Volume 11 | Issue 11 |

 Abstract

A human sound-based disease detecting system leveraging machine learning involves collecting diverse audio samples capturing specific human sounds related to diseases or health conditions. Through signal processing and feature extraction methods like spectrograms or MFCCs, meaningful features are derived from these audio signals. Supervised machine learning models, such as CNNs or RNNs, are trained on these extracted features to learn patterns and correlations between audio characteristics and particular diseases. After validation and performance assessment, the trained model is integrated into an application or system to analyze incoming audio input and predict potential diseases or health issues, and ethical use of health data remain pivotal throughout the development process. Employing signal processing techniques and feature extraction methods like spectrograms or MFCCs, the system abstracts meaningful patterns from the audio data. Through supervised learning algorithms such as CNNs or RNNs, the model learns to correlate these sound features with specific diseases during the training phase. Validation and fine-tuning ensure its accuracy and generalizability, following which it gets integrated into an interface for real-time audio input processing and disease prediction. Ethical considerations, data privacy, and collaboration among medical professionals and AI experts are essential throughout the development to responsibly deploy this system, potentially enabling early disease detection and remote healthcare accessibility

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 Keywords

sound detection,disease prediction,machine learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

AN EXPRESSIVE STUDY ON CHILD HEALTH STATUS IN RAJASTHAN

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AN EXPRESSIVE STUDY ON CHILD HEALTH STATUS IN RAJASTHAN

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This study presents a comprehensive geographical analysis of underground water resources in Gurugram district, Haryana, India, spanning the years 2000 to 2020. Gurugram, a rapidly urbanizing region, has witnessed significant changes in land use, population, and economic activities during this period, which have put substantial pressure on its groundwater reserves. The research employs a combination of remote sensing, geographic information systems (GIS), and statistical techniques to evaluate the spatiotemporal trends in groundwater levels, assess the impact of urbanization and climate change, and suggest potential mitigation strategies. The study reveals a consistent decline in groundwater levels over the two decades, with the most significant depletion occurring in the urbanized areas. Land use changes, particularly rapid urban expansion. The analysis also highlights variations in groundwater levels across different seasons, with the monsoon season playing a crucial role in recharging aquifers. The research underscores the need for a holistic approach that integrates geographical data, remote sensing technology, and community involvement to safeguard Gurugram's underground water resources for future generations.This research aims to scrutinize the extent and pace of groundwater depletion in Gurugram district while also shedding light on the contributing factors and their impact on the local populace. The research conducted uncovered significant disparities in the magnitude of groundwater depletion among different blocks within the district.

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This study presents a comprehensive geographical analysis of underground water resources in Gurugram district, Haryana, India, spanning the years 2000 to 2020. Gurugram, a rapidly urbanizing region, has witnessed significant changes in land use, population, and economic activities during this period, which have put substantial pressure on its groundwater reserves. The research employs a combination of remote sensing, geographic information systems (GIS), and statistical techniques to evaluate th

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Abstract Women empowerment and bihar economic development are closely related :in one direction, development alone can play a major role in driving down inequality between men and women; in the other direction , empowering women may benefit development. Development policies and programs tend not to view women as integral to the economic development process. This is reflected in the higher investments in women's reproductive rather than their productive roles, mainly in population programs, yet women throughout the developing world engage in economically productive work and earn incomes. They work primarily in agriculture and in the informal sector and increasingly, informal wage employment, their earnings, however are generally low, since the 1950's , development agencies have responded to the need for poor women to earn incomes by making relatively small investments in income generating projects. Often such projects fail because they are motivated by welfare and not development concerns, offering women temporary and part-time employment in traditionally feminine skill such as knitting and sewing that have limited markets.by contrast , over the past twenty years, some non- governmental organizations, such as the self- employed women's association in india have been effective in improving women's economic status because they have started with the premise that women are fundamental to the process of economic development.

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Key words :- Women empowerment, Population, programs, informal sector, development agencies, income generating projects.

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Nature tourism is responsible travel to natural areas, which conserves the environment and improves the welfare of local people. It is tourism based on the natural attractions of an area. Biligiriranganabetta, popularly known as B.R. Hills in Yelandur Taluk, of Chamarajanagara District, Karnataka, is primarily a hilltop pilgrimage centre. Situated in South Eastern Karnataka, BR Hills or Biligiriranganatha Swamy Temple Wildlife Sanctuary is home to ecosystems that are unique to both the mountain ranges. Since it is located at the north-west of the Western Ghats and westernmost edge of the Eastern Ghats, it supports a diverse flora and fauna given the various habitats present. It is a pilgrimage site and derives its name from the Rangaswamy Temple located on top of a white cliff. The Temple is dedicated to Lord Ranganatha and the festivities in this temple during April attract a lot of tourists.

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Nature tourism, B R Hills, Mountain Range, pilgrimage, wildlife sanctuary.

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Creative Commons Attribution 4.0 and The Open Definition

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Many individuals facing neurological disorders or paralysis from accidents encounter difficulties using computers for tasks like messaging, web surfing, and entertainment. Recent research indicates that due to the natural movement of eyeballs during computer interaction, they present an ideal option for universal computing. It suggests the possibility of re-enabling computer usage for such patients by utilizing information derived from eye movements. Our proposal advocates for a completely eye-controlled mouse gesture system. The project's goal is to develop an open-source, free eye-controlled gesture control system that precisely tracks eye movements, enabling users to perform computer-related activities through specific eye motions or gestures captured by the computer webcam. The system identifies the user's pupil on the face and monitors its movements in real-time for comfortable use.

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Eye Controlled, mouse gesture, motion, pupil, interaction, neurological disorder

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ABSTRACT: Pain and discomfort are among the most frequent side effects of orthodontic therapy. Patients who have orthodontic pain are more likely to self-medicate with over-the-counter medications before seeing a dentist. An orthodontist must respond to questions that may arise in a clinical setting by considering the viewpoints of the physicians and the parents/patients.The mechanical stresses placed on the teeth and supporting tissues during orthodontic treatment are the main cause of orthodontic pain. It can be divided into two categories: chronic pain that may last the entire course of treatment, and acute discomfort that occurs after orthodontic modifications. Different patients have different expectations about how painful orthodontic treatment will be, so it's important to appropriately address and manage these concerns. This literature review's primary goal is to go over both contemporary as well as conventional ways of managing pain during orthodontic treatment.

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Keywords: orthodontic pain, acute and chronic, self-medicate, mechanical stresses.

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Creative Commons Attribution 4.0 and The Open Definition

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We are using Machine learning (ML) to predict concrete strength using various input parameters. This study uses a large dataset from several construction projects and various ML algorithms, such as multiple linear regression (ML), decision trees (ML), random forests (ML), support vector machines (SVM), and artificial neural networks (ANN). The results demonstrate high accuracy levels with the ANN model having the highest performance. The implications of this study for the construction industry are to streamline the design process, reduce reliance on laboratory testing and optimize material usage while meeting safety standards and reducing costs. However, there are limitations, such as dataset size, real world conditions, and fine-tuning. Hyperparameter tuning uses random search to train models with higher predictive performance. The missing data is filled with the average of the data available, allowing for more data to be included in the training. Comparative studies on two well-known compressive datasets of tensile strengths and high performance concrete suggest that the current approach is significantly improved in terms of prediction accuracy as well as computational effort. According to comparative studies, for this specific prediction problem, GBR and xGBoost-trained models perform better than models based on SRV and MLP

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Concrete Strength Prediction , Machine Learning , Regression Models , Artificial Neural Networks , Predictive Analytics ,Building Materials

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Ayurveda has blessed us with multiple, effective harmless treatments and medications. Among them Viddha Karma is a unique treatment of Ayurveda which gives instant relief and disease management. Viddha Karma is one among the Shastra Karma as explained in Brihatrayee, Laghutrayee and other classics. It is the treatment of puncturing or piercing certain points that reduce pain. It removes the obstruction of the blood vessels and establishes the circulation by clearing Srotas and stimulation to sensory fibers from peripheral receptors reduce the transmission of irritating signals from the affected area is the main mechanism of action of Viddha Karma.

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Ayurveda, Viddha Karma, Shastra Karma, Brihatrayee, Laghutrayee, Puncturing, Receptors, Sensory fibers, Stimulation etc.

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It can be challenging to secure the cyber physical systems (CPS) that underpin the Internet of Things (IoT) since security measures taken into account for general information and technology operations (IT/OT) might not function well in a CPS environment. In this paper, we suggested an automatic cyber attack detection and classification framework based on machine learning. For the purpose of ensuring the safety of Internet of Things use cases, it employs a variety of machine learning models. Learning Based - Cyber Attack Detection(LB-CAD) is the approach we suggested. The input of the algorithm consists of an ML pipeline and an IoT integrated use case dataset. Proposed methodology to train classifiers, and subsequently use the generated models to identify and categorize cyberattacks automatically. An empirical investigation is utilized to assess our methods. Performance results revealed that the ML models are capable of detecting and classifying cyber-attacks. In case of binary classification, LSTM(LONG SHORT - TERM MEMORY) showed highest accuracy 78.36%. For multi-class classification K-NN showed highest performance with 82.10% accuracy.

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 Keywords

Machine Learning, Cybersecurity, Internet of Things, Binary Classification, Multi-Class Classification

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Creative Commons Attribution 4.0 and The Open Definition