Volume 12 | Issue 4

 Abstract

Stress, an increasingly prevalent aspect of modern life, can significantly impact an individual's physical and mental well-being. Hence, understanding and monitoring stress levels play a crucial role in promoting overall health and quality of life. This paper "Human Stress Detection Based on Sleeping Habits Using Machine Learning Algorithms" presents a novel and effective approach to detect human stress levels by analyzing their sleeping habits. These parameters include the user's snoring range, respiration rate, body temperature, limb movement rate, blood oxygen levels, eye movement, the number of hours of sleep, heart rate, and stress levels categorized into five classes: 0 (low/normal), 1 (medium low), 2 (medium), 3 (medium high), and 4 (high). The inclusion of these diverse parameters ensures a comprehensive analysis of sleep patterns and their correlation with stress levels. The model is trained using the dataset, and its performance is evaluated on a separate test dataset to ensure generalization and unbiased assessment. The results of the experiments reveal a Training score of 100% and an impressive Test score of 97%, demonstrating the effectiveness and robustness of the proposed methodology. The achieved high accuracy showcases the model's capability to learn intricate patterns from the dataset and make accurate stress predictions based on the user's sleeping habits.

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 Keywords

Machine learning, training score, Sleeping patterns, human stress

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Flood is one of the natural disasters that can not be avoided.it happen stoof a stand affected so many lives and properties. Before this most of the existing system that as been developed are only focus on certain area. other than that , majority of the public cannot monitor and have no idea when the flood going to be happened since they do not have any information and data about the weather condition. This system is suitable for cities and village area. furthermore, if the public has an internet access, they can monitor what is happing and predict if there is any upcoming flood at the web server. This project will update the water level at the web server and the system will issue an alert single to the citizens for evacuation so that fast necessary actions can be taken.

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Arduino UNO, Ultrasonic sensor, GSM Module , Red ,Green , Yellow LED , LCD Display, Water level sensor, Web Application , Battery.

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Even in areas where modern medicine is available, the interest in herbal medicines and their utilization has been increasing rapidly in recent years. Plant-derived substances and herbal medicines have recently attracted great interest in their versatile application, as medicinal plants are the richest source of bioactive compounds used in traditional and modern medicine. The present research aimed to formulate and evaluate the herbal ointment containing Neem (Azadirachta indica) and Lantana Camara leaf extract. The ethanolic extracts were prepared by using the Soxhlet method. Extracts of the plant were incorporated into an ointment base and evaluation of its physicochemical parameters like colour, odour, PH, physical Examination, consistency, spreadability, washability etc. The physicochemical evaluation of the developed formulation showed uniform colour dispersion without lumps. Stability testing at different temperatures indicated no change in spreadability, along with easy washability and good spreadability. The antimicrobial activity for Neem and Lantana Camara using the disc diffusion method was carried out. The antibacterial study of the developed formulation showed dose/concentration proposed inhibitory activity against Staphylococcus aureus, Staphylococcus epidermis and E. (Escherichia) coli. The results concluded that the extract of Neem (Azadirachta indica) and Lantana Camara is an appropriate formulation for the topical therapy.

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 Keywords

Herbal ointment, Soxhletion method, Neem (Azadirachta indica) and Lantana Camara, antimicrobial activity, topical therapy.

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Herbs have been used as medicine since the ancient period. It is widely used in India. The project work is to formulate and evaluate a gel containing neem and lantana camara extract. The extract was formed into the gel using carbazole 634 by continuous stirring and evaluated for its physicochemical properties such as pH, viscosity, etc. The formulation of Neem and Lantana shows no lumps and has proper color dispersion. It was also observed that the formulation also has easy washability and spreadability. The antifungal activity of Lantana Camara and Neem using MINIMUM INHIBITION CONCENTRATION was carried out. The ethanolic extract of Neem and Lantana was prepared using Soxhlet Extraction. The results concluded that the extract of Neem(Azadirachta Indica) and Lantana Camara is an Appropriate formuation for the topical application

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Lantana Camara,Herbal Gel,Antifungal test,Evaluation test

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This research study about of small scale industry and their growth and development strategies, aim of study help in appraising the common strategies that help to improve small scale industry. In this study we used literature review, primary data as well as secondary data methods to clarifies the characteristics of the study. This study reviews on the characteristics, challenges, and opportunities of SSIs, highlighting their contributions to employment generation, income generation, and poverty alleviation. Small scale sector has been assigned an important role in the economy of the country

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small scale industry, types, growth, development strategy, economic development

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In view of the inadequacy of wireless resources, such as radio channels, and user mobility, achieving quality of service (QoS) in wireless networks is a huge challenge. Call admission control (CAC) is a proven approach for network QoS provisioning.With The ultimate objective of the femtocellular network deployment is the integration of dense femtocells with macrocells. Integrated macrocell/femtocell networks are unquestionably capable of providing high data rates for indoor users and offloading massive traffic from macrocellular networks to femtocell networks. Spectrum, power regulation, higher functioning capacity, and high-quality networks are all necessary due to the substantial rise in internet users and the prerequisites for larger data capacity per user.

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Call Admission Control, femtocell, 5G, IOT,Macrocell

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Liposomes are thought to be diverse and promising drug delivery systems. When it comes to site-targeting, regulated or sustained release, shielding medications from deterioration and elimination, better therapeutic outcomes, and less harmful side effects, liposomes outperform conventional drug delivery methods. Because of these benefits, during the past few decades, a number of liposomal medicinal items have been approved and successfully used in clinics. This overview covers the liposomal drug products that have been approved by the European Medicines Agency (EMA) and the Food and Drug Administration (FDA) in the United States. The marketed liposomal products' lipid excipient, manufacturing processes, nanosizing technique, and drug formulation are all based on the FDA's published approval package and the European Public Assessment Report (EPAR) in the EMA, as well as critical chemistry information and sophisticated pharmaceutical technologies. Critical quality attributions (CQAs) of items and loading techniques are presented. Furthermore, a summary of the most recent regulatory advice and anticipated developments pertaining to liposomal products is provided. This information can be applied to the study and development of liposomal drug candidates in a number of settings, such as pilot plants, commercial manufacturing facilities, and lab benches.

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Drug loading, lipid excipient, drug delivery, and liposomes.

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The gradual emergence of conservative social thoughts, rules and customs have downgraded the position of women and made them weak or deprived in Indian society. Now, as India is emerging as an economic power in the world, the resultant techno-socio-economic developments and rapid urbanization have enhanced the women's' work participation. The studies indicate that the unorganized sector workers have remained under privileged in the workforce due to their predominantly informal nature of employment and lack of job security and facilities. In this context this present research makes an attempt for comparative study of the economic condition of urban working women from organized and unorganized sectors in Bhubaneswar urban complex. The present study relied upon primary data collected through sample questionnaire survey of 200 respondents from working women in study area from two strata, namely: organized and unorganized. As the study reveals, there is marked difference between economic condition of organized sector and unorganized sector working women. The basic reason behind the poor economic condition of unorganized sector working women may be attributed to their young working age along with lack of proper education. Further, though the economic condition of organized sector working women is comparatively better, their major issue is negligible role in decision making in the family, workplace and society.

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Working Women, Organized sector, Unorganized sector, Economic condition

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Genotoxins refer to agents or carriers, such as chemicals or radiation that have the ability to induce damage to DNA or the structure of chromosomes. This damage can lead to mutations, and the overall process is known as genotoxicity. It is crucial to identify and comprehend genotoxins during the early stages of drug development in order to prevent potential harm caused by these agents. Various regulatory bodies, including the International Council for Harmonization, EMEA, USFDA, and European Pharmacopeia, have provided guidelines to restrict the presence of impurities in both drug substances and drug products. These guidelines aim to ensure the safety and efficacy of pharmaceuticals. A potential genotoxic impurity (PGI) has been defined as an "Impurity that shows a Structural alert for genotoxicity but that has not been tested in an experimental test model. Here potentially relates to genotoxicity, not to the presence or absence of this Impurity". The current study is based on analysis of data to determine the presence of genotoxic impurities in drugs and medicinal products. Start with the definition of genotoxic impurities, their sources, properties, and classification by toxicity. This article also describes various regulatory mechanisms for genotoxic impurities in pharmaceuticals. This review also describes the separation, identification and characterization of impurities and their measurement by various analytical methods.

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Genotoxic, Impurities, Drug substances, Guidelines, Pharmaceutical drug product.

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Insurtech, which stands for "insurance technology," refers to technology and innovation with the primary purpose of providing better services and technology to the insurance business in today's progressive technological environment and industrial revolution. That industry is increasingly reliant on technology to gain a competitive advantage, and it helps decision-makers make sound decisions. We employ bibliometric analysis to evaluate the trends in insurance technology. We examined all Scopus-indexed publications linked to insurance technology, totalling 568 articles, using keywords relevant to insurance technology in the titles, keywords, and abstract. Microsoft Excel is used for frequency analysis and data visualisation, as is the VOS viewer. We use the following bibliometric indicators: publication year, document type, source type, keyword analysis, authorship, and citation analysis. Since 2017, the number of publications on insurance technology has increased dramatically. The expanding number of Insurance Technology publications highlights the importance of technology in the insurance industry, which will surely have an impact on the economy and society. Keyword analysis suggests that employing insurance big data in diverse studies necessitates a theoretical link between the Insurance Technology issue and the insurance contract, which could be a future research topic.

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Insurance technology Insurtech Bibliometric Analysis Scopus database Digital innovation

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The Department of Pharmaceuticals initiated the Pradhan Mantri Bhartiya Janaushadhi Pariyojana (PMBJP) initiative to offer excellent medications at reasonable costs to the general public. The purpose of the PMBJP shops is to sell generic medications, which are equally effective and high-quality as branded medications but are offered at lower costs. India is popularly called as the "Pharmacy of the World" since it exports many different medicines to other parts of the world. But it is facing a problem of higher per capita medical expenditure due to expensive branded medicines in the market. Hence, to reduce the medical expenditure of individuals, the government came out with the concept of providing generic medicines, which is similar to the branded medicines, to the general public at a lower price through the Jan Aushadhi Kendra under the Pradhan Mantri Bhartiya Janaushadhi Pariyojana (PMBJP) scheme. This paper focused on the significant factors influencing the purchasing of generic medicines from Jan Aushadhi medical stores. It revealed cost and quality, promotional activities, customer awareness, and customer psychology and availability of required medicines in Jan Aushadhi medical stores were the key factors influencing customers buying behavior.

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PMBJP, Branded Medications, Customer Behavior and Psychology.

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This paper presents a strategy for perceiving street traffic signs that depends on profound learning and holds incredible commitment for the making of independent vehicles and High level Driver Help Frameworks (ADAS). The framework design is expected to order traffic sign pictures in view of their essential attributes. To play out the acknowledgment, the introduced strategy utilizes a changed LeNet-5 organization to separate a profound portrayal of traffic signs. It is involved a Convolutional brain organization (CNN) changed by partner the consequence of all convolutional layers to the Multi-layer Perceptron (MLP). The German Traffic Sign Dataset is used in the training, which helps students recognize traffic signs well.

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Traffic, Signals, Autonomous vehicles, Advanced Driver Assistance Systems, Extract, Multi-layer Perceptron.

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The first method of calculation for Modified Grey Wolf Optimization (MGWO) has a modest number of limitations of low tackling precision, horrible neighbourhood looking through capability and reasonable combination efficiency. In order to resolve these impediments of MGWO, a further version of GWO calculation was suggested by modifying the Grey Wolf Optimization Algorithm's enclosing conduct and positioning upgrade conditions. The accuracy and combination execution of modified variation has been progressively checked on a few prominent old types including sine dataset and shaft configuration capabilities. This paper presents a use of changed Grey wolf analyser (GWO) to discover the parameters of the critical representative circle for effective AGC of two interconnected force structure territories. This paper is concerned with ensuring the ideal qualities for the corresponding indispensable subsidiary control parameters of burden recurrence control and AVR multi-zone power system using the altered Grey Wolf Algorithm (GWO) process. The LFC circle controls genuine force and recurrence, and the AVR circle controls force and voltage sensitivity. MGWO's enhancement execution is contrasted, and various measurements are based on standard deviations in parameter and target capability estimates.

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Modified Grey Wolf Optimization (MGWO),Grey Wolf Optimization (GWO), Particle swarm Optimization (PSO), Load Frequency Control (LFC), Automatic Voltage Regulator (AVR).

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The main goal of this project is to know the actual car prices, check prices, and estimate the lifespan of a certain including the vehicle's mileage, manufacturing year, fuel consumption, transmission, road tax, type of fuel, and engine size. A new car is reported to lose 10% of its value when driven out of the car's showroom. In this, the no. of kilo-metres the car has been driven is the most essential factor in figuring out its price. As other factors include, it's necessary to understand that different car manufacturers price their vehicles differently, which results in price differences in models. Therefore, to find the car price that every factor is suited for the buyer,

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car price, machine learning, prediction, python, vehicles.

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: Intrusion Detection Systems (IDS) are essential for protecting against a wide range of cyberthreats in modern network security. In order to improve the effectiveness of intrusion detection systems, this paper provides an implementation methodology that focuses on four different machine learning algorithms: Support Vector Machines (SVM), Random Forest, Decision Trees, and Naive Bayes. Every algorithm is carefully customized and included into the IDS architecture to meet certain needs presented by contemporary network environments. Each algorithm's effectiveness is evaluated in terms of computing efficiency, false positive rates, and detection accuracy through extensive testing and analysis. The usefulness of the suggested framework in detecting different kinds of intrusions while reducing false alarms is verified using real-world datasets. In addition, issues of scalability, flexibility, and deployment feasibility are covered in order to promote smooth integration across various network infrastructures. For researchers, practitioners, and organizations looking to implement reliable and adaptable intrusion detection systems using cutting-edge machine learning methods, this paper is an invaluable resource.

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- machine learning; deep learning; support vector machine; intrusion detection system; cyber security

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The impact of Lean Manufacturing principles on customer satisfaction in the automotive industry is a topic of significant importance. Lean Manufacturing, which originated from the Toyota Production System, is a set of principles and practices aimed at minimizing waste and maximizing efficiency in production processes. When applied in the automotive sector, these principles can have a profound influence on various aspects of the industry. First and foremost, the implementation of Lean principles can lead to cost reduction by eliminating non-value-added activities, streamlining production, and reducing inventory levels. This cost savings can, in turn, be passed on to customers in the form of more competitive pricing or improved product features. Furthermore, Lean Manufacturing emphasizes continuous improvement, employee involvement, and a focus on delivering value to the customer. These aspects can directly impact customer satisfaction. Continuous improvement means that companies are constantly seeking ways to enhance their products and processes, resulting in higher quality and reliability. Employee involvement encourages a culture of teamwork and ownership, which can lead to a more engaged and motivated workforce, ultimately contributing to better products and services. The customer-centric approach inherent in Lean principles ensures that automotive manufacturers prioritize meeting customer needs and expectations, leading to products that are more aligned with market demands.

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Lean manufacturing, Customer satisfaction, Automotive industry, Efficiency, Waste reduction, Continuous improvement, Quality management

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After extensive review of prominent research papers on deep learning techniques for food classification and nutrient analysis, we have identified an optimal deep learning algorithm for classifying food and its nutrient composition, alongside selecting a suitable image data set. Our primary goal is to utilize convolutional neural networks (CNNs) to classify food based on nutrient composition. The chosen data set will train the model to recognize patterns and characteristics of food images, categorizing them by fats, carbohydrates, proteins, calories and more. Additionally, our paper integrates sugar, blood pressure, and calorie calculators to offer personalized dietary recommendations. By inputting user data such as age, gender, weight, height, sugar levels, and blood pressure, the application suggests suitable foods tailored to individual needs, promoting balanced nutrition and overall well-being. Furthermore, the application provides information on reputable hospitals, aiming to facilitate access to quality healthcare resources. Our paper aims to empower individuals to make informed dietary choices by enhancing their understanding of nutritional content in food. By offering personalized recommendations and access to healthcare resources, we strive to promote healthier lifestyles and support overall well-being. We ensure the originality of our work by conducting thorough research and implementing innovative solutions, thus contributing to the advancement of knowledge in the field of nutrition and healthcare.

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Deep learning, Food classification, Nutrient analysis, Personalized nutrition, Healthcare resources.

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India's biotechnology industry is expanding quickly, providing social entrepreneurs with numerous chances to tackle important social issues and promote economic development. This study examines the changing biotech landscape in India with an emphasis on opportunities for expansion, sources of funding, public awareness campaigns, and the influence of social entrepreneurship. The study highlights professional consensus about the potential growth of the biotechnology sector by identifying emerging trends based on a thorough review of the literature. It also looks into the various funding options that are available to support biotechnology research and development efforts, highlighting their significance in fostering innovation. In addition, the study looks at how current social entrepreneurship initiatives in the biotech sector are affecting society and the environment, highlighting successful business strategies and models that have improved environmental sustainability and societal well-being. These successful initiatives provide important benchmarks for the field's future growth and development. All things considered, this study sheds light on the complex dynamics of the Indian biotechnology scene and offers social entrepreneurs a road map for overcoming obstacles, seizing opportunities, and promoting constructive change within the sector.

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Biotechnology industry, Biomass utilization, Entrepreneurial opportunities, Growth potential, Social entrepreneurship, Funding sources, Public awareness, Biotech landscape in India, trends, Funding, Environmental sustainability

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The agricultural sector holds a pivotal position in India's economy, employing a substantial portion of the population and making a significant contribution to the nation's Gross Domestic Product (GDP). In pursuit of sustainable growth, enhanced farm productivity, and improved livelihoods for farmers, the Indian government has rolled out various agriculture schemes over the years. Farmer welfare schemes in India represent a concerted effort by the government to address the multifaceted challenges faced by the agricultural community. These schemes are designed to improve the livelihoods of farmers, enhance agricultural productivity, ensure food security, and promote sustainable agricultural practices. This abstract provides an overview of farmer welfare schemes in India, highlighting their objectives, implementation strategies, and impacts. The abstract examines various farmer welfare schemes, including those aimed at providing financial support, crop insurance, irrigation infrastructure development, technology adoption, market access, and soil health improvement. It explores the evolution of these schemes over time, tracing their historical context and the policy initiatives that have shaped them. Through a review of relevant literature and government documents, this abstract analyzes the effectiveness of farmer welfare schemes in addressing the needs of the agricultural sector. It discusses the challenges faced in the implementation of these schemes and identifies areas for improvement to ensure better outcomes for farmers. Overall, farmer welfare schemes in India play a crucial role in supporting the agricultural community and driving rural development. By addressing the diverse needs of farmers and promoting inclusive growth, these schemes contribute to the overall well-being of the agricultural sector and the nation as a whole.

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Agriculture schemes,rashtriya krishi vikas yojana; pradhan mantri fasal bima yojana;

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Supply chain optimization plays a crucial role in enhancing efficiency, reducing costs, and ensuring sustainability in the chemical industry. This study explores various strategies and methodologies for optimizing supply chain networks within the chemical sector. Through a comprehensive review of literature, the study identifies key challenges faced by chemical companies, including volatile market demands, complex transportation networks, regulatory compliance, and risk management. Additionally, it examines emerging trends such as digitalization, green supply chain practices, and circular economy principles that influence supply chain optimization efforts. Various optimization techniques such as mathematical modelling, simulation, and data analytics are discussed in detail, along with their applicability and effectiveness in addressing the unique challenges of chemical supply chains. Moreover, the study highlights the importance of collaboration among stakeholders, technological advancements, and innovation in driving continuous improvement within the chemical supply chain network. By synthesizing insights from academic research and industry practices, this study provides valuable guidance for chemical companies aiming to optimize their supply chain networks to achieve competitive advantage, sustainability, and resilience.

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Supply Chain Optimization, Chemical Industry, Network Design, Mathematical Modelling, Simulation, Data Analytics, Sustainability, Circular Economy, Risk Management, Collaboration, Digitalization.

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Creative Commons Attribution 4.0 and The Open Definition