Volume 13 | Issue 4

 Abstract

Computer vision has revolutionized the field of automated medical screening by enabling the efficient analysis of medical images for early disease detection and diagnosis. With the integration of deep learning techniques, especially convolutional neural networks (CNNs) and transformer-based models, computer vision systems can now accurately interpret complex patterns in radiology, ophthalmology, dermatology, and pathology. These systems enhance diagnostic precision, reduce human error, and offer scalable solutions, particularly in underserved and remote areas. Despite significant advancements, challenges such as limited access to diverse, annotated datasets, data privacy concerns, algorithmic bias, and lack of clinical validation persist. Moreover, ensuring model interpretability and seamless integration into existing healthcare workflows remains a critical hurdle. Recent developments in multimodal learning, federated learning, explainable AI, and mobile-based screening tools are addressing these limitations, paving the way for more equitable and transparent healthcare delivery. Performance evaluation using robust metrics and regulatory validation is vital to ensure safety and effectiveness in clinical practice. This review outlines the applications, challenges, and future directions of computer vision in medical screening, emphasizing the need for interdisciplinary collaboration and ethical considerations. Ultimately, computer vision has the potential to transform medical diagnostics by making healthcare more proactive, accessible, and data-driven.

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 Keywords

ComputerVision, Screening, Diagnosis, Healthcare, Automation

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The goal of this project is to create an automated system for detecting cyberbullying on social media platforms using Natural Language Processing (NLP) for text classification and Machine Learning for behavioral analysis. Cyberbullying, a growing issue in online interactions, often leads to significant psychological and emotional harm, especially among young users. This project employs NLP techniques to identify and classify harmful content, distinguishing it from neutral or positive interactions based on linguistic patterns, sentiment, and tone. Text data from various social media sources, annotated with labels for bullying and non-bullying content, serves as the dataset. The first phase involves data preprocessing, including text cleaning, tokenization, and word embedding techniques such as Word2Vec or BERT embeddings to capture semantic meaning. With these prepared data inputs, machine learning models such as Support Vector Machines (SVM), Random Forest, or deep learning models like Recurrent Neural Networks (RNNs) and Transformers are trained to classify text accurately. To enhance detection accuracy, this project also includes behavioral analysis by examining user interaction patterns, frequency of harmful words, and network analysis to track the dynamics of cyberbullying incidents. Integrating these analyses enables the model to detect complex bullying patterns that rely not only on language but also on behavioral indicators. This system aims to provide social media platforms with a reliable tool to flag and mitigate cyberbullying, promoting safer online environments.

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-- Text Classification, Cyber bullying Detection ,Social Media Monitoring, Sentiment Analysis, Behavioral Pattern Analysis, Machine Learning Models.

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Skin diseases are among the most common health problems worldwide. According to recent data, the prevalence of skin diseases in India among adults is significant, with studies reporting that between 23.7% and 40.1% of adults in India suffer from various skin disorders. In Ayurveda,skin disorders have been described under headings of Kushtha,Visarpa,Sheetpitta, Kshudra roga,etc. Visarpa is one of the common disorders and suffered by a large scale of population. Blistering disorders are a group of diseases presenting with vesicles and bullae over the skin and mucous membranes. 'Bullous Impetigo' is a bacterial skin infection caused by Staphylococcus aureus that results in large,fragile blisters called bullae. Here is the case of 33 years male patients came in opd with complaints of pus filled blisters in both axillas and groin region associated with crusting of skin and erythema,Boils on both hands,Generalised weakness since 6-7 days. Patient was treated with Both Ayurvedic as well as Allopathy medicine. Assessment of treatment was done on the basis of improvement of signs and symptoms of Kaphaj visarpa vyadhi.Main aim of managing visarpa is shaman chikitsa, local ointments (Bahyaupchar) and Raktamokshana along with modern medicines. Integrated treatment for Visarpa Vyadhi, combining Ayurvedic and modern medical approach offers comprehensive management by addressing the root cause of the disease through Ayurvedic detoxification and rejuvenation therapies. And alleviating symptoms and preventing complications with modern medications.

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Skin Diseases , Bullous Impetigo, Visarpa, Raktamokshan, Shodhana Chikitsa

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The study of this subject attempts to make out how ritualistic life exists among the Nocte tribe. An effort is made to examine the subject with the application of empirical study and method. The study is on historical analysis. Valuable data is gathered through field studies and interaction with the people of the community. Secondary sources are also referred to further authenticate the research work. The Noctes are one of the ethnic groups of the Tirap District of Arunachal Pradesh, inhabited in the easternmost part of India. They are the worshipper of animism. The institution of the indigenous belief system of the tribe is not organized as such like a permanent place for worship, idol of god so on and so forth. They personified all the natural forces as gods or spirits. They believed in the existence of both malevolent and benevolent spirits. Rituals are an integral part of their belief system. Priest acted as an intermediate between the gods and the people. They appease these spirits through performing various rituals as recommended by the village priest.

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Ritual, Ethnic, Animism, Spirit, Appease, Priest, Benevolent, Malevolent.

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RISC-V is a widely used open-standard instruction set architecture (ISA) based on RISC principles. It is supported by popular software tools like GNU, LLVM, DevOps, QEMU, and Spike. RISC-V can be used in simple embedded systems as well as high-performance applications like neural networks. This paper describes the design and implementation of a 32-bit RISC-V (RV32I) processor using VHDL and Vivado 2024.1 version. The processor's performance is tested through simulation, synthesis, and power analysis. The results provide insights into execution speed and power consumption, proving that an FPGA-based RISC-V processor is a good choice for low-power and efficient computing.

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Instruction set architecture, RISC-V, Simulation, Synthesis, VHDL, FPGA, Vivado and Power reports.

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In today's data-centric landscape, effective database interaction is vital for informed decision-making. However, traditional querying methods require technical expertise in Structured Query Language (SQL), creating a barrier for non-technical users. This project proposes a user-friendly solution that enables natural language interaction with SQL databases, thereby democratizing access to structured data. We present a Streamlit-based web application that integrates LangChain agents with a large language model (LLM). This architecture allows users to input conversational prompts, which are interpreted and translated into executable SQL queries. The system removes the need for SQL proficiency, offering a simplified, scalable, and intuitive interface for data retrieval. Amid rapid advancements in AI and natural language processing (NLP), this solution exemplifies practical application by transforming complex database interactions into accessible tasks. It serves both technical and non-technical users, such as data analysts, decision-makers, and business professionals, enabling them to derive insights independently and efficiently. By reducing reliance on IT specialists and facilitating rapid data access, the proposed system contributes to more agile and datadriven business processes. Its design prioritizes usability, flexibility, and real-world applicability, addressing a growing need for intelligent, inclusive database tools in modern digital environments.

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Natural Language to SQL, Conversational Database Interface, AI-powered Query Generation, SQL Automation, Intelligent Database Interaction, Natural Language Query Processing.

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The main goal of this project is to help visually impaired people by designing and implementing an Internet of Things (IoT)-based real-time obstacle detection and alert system. The system makes use of the Blynk IoT platform for user interaction and remote monitoring, as well as the ESP8266 Node MCU microcontroller for connectivity and processing. The project's main component is an ultrasonic sensor that calculates the user's distance from nearby obstacles. The user is immediately alerted to possible danger by a buzzer that sounds when an object is detected within a predetermined threshold (20 cm). The system has a push-button-based manual alert mechanism in addition to automatic detection. The system sends a status update to the Blynk mobile app via virtual pins (V1 and V2) when the button is pressed, registering it as a "PROBLEM" state. Users can easily alert guardians or caregivers to distress situations with the help of this functionality. Additionally, through the Blynk dashboard, remote users can access status updates from the device from any location thanks to the system's support for real-time Wi-Fi-based communication. The user's safety and independence can be increased by integrating extra features like voice alerts, location tracking, or even emergency contact notifications with this configuration.

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Smart Blind Stick, Internet of Things (IoT), ESP8266 Microcontroller, Ultrasonic Sensor, Obstacle Detection, Blynk Platform, GPS Location Tracking.

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Job portals have become an essential tool for job seekers and recruiters in the digital era. These platforms simplify the hiring process by providing a centralized space for job listings, applications, and candidate shortlisting. However, traditional job portals face numerous challenges, including irrelevant job recommendations, spam listings, inefficient search filters, and data privacy concerns. This paper explores the advantages and disadvantages of job portals, evaluates their effectiveness in recruitment, and proposes innovative solutions to enhance their functionality. Emerging technologies such as artificial intelligence (AI), blockchain, and real-time filtering mechanisms are analyzed for their potential to improve job search efficiency and hiring outcomes.

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Job Portals, Recruitment Platforms, AI in Hiring, Job Search Efficiency, Employment Technology

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Abstract: The Sundarbans, the world's biggest contiguous mangrove forest, is one of the world's most diverse and distinctive ecosystems. 4.5 million of India's poorest and most vulnerable citizens reside in the Sundarbans. The region's per capita income is around 50 cents per day, or half of the threshold for extreme poverty as defined by the international community. The only sources of income available to the residents of the Sundarbans are land and resource-based enterprises, as they are not allowed to pursue industrial growth. In the Indian Sundarbans, agriculture and fishing are the two main sources of income, while animal husbandry also plays a significant role in this area. In addition to paddy and various vegetables, the Indian Sundarbans' inhabitants benefit economically greatly from the growth of betel vine. Approximately eighty percent of the households engage in aquaculture, fishing, and agriculture using inefficient techniques of production. Because the mangroves produce fish, honey, fish oil, fire wood, fish, and medicines, the local people is strongly dependent on them. Marginal farmers and fishermen make up the majority of these populations; they are totally reliant on the local natural resources, particularly mangroves. Extreme weather events and their frequency and intensity present a risk to climate change. Sea level rise, contaminated salt water, increased storms and flooding, and draughts are a few possible ones. The purpose of this article is to assess local residents' existing and alternative livelihood prospects, as well as the hazards of climate change to their livelihoods in the surrounding Sundarbans.

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Key word: Mangrove Forest, Ecosystems, livelihood, agriculture, climate change.

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: With the rapid increase in urban vehicle ownership, inefficient parking management has led to congestion, fuel wastage, and increased travel time. This paper presents a Smart Parking System designed to provide users with real-time parking availability and navigation assistance. The system utilizes a web-based platform integrated with Google Maps API to help users locate nearby parking spaces for both cars and bikes. A Node.js backend is used to manage parking data, ensuring that users receive updated availability status. Additionally, an admin panel allows parking managers to update spot occupancy, enhancing system reliability. Unlike traditional parking methods, this system minimizes manual intervention, optimizes space utilization, and reduces traffic congestion. The proposed system is cost-effective, scalable, and can be extended to include IoT sensors for automated parking detection. Experimental results demonstrate improved efficiency in parking management and a reduction in the average time spent searching for parking. Future enhancements will focus on integrating an advanced booking system and mobile application support to further improve user convenience and accessibility.

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Smart Parking, Real-Time Monitoring, Google Maps API, Web-Based System, Node.js, Traffic Management

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This paper explores how companies are connecting SAP systems with other business applications in real-time. As businesses increasingly need instant access to data, old methods of batch processing have fallen short. We examine how organizations are implementing real-time connections between SAP S/4HANA, Business Technology Platform (BTP), and SAP Datasphere with cloud data warehouses like Snowflake, ultimately feeding this data to visualization tools like Power BI. We specifically investigate the roles of CDS views and Azure Data Lake Storage (ADLS) in modern SAP integration scenarios. Through real company examples and performance analysis, we identify what makes these integration projects successful and what challenges companies typically face. Our findings show that real-time integration is no longer just a technical nicety but a crucial business capability in today's competitive environment.

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ADLS, API Management, BTP, CDS Views, Change Data Capture, Cloud Data Warehouse, Data Governance, Data Replication, Datasphere, Event-Driven Architecture, Integration Patterns, Power BI, SAP S/4HANA, Snowflake, Real-time Integration, Semantic Layer.

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Abstract: This study investigates the influence of international tariff policies on the Indian agricultural sector focusing on both sectoral outcomes and policy implications. As a critical component of the Indian economy, agriculture is highly sensitive to global trade dynamics, particularly tariff regimes set by key international players. The research analyses the effect of tariffs imposed by major economies and multilateral trade agreements on Indian agricultural exports, imports, and domestic price volatility. Using a mixed-methods approach, the study evaluates trade data trends, policy frameworks, and case-specific scenarios involving commodities such as rice, wheat, cotton, and sugar. The findings highlight how international tariff changes impact farmer incomes, market access, and rural livelihoods, while also examining the Indian government's trade and support policy responses. India's trade policies regarding rice, wheat, cotton, and sugar have undergone significant changes between 2020 and 2025, influenced by domestic supply considerations, global market dynamics, and inflation control measures. Below is an overview of the import, export, and tariff developments for these commodities during 2020 to 2025. The paper concludes with recommendations aimed at enhancing the sector's global competitiveness and policy adaptability in the face of an evolving trade landscape.

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Tariff, International Tariff, Tariff Policies

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In modern computing systems, achieving a balance between accuracy and power consumption is crucial. As technology gets smaller, it becomes harder for traditional methods to work efficiently. This is applicable even in tasks like videos, signal processing, where exact accuracy is not always needed. So, we go for approximate adders for applications in which accuracy is not significant but there is a need for reduced power consumption and delay. Approximate adders often skip some computations to achieve better performance in terms of energy efficiency and speed. The project focuses on the designing of exact mirror adder, two types of approximate adders single exact single approximate adder (SESA) and single exact dual approximate adder (SEDA) circuit using 18nm Fin FET technology. These circuits are evaluated using the Cadence virtuoso tool. SESA and SEDA have two modes of operation, exact mode for accuracy of the adder and approximate mode for low-power consumption. Using SESA and SEDA, modes can be shifted easily and also allow to vary the amount of approximation .To demonstrate the practical utility of the adders, applied SESA and SEDA architectures in two key application areas: image enhancement and checksum generation.

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Single Exact Single Approximate(SESA)Adders ,Single Exact Dual Approximate(SEDA)Adders, Power Gating, Image Enhacement Applications

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Preserving water quality is vital for sustaining aquatic life and maintaining ecosystem balance. This project extends the existing IoT-based water quality monitoring system by introducing an advanced alert mechanism based on real-time data from pH, turbidity, and Total Dissolved Solids (TDS) sensors. The system employs an Arduino (ESP32) microcontroller integrated with NEO GPS to accurately identify the location of water quality issues. Collected data is transmitted to the cloud and analyzed via the Arduino IoT Cloud Remote App. The system generates visual alerts as a red zone alert for poor water quality and a green zone alert for acceptable water quality, based on thresholds optimized for aquatic species. The system's capability to provide real-time, location-based alerts enhances monitoring efficiency and supports proactive measures to protect aquatic ecosystems.

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ESP32 microcontroller, GPS, Arduino IoT Cloud, Arduino IoT Cloud Remote App

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'Digital Payments' In A Globalized Framework Dr. Rashmita Sahoo* Mr. Nirmala Chandra Pattanayak** Dr. Akhaya Kumar Panda*** ABSTRACT Digital finance is a process of acquiring, using and distributing financial resources to economic factors such as people, households, businesses and governmental organisations through digital infrastructure which includes digital devices and associated digital technologies (Ozili, P.K., 2018; Siddik and Kabiraj, 2020). Digital finance comprises of a host of new financial services, products, businesses, software and innovative methods for customer engagement delivered through fintechs and providers of financial services (Gomber, Koch & Siering, 2017). The current article made an attempt to examine the impact of various socio-demographic factors such as (Age group, Gender, Education level, social stratification, Occupation and Annual Family Income) basically on the adoption of digitalized financial services such as (Credit / Debit Card, Pre-paid Card, Internet Banking, UPI, Mobile Wallets and Mobile Banking). There are two dimensions such as rural and urban. In order to accomplish the objectives a mixed research design has been adopted. The sample magnitude has been determined using Cochran's sampling technique. The determined sample size is 384; however, for better result double the determined sample size, (768) has been undertaken. However, only 660 responses have been received at an approximate response rate of 86%. A pre validated and structured questionnaire has been used to obtain the data from bank customers. Chi-Square test has been administered to test the association between the demographic profiles of the respondents with respect to level of adoption of digital financial services. Cramer's V alongside chi-squared estimates to provide a clearer understanding of effect sizes in studies involving nominal variables. It has been concluded that all the socio demographic variables such as Age Group, Gender, Social Stratification, Occupation and Annual Income are significantly associated with UPI and Internet banking in rural areas whereas all the socio demographic variables in urban areas are significantly associated with UPI, Internet banking and mobile banking. * Associate Professor, P.G. Department of Business Administration, Utkal University, Vani Vihar, Bhubaneswar. ** Nirmal Chandra Pattnayak, Research Scholar, P.G. Department of Business Administration, Utkal University, Vani Vihar, Bhubaneswar. *** Assistant Professor, P.G. Department of Business Administration, Utkal University, Vani Vihar, Bhubaneswar.

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Key Words: digital finance, fintech, Socio-demographic factors.

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This study delves into the nuanced portrayal of tribal human rights issues within Malayalam cinema, examining how these films visually and narratively construct the lived realities and struggles of indigenous communities in Kerala, India. Through a rigorous critical discourse analysis of selected Malayalam films, this research identifies recurring thematic patterns, visual motifs, and narrative strategies employed to depict the complex experiences of tribal populations, including land rights violations, cultural erosion, and systemic social marginalization. The study posits that Malayalam cinema serves as a pivotal platform for amplifying marginalized tribal voices, challenging dominant socio-political narratives, and advocating for the recognition and protection of indigenous rights. By meticulously analyzing the intersection of cinematic representation, human rights discourse, and tribal identity, this research aims to contribute to a deeper understanding of cinema's role in shaping public discourse and fostering social justice in India, particularly concerning indigenous communities.

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Visualization, Malayalam films, tribal issues, human rights, indigenous representation, critical discourse analysis, social justice, land rights, cultural erosion

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Creating Images Descriptions is a critical interdisciplinary research field, involves generating descriptive text for visual content using deep learning models and Natural Language Processing (NLP). The objective of this project is to develop an automated system that accurately analyzes and describes images, bridging the gap between visual and linguistic information. Through the integration of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), this project utilizes the feature extraction capability of CNNs to capture key visual attributes of images, followed by RNNs, particularly Long Short-Term Memory (LSTM) networks, which process these features to generate coherent and contextually relevant captions. This project involves multiple phases: dataset collection and preprocessing, model training, and caption generation. A large, annotated dataset such as MS COCO or Flickr30k serves as the foundation, providing both images and associated textual descriptions to train the model effectively. The model undergoes supervised learning to understand complex patterns and associations between visual features and language, allowing it to describe new images accurately. Transfer learning and fine-tuning techniques further optimize model accuracy, making it adaptable to diverse image types. Furthermore, NLP techniques like tokenization and embedding enhance the language model's ability to generate fluent and contextually precise captions. This image captioning model has significant applications, including assisting visually impaired individuals, automated content generation, and enhancing image retrieval systems. The project aims to achieve a robust, scalable solution that contributes meaningfully to AI-driven accessibility and automated interpretation of visual media.

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Image Captioning, Deep Learning, Natural Language Processing (NLP), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), Transformer Models, MS-COCO Dataset, Flickr8k Datasets, BLEU Score, CIDEr Score.

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Concrete is a composite material,which is composed by ordinary Portland cement,water and also included granular aggregates which are fine aggregate and coarse aggregate .The increasing demand for sustainable and high-performance construction materials has led to the exploration of alternative cementitious materials. This study investigates the potential of M30 concrete grade having a partial replacement of cement by natural zeolite , focusing on its effects on self-curing properties and strength enhancement. Zeolite, a naturally occurring aluminosilicate, is known for its high water retention capacity and pozzolanic activity, making it a promising candidate for improving concrete performance. In this research, different replacement levels of cement with zeolite by 5%,10%,15%,and 20% of cement weight were evaluated for their impact on workability, hydration, compressive strength, and self-curing efficiency. To evaluate the performance of this modified concrete, both fresh and hardened properties are analyzed. Fresh properties, such as workability and slump, are tested to ensure the concrete mix remains practical and easy to handle during placement. Hardened properties, including compressive strength and split tensile strength are measured after 7days and 28 days.To understand the performance of concrete at different levels of zeolite Powder replacement,the cubes were cast and evaluated after seven and twenty-eight days.The best percentage of replacement of zeolite in cement is calculated by performing tests on the cubes casted with zeolite replacement ratios in concrete.

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Zeolite, Superplatisicer, M30 Grade , Compressive Strength, Split Tensile Strength.

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The research focuses on key GHRM practices such as green recruitment and selection, green training and development, green performance management, employee participation in environmental initiatives, and green compensation and rewards. The study investigates how these practices contribute to improved organizational outcomes such as cost efficiency, employee productivity, corporate image, regulatory compliance, and sustainable innovation.

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Green Human Resource Management (GHRM), Corporate Performance, Sustainable HR Practices, Environmental Sustainability, Green Recruitment, Green Training and Development.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper analyzes the effect of reforms on the 'free and fair' elections of India in the context of democracy, revealing the shortcomings of democracy in Indian perspective, especially concerning election sobriety and minimal conditions for actually free elections. The Indian experiment of democracy in creating an electoral system after the Indian Constitution is an indicator of the growth of democratic ethos in the nation and the radical changes desired by enlargement of suffrage, honesty in elections, and minimization of malpractices. The country's electoral system modernization was facilitated by the People's Representation Act, the growing role of the Election Commission of India, and the use of Electronic Voting Machines (EVMs). Despite these reforms, the electoral system of India continues to experience persistent challenges. The research targets critical concerns of modern-day elections such as the social and conventional muscle resources, increasing political influence of prisoners, breach of political norms, and cyber political battles via social media. Such issues threaten the sovereignty of a democratic nation and have much graver consequences in the long-term democratic process. The paper also examines the laws that are tied to the Constitution governing elections in India with specific focus on the role of democracy in India.

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Electoral Reforms, Democracy, India, Constitutional Perspectives, Free and Fair Elections

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