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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ComputerVision, Screening, Diagnosis, Healthcare, Automation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: 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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition