Volume 13 | Issue 4 |

 Abstract

Chronic Kidney Disease is a critical global health issue that demands accurate and timely diagnosis. The proposed system, CKD-Predict, leverages advanced machine learning algorithms such as Random Forest and XG Boost to provide reliable predictions. Utilizing the CKD dataset, it emphasizes rigorous data cleaning and preprocessing to handle missing values effectively. With a user-friendly web interface built using Flask, CKD-Predict ensures real-time accessibility for medical practitioners and healthcare institutions. This proposed system's adaptive machine learning backend continuously improves its prediction accuracy as more data is incorporated, making it a robust and evolving tool. By facilitating early detection and intervention, the proposed system assists healthcare professionals in identifying patients at risk, ultimately contributing to better management and outcomes for CKD cases. With its ability to process data efficiently and provide actionable insights, the proposed system aims to empower the medical community and improve the quality of life for CKD patients worldwide.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chronic Kidney Disease (CKD), Machine Learning, Random Forest, XG Boost, Flask.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Menopause is the period of time during which a woman passes from reproductive to non reproductive stage.Menopause means permanent cessation of menstruation at the end of reproductive life due to loss of ovarian follicular activity. The age of menopause is not related to age of menarche,race poverty,weight or height.

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Creative Commons Attribution 4.0 and The Open Definition

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Menopause

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT: Depression is a prevalent mental health disorder that significantly impacts an individual's quality of life. This study aims to evaluate the efficacy of individualized homeopathic medicine in the management of depression. A case series study was conducted on 30 patients diagnosed with depression, who were treated with homeopathic remedies based on their individualized symptomatology. The findings suggest that individualized homeopathic treatment may have a beneficial role in managing depression. Primary objectives of this study was to evaluate the effectiveness of individualized homoeopathic remedies in reducing depressive symptoms and enhancing quality of life. Methods: This case series study was conducted with 30 cases of depression, selected through stratified random sampling from the OPD/IPD of a homoeopathic medical college and hospital, peripheral OPDs, schools, and health camps. Each case was assessed and treated with individualized homoeopathic remedies. The severity of depression was evaluated using BDI score scale before and after treatment.Result: This case series study suggests that individualized homeopathic medicine may be effective in managing depression, as 20 out of 30 patients showed improvement. However, the lack of response in 10 patients indicates the need for further research with larger sample sizes and controlled trials to establish its efficacy more definitively.

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 Keywords

Keyword:-Depression ,sadness,insomnia ,disappointment ,anxiety.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Prakruti pariraksana parijnana margalu - balala geyalu

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Creative Commons Attribution 4.0 and The Open Definition

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Prakruti pariraksana parijnana margalu - balala geyalu

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In electrical engineering, managing Bill of Materials (BOM), equipment manuals, standard drawings, and price lists is a critical yet time-consuming and error-prone process when handled manually. Traditional methods involve manual data extraction, validation, and organization, which often leads to inefficiencies, misclassifications, and procurement delays. To address these challenges, this research presents ElectroDrawManager, a machine learning (ML) and automation-driven solution for optimizing BOM management and document retrieval. ElectroDrawManager employs Optical Character Recognition (OCR) and Natural Language Processing (NLP) to extract data from PDF, DWG, and CSV files, ensuring structured storage in a centralized database. The system allows users to efficiently access equipment manuals, standard drawings, and price lists, reducing manual intervention and improving decision-making. Additionally, predictive analytics enhances the accuracy of BOM generation, ensuring better material forecasting and error detection. The proposed system integrates a user-friendly interface, enabling users to upload files, extract relevant information, and retrieve processed data seamlessly. Through automated classification and anomaly detection, ElectroDrawManager significantly improves workflow efficiency, data accuracy, and operational productivity in electrical engineering projects. This paper discusses the methodologies, technologies, and implementation strategies used to develop ElectroDrawManager, highlighting its potential in revolutionizing BOM and document management workflows.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bill of Materials (BOM),PDF, DWG, and CSV files

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cleaning is necessary or basic need of all humans and animals. We design and develop new fully manual operated manual operated road and floor cleaning machine which has simple mechanism and structure , light in weight which easily carrying anywhere. The road cleaner and floor cleaner machine which has wide range of applications. The working principle of machine is dependent on mechanical design. The intention of the project to develop manual process for cleaning road with brush. In railway station, fuel pump, airport, footpath, stadium, cinema hall , etc. In our project we use easily available material at less cost it no need of any fuel and pollution free machine it can be used in our daily life.

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Creative Commons Attribution 4.0 and The Open Definition

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Mechanism and structure , pollution free , manual operated , mechanical design , road cleaner , etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sustainability accounting has gained attention in recent years. The trend has become rampant in Zambia after singing the UN agreement agenda 2030. Despite being part of the agreement, SA adoption rate in Zambia has been low primarily due to the voluntary nature and the discretion exercised by management on year-end reports. The requirement by SEC to disclose the ESG activities has not been enough to mirror the adoption rate in the country as there are a number of large organizations not listed whose activities affect the society and environment. This led to conducting the study with a specific focus on IDC. The research objectives were to evaluate the current adoption levels of SA practices by companies under IDC, to identify factors affecting the application of SA by companies under IDC and to determine the strategies that IDC can adopt in order to enhance the SA practices. The overall results revealed a low level of disclosure a situation that has been gradually improving from a sustainability reporting index of 0.39 in 2017 to 0.49 in 2022. The low levels of disclosure were attributed to several factors such as lack of knowledge, additional costs, time constraints and lack of government initiatives. Statistical analysis revealed a significant correlation between the current level of adoption and the need to a mandatory adoption of sustainability accounting practice. The negative correlations indicated that higher levels of sustainability accounting practices corresponded with greater value creation for stakeholders.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sustainability accounting, Sustainability indicators, Disclosures, IDC and Stakeholders

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Creative Commons Attribution 4.0 and The Open Definition

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In the present-day rapid and technology-oriented supply chain scenario, real-time inventory decision-making is a crucial element of operational effectiveness as well as competitive edge. Conventional inventory systems usually do not possess the sufficient responsiveness and precision that can accommodate the demands of today. The merger of the Internet of Things (IoT) and Blockchain technologies holds a compelling answer to this dilemma. IoT allows ongoing real-time tracking of inventory using smart sensors, RFID tags, and networked devices, enabling precise tracking of stock levels, movement, and storage conditions. In contrast, Blockchain offers a decentralized, secure, and unalterable ledger that guarantees data transparency and integrity to all supply chain partners. By merging these two technologies, companies can create smart, automated, and data-based inventory systems. This article suggests a conceptual model that uses IoT for real-time data capture and Blockchain for secure data storage and automated decision-making. The model seeks to streamline inventory operations by enhancing visibility, trust, and enabling quicker, wiser decisions along the supply chain.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT (Internet of Things), Blockchain, Inventory Management, Real-Time Tracking, Smart Contracts, Transparency, Security, Predictive Analytics, Supply Chain Optimization

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Creative Commons Attribution 4.0 and The Open Definition

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India's rural development plan has increasingly centered not only on developing infrastructure but also on the development of human capital in the form of skill upgradation and employment generation. Deen Dayal Upadhyaya Grameen Kaushalya Yojana (DDU-GKY), initiated by the Government of India, Ministry of Rural Development, is just such a flagship programme aimed at empowering rural youths by way of market-oriented skill training and employment. This research aims to measure the awareness of DDU-GKY among rural youth of Coimbatore district, Tamil Nadu, and evaluate its contribution to promoting sustainable rural development. The principal aim of this research is to measure the level of awareness, participation, and perceived effect of DDU-GKY among the intended beneficiaries. Aside from this, it also delves into the functions of different stakeholders such as training providers, local government units, and community leaders in the implementation of the program. The study is based on a mixed-methods research design where it merges quantitative surveys of 150 rural youth belonging to different blocks of Coimbatore with qualitative interviews of local government officials, training center coordinators, and program participants. Statistical tools and thematic content analysis were used to analyze the data to determine patterns and insights. Nevertheless, the impact of the programme on the beneficiaries has been generally positive. Improved skills, better employability, and, in a majority of cases, proper placement in retail, hospitality, and electronics industries were indicated by the beneficiaries. Even a few could transition into self-employment or entrepreneurship, which is testimony to the capacity of the scheme to generate livelihoods that are sustainable.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Rural development, Skill development, Employment generation, Vocational training.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Numerology, the mystical study of numbers and their influence on human life, has been a topic of intrigue for centuries. Rooted in ancient philosophies and diverse cultures, numerology posits that numbers are not merely mathematical symbols but also carriers of spiritual and metaphysical significance. This paper explores how numerology serves as a tool to understand individual qualities and predict future possibilities. By examining its historical origins, methodologies, and applications, this research aims to evaluate the validity of numerology as a framework for personal insight and future forecasting.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Numerology, Future, Lens,

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Creative Commons Attribution 4.0 and The Open Definition