Volume 11 | Issue 5 |

 Abstract

Fake product identification is a growing concern in today's global market. The use of blockchain technology can help address this issue by providing a secure and transparent way to track the provenance of products. This paper proposes a system for fake product identification using blockchain, which involves assigning a unique identifier to each product at the time of manufacture and storing its transaction history on the blockchain. By leveraging the decentralized nature of blockchain, this system ensures the authenticity and integrity of product information, making it virtually impossible to tamper with. This paper also discusses the benefits and challenges of implementing such a system and highlights the potential impact it could have on supply chain management and consumer trust. Overall, this paper provides insights into the potential of blockchain technology to tackle the issue of fake products in a secure and efficient manner. Moreover, blockchain-based solutions for fake product identification enable stakeholders to trace the source of counterfeit products. The technology allows them to follow the product's journey from the manufacturing facility to the point of sale, identifying where the counterfeit entered the supply chain. This enables them to take appropriate measures to prevent further counterfeiting and safeguard their brand reputation. In conclusion, blockchain-based solutions for fake product identification offer a secure and transparent way to combat counterfeiting and protect consumers from potentially harmful products. By creating an immutable record of a product's journey through the supply chain, blockchain technology can enable manufacturers, retailers, and consumers to verify the authenticity of products and prevent counterfeiting.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fake product, Blockchain, Decentralized

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Creative Commons Attribution 4.0 and The Open Definition

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Yoga is a popular practice that involves various body postures and breathing exercises to improve physical and mental health. In this project, we have developed a system that detects yoga poses in real-time using a webcam and machine learning algorithms. The system uses a total of eight yoga poses including Bhadrasan, Shavasan, Gomukhasan, Vajrasan, Sarvangasan, Shirsansan, Chakrasan, and Dhanurasan. The system works by first collecting a dataset of yoga poses with corresponding virtual coordinates for each pose. We manually annotated the poses with 501 virtual coordinates on the body and face of the yoga practitioner. The dataset was preprocessed by normalizing the coordinates and splitting them into training and testing sets. We used OpenCV and MediaPipe libraries to extract features from the virtual coordinates for each pose. Once the model was trained and validated, we used OpenCV and MediaPipe libraries to capture live video feed from the webcam and extract virtual coordinates from the video frames. The extracted coordinates were then passed through the trained model to predict the corresponding yoga pose. The system displays the name and accuracy of the predicted pose on the screen in real-time. In addition to pose detection, we implemented a user registration and login system using the tkinter library and an SQLite database. This system allowed users to register their information, which was stored in the database for future logins. The login system ensured secure access to the real-time pose detection system. The proposed system achieved an average accuracy of 95% in detecting the eight yoga poses in real-time. The system can be used by yoga practitioners to monitor and improve their practice, as well as by instructors to monitor their students and provide personalized feedback. Future work includes expanding the dataset to include more yoga poses and incorporating feedback mechanisms to improve the accuracy of the system.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Deep Learning, Yoga Steps, Logistic Regression, Computer Vision.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India, Being the world's fastest-growing economy, India holds immense potential to attract global customers and adapt to new technologies and changes, possesses tremendous potential to attract global customers and embrace new technologies and advancements. The process of digitalization holds immense capabilities, fostering improved connectivity across nearly every sector of the Indian economy. However, the distribution of these approaches can sometimes be uneven among certain government sectors. Embracing the latest technological advancements can bring about significant value and catalyze a drastic transformation in the mode of operations and work for a large segment of the population. One technology that stands out in this regard is blockchain. Blockchain is being globally adopted due to its decentralized approach, secure nature, immutability, and tamper-proof characteristics. In contrast, the management of funds in India remains a contentious issue, with substantial amounts of money allocated to various schemes in the public interest. Yet, due to a lack of transparency, blockchain can serve as a solution to bridge this gap and provide a fully secure and immutable environment for tracking funds.

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 Keywords

Blockchain, HyperLedger, IPFS, Blockchain applications

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Herbal medicine was prepare from various part of plant like flower, leaves, seeds, root etc. For the medicinal use the herbal salve apply externally on human body. This study aimed at formulating and preparing a herbal salve from Lavandula angustifolia, Matricaria chamomilla L. and Aloe barbadensis establishing the quality, healing efficacy of the prepared herbal ointment. The present work is to formulate and evaluate the herbal salve for its antibacterial, anti-inflammatory, antifungal, carminative (smooth muscle relaxing), sedative, antidepressive and effective for burns and insect bites.The formulations were evaluated for their physicochemical parameters like colour, odour, spreadability,consistency, washability. Also the formulation was evaluated for its stability at various temperature conditions which shows no change in the irritancy, spreadability.

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Herbal salve, lavender essential oil, Olive oil, Matricaria chamomilla L. , Aloe barbadensis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

To predict the weather of a particular place at a specific time is known as Weather Forecasting. It is an application of science and technology. Weather forecast is more helpful for people as it predicts the possibilities of changes in weather conditions. The weather forecast can be done in many ways, collecting data and analysing it, image processing, by using methodologies like Normalization, Clustering, and cloud mask algorithms, etc. This paper is based on the process of Weather Forecasting. This system will be using Machine learning algorithms like Support Vector Machine(SVM), Time series based recurrent neural network, Random Forest, Naive Bayes, Artificial Neural Network, and Decision Tree. This system will accept data on current weather conditions such as current temperature, wind conditions, and humidity. It will predict the weather conditions of a certain location on a given day and time. This system will be useful in Air Traffic, Marine, Agriculture, Forestry, Military, and Navy, etc.

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 Keywords

: Weather Forecasting, Weather prediction, machine learning, SVM, ANN, Naive Bayes.

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Creative Commons Attribution 4.0 and The Open Definition

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It is more acceptable to believe that natural remedies are safer with synthetic subjects than with fewer side effects. The global market demand is increasing due to the fusion of herbs. Current work Herbal anti-acne is the development and evaluation of flammable extracts with facial spray containing leaf extract of Tulsi (Ocimum Sanctum),Hydroalcoholic extract of turmeric (curcuma longa), Although there are some specific local herbal formulas available on the market, we propose to make pure herbal formulations without using any artificial ingredient. The plants have been reported in the literature with microorganisms, anti oxidants and anti-inflammatory activity. Ayurvedic face wash was prepared from the extract of various ingredients such as Neem leaves, Turmeric rhizomes, Nutmeg seed, Liquorice root, Honey, Orange tincture, Lemon juice, Xanthan gum, Orange peel extract, Rosewater, Propyl paraben, Methyl paraben, Sodium laury sulfate. The prepared face wash was evaluated for various Physical parameters such as Washability, Colour, pH, Viscosity, Spreadability and Irritancy test.

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Keywords:- face wash, Turmaric, Rose water. Spreadabilitylity, Irritancy test

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Creative Commons Attribution 4.0 and The Open Definition

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In this article, we demonstrate how deep learning was used to implement handwritten character recognition in Marathi. Because of its significant contribution to automation systems, handwritten character recognition is becoming more important. One of the several language scripts used in India is the Devanagari script. There are 12 vowels and 36 consonants in it. Here, we used a deep learning model to implement character recognition. Pre-processing, segmentation, feature extraction, prediction, and post-processing are the five main phases in character recognition. To train the model and employ character recognition and anticipate the accuracy of recognition, the model will make use of convolutional neural networks and image processing techniques.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pre-processing, Segmentation, Classification, Convolutional Neural Network, Deep Learning, Devanagari Character Recognition.

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Creative Commons Attribution 4.0 and The Open Definition

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Introduction: Putting one step towards to extend the family is the crucial stage of life to become a parent. When a couple is seen and counselled about pregnancy, its course and outcome well before the time of actual conception is called periconceptional counselling. Aim of the study: The aim of the study was to identify the effect of structured teaching program on knowledge regarding Preconception care among the eligible women in selected villages. Objectives: 1) To assess the pre-test level of knowledge regarding preconception care among the eligible women in selected village of south Gujarat. 2)To assess the effectiveness of structured teaching programmed on knowledge level regarding preconception care among the eligible women. 3) To find out the association between pre-test score of knowledge regarding preconception care among the eligible women in villages of South Gujarat with their selected socio demographic variable. Method: Quantitative Research Approach design is sub-division of pre-experimental research design. With one group pre-test post-test research design was adopted for this study. A total of 100 eligible women who were selected by Purposive sampling technique. Data was collected by using structured teaching program consisting of socio demographic variables and self-structured questionaries. Results: The overall mean percentage of knowledge in the pre-test was 10.41 with standard deviation 2.01. The overall mean percentage of knowledge in the post-test was 15.54 with standard deviation 1.7 with a positive mean difference 5.13. there is significant association between pre-test knowledge score of eligible women and selected socio demographic variables is accepted for age of the mother and education. Interpretation and conclusion: Results shows that post-test knowledge score is significantly higher than the pre-test score at p <0.05 level of significance i.e., mean difference is 5.13. There is significant improvement in knowledge of eligible women regarding pre- conception care.

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 Keywords

STP, DF

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Creative Commons Attribution 4.0 and The Open Definition

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The goal of the current analysis is to examine how children in the Cuddalore District of Tamil Nadu perceive about the environment. 286 samples from the research area were taken using the random sampling technique. Use of the normative survey method was made. The goal of this study is to ascertain the levels of environment attitudes among school pupils and determine whether there are any notable differences between the sub-samples and predictors that have been chosen. This study makes use of the Environmental Attitude Scale that researchers Dr. D. Ponmozhi and G. Ranjitha developed and validated in 2023. The five dimensions of environmental attitude are covered by the 40 statements that make up this scale: Garden Management, Air & Soil Pollution, Water Recycling, Environmental Awareness, and Sources of Energy & Ecofriendly Products. With the aid of chronph alpha, the scale's reliability and validity were determined. The reliability of the scale was 0.876, and the validity of the scale was 0.93.With the use of SPSSIBM23, descriptive, inferential, correlational, and regression analysis were performed. Students at the school show poor attitudes towards the environment. Two steps and the removal of 10 variables later, the prediction model was established, which comprised two of the twelve predictors. The model explained almost 7% of the variance in environmental attitude (R2=0.075 Adjusted R2=0.068) and was statistically significant (F(2, 283) = 11.397, p .001). Gender and age are the main predictors of environmental attitude. Therefore, the gender and age of schoolchildren were rather reliable indicators of their environmental attitudes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Environmental attitudes, School children

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Creative Commons Attribution 4.0 and The Open Definition

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Agriculture plays a critical role in the economic development of any country, and in India, a significant portion of the population relies on it. Crop diseases pose a major challenge, as they can have detrimental effects on plant health and agricultural productivity. This paper presents an AI-based system for automated detection and classification of plant leaf diseases. The proposed system aims to assist farmers in quickly identifying diseases and implementing appropriate measures. The methodology involves image collection, preprocessing, segmentation, and classification using artificial intelligence techniques. By enhancing disease detection and management, this system aims to improve crop productivity in the field of agriculture.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

plant disease detection,deep learning algorithm, cnn,svm,image processing,classification,prediction.

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Creative Commons Attribution 4.0 and The Open Definition