Volume 12 | Issue 4

 Abstract

Now day's people are searching for something creative and smart technologies for the various events and also for the entertainment purpose, so we are creating our project on the pyro machine or the automatic fire blast machine.

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smart pyro machine, fire blast, automatic, creative

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A brain stroke is a medical disorder where the brain is damaged due to a burst in the blood vessels in the brain. These symptoms occur if the supply of blood or any other nutritional resources to the brain are interrupted. The studies indicate that brain stroke is the primary cause of death and disability worldwide. Timely detection of strokes is essential for effective treatment. Current stroke detection techniques include machine learning, but they struggle with complex patterns in medical imaging and need human-designed features. These approaches cause slower diagnosis and erroneous outcomes. To estimate the probability of early-stage brain strokes, the paper experiments using various algorithms, including VGG16, XGBoost, GNN, and EfficientNetB3 architectures. To determine the effectiveness of the algorithms, a reliable dataset for stroke detection was taken from Kaggle website. Several classification models, including XGBoost, VGG-16, EfficientNetB3, and GNN were used. By training the model on a large dataset and classifying using different algorithms the XGBoost has produced the highest accuracy of 97.94% than the GNN, VGG-16, and EffiientNetB3 which produced an accuracy of 73.68%, 87.26%, 75.28% accuracy. This paper showed that XGBoost performed better compared to other algorithms.

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Extreme Gradient Boosting, Visual Geometric Group 16 (VGG 16), Graph Neural Network ( GNN), Stroke detection XG Boost.

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English as a Second Language (ESL), is an educational curriculum designed to help non-native speakers improve their English language skills. In today's increasingly interconnected and diverse world, having proficiency in English is a threshold to global opportunities. ESL students face a number of challenges as they venture down the path of learning the English language, hence the role of English teachers is substantial in helping students face and overcome the challenges. This paper focuses on the variety of learning difficulties the ESL students face in the classroom, which could negatively impact the student's learning progress, and features the valuable insights to effectively support students in overcoming them.

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Keywords: ESL, learning, challenges, skills, strategies, understanding

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The Paper begins with the Introduction of the title and on which thesis will develop upon. The paper will give deep explanation to the concept of feminism dividing it in different section such as definitions, characteristics and waves of feminism so that it will be clear to the readers who are not aware of the term feminism, the detailed information will be given on writer's ideology on feminism, with it the concept of identity will also be introduced to the readers by giving its definition, importance and how it is related with the novel The Golden Notebook and The Grass is Singing and how the writer have shown both Feminism and identity in her novel. The Golden Notebook and The Grass is singing will be shown how it is meant to be a feminist Novel as other feminist works. Second a brief introduction of the novel will be given with its background, thematic concerns and the character sketch of protagonist which will give idea and hint to the readers.

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The Quest for identity and Feminist approach in Doris Lessing's The Golden Notebook and The Grass is Singing

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Digital platforms can connect people, organizations, and resources to facilitate the core interactions between businesses and consumers To facilitate the essential interactions between businesses and consumers and ensure increased efficiency for company management, digital platforms can connect people, organizations, and resources. As a result, the foundation of new company concepts, like creative start-ups, is built on creativity, scalability, and connections with the surrounding community. The objective is to identify important organizations that support startups in their establishment and growth, pinpoint regions in which startups receive assistance from the social networks of their key members and/or founders, and examine the correlation between the kinds of contacts and support offered. These networks comprise friends and business partners in terms of their use rates, important roles, and level of support, as well as business angels in terms of finance and advice on technology and marketing. Certain weak ties have different uses (both positively and adversely) than they have importance. Although business incubators assisted 50% of businesses, the incubators' assistance in creating networks and connections with the outside world appears to be underappreciated. Our findings suggest that networking initiatives with outside parties should be part of startup support programs

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Digital platforms, Startups, Community connections, Business partners, Startup support programs.

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In this era where every aspect of our day-to-day life is gadget-oriented, there is a huge volume of data that has been emanating from various digital sources. Today there are millions of data sources that generate data at a very rapid rate. Data analytics uses analytic techniques to examine data, thus obtaining and find out information like hidden patterns. The agriculture industry has witnessed a remarkable transformation in recent years, thanks to the integration of Big Data and advanced technologies such as machine learning(ML) and Internet of Things(IoT). Big Data analytics has opened up new possibilities for optimizing farming practices, increasing yields, and ensuring food security. This paper will explore how Big Data has revolutionizing agriculture and provided some applications. Big Data contribute to making timely recommendations to farmers with regard to smart agricultural techniques. One purpose of current research is to get a better knowledge of the present state of Big Data processing in Agriculture and even to uncover underlying challenges that need to be addressed.

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Big Data, Data Analytics, smart agriculture, Machine Learning(ML), IoT

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The unique strategy to tracking and monitoring mental health that this paper presents makes use of data science and artificial intelligence/machine learning (AI/ML) approaches. The project's goal is to produce a complete mental health tracker system that can analyze various data sources and offer chances for early intervention and individualized insights. The system integrates information from several sources, including wearable technology, social media activity, calendar events, and self-reported mood assessments, by utilizing AI/ML algorithms. The tracker uses sophisticated data analysis and predictive modelling to find patterns, trends, and possible risk factors related to variations in mental health. In addition, the system makes use of feedback mechanisms and real-time monitoring to enable people to take proactive measures to maintain their mental health. The project offers a scalable and easily available solution for ongoing mental health monitoring and support, helping to close the gap between conventional mental health evaluation techniques and cutting-edge technologies.

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logistic regression, K-nearest neighbors (KNN), behavioral analysis.

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The paper "Examining the Adoption and User Experience of Mobile Payment Solutions in the Era of Fintech Revolution" delves into the evolving landscape of financial technology, focusing particularly on the rise of mobile payment options. With the fintech revolution reshaping traditional banking practices, mobile payment systems have emerged as convenient, secure, and efficient alternatives to cash and cards. The research aims to understand the factors influencing user adoption and experience with these technologies, spanning across demographic, cultural, regulatory, and technological dimensions. Despite their potential to promote financial inclusion and streamline transactions for individuals and businesses alike, mobile payment systems face challenges such as digital divides, technological biases, and regulatory differences. By exploring these complexities and limitations, the study seeks to provide valuable insights for policymakers, businesses, and researchers navigating the dynamic landscape of mobile payments in the digital age.

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Fintech, Mobile Payment Solutions, User Experience

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A macrobenthic study was carried out at different ghats of Yamuna river at Mathura after falling down Drain effluents. 7 Ghats (Gau ghat, Swami ghat, Askunda ghat, Vishram ghat, Bangali ghat, Dhruv ghat, Mahadev ghat) were used as sampling stations for sampling of Macrobenthos from (March 2021 to April 2022). Macrobenthos from three types of phylum Arthropoda, Annelida, Mollusca were recorded. Among these three phylum, Maximum species of phylum Arthropoda were recorded at every station in summer. Maximum species density of Molluscs and Annelids were recorded at Gau ghat & Dhruv ghat may be due to shallow clean water and river soil having highest organic carbon and Minimum at Mahadev ghat and Askunda ghat may be due to dirty water, because of falling drain effluents. Annelid's species Namalyastis sp. and Mollusc's species Pila sp. were present at maximum stations from others. Arthropoda community were observed dominated from Annelids and Molluscs. Arthropodal species Caenis sp. and Chironomial sp. were dominant at maximum stations from others. Following results were determined as species richness from classes - Insecta - Arthropoda at polluted ghats (station -3,7) Oligochaeta & Hirudinea - Annelida at (station-1,6) and Gastropoda &Bivalvia - Mollusca at less polluted site (station-1,2,6).

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Macrobenthos, Drain effluents, Gastropods, Species richness.

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This approach not only increases time to market, but also ensures that the asset is reliable and meets safety and quality standards. Additionally, SIL simulation facilitates collaboration between different teams, accelerates process improvement, and encourages innovation in vehicle design. Rapid advances in technology require advanced techniques for designing and implementing complex systems such as measuring devices. Software-in-the-loop (SIL) simulation has become an important technology to improve the efficiency and accuracy of the development process. network integration

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Seat belt monitoring, CAPL scripting, Automotive safety, Electronic control units, Communication protocols.

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The probe paper named" The Future of 5G Wireless Systems Trends, Challenges, and operations" delves into the vital part of 5G technology in revolutionizing telecommunications. pressing its significance, 5G wireless systems promise unequaled advancements over former generations, boasting briskly data rates,ultra-low quiescence, and massive device connectivity. These attributes fuel a multitude of operations gauging colorful sectors, including healthcare, transportation, manufacturing, and smart metropolises. Examining crucial trends, the paper underscores the global instigation in 5G deployment, underlined by substantial investments in structure and diapason allocation. still, challenges impend large, encompassing diapason failure, structure costs, cybersecurity vulnerabilities, and nonsupervisory hurdles. Despite obstacles, the implicit operations of 5G are immense. From empowering IoT ecosystems to enabling independent vehicles and easing remote healthcare services, 5G unlocks a diapason of innovative possibilities. In conclusion, the paper accentuates the transformative eventuality of 5G wireless systems. By navigating challenges and employing arising trends, stakeholders can subsidize on 5G's capabilities to usher in a new period of connectivity, invention, and socioeconomic growth.

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Wireless Systems,ultra-low quiescence, transportation, 5G deployment, cybersecurity , nonsupervisory , stakeholders

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The effectiveness of the majority of traditional classification systems depends on accurate data representation, and a large portion of the work is focused on feature engineering, a challenging and drawn-out procedure that leverages previous expert domain knowledge of the data to produce valuable features. However, deep learning does not require a domain expert to construct feature extractors; instead, it can extract and arrange the discriminative information from the data. The research community and industry have taken an interest in Convolutional Neural Networks (CNNs), a specific kind of deep, feedforward network that has shown empirical success in tasks like speech recognition, signal processing, object recognition, natural language processing, and transfer learning. To guarantee the efficacy of the model, the project carries out extensive data exploration, visualization, and preprocessing procedures in this work. The suggested model architecture performs well and classifies medical images with a high degree of accuracy. The findings demonstrate the potential of deep learning methods to support medical practitioners in the diagnosis and planning of diseases.

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Key words: medicine; breast cancer The World Wide Web. applications in healthcare. algorithm for machine learning. Transfer learning, CNN.

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Post-independence industrialisation and aggressive industrialisation with the onset of globalisation have led to rubbed development in the tribal inhabited areas of the state. It has been a continuous observation that industrial development in Odisha has proved to be detrimental to the tribal population by uniformly affecting their human rights, quality of life, and security in myriad forms. Industries have been established in the hinterlands of the state rich in terms of physical and human resources. These hinterlands are the tribal terrains dominated by the native tribals. The state in the pursuit of capitalist ideology has overlooked the human rights of the human rights and the protocols of human rights. The present paper through a meta-synthesis of the studies undertaken on the issue tries to establish how rich lands being under industrial invasions under state patronage crate risk populace in the tribal landscape of the state. It tries to establish the trajectory of industrial development in the state, sketching the tribal situation, industry-led displacement scenario, and the way that affects tribal rights. The article concludes the carnage of tribal lives through industrial invasions and appeals to the system of governance to make a shift from the profit-centric growth approach to a people-centric distributive development and to echo the voices of the tribal, accommodate their needs and to prioritize their basic rights in any industry induced displacement planning and designing.

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Industrialisation, Displacement, Tribal, Indigenous Rights, Resettlement & Rehabilitation, Policy

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In India, kohl has been used for cosmetic purposes for centuries it is use as cosmetic and treats the eye Problem Herbal kohl is a product used as a medicine because a cosmetic was a new prescribing method. Kajal is mainly used for eye makeup. The aim of the preparing formulation that is medicated herbal kajal is to treat eye inflammation and eliminate redness of the eye. The medicinal products Aloe-vera, Camphor, Almond oil, Coconut oil and Ghee are used to formulate the herbal kajal. the black soot (kajal powder) is prepared by using copper plate and evaluated by microbial activity

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Kajal, Kohl, Aloe-vera, Camphor, Anti-inflammatory

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Crime is nothing but illegal behavior or activities and which people are punished. Cyber-crime is nothing but person who has done something illegal or criminal activity that either victim or uses a computer or laptop, a computer network or a networked device. Cybercrime is committed by cyberpunk (cyber-criminals or cyber crooks) or hackers who want to make money. Cyber-crime aims to harm or destruction computers or networks for reasons other than profit, these could be political or personal. Cyber-crime can be executed by individuals or organizations. Some cyber crooks are organized, use advanced techniques and are highly technically skilled. Others person who is beginning to learn a job or an activity and has little or no experience or skill in it.

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Cyber-attack, Digital, Education, Threat, Type of Crime

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Accurate stock price prediction is a challenging task due to the inherent complexity and volatility of financial markets. However, the availability of large historical datasets and advancements in machine learning algorithms have opened up new possibilities for developing predictive models.

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Machine Learning, Stock Price, Prediction, American Airlines, Support Vector Machine (SVR), Artificial Neural Network (ANN), Random Forest (RF), Decision Tree (DT).

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Satellite imaging is widely used to monitor weather and interpret satellite images. Time limitation in accessing weather satellite image data is still a major problem for satellites. Automatically send images on 137.9125 MHz and 137.1000 MHz. NOAA 18 and NOAA 19 weather frequencies. In this study, data was collected with the help of a quadrangular helical antenna and RTL-SDR. Four-line H satellite imaging to obtain these two frequencies is widely used to monitor weather and interpret satellite images. Limiting immediate access to weather satellite imagery is still a major challenge for the 137.5 MHz design elix antenna. Use WXtoImg software to collect, analyze, edit and display automated transmission images. Although the automatic transmission image of NOAA 18 received a frequency shift of 0.0685% and NOAA 19 had a frequency shift of 0.0686%, the results are clear enough and explainable. Use WXtoImg software to collect, analyze, edit and display automated transmission images. The results show that although there is a difference of 0.0685% and a frequency shift of 0.0686% in the automatic transmission images received by NOAA 18 and NOAA 19, the received weather satellite images are clear and descriptive enough.

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QFH Antenna,NOAA,Satelite Pass,Doppler shift,SDR,WXTOIMG,Demodulation,Orbit Prediction,Polarization

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India is predominantly an agricultural economy. Although agriculture accounts for more than 65% of employment, it has been growing only at 3.3% compared to industry's 7.5% per year. Drought conditions have lead to crop failure, mounting debts chronic unemployment ultimately compelled to distress migration Anantapur district in Andhra Pradesh is one such district where drought conditions are prevailing consistently over many years. The present paper analyses the adverse impact of drought conditions leading to migration and facing problems in search of employment in urban areas and its effect on their Socio-Economic conditions.

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Drought Conditions, Chronic unemployment, Debts, Migration, Socio-Economic conditions

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Global education is currently in high demand worldwide. Today, access to education is no longer limited by national lines but has spread globally. The exodus of highly skilled individuals, termed as "brain drain,"[1] has several negative effects on developing countries. If students return to their home country after receiving expertise in aspects such as technology, healthcare, engineering products, and strategic planning, there is a scope for technical and economic progress in the parent country that will be on par with developed nations. We develop a predictive model to forecast future brain drain trends based on current factors such as Economic Growth and Job Opportunities, Salary and Compensation Packages, Global Mobility and Connectivity, and Government Policies and Initiatives. A regression model, such as linear regression, or response surface model will help us forecast the number of immigrants and assess the influence of various factors. This analysis could help in anticipating potential challenges. Future iterations can offer more customization that might support social policymakers in their decision-making about brain drain.

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Brain drain, developing countries, migration, regression analysis.

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This traditional approach, which seems reasonable at first look but may really result in biases, unforeseen errors, and higher expenses, may endanger patients' QoS (Quality-of-Service). Almost all of the hospitals in Bangladesh do not give exercise bikes since there aren't any intelligent technologies that are both scalable and simple to install. The main goal of this project is to help hospitals treat severely sick patients by providing a feedback system that works in as it happens. we provide a standardized architecture, associated nomenclature, and a categorization model for evaluating the critical patient's health status. Predicting patients' total fitness using machine learning (ML) is the fundamental principle of this work. Our data and ML models may be saved and accessed using IBM Watson Studio and the IBM Cloud. Naive Bayes, Logistic Regression, K-Neighbors, Decision Tree, Random Forest, Gradient Boosting, and MLP were the Base Predictors used by our machine learning models. To increase the model's accuracy, the bagging approach of ensemble learning was used. Collectively, ensemble learning techniques include bagging ridge, bagging support vector machines, bagging additional trees, and bagging random forest.

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Critical Patient Management System - CPMS, MLP, Gradient Boosting, Naive Bayes

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