Volume 13 | Issue 4 |

 Abstract

Diabetes are widespread health issues around the world. Both Insulin Dependent (Type 1) Diabetes Mellitus and (Type 2) Diabetes Mellitus are prevalent, with Type 2 diabetes being more common and often associated with lifestyle and diet. The prevalence of heart disease varies by region, but it affects people of all ages, genders, and backgrounds. Neural networks techniques have been applied to diabetes in various ways to assist in diagnosis, management, and treatment. Neural networks can be used to develop predictive models that analyses patient data, including Cholesterol, BMI, to diagnose diabetes or predict the risk of developing diabetes in the future. Neural networks can be trained to predict the risk of diabetes. The existing dataset is pre-processed. Using feature extractions, highly correlated features are extracted. The performance of the model was evaluated through accuracy. A user interface was also developed for clinical use.

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 Keywords

Random Forest, BPNN, PCA, CV, ECV, Cardiovascular, Diabetic,PSO

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 Abstract

Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such as URL length, domain age, HTTPS usage, and redirection patterns to train a CNN model.The potential applications include browser extensions, email filters, and cybersecurity tools. The proposed approach improves user protection against phishing attacks and mitigates the risks associated with it. This research underlines the efficiency of machine learning in dealing with dynamic and evolving cybersecurity challenges.

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 Keywords

Phishing Detection, URL Analysis, Machine Learning, Deep Learning, Feature Extraction, Decision Trees, Real-Time Detection, Convolutional Neural Networks (CNNs)

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 Abstract

A dual-axis steering mechanism is an advanced steering system that allows a vehicle or robotic system to operate with two independent axes of rotation, usually one horizontal and one vertical. This innovative mechanism is designed to provide enhanced maneuverability, precision, and control over conventional single-axis steering systems. By enabling movement along both axes simultaneously or independently, the dual-axis steering mechanism significantly improves a vehicle's ability to navigate through tight spaces, sharp turns, or uneven terrains. In traditional steering systems, movement is restricted to a single axis, typically horizontal, limiting the vehicle's ability to change direction efficiently or perform complex maneuvers. The dual-axis system, on the other hand, allows for more versatile movement, including the ability to make sharp turns while maintaining stability, reduce the turning radius, and increase the adaptability of the system in diverse environments. This makes the dual-axis steering particularly valuable for applications in autonomous vehicles, off-road vehicles, and robotic systems where precise control and navigation are essential. The dual-axis mechanism involves intricate mechanical components, such as rotating joints, actuators, and control systems, which work together to achieve independent movement on both axes. While offering significant benefits in performance, such systems also introduce challenges related to mechanical complexity, weight distribution, energy efficiency, and durability. Nonetheless, the advantages in terms of improved maneuverability, stability, and control make the dual-axis steering a promising technology for future applications in various fields, including robotics, autonomous vehicles, and specialized transportation systems. The dual-axis steering mechanism represents a significant advancement in steering technology, offering enhanced maneuverability, precision, and control compared to traditional single-axis systems. By enabling independent movement along both horizontal and vertical axes, it allows vehicles and robotic systems to navigate complex environments with greater ease, making it especially valuable in applications like autonomous vehicles, off-road navigation, and robotics. While the implementation of dual-axis steering presents challenges such as mechanical complexity, energy efficiency, and weight management, the potential benefits in terms of improved stability, reduced turning radius, and increased adaptability outweigh these obstacles. As technology continues to evolve, the dual-axis steering mechanism is poised to play a pivotal role in the future of advanced mobility and autonomous systems, driving innovation and performance across various industries.

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 Keywords

Conventional steering mechanism,constant velocity axle,Design and planning

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 Abstract

The research conducted focused on examining the unique properties of Agave Americana Flower Stem fiber (AAFS), particularly its behavior under quasi-static tensile conditions. A total of 200 AAFS fibers were subjected to tensile tests using a standard gauge length of 40 mm. Tests spanned seven groups with quantities (N) ranging from 30 to 200. The study aimed to understand the fibers' mechanical traits, as tensile resistance and modulus of elasticity, and to see how different test quantities influence these properties. A significant observation was the dispersion of the tensile characteristics of AAFS fibers, a common trait of natural fibers. To understand this, we applied rigorous statistical tools, including the Weibull distribution at a 95% confidence interval and one-way ANOVA. A mathematical model was produced utilizing data from experiments regarding the tensile behavior of AAFS fibers. The ANN provided correlation coefficients (R2) of 0.9897, 0.9971, 0.9993, and 0.9939 for training, validation, testing, and all datasets respectively, which were able to accurately predict the experimental data. The proposed model would be of tremendous assistance to engineers and designers in obtaining green composite materials that are based on natural fibers and thereby more durable. These methods illuminated the patterns in our results, enriching our understanding of AAFS fiber mechanics.

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 Keywords

Agave americana, Artificial neural network, tensile behavior, statistical methods,Weibull, statistic, hazard function, Wireless sensor network.

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 Abstract

AI Resume Analyzer is an intelligent system that leverages Natural Language Processing (NLP) and Machine Learning to evaluate resumes efficiently. It extracts key information, matches qualifications with job descriptions, and provides insights to streamline recruitment, ensuring accurate, unbiased, and faster candidate screening for HR professionals and employers.

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 Keywords

NLP (Natural Language Processing) Resume Parsing, Resume Analysis, Google Gemini AI, Streamlit Application, Skill Gap Detection, Career Recommendation System, OCR Resume Parsing

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Creative Commons Attribution 4.0 and The Open Definition

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Ayushman Bharat, launched by the Government of India in 2018, represents a landmark reform in the country's healthcare landscape. Envisioned as a step toward Universal Health Coverage (UHC), the scheme combines health insurance for secondary and tertiary care with the establishment of comprehensive primary healthcare infrastructure. This article examines the structure, objectives, implementation, achievements, and emerging challenges of Ayushman Bharat, with a focus on its role in transforming India's healthcare delivery system.

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 Keywords

Ayushman Bharat, Universal Health Coverage (UHC), Public-private partnership, Pradhan Mantri Jan Arogya Yojana (PM-JAY), Health and Wellness Centres (HWCs), out-of-pocket Expenditure

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The aim of this study was to evaluate the knowledge gap by assessing the knowledge and attitude regarding pulmonary TB among the rural population of Charar-i- Sharief Budgam Kashmir. This descriptive study aims to assess the level of knowledge and attitude towards pulmonary tuberculosis (TB) among the rural population of Charar-i-Sharief, Budgam, Kashmir. A quantitative research approach was adopted, and a convenient sampling technique was used to select participants. Data were collected using structured questionnaires for assessing knowledge and attitude, with an interview schedule to facilitate data collection. Data collected was organised and analysed according to the objectives of the study using descriptive and inferential statistics.

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 Keywords

Knowledge, Attitude, pulmonary tuberculosis, AFB, DOTS.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research focuses on the creation and assessment of CNN-based models to categorize brain tumors into three main groups: pituitary, meningioma, and glioma. The suggested model is trained and validated using an MRI dataset that is openly accessible. To maximize performance, the study investigates different CNN architectures, pre-processing methods, and training approaches. The efficacy of the model is evaluated using key evaluation metrics like accuracy, precision, recall, and F1- score.

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 Keywords

Brain Tumor Classification, Convolutional Neural Networks(CNN), Magnetic Resonance Imaging(MRI), Deep Learning, Medical Image Analysis, Transfer Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Students frequently struggle with academic anxiety, which impairs their capacity to study and perform well. Simultaneously, metacognition--the understanding and control of one's own mental processes--is essential for academic achievement. In order to comprehend how students view and control their anxiety through metacognitive techniques, this qualitative study investigates the connection between academic anxiety and metacognitive skills. Semi-structured interviews with college and high school students were used to gather data, and thematic analysis was used to find important trends. According to research, students who regularly practice metacognition report feeling less anxious and performing better academically. Implications for educational interventions and future research areas are discussed in the study's conclusion.

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 Keywords

academic anxiety, metacognition, qualitative, interventions.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the twenty-first century the advancement and rapid development in the field of Information and Communication Technology (ICT) has brought change in use and pedagogy of English language. It has also enabled new forms of discourse as well as knowledge and new ways to create and participate in communities. Freeman and Anderson have pointed out in their book 'Techniques & Principles in Language Teaching' - "Rapid evolution of communication technologies has changed language pedagogy and language use, enabling new forms of discourse, new forms of authorship and new ways to create and participate in communities (Kern 2006:183, cited in Freeman and Anderson 2019: 200)". Internet and Social Media are the part of ICT that have tremendous effect on daily activities of human life. People spend much of their time on internet and social media for various purposes like entertainment, acquiring knowledge, sharing and collecting data and information, and so on. It provides lots of opportunities and creates attractive environment to learn English language easily. At the same time it also provides the liberty to distort the standard format of language use. Internet enables the users share information, ideas, data and services through various platforms of ICT. It connects billions of users across the globe. Social media platforms like Twitter, YouTube, Instagram, Facebook, and so on provide a space to create an interesting and entertaining environment to learn English language efficiently, as English is used frequently on these platforms. Internet and social media facilitate and motivate the learners to learn English language in an unconscious way. English language plays a crucial role in modern life and is also influencing each and every field of human activities like education, trade and commerce, art and culture, research and development, science and technology, administration and jurisdiction and many more. The purpose of this research paper is to explore the role of various internet services like online music, email, webpages as well as some educational websites and social media platforms in gaining competence in the use of English language, in both spoken and written forms. ICT encourages the learners to develop the four language skills, like listening, speaking, reading, and writing and components (pronunciation, vocabulary, phrase, sentence formation and its use in proper context) of English language. It can be practised by language learners through constant use of audio- visual aids, emails, chats, messages, reading a novel in English, visiting e-library, the meaning of emoji or icon and logo. It helps in interacting and communicating with English language experts on internet.

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 Keywords

Communication Skills, ELT, ICT, Internet, Social Media, Technology.

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Creative Commons Attribution 4.0 and The Open Definition