Volume 11 | Issue 5 |

 Abstract

At first, blockchain was solely utilised as the basis for cryptocurrencies, but as time goes on, we are witnessing the adoption of this brand-new, rising technology across a range of businesses. Blockchain is anticipated to be used by the majority of technology as an effective method of conducting online transactions in the future. One application for blockchain technology is in crowdfunding sites. The biggest problem with the current global crowdfunding industry is that campaigns are not regulated and some of them have proven to be fake. Additionally, some projects have been considerably delayed in their completion. By integrating Smart contracts into the crowdfunding platform, enabling the contracts to be fully automated, eliminating fraud, and other concerns, this project aims to address them.

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 Keywords

Blockchain, crowdfunding, Ethereum; smart contracts, metamask.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The project mainly focuses on measuring peel strength of adhesive tapes. Peel strength is average force required to separate two bonded materials from one another. It is properly applicable to various industries such as aerospace, automotive, adhesives, packaging, bio-materials, microelectronics, etc. Peel test data is used to determine the quality of the adhesive joint. Peel strength is very important factor for any type of adhesive as it plays very important role for the selection of adhesive tape and as per the requirement parameter.

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 Keywords

measuring peel strength of adhesive tapes

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Soil analysis is a valuable tool for your operation because it identifies the inputs needed for efficient and economical production. A proper soil test helps ensure that enough fertilizer is being applied to meet crop needs while using nutrients already present in the soil. A series of different chemical processes determine the amount of plant nutrients and the chemical, physical and biological properties or "soil health" of the soil, which are important for plant nutrition. Taking soil samples, analyzing the samples in the laboratory, issuing fertilizer recommendations and interpreting the results is a very time-consuming process for farmers. Therefore, we have developed a soil analysis system. I have two data sets, one of which is an image of a different soil 1. Red soil 2. Black soil 3. Hill soil 4. Desert soil is a different plant. The model can suggest soil types and suggest suitable plants depending on the soil type. Use CNN (Convolutional Neural Network) algorithm to train the models and find the results. The final application is a web browser that loads the clay image. The app predicts the soil type and, depending on the soil type, it also predicts the suitable crop for the soil.

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 Keywords

(CNN)Convolutional Neural Network, Crop Suggestion, Soil Classification, Soil Testing, Soil Types.

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 Abstract

Recognizing human activities is a crucial yet difficult study area in the field of computer vision. We suggest context features in this work together with a machine learning model to identify the specific subject activity in the image. To enhance the performance of recognition, we use the dataset from various sources. To provide a high-level representation of human activity recognition based on an image collection, we develop a deep neural network structure. Recognizing human activity necessitates forecasting a person's behaviour using image-based information. The photos are divided into recognized activities. The goal is to forecast human activity using machine learning techniques with the highest degree of accuracy. The CNN Algorithm can be used to categorize the photos. To choose the best architecture, more than two architectures were compared. Finally, the model can be deployed in Django framework.

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 Keywords

Image Classification, CNN, neural nework,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Brain tumors have recently emerged as one of the most critical issues for individuals suffering from severe headaches. However, most people are concerned that their headache is the result of a serious problem, such as a brain tumor, especially if they experience severe pain on a regular basis. In general, practically all brain tumors do not induce headaches since the brain has the ability to modulate discomfort. Some tumor cause more frequent headaches if the patient's brain contains a large tumor that puts pressure on nerves. A brain tumor is a sort of abnormal cell that develops in the human brain and is always classified as benign or malignant. If the tumor is detected in its early stages and therapy is initiated, the quality of life and life spam may improve. There is currently a high need for brain tumor diagnosis using various machine learning and deep learning techniques. With the advancement of artificial intelligence, deep learning models are being used to diagnose brain tumors using magnetic resonance imaging pictures. Magnetic resonance imaging (MRI) is a sort of scanning procedure that produces detailed images of the inner body by using powerful magnetic fields and radio waves. Deep learning methods such as convolutional neural network (CNN) models and VGG-16 architecture (developed from scratch) are used in this study to locate tumor regions in scanned brain pictures. We looked at brain MRI scans from 253 patients, 155 of which were tumors and 98 of whom were not. The research compares the outputs of the CNN model and the VGG-16 architecture used.

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 Keywords

Brain Tumors, Magnetic Resonance Imaging, VGG-16, Convolutional Neural Network (CNN) Model, Deep Learning Model, Abnormal Cell

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 Abstract

In earlier days, the consumer or the retailer could not buy or sell the commodities directly from the manufacturer. There have always been some middlemen whose involvement led to increase in transactions and the product price, which intern would help them in making enormous profits leaving the retailers with very marginal profits and the consumers with the least. The e-commerce platform is playing a very important role in today's Trade and Business. There are many social enterprises connecting manufacturers and consumers which help in providing qualitative and quantitative products to consumers and ensure sustainability and fair income to manufacturers. The aim of this proposed project is to build and develop a reliable website for an Enterprise with the vision of changing the landscape of business practices in our country as per the current e-commerce theories and standards, develop effective and well-designed web pages with robust data storage. This proposed website will help consumers/retailers buy or sell products online which will intern help manufacturers buy or sell their products online without the involvement of middlemen. The speciality of the website will be that even buyers will be able to view the analytic of the sales in a graphical format so that they can know the most selling items. The buyers will be able to buy the product in bulk so they get the product at the best price. This way both consumers and manufacturers get fair prices throughout the year irrespective of market fluctuation and consumers get to experience transparency throughout the processes.

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 Keywords

--middlemen, robust data storage, graphical format, bulk

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 Abstract

The main objectives of this study are to compare the growth of Milch animals and Milk Production in Uttar Pradesh and Lucknow District because Uttar Pradesh are the milk surplus states in India and Lucknow is one of the top district on the basis of milk procurement in Uttar Pradesh in 2017-18. Lucknow Plant with capacity of 3 lakh litre production that has expected cost Rs. 117.43 crore in which milk manufactured products is- packed milk powder, Paneer, Yogurt, Ghee and Khoya. Hence, Uttar Pradesh has considerable potential for generating additional employment through milk production. Study shows that the growth of milch animals has been statistically Change in Uttar Pradesh with 2% while the growth of milch animals has not been statistically Change in Lucknow District. On the other side, the growth of Milk Production has been statistically Change in UP with 4.3% as same as in Lucknow district.

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 Keywords

Keywords- Dairy Farming, Milk Production, Milch Animals, Growth comparison, Lucknow, Uttar Pradesh, etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this study we have investigated both the discipline of pure mathematics and its application to the solution of significant mathematical problems. In mathematics, we frequently utilise apparatus designed for multiple purposes. Contemporary algebra refers to the study of groups as group theory. In this context, a group is a device that satisfies a set of axioms by joining together to satisfy a fixed set of axioms and is made up of a fixed set of devices and binary characteristics that can be used in units. This requires that the Groups be shut down as part of the procedure, that it adheres to the merger rule, and that it consists of an inverted proprietary object. When a set also satisfies the rule of exchange, it is known as an abelian or versatile group. This is the case because the set conforms to the law of exchange. An abelian group is a collection of subscript numbers in which the detail equals zero and the alternative may be of either high or low argument variety quality. Groups play a crucial role in modern algebra; their fundamental structure can be observed in the most radical mathematical situations. In geometry, the concept of groups can be observed; these groups characterise activities that occur in conjunction with measurements and particular transformations. The group concept can be applied to disciplines such as physics, chemistry, and computer science.

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A SURVEY ARTICLE ON THE CHALLENGES AND DISCOVERIES MADE IN THE STUDY OF GROUP THEORY

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 Abstract

THE IMMEDIATE EFFECT OF FOAM ROLLING IN PARASPINAL MUSCLE SPASM AND PAIN IN UNDERGRADUATE PHYSIOTHERAPY STUDENTS WITH GENERALIZED MECHANICAL LOW BACK PAIN.

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THE IMMEDIATE EFFECT OF FOAM ROLLING IN PARASPINAL MUSCLE SPASM AND PAIN IN UNDERGRADUATE PHYSIOTHERAPY STUDENTS WITH GENERALIZED MECHANICAL LOW BACK PAIN.

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 Abstract

Online exam cheating has become a significant challenge for academic institutions worldwide due to the ease of access to online resources and the difficulty in monitoring students remotely. The existing systems for detecting online exam cheating are limited to simple rules-based systems that can only identify a small number of dishonest behaviors. In this essay, we suggest a Deep Learning-based Online Exam Cheating Detection System using Behavioral Modeling. Deep learning algorithms and a camera are used by the system to monitor the behavior of students during online exams. The deep learning algorithm is trained to classify normal and abnormal behavior based on the features detected by the camera. To evaluate the proposed system, we conducted experiments on a dataset of online exam scenarios that included both normal and abnormal behavior. The results of our experiments demonstrate that the proposed system can accurately detect cheating behavior in online exams with a high degree of accuracy. Our proposed system has several advantages over existing systems, including the ability to detect a wider range of cheating behaviors, high accuracy, and low instances of false positives. The proposed system can be used to enhance the security and integrity of online exams and can help academic institutions to maintain the quality of their assessment process.

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 Keywords

Online exam cheating, Deep Learning, Behavioral Modeling, Detection System, Camera, Monitoring, Normal behavior, Abnormal behavior, Accuracy, False positives, Security, Integrity, Academic institutions, Assessment process.

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Creative Commons Attribution 4.0 and The Open Definition