Volume 13 | Issue 4 |

 Abstract

The design of a system capable of heating two magnetically independent ferromagnetic loads placed on different horizontal planes, which uses a combination of induction heating and inductive coupling, called inductively coupled heating. The system uses a single primary inductor acting as a transmitter to transfer power to a secondary inductor attached to the bottom load, which is connected electrically with a third inductor that heads the top load. Since power of the whole system is supplied by a simple half bridge inverter, the ratio of the delivered power to each of the loads, which is critical for cooking results, is entirely dependent on the systems geometry, coil's number of turns, and compensation capacitors. The proposed system utilizes a unique coil design and control algorithm to efficiently transfer energy to both loads, while maintaining precise control over the heating process. The advantages of this approach includes reduced material costs, increased reliability, simplified design.

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 Keywords

Induction heating (IH), Inductive coupling, Wireless Power Transmission

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 Abstract

ABSTRACT This study assesses the effectiveness of a structured teaching program in improving knowledge about postmenopausal symptoms and their management among women. Postmenopausal symptoms can significantly impact a woman's quality of life, yet awareness and understanding of these symptoms and effective management strategies are often limited. A quasi-experimental design was used, involving [sample size, e.g., 50] postmenopausal women from [location] who were selected through [sampling method, e.g., convenience sampling]. A pre-test assessed participants' baseline knowledge, followed by a structured teaching program over [duration, e.g., two weeks]. Post-intervention knowledge was then measured using a standardized questionnaire, and pre-test and post-test scores were statistically analyzed to evaluate the program's effectiveness. The results revealed a significant increase in knowledge about postmenopausal symptoms and their management following the intervention, indicating the structured teaching program's positive impact. This study suggests that structured education programs can effectively raise awareness and enhance understanding of postmenopausal health, equipping women with information to manage their symptoms better and improve their overall well-being. Further research could expand on these findings across diverse populations and longer timeframes to validate and generalize the effectiveness of such programs. INTRODUCTION When a woman permanently stops having menstrual periods, she has reached the stage of life called menopause. Often called the change of life, this stage signals the end of a woman's ability to have children. Many healthcare providers actually use the term menopause to refer to the period of time when a woman's hormone levels start to change. Menopause is said to be complete when menstrual periods have ceased for one continuous year. The transition phase before menopause is often referred to as perimenopause. During this transition time before menopause, the supply of mature eggs in a woman's ovaries diminishes and ovulation becomes irregular. At the same time, the production of estrogen and progesterone decreases. It is the big drop in estrogen levels that causes most of the symptoms of menopause. OBJECTIVES: 1. To assess the effectiveness of a structured teaching program on enhancing women's knowledge of postmenopausal symptoms and their management. 2. To implement a structured teaching program focusing on postmenopausal symptoms and management strategies. 3. To evaluate the change in knowledge on postmenopausal symptoms and their management among women following the structured teaching program. 4. To compare pre- and post-intervention knowledge levels to determine the effectiveness of the structured teaching program. 5. To identify factors influencing the knowledge acquisition regarding postmenopausal symptoms and management among participants (e.g., age, educational background, prior health knowledge). METHODOLOGY The present study was conducted to evaluate the A study to assess the effectiveness of structured teaching programme on knowledge of postmenopausal symptoms and its management among women of village saunti district fatehgarh sahib .The population in the present study include 400 postmenopausal women at selected village. the sample were drawn by Purposive Sampling Technique. The data was collected by a structured demographic sheet and self-structured questionnaire. Findings of the Study: Major Findings are: ? With regards to age, mostly 65 (32.5%) were in the age group of 49 -52 years in experimental group and similarly most of them 65 (32.5%) were in the age group of 49 - 52 years in control group also. More or less similar percentages (31% and 30.5% and 17% and 18%) of them were in the age group of 53-56 and 57- 60 years in experimental group and control group. ? 73 (36.5%) were belong to socioeconomic status of Rs. 2001 - Rs.3001 in experimental group and more or less similar findings 76 (38%) were belong to socioeconomic status of Rs. 2001 - Rs.3001. Higher percentages of (30%and 29.5%) were in the socioeconomic status of Rs. 3001 - Rs.4001 in both the groups. ? With regards to education, majority 83 (41.5%) had primary education in experimental group and 63(31.5%) had no formal education in control group. More or less similar percentages (26.5% and 28.5%) of them had secondary education in experimental group and control group. Only 4.5% and 5% of them were graduates in both groups. ? With regard to occupation, majority 114 (57%) and 99 (49.5%) were housewives in both the groups. 21% and 26% were sedentary workers in both the groups. Only 5% and 5.5% of them were heavy workers in both groups. ? In the current study, more or less similar 105 (52.5%) and 107 (53.5%) were attained menarche at the age of 13 years in both the groups. 17.5% and 14.5% of them attended the menarche at the age of below 12 years. Only 5% and 2.5% of them attended the menarche at the age of 14 years above. ? In the study findings, 106 (53%) and 86 (43%) were hindus in both the groups. ? Based on their dietary pattern, majority 178 (89%) and 178 (89%) of them had mixed diets. ? With regards to personal habits, 145 (72.5%) and 164 (82%) of them had no bad habits. 14.5% and 12% had the habit of tobacco chewing. Only 13% and 6 % had the habit of betal nut chewing. ? As discussion of findings related to period of cessation of menstruation depicts that majority (47.5% and 46.5%) of menopausal women had cessation of menstruation between 1-2 years in both groups. Similar percentage (30.5% and 29% and 20% and 22%) had cessation of menstruation below 1 year ? With regards to type of family, 94 (47%) and 99 (49.5%) were in nuclear family. 43% and 38.5% of menopausal women were living as a joint family ? About 169 (84.5%) and 165 (82.5%) of them were not used any home remedies for menopausal symptoms in both the experimental group and control group. LIMITATIONS o It was difficult for the investigator to arrange common venue for group yoga practice for Weekly session class o It was time consuming to explain the menopausal women about video yoga therapy demonstration and assessment of menopausal symptoms because of difference in their level of understanding. ? The investigator had constraints in reaching the menopausal women in the evening time during the study period although it was tackled with the help of VHN and Mazhalir Kuzhulu (Local Worker) o Most Menopausal women felt that, teaching yoga at their door step would be convenient. o Data collection time was re-altered by the investigator as per the feasibility of the sample. o Satisfaction of subject would have been difficult to measure. CONCLUSION From the findings it concluded that, In present study the researcher has identified that the Knowledge on menopausal symptoms can be improved by STP (Structured Teaching Programme) and level of menopausal symptoms can be reduced by Yoga therapy, thereby the quality of life among menopausal women was improved and their stress level was significantly reduced. The identified results are highly generalisable because of the increased sample size and presence of control group. REFERENCE ? Abdullah. B & Moize Ismail. B.A (2016) ?Prevalence of menopausal symptoms, its effect on quality of life among Malaysian women and their treatment seeking behavior': Medical Journal of Malaysia: Vol 72, No 2, pp 94 - 99? ? Abedzadeh Kalarhoudi M, Taebi M, and Saberi F( 2011). ?Assessment of? Quality of Life in Menopausal Periods: A Population Study in Kashan, Iran': Iran Red Crescent Med Journal, 13(11): 811-817. ? Abolill. M.Z (2015) ?Prevalence of Menopausal related symptoms and their impact on Quality of life among Egyptian women': Journal of Clinical experience of obstetrics and gynaecology, vol XLII, n (2), pp 983 - 988? ? ACC Ikeme, T C Okeke & SPO Akogu (2011) ? Knowledge and Perception of Menopause and Climacteric Symptoms among a Population of Women in Enugu, South East, Nigeria' : Annals of Medical & Health Science Research .vol; 1(1):pp 31-36.? ? Al Dughaither. A, AlMutairy.H, AlAteeq. M (2015) ?Menopausal symptoms and quality of life among Saudi women visiting primary care clinics in Riyadh, Saudi Arabia': International Journal of Women's Health, Volume:7 Pages 645-- 653? ? Baig L, et al., (2009) ?Association of menopause with osteopenia and osteoporosis: results from population based study done in Karachi' , Journal of Collaborative Physicians Surg Pak, 19 (4),pp 240 -244? ? Bairy L, Adiga S, Bhat P et al (2009) ?Prevalence of menopausal symptoms and quality of life after menopause in women from South India' Aust N Z J Obstet Gynaecol.;49(1):106-109.? ? Bakouei et al. (2013) ?Assessment of women's awareness level about symptoms and complications of menopause', Journal of Local and Global Health Science: pp 1 - 6? ? Bansal P, Chaudhary A, Soni RK, et.al (2013) ?Menopausal problems among rural middle aged women of Punjab', International Journal of Research Health Science; vol 1: pp 103-109? ? Batool Mazhar. S & Rasheed. S (2009) ?Menopause Rating Scale (MRS): A Simple Tool for Assessment of Climacteric Symptoms in Pakistani Women', Annual Pakistan Institute of Medical Science; 5(3): pp 158-161? ? Beigi M et al.,(2012) ? A comparative study on sexual dysfunction before and after menopause,' Iran Journal of Nurses Midwifery Research, ( 2 suppl 1): S 72? -75 ? Bhattacharya P.K Enu Boro (2016) ?Effectiveness of Self Instructional Module on Coping Strategies of Tri-Dimensional Problems of Premenopausal Women - A Community Based Study', Journal of Clinical Diagnostic Research. Vol 10(11): pp 15-18.? ? Caldwell S., Gass, M.L., Kolsky, K., Low Dog. et.al (2012) ?Menopausal symptoms and complementary health practices', Retrieved from http://nccam.nih.gov/health/menopause/menopausesymptoms? ? Cathryn Booth-LaForcea, Rebecca C ( 2007) ?A pilot study of a Hatha yoga treatment for menopausal symptoms', Maturitas, vol 57 (3): 286-295?

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postmenopausal symptoms, knowledge, structured teaching program, women's health, symptom management.

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The Mud Ring Algorithm (MRA) is used in the study to improve the performance of machine learning classifiers in maternal health risk prediction. The technique is applied in two steps: first, MRA increases the predicted accuracy of the Support Vector Machine (SVM) by optimizing its parameters. Multiple datasets are used to assess the model, and it is contrasted with current optimization methods. A crossover oversampling strategy is used in the second stage to rectify the class imbalance in the maternal health risk dataset. K-Nearest Neighbor and Random Forest are two more classifiers that are incorporated to increase prediction accuracy. The suggested method considerably improves classification performance, according to experimental data, with MRAbased optimisation raising accuracy by 11.8% for SVM, 9.11% for Random Forest, and 17.08% for KNN. In order to follow the health of mothers and children, a digital health monitoring system is also introduced. In addition to gathering health data, the technology forecasts hazards including preeclampsia and gestational diabetes and offers real-time insights. Following delivery, it keeps track of immunisations and development indicators, produces digital birth certificates, and documents important infant information. Authorised users can effectively monitor and manage healthcare because data security and accessibility are guaranteed. This strategy streamlines administrative procedures while enhancing maternal and child health outcomes by fusing predictive analytics with automated healthcare management.

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Mud Ring Algorithm (MRA), Maternal Health Risk Prediction, Support Vector Machine (SVM), Parameter Optimization, Crossover Oversampling, Class Imbalance, K-Nearest Neighbor (KNN), Random Forest, Classification Performance, Digital Health Monitoring, Predictive Analytics, Healthcare Management, Preeclampsia Prediction, Gestational Diabetes, Immunization Tracking, Infant Development Monitoring, Data Security, Automated Healthcare.

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Distributed Denial of Service (DDoS) attacks are among the most disruptive cybersecurity threats, targeting the availability of online services. Attackers leverage networks of compromised devices to flood target systems with malicious traffic, rendering them inaccessible to legitimate users. This review explores various DDoS mitigation strategies, emphasizing prevention, detection, and response techniques. We discuss anomaly detection methods, machine learning models, and rate limiting techniques to prevent volumetric attacks. Additionally, we analyse recent advancements and highlight future research directions aimed at improving the effectiveness of DDoS mitigation. which enhance the adaptability and scalability of modern defence mechanisms. Finally, we outline the challenges of mitigating evolving DDoS threats and propose future research directions to strengthen cybersecurity frameworks. Our findings underscore the importance of integrating multiple layers of defines to ensure the robustness of online services against increasingly complex DDoS attacks

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DDoS mitigation, anomaly detection, machine learning, network security, traffic filtering

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Railway accidents are a serious safety issue and are frequently triggered by track failures, signal malfunctions, and train collisions. In this paper, a Railway Accident Prevention System based on IoT-based sensors and real-time communication is proposed to improve railway safety. The system includes LiDAR sensors for detecting rail track cracks, wireless communication modules for train-to-train collision avoidance, and intelligent signaling mechanisms for avoiding human mistakes. The system to be proposed uses an ESP32 microcontroller for processing data and wireless notifications to inform railway authorities of impending dangers. Through real-time monitoring and automation, the system seeks to reduce derailments, signal accidents, and train collisions, making the railway network safer. Experimental results show enhanced accuracy in track anomaly detection and proper communication between trains and control stations. This study emphasizes the viability of IoT-based railway safety solutions for preventing accidents and enhancing operational efficiency.

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Railway Accident Prevention, IoT-based Safety System, Real-time Monitoring, Track Failure Detection, Train Collision Avoidance, LiDAR Sensors, Wireless Communication, ESP32 Microcontroller, Intelligent Signalling.

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This paper presents an innovative approach to monitoring and protection of three-phase induction motor using Arduino Nano. The objective is to continuously monitor motor parameters (voltage, current and temperature) to detect abnormal conditions in real time. A protection system was developed using Arduino Nano, current and potential transformer, relay, three phase contactor and LCD display for real-time data visualization. Experimental results shows the success of the proposed method in monitoring and protection of three-phase induction motor and improves motor's lifespan by providing protection from various fault conditions.

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induction motor, overvoltage, protection, overcurrent, single phasing. Arduino.

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Artificial Intelligence (AI) has emerged as a transformative force in the field of marketing management, especially within predictive analytics. This research investigates how AI technologies are integrated into predictive marketing practices, evaluating how they enhance customer segmentation, forecast consumer behaviour, and personalize marketing strategies. The study explores some of the AI tools and methodologies--such as Machine Learning (ML), Natural Language Processing (NLP), Big Data Analytics etc. by analysing their real-world applications through case studies of leading global brands. It also explores how AI improved decision-making, increased customer engagement, and higher return on investment. Moreover, the research addresses various challenges that marketing firms and various organizations are facing in implementing AI, such as data privacy concerns, algorithmic bias, and integration complexity. This research paper evaluates current trends and ethical considerations and provides a complete view of AI's growing role in redesigning marketing analytics and strategy, ultimately contributing to more data-driven and customer-centric business environments.

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Artificial Intelligence, Predictive Analytics, Marketing Management, Customer Segmentation, Personalization, Machine Learning, Natural Language Processing, Big Data

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The overarching mystery of the novel serves as a major contributor for the emotional imbalance that is witnessed throughout the work. Emotional imbalance could be identified in the characters when they try to shift their emotions from one to another at an irregular pace. Emotions like anger, fear, despair and hope influence individuals to a great extent, and when a person shifts among these emotions rapidly and erratically, emotional imbalance becomes visible predominantly. Various factors contribute to emotional imbalance in 400 Days.

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Artificial Intelligence (AI) has emerged as a transformative force in manufacturing, enhancing efficiency, reducing costs, and improving quality control. The paint industry, characterized by complex production processes, is increasingly leveraging AI-driven solutions such as predictive maintenance, process automation, and real-time quality monitoring. This study examines the impact of AI implementation in paint manufacturing, focusing on three key areas: operational efficiency, cost reduction, and quality control. Using a mixed-method approach, including industry surveys and case studies, the research evaluates AI adoption levels, its tangible benefits, and the perception of industry professionals. Findings indicate that AI significantly enhances operational efficiency by optimizing workflows and reducing downtime. Cost savings are primarily observed through waste minimization and energy efficiency, while AI-driven quality control mechanisms improve product consistency. However, challenges such as high implementation costs and workforce adaptation persist. The study concludes with recommendations for scalable AI adoption in the paint manufacturing sector.

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Artificial Intelligence, Paint Manufacturing, Cost Reduction, Quality Control, Operational Efficiency.

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Recruitment processes have undergone considerable change with the introduction of automation tools and analytics in the field of Human Resource (HR) management. This research examines the influence of HR automation tools on recruitment efficiency which includes candidate sourcing, evaluation, and decision-making pertaining to hiring. This study analyzes multiple HR technologies such as applicant tracking systems (ATS), chatbots, and predictive analytics, and illustrates their impacts on reduced hiring timelines, candidate experience, and bias mitigation. The research also analyzes how insights derived from data aid the decision-making process and detail the impact on the strategic hiring decision. The study intends to provide implementable propositions regarding recruitment strategy optimization through analysis of leading automation tools and case studies of organizations that incorporated these tools into their processes. The results of the research indicate that there is a growing need for incorporating automation and analytics into human resources workflows to optimize efficiency, scalability, and fairness in the hiring process.

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HR Automation, Recruitment Efficiency, Digital Transformation in HR, Applicant Tracking System (ATS), Automated Resume Screening, Hiring Process Automation

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