Volume 12 | Issue 4 |

 Abstract

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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 Keywords

PMBJP, Branded Medications, Customer Behavior and Psychology.

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 Abstract

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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 Keywords

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

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 Abstract

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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 Keywords

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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 Keywords

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

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 Abstract

: 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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 Keywords

- 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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 Keywords

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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 Keywords

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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 Keywords

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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 Keywords

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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 Keywords

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