Volume 12 | Issue 5 |

 Abstract

This case study aims to highlight the integration among st all first year subjects done to the O.P.D level cases observed by the first B.H.M.S students as prescribed by National commission for homoeopathy through the newly introduced Competency based dynamic curriculum (C.B.D.C) in 2023. This kind of integration would be an exhaustive exercise and needs a thorough study of the case prior to the actual evaluation, however, it fosters a comprehensive understanding of each case by making the results less subjective.

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 Keywords

Acute case based learning----Integrated learning----Homoeopathic prescriptions

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 Abstract

This study investigates the structural integrity of a tricycle frame using finite element analysis (FEA) in ANSYS. The research focuses on identifying stress distribution, deformation, and potential failure points under various loading conditions. The tricycle frame model, designed with specific material properties, is subjected to realistic boundary conditions and loads to simulate operational stresses. Validation of the simulation model is performed through comparison with theoretical calculations and existing experimental data. The results reveal critical stress regions and deformation patterns, providing insights into design vulnerabilities and areas needing reinforcement. This analysis contributes to optimizing tricycle frame design for improved durability and performance. The findings align with existing literature, offering both confirmations and novel perspectives on tricycle frame structural behavior. Recommendations for design enhancements and suggestions for future research are also presented, aiming to advance the field of vehicle frame engineering.

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 Keywords

Tricycle frame, Finite element analysis (FEA), Structural integrity, ANSYS simulation, Stress distribution

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Heart disease remains a leading cause of mortality worldwide, necessitating the development of accurate predictive models for early diagnosis. This paper presents a heart disease prediction system based on the Naive Bayes algorithm. Utilizing a dataset from the UCI Machine Learning Repository, we preprocess the data, implement the Naive Bayes classifier, and evaluate its performance. The results indicate that the Naive Bayes algorithm provides a reliable prediction with an accuracy of XX%, demonstrating its potential in clinical applications.

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 Keywords

Heart Disease, Naive Bayes, Machine Learning, Predictive Model, UCI Dataset

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Blockchain technology can benefit in many ways in the supply chain as it does in many other application areas. Employing blockchain in supply chain processes provides transparent, decentralized, secure, faster and low cost transactions. By eliminating unnecessary third parties and covering more daily life processes in digital systems minimizes paperwork. Blockchain establishes trust among trading partners. Making more detailed data available in blockchain, improves supply chain monitoring ability and safety. Thus, increasing focus on providing integration and cooperation with technologies such as Artificial Intelligence, Big Data Analytic, Cloud Computing and IoT will help to realize advanced supply chain systems.

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Blockchain, Supply chain, Smart contracts, traceability, efficiency, transparency

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The rapid development of e-commerce, e-banking, and social organizations has exposed a large number of phishing attacks to cyber security systems. To support the viability of anti-phishing efforts, we present an advanced scientific show based on machine learning. In this image, six specific calculations are tuned: estimated recurrence, K- nearest neighbours, trusted Bayes, random forest, support vector machine, and extreme gradient boosting (XGBoost). Our study used a large dataset consisting of 58,000 genuine and 30,647 phishing websites, each with 112 characteristics. Improvements in highlight selection, including dataset tuning and removal of immutable highlights, have generally improved the execution process. Extensive testing of eight unique scenarios showed that all calculations reliably achieved over 93% accuracy, with XGBoost achieving the highest score. Accuracy is 99.2%, precision is 99.1%, recall is 99.4%, and specificity is 99.1%. Additionally, the Foremost Component Examination (PCA) technique was used to significantly reduce the XGBoost calculation execution time from 1500ms to 869ms. These findings validate the suitability of our strategy for both offline and real-time dispatch, highlighting its reasonable relevance in modern cyber security operations.

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 Keywords

Phishing Detection, Machine Learning Algorithm, Feature selection, Dataset, Model Evaluation Random Forest, SupportVector Machine, Machine Extreme Gradient, Feature Engineering Performance Metrics.

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 Abstract

Background: A stroke is often described as a Cerebral Vascular Accident. Many people don't know what a stroke is or why it happened. It is important to know about stroke when caring a stroke patient. Patient and family education is a fundamental component of rehabilitation, ample opportunity for learning about the stroke causes and prevention. The gain in knowledge will reduce the caregiver burden and will contribute to improve the quality of life of both the patient and caregiver. Aim: The aim of this study was to assess the knowledge among the caregivers of stroke patient regarding home care management, to assess the practices among the caregivers of stroke patient regarding home care management, to correlate the knowledge and practices among the caregivers of stroke patient regarding home care management, to associate the knowledge and practices among the caregivers of stroke patient regarding home care management with selected demographic variables. Methodology: Quantitative Descriptive approach with Descriptive research design was adopted for the study. Non probability convenient sampling technique was used to draw 50 caregivers of stroke patients from GRNC (Dispur) hospital. Data collection was done by using structured demographic performa, structured knowledge questionnaire and practice checklist. Results: Out of 50 samples, 10 samples (20%) had inadequate knowledge, 23 samples (46%) had moderately adequate knowledge and 17 sample (34%) had adequate knowledge. The overall mean knowledge score was found to be 18.50 and standard deviation 3.30. Out of 50 samples, 28 sample (56%) had inadequate practices and 22 samples (44%) had moderately adequate practices. The overall mean score of practice was 17.44 standard deviation 1.89. The study also revealed that there was positive correlation between knowledge and practice of caregivers is 0.42. There was no association between knowledge and practice of caregivers of stoke patients with selected demographic variables. . Conclusion: The study concluded that most of the caregivers of stoke patients had moderately adequate knowledge and moderately adequate practices regarding home care management of stroke patient. Therefore an information booklet on home care management of stroke patient was prepared and distributed by the investigator to help the caregivers to know more about the care of stroke patient.

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 Keywords

Knowledge, practice, caregivers and stroke patient

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In this research paper, we will explore how web engineering techniques can be used to improve the performance and user experience of Indian traveling websites. We will also look at the key engineering challenges that these platforms face, such as scalability and reliability, as well as security and UI design. We will combine empirical analysis with user studies and best practices to present strategies for improving the website's functionality and usability. We will also explore how to integrate advanced technologies like machine learning to provide personalized recommendations, and data analytics to understand user behavior.

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 Keywords

Tourism Industry | Web Engineering |Economic Impact | Data Analytics |Tourism in India | GDP | Culture Heritage | Employment in Tourism | FTA | Websites

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Rucaparib, RP-HPLC, Validation, Accuracy, Precision, Robustness, ICH Guidelines.

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Aim-The present study aims at assess the effect of teaching cum demonstration on knowledge regarding selected aspects of Essential Newborn Care among postnatal mothers. The present study is based on General System Theory (Ludwig von Bertalanffy). Introduction- The Essential Newborn Care Course (ENCC) aims to ensure health workers have the skills and knowledge to provide appropriate care at the most vulnerable period in a baby's life. Health workers are taught to use WHO's Pregnancy, Childbirth, Postpartum and Newborn Care. The investigator during her clinical posting observed that postnatal mothers were not having sufficient knowledge regarding newborn care, so that's why their baby becomes sick and unhealthy. Globally 4 million newborns die every year before they reach the age of one month and approximately 3.4 million newborns die within the first week of life. Objective-The main objective of the present study is to assess the pre-existing knowledge regarding selected aspects of Essential Newborn Care among postnatal mothers. Methodology-The research approach is quantitative approach and the design selected for the study is pre-experimental design, in which one group pre-test - post-test design. Sampling technique is convenience sampling. Samples consists of 30 postnatal mothers who was admitted in selected hospital and those postnatal mothers who satisfies the inclusion criteria are considered as samples. Content validity is done with the help of experts. Split-Half method is used to check the reliability. Result- Evaluate the effect of teaching cum demonstration on selected aspects of Essential Newborn Care among postnatal mothers. And associate the knowledge with selected demographic variable among postnatal mothers. The mean 22.433 of post-test score was more than the mean 13.200 of pre-test score of postnatal mothers. There is total enhancement occur 9.233. The comparison of Pre-test and post-test knowledge on selected aspects of Essential Newborn Care among postnatal mother had significant difference with t value (13.052) at p< 0.05 Level of significance. Conclusion- From this study researcher found that the postnatal mothers have gained knowledge on selected aspects of Essential Newborn Care among postnatal mothers.

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Keyword: Teaching cum demonstration, Knowledge, Postnatal mothers.

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 Abstract

Smart home security and remote monitoring have become vital and indispensable in recent times, and with the advent of new concepts like Internet of Things and development of advanced authentication and security technologies, the need for smarter security systems has only been growing. The design and development of an intelligent web-based door lock control system using face recognition technology, for authentication, remote monitoring of visitors and remote control of smart door lock have been reported in this paper. This system uses Haar-like features for face detection and Local Binary Pattern Histogram (LBPH) for face recognition. The system also includes a web-based remote monitoring, an authentication module, and a bare-bones embedded IoT server, which transmits the live pictures of the visitors via email along with an SMS notification, and the owner can then remotely control the lock by responding to the email with predefined security codes to unlock the door. This system finds wide applications in smart homes where the physical presence of the owner at all times is not possible, and where a remote authentication and control is desired. The system has been implemented and tested using the Arduino Uno Board, Python along with OpenCV are used to program the various face recognition and control modules.

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 Keywords

Arduino Uno, Face Module Camera, Motion Sensor, Wire.

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