Volume 13 | Issue 6 |

 Abstract

AI refers to the development of intelligent computational systems capable of mimicking human-like cognitive functions such as perception, reasoning, and decision-making. Unlike traditional programming, AI can operate beyond biologically inspired models to solve complex problems. With exponential data growth from both human and machine sources, AI plays a critical role in processing information and automating decision-making. This study reviews the foundational concepts, historical evolution, core technologies, and real-world applications of AI across various industries.

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 Keywords

machine learning, deep learning, neural networks, Natural Language Processing and Knowledge Base System

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In an era of rapid technological advancements and growing scientific curiosity, the field of seedbed preparation has seen significant transformations. This review paper explores the latest developments, challenges, and future prospects within the domain, providing a comprehensive understanding of how innovations are shaping both theoretical and practical aspects. A key focus of this review is the evolving methodologies that have redefined traditional approaches, offering improved efficiency, accuracy, and applicability. From foundational concepts to cutting-edge advancements, the discussion highlights the integration of novel techniques and interdisciplinary perspectives that have propelled progress. Additionally, the paper examines real-world applications, demonstrating how these advancements contribute to solving complex problems and enhancing everyday experiences. Despite notable progress, challenges remain. Issues such as scalability, ethical considerations, and practical implementation hurdles pose significant barriers to widespread adoption. This review critically evaluates these challenges while shedding light on ongoing efforts to address them through emerging technologies and innovative solutions. Looking ahead, the future of Agriculture holds immense promise, with research trends indicating a shift towards greater automation, sustainability, and inclusivity. As the field continues to evolve, collaborative efforts across disciplines will be crucial in unlocking its full potential. This review aims to provide an insightful and engaging narrative, making complex concepts accessible while encouraging further exploration. By bridging the gap between past achievements, present developments, and future possibilities, it serves as a valuable resource for researchers, professionals, and enthusiasts alike.

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Seedbed Preparation in Nurseries: A Systematic Review of Techniques and Best Practices

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This project presents the design and implementation of a measurement system using a Field-Programmable Gate Array (FPGA) and an Analog-to-Digital Converter (ADC) to process mixed-signal inputs and perform a variety of signal measurements. The system is capable of accurately measuring essential parameters of the input signal, such as voltage levels, 8 bit parallel digital data and 8 bit serial digital data (in formats like hexa decimal or Binary).The FPGA is responsible for the real-time processing of the signals and the extraction of these measurements, leveraging its parallel processing capabilities to ensure high-speed performance. The system integrates a USB-to-UART interface for communication between the FPGA and a personal computer. This interface enables the transmission of the measured data to the PC, where it can be displayed and analyzed via a user-friendly graphical interface. The measured values, including voltage, digital input are presented on the PC in an easily interpretable format, allowing for real-time monitoring and evaluation of the input signal.

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Mixed-signal measurement system, FPGA, ADC, UART, real-time monitoring, signal analysis, digital data acquisition.

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This paper presents a comparative study on the structural performance of flat slab, waffle slab, and conventional slab systems in a multi-storey (G+5) commercial building using ETABS software. The building is modelled and analyzed under seismic zone III conditions using dynamic response spectrum methods. The comparison focuses on critical parameters such as lateral load, storey displacement, storey drift, base shear, and base reactions. The results of flat slabs exhibit higher storey drift and base shear due to increased flexibility. The findings aim to inform optimal slab system selection for commercial buildings in seismic zones.

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 Keywords

Flat slab, Waffle slab, Conventional slab, RCC building, Seismic analysis, ETABS, Response spectrum, Storey drift, Displacement, Base Shear.

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract- Credit card fraud is a serious risk to financial institutions and consumers, resulting in huge monetary losses globally. Rule-based fraud detection systems often fail to respond effectively to changing fraudulent patterns, making machine learning (ML) a viable alternative. The present work investigates the use of diverse ML algorithms such as Logistic Regression, Decision Trees, Random Forest, Support Vector Machines (SVM), and Neural Networks to identify fraudulent credit card transactions. The research utilizes a real-world dataset with highly imbalanced class distribution, which requires advanced data preprocessing techniques such as Synthetic Minority Over-sampling Technique (SMOTE) to improve model efficiency. Several evaluation metrics, such as Precision, Recall, F1-score, and the Area Under the Receiver Operating Characteristic (AUC-ROC) curve, are used to measure model efficacy. Experimental outcomes illustrate that ensemble learning methods, specifically Random Forest, perform better than other classifiers in terms of accuracy and fraud detection ability. The results reflect the strengths of ML- based fraud detection systems to detect fraudulent transactions with better precision and avoid false positives. Still, challenges such as interpretability of the model and limitations on real-time detection are topics of future work. This research presents useful findings towards improving fraud detection mechanisms and identifies future work on optimizing ML strategies in financial security.

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 Keywords

Credit Card Fraud Detection, Machine Learning, Imbalanced Data, Fraud Prevention, Financial Security.

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The study analyses the many outcomes of demonetisation for the Indian economy and financial sector which resulted from the government's historic announcement to withdraw INR500 and INR1,000 currency notes on November 8, 2016. The government wanted to tackle black money, lower corruption and make the economy more digital, but what resulted was a wide-ranging complication. Using qualitative and secondary information, this report explores the challenges businesses experience, looks at how people spend and save and notes the quick increase in online payment solutions. It also studies how viable are GDP targets, manage employment, assure the operarness of SMEs and regulate liquidity, bad debts and trust in banks. It is evident from the research that although demonetisation briefly hit non-bank sectors and rural areas, it gave an impetus to changes in the financial system by promoting bank savings and bank accounts for the unserved. The study finishes with proposals for changes in policy to accomplish better monetary interventions using what we have learned from what took place in India. By doing this, we hope to support the wider thinking about reforms to monetary policy in developing economies.

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 Keywords

Demonetisation, Indian Economy, Financial Sector, Digital Payments, Informal Sector, Monetary Policy, Financial Inclusion, Banking System.

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Fast Dissolving Tablets (FDTs) have emerged as a popular dosage form due to their rapid disintegration, enhanced patient compliance, and suitability for pediatric and geriatric populations. A variety of FDTs are available globally across multiple therapeutic categories such as migraine, pain relief, allergies, gastrointestinal disorders, and nutritional supplementation. Leading pharmaceutical companies like GlaxoSmithKline, Eli Lilly, and Merck & Co. market well-known brands such as Zofran ODT, Zyprexa Zydis, and Maxalt-MLT. These tablets are widely distributed in regions including the USA, Europe, India, and Asia-Pacific. With growing demand for ease-of-use medications, the development and market expansion of FDTs continue to thrive, making them a key innovation in modern drug delivery systems.

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Fast Dissolving Tablets, Patient Compliance, Oral Drug Delivery, Therapeutic Categories, Marketed Formulations

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Security and surveillance in hazardous or restricted environments require solutions that minimize human risk while maximizing monitoring capabilities. This project introduces a semi-autonomous Long Range Spy Robot equipped with night vision and remote control functionality using DTMF (Dual Tone Multi Frequency) technology. Powered by a 12V battery and regulated for microcontroller and peripheral operation, the system utilizes an 8051 microcontroller to interpret signals from a DTMF decoder connected to a mobile phone. This enables remote actuation of motors through a motor driver, facilitating controlled movement of the robot. A wireless night vision camera provides real-time video feedback to a remote television receiver, supporting surveillance in low-light or night-time conditions. This robot proves effective for applications in security, military reconnaissance, and remote inspection, offering long-range control without direct line-of-sight and reducing human exposure in risky environments

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Surveillance Robot, DTMF Control, Night Vision, Remote Monitoring, 8051 Microcontroller.

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This research presents a detailed examination of communication practices within various workplace environments in the city of Mysuru, with the objective of identifying existing challenges, evaluating their impact on employee engagement, and proposing actionable strategies to enhance communication effectiveness. The study surveyed 50 employees from diverse functional areas such as human resources, finance, IT, sales, operations, and administration, ensuring a well-rounded perspective on communication across organizational levels. The findings reveal a strong consensus on the fundamental importance of communication in maintaining smooth operations, fostering collaboration, and achieving organizational goals, with 91.7% of participants affirming its critical role. Despite this recognition, 75% of respondents reported encountering significant communication-related challenges at their workplaces. The most common issues included lack of message clarity, frequent misunderstandings, and insufficient feedback mechanisms. These problems not only disrupted workflows but also negatively influenced interpersonal relationships, especially between subordinates and supervisors, with 55% reporting adverse effects on their rapport with management. Moreover, the study uncovered a direct link between poor communication and employee attrition, as 60% indicated that communication failures contributed to their decision to leave or consider leaving a job. Inadequate formal training in communication skills, discomfort with digital communication tools, and dissatisfaction with meeting structures were also cited as major barriers to effective interaction. Remote work environments added further complications, with 50% of respondents stating that the lack of face-to-face interaction and non-verbal cues impeded communication. The overall satisfaction with communication within organizations was moderate, averaging 2.9 on a 5-point scale. These findings point to a pressing need for improvement. Based on the analysis, the study recommends implementing regular communication skills training, developing structured and inclusive feedback systems, enhancing digital literacy, improving managerial communication, and fostering a workplace culture centered around openness, clarity, and collaboration. Ultimately, the study emphasizes that effective communication is not just a soft skill but a strategic asset that significantly influences employee retention, productivity, morale, and the long-term success of an organization. Addressing the identified gaps through deliberate, organization-wide efforts can lead to a more connected, efficient, and resilient workforce.

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Key words: Effective Communication, Workplace Communication, Remote Work Communication, Employee Attrition, Digital Communication Tools, Communication Satisfaction, Workplace Productivity, Organizational Culture

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Creative Commons Attribution 4.0 and The Open Definition

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This study investigates the investment behavior, perceptions, and socio-economic characteristics of stock market investors in Kerala, with a specific focus on the Alappuzha district. Using both primary and secondary data, the study applies a descriptive and analytical research approach. Primary data were collected through structured questionnaires distributed to 50 respondents, while secondary data were sourced from official platforms such as SEBI, NSE, BSE, and RBI. The findings reveal that the majority of investors are female, aged between 25-50 years, and primarily motivated by the potential for high returns and financial independence. Smartphones and social media dominate as investment tools and information sources. Despite growing interest among young investors, equity market participation remains limited due to challenges such as lack of capital, limited knowledge, and fear of risk. The study highlights the need for improved investor education and policy initiatives to encourage greater retail participation in India's equity markets, particularly in financially literate regions like Kerala.

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 Keywords

investment pattern , perception, equity investor

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Creative Commons Attribution 4.0 and The Open Definition