artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), have transformed ophthalmic diagnostics and opened new avenues for early detection and treatment planning. This review paper presents a comprehensive analysis of achromatopsia, focusing on its clinical features, genetic basis, diagnostic approaches and therapeutic developments, with a strong emphasis on AI-driven methodologies. The paper also explores the integration of AI in retinal imaging, genotype–phenotype correlation, and gene therapy optimization. Finally, challenges, limitations and future research directions are discussed.

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Published by: vikaspatanker

Authors: N. Santosh Kumar, U. Reshma, V. Sandhya, S. Santhi vardhan

Abstract: This project presents an innovative Battery Management System (BMS) for electric vehicles, leveraging Arduino UNO to ensure optimal battery performance, safety, and longevity. The system is designed to monitor critical parameters such as voltage, current, temperature, and state of charge (SOC), while also assessing the state of health (SOH) of the battery. The BMS supports both fast and slow charging modes, intelligently managing charging processes to prevent overcharging and thermal runaway. User-friendly interfaces, including real-time data displays, offer intuitive insights into battery status, empowering users with actionable information. This project combines cost-effective hardware with comprehensive safety and performance monitoring, making it a significant step toward safer and more efficient electric vehicle batteries. Real-time SOC/SOH evaluation, and versatile charging management, which collectively advance the capabilities of conventional battery management solutions.

Published by: vikaspatanker

Authors: N.Santosh Kumar, V.Kavya, M.Harshitha, P.SudheerKumar, V.Karthik

Abstract: Train collisions are one of the critical safety concerns in railways, which could result from human error, signal failure, communication delay, or reduced line of sight owing to complex terrain. This paper proposes a low-cost intelligent TCPS designed using ESP32 microcontrollers, ultrasonic sensors, ESP-NOW wireless communication, and an automatic servo-based braking mechanism. The trackside unit constantly monitors the movement of the train through two ultrasonic sensors and calculates real-time distances for potential head-on collision detection. When the system identifies a threat, it issues an instantaneous emergency braking signal to the onboard units, which trigger the servo-driven brake assembly. Further, the proposed system is integrated with regenerative braking to recover the kinetic energy for recharging the lithium-ion battery supply present in the system. Experimental testing on a prototype railway track has shown high detection accuracy, quick wireless communication, and reliable automatic braking. The proposed system gives a scalable, modular, and energy-efficient alternative to conventional railway safety mechanisms that can be integrated with state-of-the-art signalling and AI-based prediction in future applications.

Published by: vikaspatanker