Volume 11 | Issue 4 |

 Abstract

Medicinal herbs are the local heritage with global importance. They have curative properties due to presence of various complex chemical substances of different composition, which are found as plant secondary metabolites in one or more parts of these plants.Mashabaladi Kwatha is a multi-herb decoction which contains seven important herbs in equal quantity and two drugs as Prakshepa dravya. The present study provides updated information on its phytochemical analysis, pharmacological properties and probable mode of action of Mashabaladi Kwatha. The decoction has Tridoshaghna action mainly Vata-Kaphashamaka along with Nadibalya (nervine), Dhatuvardhaka-Pushtikara (nourishes and strengthening the body tissue, fluids etc.), Shophahara(anti-inflammatory), Shoolahara(subsides pain), Raktapittahara (haemostatic), Amapachana (digestive), Rasayana(rejuvenating), Vrushya (aphrodisiac) etc. All these properties of Mashabaldi Kwath are considered to combat vitiation of Vata in Pakshaghata (hemiplegia), Manyasthamba (cervical spondylitis), Karnanada (tinnitus) and Ardita (facial paralysis). Last decade have witnessed exceptional rise in demand of plant based Medicine and herbal product in International market. Due to excessive demand in the Global market, the rate of extraction of medicinal plants from natural sources is higher than the rate of their regeneration. That directly contributes to the present scarcity of medicinal plants. This study highlights the results of standardization (identity, purity & strength) tests, preliminary phytochemical screening and TLC findings. All the said tests are conducted in The Tamil Nadu Dr. M.G.R. Medical University, Chennai. These studies are important in way of establishing quality-control, efficacy & accept ability of herbal drugs.

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 Keywords

Mashabaladi kwatha,Tridoshagna,Nadibalya,Shophahara,Pakshaghata

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 Abstract

Bharat pak sambandho me kasmir samsya ka ek vishleshanatmak adhyanan

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Bharat pak sambandho me kasmir samsya ka ek vishleshanatmak adhyanan

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With the increasing pace of modern life, consumers are increasingly seeking convenient food options that are easy to prepare and consume. Most of the time people prefer instant food like cup noodles, chapati, nuggets, instant idly, dosa mix etc. specially youngsters. Ready-to-eat (RTE) foods have emerged as a popular solution to this need, offering a range of convenient and easy-to-prepare options that require minimal time and effort. This study is limited to 102 respondents between the ages 15 to 45 in Tamil Nadu which had been contacted using social media. In this study 59.8% are males and 40.2% are females. Each respondent to this study asked to complete a short questionnaire in order to analyse the data. This study aims to investigate consumer behaviour towards RTE foods and identify the factors that influence their purchasing decisions, analyse the consumer perception and consumer satisfaction towards Ready-To-Eat Food products. The results of the study reveal that convenience, taste, and availability are the most important factors that influence consumer behaviour towards RTE foods. Consumers prefer RTE foods that are easy to prepare and have a long shelf life, and are willing to pay a premium price for RTE foods that they perceive as healthier and of better quality. Overall, the study provides important insights into consumer behaviour towards RTE foods and highlights the need for further research to explore the potential health risks associated with RTE foods.

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 Keywords

Consumer behaviour, Ready-to-eat foods, Convenience, Health concerns, Brand reputation, Marketing strategies, Consumer satisfaction

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 Abstract

Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone assisted disease diagnosis. Using a public dataset of 2000 images of diseased and healthy plant leaves collected under controlled conditions, we train a deep convolutional neural network to identify Cotton crop species and 3 diseases (or absence thereof). The trained model achieves an accuracy of 82.35% on a heldout test set, demonstrating the feasibility of this approach. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets presents a clear path toward Web based crop disease diagnosis on a massive global scale. The advance and novelty of the developed model lie in its simplicity; healthy leaves and background images are in line with other classes, enabling the mode l to distinguish between diseased leaves and healthy ones or from the environment by using deep CNN. Novel way of training and the methodology used facilitate a quick and easy system implementation in practice. All essential steps required for implementing this disease recognition model are fully described throughout the paper, starting from gathering images in order to create a database, assessed by agricultural experts, a deep learning framework to perform the deep CNN training. This method paper is a new approach in detecting plant diseases using the deep convolutional neural network trained and fine-tuned to fit accurately to the database of a plant's leaves that was gathered independently for diverse plant diseases. The advance and novelty of the developed model lie in its simplicity; healthy leaves and background images are in line with other classes, enabling the model to distinguish between diseased leaves and healthy ones or from the environment by using deep CNN.

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 Keywords

Acquisition, Disease Diagnosis, Cotton Detection, Identification of plant diseases, Agricultural experts, Convolutional Neural Network, Pathogens.

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 Abstract

The electric car plays a vital role in current technology due to its various features. There is a need for an effective transportation system, particularly four wheelers, due to overpopulation. The amount of fossil fuel being consumed to make petroleum products is rising. As a result, the price of petroleum items is steadily rising every day. Individuals frequently suffer as a result of the rising price of petroleum products. There are also new models of electric cars on the market that can run entirely on electricity stored in a battery, eliminating the need for fuel energy. As a result, lots of individuals are enthusiastically purchasing and using it. But, compared to a typical petrol car, an electric car is unable to travel farther, climb hills more easily, or run at its top speed. We presented a new electric car that addresses the flaw of existing cars in order to get over these issues with gasoline and electric cars. Both an internal combustion engine and an electric motor are used to power our car. The drives of internal combustion engines and electric motors operate independently of one another. The user has the option of selecting between the electric mode as the driving mode. The client can experience a dual mileage system with our car by using battery power. Our car has a regenerative braking mechanism installed, which results in a little amount of battery charging. Fast battery charging is not possible with electric cars, making it uncomfortable for the rider in an emergency. Yet, under our system, a user can work in fuel mode during an emergency, charge the battery during downtime, and then use. We provide a detachable electric fitting; client can use the same component for another model of petrol car. Also, we offer a battery overheating warning system and a theft alarm, which will undoubtedly help the user avoid fire. This car offers the rider excellent durability and high flexibility while requiring less maintenance. Our method will undoubtedly benefit the user with greater efficiency in the world we live in today, where there is a huge demand for gasoline.

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 Keywords

Battery, Petrol car, Electric Propulsion and Hybrid electric vehicle.

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Whether a car has front-wheel drive, rear-wheel drive, or all-wheel drive, the majority of current models use a two-wheel steering system to control their movement. However, four wheel steering vehicles are being employed more frequently as a result of increased safety awareness because they are also renowned for their outstanding performance and stability. They are wheels of conventional two-wheel steering vehicles do not assist with steering and simply follow the front wheels' route. In four-wheel steering, the wheels can be turned left or right depending on the situation. The direction of rotation for the rear wheels might be either parallel to the front or opposite. The four-wheel system is made to operate in three different ways. Specifically, rotations that are in-phase, out-of-phase, and zero.

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 Keywords

Design, fabrication, dual axis steering mechanism, review.

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This research study explores the role and benefits of modern technology in hiring processes in India. The study examines key technological advancements, such as applicant tracking systems, AI-powered chatbots, machine learning, video interviewing, and social media recruiting, and how they have improved the efficiency and effectiveness of the hiring process. The study also considers the challenges in implementing technology in hiring and provides case studies of companies, such as HDFC Bank, Reliance Industries, and Tata Consultancy Services, who have successfully implemented technology-driven solutions in their hiring process. The research concludes with insights into the future of technology in hiring in India. The key takeaways from this study are the increased efficiency, cost savings, reduced bias, and improved candidate experience that technology can bring to the hiring process.

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modern technology, hiring process, applicant tracking systems, AI-powered chatbots, machine learning, video interviewing, social media recruiting, efficiency, effectiveness, cost savings, bias reduction, candidate experience

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With the increase in urbanization, traffic congestion and environmental pollution have become significant issues in many cities worldwide. Electric foldable cycles are an innovative solution that provides a sustainable and efficient mode of transportation for urban commuting. Electric foldable cycles have become a popular mode of transportation due to their versatility, convenience, and eco-friendliness. This paper provides an overview of electric foldable cycles, including their history, design, features, and benefits. The paper also discusses the current market trends and future outlook for electric foldable cycles. This paper aims to examine the rise of electric foldable cycles as a popular and viable option for urban mobility. The paper reviews the current market trends, advantages and disadvantages, technical specifications, and future prospects of electric foldable cycles.

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 Keywords

Electric Foldable Cycle, Pollution, Urban Commuting.

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Because of its effects on the various communication and security domains, intrusion detection in computer networks is crucial. It can be difficult to find network intrusions. Furthermore, network intrusion detection is still a difficult task because it takes a tremendous amount of data to train modern machine learning models to recognize network intrusion threats. Recently, a number of methods have been put out for network intrusion detection.

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 Keywords

NSL-KDD, machine learning, feature scaling, network intrusion detection system (NIDS), software defined network (SDN), Ada Boost.

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The future of the automobile industry is electric vehicles which are advantageous to us in many ways. Electric vehicles do not emit pollutants which make them eco-friendly and are generally differentiated with the help of a green license plate. The proposed system aims at building an intelligent model that can recognize electric vehicles such as cars, buses, autos and two-wheelers from its green license plate. The technique used here is image processing which works by processing the images of vehicle license plates. The final objective is to create an automatic authorized electric vehicle recognition machine. The data can be used by the government to conduct surveys and monitor the growth of electric vehicles in society. The data can also be further analyzed by environmentalists to understand the level of impact the electric vehicles have on the environment.

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 Keywords

Electric Vehicles, Recognition, Machine Learning, OpenCV, Color detection, License plate detection

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