Volume 12 | Issue 6 |

 Abstract

Abstract: Background: In the ever-evolving landscape of healthcare delivery, domiciliary emerged as a dynamic approach to community well-being at Medical College. From a research healthcare services have perspective, undertaking social responsibility and extension activities contributes to a deeper understanding of community dynamics and fosters meaningful connections between academia and society. This research embarks on a comprehensive investigation, seeking to evaluate the profound impact of domiciliary healthcare on individual families, community health, student learning, and the overall functioning of the Medical College Hospital. Initiated in the year 2000, this programme involves medical students adopting five families each, engaging in periodic Saturday visits to conduct surveys and deliver health education and health care. The families, recipients of tailored health education encompassing nutritional, environmental, residential, and personal hygiene practices, are empowered to protect themselves from both communicable and non-communicable diseases, emphasizing maternal and child healthcare family planning etc. Objectives Evaluate the impact of domiciliary healthcare on individual families, community health, student learning, and the overall functioning of the Medical College Hospital. 1. To measure the level of communication between medical students and adopted families by at end of one year of completing the domiciliary healthcare program. 2. To quantify the level of health education content among adopted families through post-program assessments conducted after the program's conclusion. 3. To ensure a sustained increase in the utilization of services at Motiwala National Homeopathic Medical College and Hospital by adopted families, as measured through monthly data reviews for six months post-program. 4. To measure a statistically significant shift in behavior towards health promotion and disease prevention, in healthy practices within adopted families, assessed post-program. 5. To demonstrate improvement in the nutritional status and residential environment of adopted families, as assessed through follow-up surveys conducted post-program. 6. To obtain a satisfaction rate among family members, as measured through post-program surveys assessing their subjective grading of the domiciliary healthcare system within one year of program completion. Method The research was designed as a Longitudinal Observational Study, spanning one year with regular interval follow-ups with health education for interventions. Data collection involved a longitudinal survey conducted throughout the study period. At the conclusion, comprehensive feedback was obtained from each adopted family. The researcher focused on assessing healthy modifications, utilizing structured questionnaires to gather feedback from the adopted families. The evaluation of this feedback played a pivotal role in determining the impact of the program. Result The qualitative analysis, drawing insights from a robust dataset of feedback, provided a nuanced understanding of the program's overall perception and its profound impact on the neighboring community. This encompassed both qualitative and quantitative feedback. As the study concluded, a thoughtfully introduced set of questions enabled a systematic quantitative analysis. The amalgamation of qualitative richness and precise quantitative data culminated in compelling research results, affirming the program's success in positively influencing the community. . .

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

: Domiciliary Health care, System, Family adoption programme ,structured questioner, qualitative and quantitative and qualitative analysis

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Many people use backpack because more flexible and easier to carry. Backpack can carry a lot of things. But, nowadays, lots of crimes of stolen backpack especially in public transportations or public areas. People are getting worried of their backpack and wants to have smart backpack that can protect the things they are carried. The objective of this research is to design smart backpack which consist of ultrasonic sensor, LDR sensor, GPS, buzzer and telegram application. The result of testing shows that backpack sends notification to telegram application if someone is trying to open backpack and buzzer is ringing. The location of backpack is also sent to telegram application so the owner of backpack knows the exact location of his backpack.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart Backpack, Ultrasonic Sensor, LDR Sensor, GPS, Telegram Application

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: Since social media platforms are still necessary for worldwide communication, strong security measures are now imperative. A three-step verification procedure is recommended by this study to increase the security of user accounts on social networking sites. The conventional username-password authentication mechanism may be vulnerable to a variety of cyber threats, of which phishing attempts and password leaks are just two examples. The initial stage establishes a foundational security layer using traditional username-password authentication. The second stage introduces MFA.the suggested three-step verification system reduces the danger of illegal access. Conventional username-password authentication is used in the first phase to create a basic security layer. In the second phase, MFA is introduced. It provides an extra layer of authentication to prevent hacked login credentials by sending OTPs to the user's registered.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mulitfactor Aurthentication (MFA),one-time passwords(OTP),Addharcard verification.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The research in a quantitative manner is all-encompassing and based on its asset size concerning the sample of public and private sector banks over the last decade. Key parameters of credit risk management including credit risk exposure, provisioning policies, and techniques of mitigation are evaluated to determine the contribution towards technological efficiency. Data Envelopment Analysis is used to check on technical efficiency, giving a robust framework on how effectively banks convert their inputs into outputs in the atmosphere of controlling credit risk. Several indicators for measuring financial performance are used, such as return on assets, return on equity, and the ratio of non-performing assets. This analysis carries a target to reveal those relationships between practices in credit risk management, operational efficiency, and financial health. Results suggest that banks having stringent frameworks for credit risk management exhibit higher technical efficiency, which ultimately is transmitted to better financial performance. In other words, banks managing their credit portfolio in a proactive manner and applying advanced tools for risk assessment are in a better position to reduce NPAs and increase their profitability. Critical areas in which Indian banks need improvement in credit risk management practice for enhanced technical efficiency and financial resilience include the following: Hence, the findings of the report could serve as guidelines and strategic suggestions for the policy makers, regulators, and banking institutions on the way for improving the process of credit risk management and focusing on efficiency gains. In view of the importance of integrating credit risk management and focusing on efficiency gains, this study contributes to the steps being taken to strengthen the Indian banking sector for future financial challenges so that sustainable growth and stability remain the cornerstones of the economy

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

CREDIT RISK MANAGEMENT, TECHNICAL EFFICIENCY AND FINANCIAL PERFORMANCE

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Numerous different kinds of bacteria, fungi, and viruses reside in the human epidermis. It has been established that these bacteria vary between individuals and between different parts of the skin. Although the causes of the skin microbiome's particular heterogeneity are still not fully understood, the findings indicate that host genetic and environmental factors play a key part. Although the causes of the skin microbiome's particular heterogeneity are still not fully understood, the findings indicate that host genetic and environmental factors play a key part. Recent metagenomic studies that have uncovered a remarkable variety within these ecosystems have prompted a new understanding of commensal microbes as having a significantly broader function in immune control and epithelial health than previously understood.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Skin Microbiome, Atopic dermatitis, Staphylococcus aureus, Staphylococcus epidermidis, Immunity, Metagenomics, Antibiotic

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cognitive Sensor Networks (CSNs) have emerged as a critical component in the development of smart environments, enabling more intelligent and adaptive systems. Integrating advanced machine learning (ML) techniques within CSNs can significantly enhance their capabilities, leading to higher accuracy in data analysis, improved energy efficiency, and greater adaptability. This paper explores various ML techniques, including supervised learning, unsupervised learning, reinforcement learning, and deep learning, and their application in CSNs. We propose a comprehensive system architecture that leverages these techniques for efficient data processing, adaptive decision-making, and resource management. Comparative numerical analysis demonstrates the proposed system's superior performance over traditional systems, highlighting improvements in detection accuracy, energy consumption, latency, and adaptability. The results indicate that ML-enhanced CSNs can provide more efficient and responsive smart environment applications. Future research directions are discussed to further refine these techniques and explore their application in diverse real-world scenarios.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cognitive Sensor Networks (CSNs), Machine Learning (ML), Smart Environments, Data Analysis, Energy Efficiency, Adaptive Systems

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this regard, the Internet of Things (IoT) based Smart Shopping Cart is proposed which consists of Radio Frequency Identification (RFID) sensors, NodeMCU

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Iot based smart cart

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Visual sorting application developed using Html, CSS, JavaScript, Bootstrap, React.js (Frontend), Node.js (Backend). A study that tested the benefits of animated sorting algorithms for teaching. To visualize four sorting algorithms, a web-based animation application was constructed and visualization of data is implemented as a bar graph, after which a data sorting and algorithm may be applied. Data Structures and Algorithm (DSA) Can play a crucial role in a visual sorting application. In this application used to visualize seven commonly sorting Algorithm: Bubble sort, Selection sort, Quick sort, Merge sort, Heap sort and Tim sort .

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

- Sorting Algorithm Visualization, Sorting Algorithm Demos, Interactive Sorting Algorithms, Array Sorting Visualization

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Major cities have been growing very fast due to good facilities for health and education. These also provide plenty of employment opportunities. The growing population also increases solid waste, which is the main cause of health hazards and pollution. So it needs an environment-friendly solution for its disposal. Only 31% of the Indian population resides in urban areas, this population generates a gigantic 1,43,449 metric tonnes per day of municipal solid waste, as per the Central Pollution Control Board, 2014-15. To further add to the problem, the total number of towns in the country has also increased from 5,161 in 2001 to 7,936 in 2011, thus increasing the number of municipal waste generation by 2,775 within a decade (GOI-manual, 2016). The three landfills in the national capital, Delhi i.e. Ghazipur, Bhalswa and Okhla landfills are examples of mismanagement of solid waste management. It can be possible by involving people at large and giving them good opportunities to earn from this garbage. This paper throws light on this grave concern and searches for people's awareness on a large scale to stimulate their participation and form a habit of solving this problem from its source of origin.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Solid Waste, Garbage, pollution, people, environment

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents a comprehensive comparative analysis of various Artificial Intelligence (AI) algorithms utilized for the prediction of Polycystic Ovarian Disease (PCOD). PCOD, a multifaceted endocrine disorder affecting women, poses diagnostic challenges due to its diverse clinical manifestations. Imposing AI in healthcare, particularly for predictive modeling, has gained traction for its potential to enhance diagnostic accuracy and treatment outcomes. This study systematically evaluates and compares the performance of distinct AI algorithms employed in PCOD prediction using relevant datasets. The findings of this comparative analysis aim to guide practitioners and researchers in selecting the most suitable AI algorithms for effective PCOD prediction, thereby facilitating early diagnosis and personalized healthcare interventions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

PCOD Prediction, Artificial Intelligence Algorithms, Machine Learning Techniques, Healthcare Applications

  License

Creative Commons Attribution 4.0 and The Open Definition