Volume 11 | Issue 5 |

 Abstract

Agriculture is a major industry in many nations, including India. Because farm output accounts for a large portion of the Indian financial system, careful examination of Critical challenges with food production exist. Crop infection nomenclature and identification now hold more scientific and financial weight in the agricultural industry. It may be highly expensive to keep track of plant ailments in an agricultural area with the assistance of professionals. A technique or system that can automatically diagnose is required. diseases because it has the potential to revolutionize monitoring. Massive crop fields and plant leaflets can be taken. Cotton leaf disease diagnosis is critical for preventing a catastrophic outbreak. Immediately following disease recognition, the purpose of this study is to provide guidance for the creation of an application that recognizes cotton plant leaf diseases. To use this, the user must first submit a photograph of a cotton leaf, and then use image processing to obtain a digitized color image of a damaged leaf, which may then be processed further by applying the mobilenet algorithm to anticipate the true root cause of the cotton leaf disease.

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Deep learning

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Breast cancer is a prevalent cancer type among women worldwide. Medical imaging techniques, such as X-ray mammography, magnetic resonance imaging (MRI), and ultrasound, have their limitations. The objective of this study was to develop a new method to detect the presence of malignant tumors using a microstrip patch antenna designed in the ISM frequency range, along with two types of 3D breast phantoms. The study aimed to identify cancerous tumors in the breast phantom by analyzing the variation of S11 parameters. The efficiency and reflection parameters were evaluated. This technique is advantageous because it uses microwaves, which are non-ionizing and do not harm biological tissues. By detecting changes in the reflection coefficient and observing higher S11 values in the presence of a tumor, this method can detect breast tumors effectively.

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 Keywords

tumor; microstrip patch antenna; S11 paramaeters ;

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 Abstract

The sun's radiation, which generates electricity, is referred to as solar energy. Solar energy is a vast, abundant, inexpensive, and environmentally friendly source of renewable energy. Because of these characteristics, the world is currently researching and discovering the most cost-effective way to harness this energy, and the solar tracking system is the result of that search. Solar panels were developed to generate this energy by absorbing sun rays and converting them into electricity or heat. This report provides an overview of solar PV cells and the materials required to construct them. There's also a discussion of the various types of solar PV systems, solar dirt cleaning and solar tracking systems. But mostly it focuses on the design and performance analysis of various dual axis tracking solar systems that have recently been proposed.

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Solar Panel Technology

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Obesity is one of the Santarapanajanya Vyadhi, originated as a result of deteriorated life style which includes sedentary daily routine and junk food habits. it occurs when the consumption of calories becomes more than its expenditure. it serves as an etiological factor for many diseases. it has reached to the epidemic proportion, affecting majority of the urban population. obesity can be estimated by various scales among which body mass index (BMI) and skin fold measurements are most common. despite the fact that man has created sophisticated machines, medical technology, and powerful medicines, he still lacks proper health. in an effort to succeed people are adopting a poor lifestyle, increasing the risk factors for disease and stress in their lives by indulging in more worldly pleasures and luxury. this is the main cause of the current rise in lifestyle disorders. whereas the primary and underlying cause of many other lifestyle disorders is obesity. in ayurvedic literature, there is a detailed description of obesity by the name of Sthaulya, but the material is dispersed and there are conflicting opinions from various Acharya. Ayurveda treats the condition holistically by addressing Diet, Lifestyle, Medication and Sodhanakarma. as a result, the current study includes a detailed review of Sthaulya with the goal of illuminating the various management strategies for Sthaulya (obesity).1

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 Keywords

Sthaulya, Santarapanajanya Vyadhi Obesity & Lifestyle Disorders.

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 Abstract

Social concern is a conventional very close flourishing issue that lives on a lack of predicament and. In its mildest arrangement, it could present as transient social disquiet, happening thinking about normal social-evaluative conditions, while its more serious advancement is portrayed by pummeling, certain apprehension and revolution. Critical clinical issues can influence various pieces of students' lives, diminishing their own fulfillment, informative achievement, ensured flourishing, and satisfaction with the school getting it, and unreasonably affecting relationship with friends and family. These issues can comparatively have critical length ideas for students, affecting their future work, gaining potential, and for the most part thriving. When gone up against with an endeavor, strain toward dissatisfaction prompts serious disquiet and can make individuals stop or over-plan or avoid the endeavor not set in stone to hinder impressions of shame.

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IMPACT OF EXAM FAILURE ON THE MENTAL HEALTH OF STUDENTS

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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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Blockchain, crowdfunding, Ethereum; smart contracts, metamask.

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 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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measuring peel strength of adhesive tapes

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

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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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Image Classification, CNN, neural nework,

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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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