Volume 14 | Issue 4 |

 Abstract

The project Smart Battery Switching and Regenerative Braking System for Electric Vehicles with Boost Converter? is designed to enhance the efficiency, performance, and energy recovery capability of electric vehicles (EVs). In this system, two dynamos are mounted on the front wheels to generate electrical energy during vehicle motion and braking. The generated voltage is processed through a charging circuit and stored in Rechargeable Battery Pack-1. A PIC microcontroller continuously monitors the battery voltage, current, and dynamo-generated voltage through sensors and displays these values on an LCD display for real-time monitoring. The system employs an intelligent switching mechanism to automatically alternate between Battery Pack-1 and Battery Pack-2, ensuring uninterrupted power supply. The switches are used to control the EV's movement, while Battery Pack-2 powers the two DC motors mounted on the rear wheels for vehicle propulsion. During braking, the regenerative braking mechanism converts kinetic energy into electrical energy, which is boosted through a boost converter and stored back into the batteries to improve charging efficiency. The system also includes LED indicators for status indication. This smart and sustainable design improves battery life, optimizes energy usage, and supports the advancement of efficient electric vehicle technology.

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 Keywords

Electrical vehicle, Embedded System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Programming education for beginners often suffers from rigid curricula, limited visualization, and a lack of personalized feedback, resulting in poor conceptual understanding and high dropout rates. This paper presents an AI-Enhanced Progressive Programming Tutor, a web-based learning platform that deliv-ers adaptive instruction, real-time feedback, and interactive visualizations to support novice programmers. The proposed system integrates an adaptive learning en-gine that tracks learner progress and understanding levels, a visual code execution and debugging environment, and an intelligent conversational assistant. The platform provides a structured default curriculum while enabling on-demand gen-eration of personalized instructional content based on individ-ual learner needs. By dynamically adjusting content difficulty, pedagogy, and explanations using learner analytics, the system emphasizes concept-driven learning over rote memorization. The proposed approach aims to bridge the theory-practice gap in programming education, improve learner engagement, and strengthen foundational programming skills. The paper outlines the system architecture, learning workflow Models' knowledge decays over time, and experimental evaluation strategy, demonstrating the educational potential of combining artificial intelligence with modern programming pedagogy.

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 Keywords

artificial intelligence, programming education, adaptive learn-ing, intelligent tutoring systems, code visualization

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Hillsides challenge old farming ways yet networks of clever sensors are changing that. A setup built for tough landscapes spreads out across fields, checking ground wetness, weather shifts, temperature swings, even slope movement. Messages hop through thin air on frugal signals reaching far distances, like those LoRaWAN pulses sneaking between rocks and trees. Boxes near the land catch these whispers, make quick choices say, waking up a pump when roots thirst. Beyond instant reactions, information flows upward, climbing into online spaces where patterns form over time. Algorithms study past behavior, then sketch possible futures hinting when water should flow next. Warnings pop if trouble brews beneath the surface or in shifting skies overhead. Data stops being just numbers; it becomes timing, rhythm, notice before damage takes root. Precision irrigation cut water use by nearly a third on sloped terrain, despite shaky signal strength at times. Results showed better harvests emerged where tech adjusted itself to tough mountain conditions. This paper presents a terrain-aware system designed for smallholder terraced farms in Karnataka and outlines sensor deployment, edge-cloud architecture, and a practical pilot plan for replication.

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 Keywords

smart agriculture, LoRaWAN, edge computing, precision irrigation, terrain-aware systems, Internet of Things (IoT).

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Antibiotic resistance is a growing global issue because some bacteria have developed the ability to survive even when antibiotics are used. This makes infections more difficult to cure. Natural environments like soil and water can act as reservoirs where these resistant bacteria and their resistance traits exist and spread. In this study, samples were taken from different environmental sources and bacteria were grown in the laboratory using basic microbiological methods. Techniques such as serial dilution were used to reduce the number of bacteria in a sample, making it easier to isolate individual types. The bacteria were then cultured on different growth media to obtain pure colonies. After isolation, the bacteria were identified by examining their shape, size, and appearance, along with performing biochemical tests to understand their characteristics.. To determine how the bacteria respond to antibiotics, the disk diffusion technique was performed. In this method, bacteria are spread evenly on a growth medium, and small discs containing different antibiotics are placed on the surface. During incubation, the antibiotics diffuse into the medium and interact with the bacteria. After some time, the areas around the discs are examined. If a clear region appears around a disc, it means the bacteria are sensitive to that antibiotic. If there is little or no clear area, the bacteria are considered resistant. The results showed a mix of responses: some bacteria were affected by the antibiotics, while others were not. Notably, certain bacteria were resistant to several antibiotics at once, indicating multidrug resistance, which can make infections more difficult to treat.. The findings of this study indicate that bacteria present in the environment can play a major role in the spread of antibiotic resistance. This shows that resistance is not only a problem in hospitals but can also develop in natural surroundings such as soil and water. For this reason, it is important to study environmental bacteria to better understand how resistance begins and spreads. To examine how these bacteria react to antibiotics, the disk diffusion method was used. In this process, small discs containing antibiotics are placed on a surface where bacteria are growing. The effectiveness of each antibiotic is judged by whether it can stop bacterial growth around the disc. The results showed that different bacteria responded in different ways. Some were easily controlled by antibiotics, while others were less affected or not affected at all. A few bacteria were resistant to several antibiotics at the same time, making them more difficult to treat. These results suggest that environmental bacteria are not just passive organisms but actively contribute to the development and spread of antibiotic resistance. Therefore, regular study and monitoring of these bacteria are necessary. It also highlights the importance of using antibiotics carefully, managing waste properly, and maintaining good environmental practices to reduce the spread of resistance and protect human health..

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 Keywords

Key Words: Bacteria, Antibiotics, environment, Environment bacteria, Resistant bacteria, Public health

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 Abstract

The quick expansion of online services for shopping, banking, and communication among many other things, users are often bombarded with phishing attempts across many vectors including URLs, SMS messaging, and emails. Cybercriminals take advantage of these vectors in various ways to mislead individuals into realizing sensitive data, such as passwords, bank account information, or pin numbers. This project shows a complete phishing attack detection system for real-time phishing detection and blocking by machine learning using fast CNN. The proposed solution is designed to overcome the limitations of traditional, blacklist-dependent methods, which often fail against zero-day phishing attempts and lack real-time capability. The core of the system is a Fast Convolutional Neural Network (Fast CNN) algorithm, specifically chosen for its superior accuracy, computational efficiency, and ability to learn complex patterns without manual feature engineering. The methodology involves extensive preprocessing, including normalization and tokenization, followed by the numerical extraction of features like URL length, subdomain count, and the presence of suspicious keywords. The trained model is integrated into a user-friendly mobile application, providing protection at the device level. This application is uniquely capable of automatically scanning incoming SMS messages for embedded URLs and instantly classifying them as malicious or legitimate. By focusing solely on URL analysis and eliminating reliance on external APIs, the system is language-independent, faster, and more privacy- preserving. The automated phishing detection system focused on incoming SMS messages, and the user manually verifies suspicious email or text by pasting them into the application. The system does feature extraction for the URL structure, keywords frequency, suspicious terms, and message length. The project uses a balanced dataset of phishing and legitimate samples from public repositories like UCI and Kaggle examination, to enable automatic high precision classification. It can protect and defend users by automated use, has scalability, at a low cost and still maintains user data safety and privacy.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fast CNN, Machine Learning, Phishing Detection, SMS Phishing, URL Analysis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Synthetic data generation is an advanced approach that produces artificial datasets preserving the statistical properties of real-world data while ensuring privacy protection. With increasing data regulations and scarcity of high-quality datasets, synthetic data plays a vital role in enabling secure analytics, machine learning model training, and system testing. This paper presents detailed methodologies, architectures, evaluation metrics, and applications of synthetic data generation using machine learning and deep learning techniques.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Synthetic Data Generation, Privacy-Preserving Data

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

With the increasing prevalence of the use of digital media, a novel behavioral pattern has emerged that could potentially affect interpersonal relations. The aim of the current research study was to investigate the relationship between doomscrolling behavior, cognitive ruminations, conflict resolution styles, and marital satisfaction levels among young married couples. A quantitative research design with a descriptive and correlational approach was adopted for the research study. A sample of 120 married couples between the ages of 21-35 years were selected for the research study through the purposive sampling technique. Standardized research instruments were administered to collect the research data from the sample participants. These research instruments we re the Doomscrolling Scale, Ruminative Responses Scale- Short Form, Conflict Resolution Styles Inventory, and the ENRICH Marital Satisfaction Scale. SPSS software was used to analyze the research data. To conduct the correlation analysis, Spearman's rank correlation coefficient test was applied due to the non -normality of the research variables. The findings revealed that doomscrolling was significantly and positively related to cognitive rumination, while cognitive rumination was significantly and negatively related to marital satisfaction. Positive conflict resolution style was positively related to marital satisfaction, while negative conflict style was negatively related to marital satisfaction. Doomscrolling was not significantly directly related to marital satisfaction. The findings suggested that cognitive processes and interpersonal processes like conflict resolution style play a more significant role in predicting marital satisfaction than digital processes like doomscrolling.

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 Keywords

doomscrolling, cognitive rumination, conflict resolution, marital satisfaction, young couples

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The appearance of digital stressors has created the urgent need to address the issue of mental health through the development of mental health monitoring systems that are proactive, as the current clinical approaches are mostly reactive and are rarely conducted at regular intervals, making it hard to keep up with the dynamic nature of mental health. This paper seeks to present a novel framework for predictive behavioral analytics using eXtreme Gradient Boosting (XGBoost) and Shapley Additive Explanations (SHAP) for the purpose of decision-making. The framework is different from other "black box" models because it can attribute specific behavioral events, such as sleep deprivation or excessive use of social media, using local feature attribution. The model also considers a temporal baseline of 15 days, which helps it provide personalized risk assessments for specific users rather than using averages for all users. The results of the experiments show a classification accuracy of 92.5.

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 Keywords

Explainable AI (XAI), XGBoost, SHAP, DNN, Mental Health, Behavioral Analytics, Digital Phenotyping

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 Abstract

Artificial Intelligence (AI) has become one of the most influential technological forces reshaping modern marketing. As organizations undergo digital transformation, AI tools--such as machine learning, generative AI, and predictive analytics--are increasingly integrated into strategic and operational marketing activities. This systematic literature review synthesizes contemporary research to examine how AI contributes to marketing efficiency, personalization, and organizational capability development. Drawing from theoretical models including the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB), the review identifies the behavioral, technological, and organizational factors influencing AI adoption. Findings suggest that while AI enhances personalization, decision accuracy, and strategic agility, adoption outcomes are moderated by organizational readiness, brand-related factors, and user perceptions. The paper concludes by proposing an integrated conceptual framework and outlining directions for future research.

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 Keywords

Marketing, Artificial Intelligence, Digital Transformation.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

One of the primary causes for inconsistent exposure and less than ideal oral absorption of small molecule treatments is still poor aqueous solubility. Pure crystalline active pharmaceutical ingredient (API) colloidal dispersions stabilized by polymers or surfactants, known as drug nanocrystals, have become a flexible platform for increasing dissolution rate, apparent solubility (through the Kelvin effect), and, eventually, bioavailability. Improvements over the past five years include long-acting parenteral nanosuspensions, scalable continuous manufacturing, hybrid bottom-up/top-down processes, shape and polymorph control, better solidification techniques for tablets, capsules, and or dispersible dosage forms, and in silico tools that speed up formulation design. This study summarizes the latest developments in quality-by-design (QbD), characterization, materials, processes, and translational pharmacokinetics. It also identifies potential future paths, such as AI-guided excipient selection, green production, and precision long-acting treatments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Poorly soluble drugs, drug nanocrystals, nanosuspensions, high-pressure homogenization, continuous manufacturing

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Creative Commons Attribution 4.0 and The Open Definition