Titlebook: Microbial Data Intelligence and Computational Techniques for Sustainable Computing; Aditya Khamparia,Babita Pandey,Deepak Gupta Book 2024

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Analytics and Decision-making Model Using Machine Learning for Internet of Things-based Greenhouse rameters. Cloud layer, fog layer, edge layer, and sensor layer are four important parts of the proposed approach. The data needed for the sensor layer of the analytical model is collected using Internet of Things-based embedded system devices in two greenhouse facilities, with sensor parameters as i

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DistilBERT-based Text Classification for Automated Diagnosis of Mental Health Conditions,linary exploration into the gut?brain axis, we acknowledge the potential role of gut bacteria, the microbiome, and microorganisms in influencing mental health. Our research specifically focuses on three distinct mental health disorder conditions: anxiety, borderline personality disorder (BPD), and a

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An Optimized Hybrid ARIMA-LSTM Model for Time Series Forecasting of Agricultural Production in Indi with an optimized hybrid model comprising characteristics of both models. The efficiency of the models was checked by using root mean square error (RMSE). The result was compared with other studies on hybrid models. It has been reported that the hybrid model is more appropriate in comparison to bot

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Deep Learning-Assisted Techniques for Detection and Prediction of Colorectal Cancer From Medical Imive choice for fast and effective detection, segmentation, and prediction of diseases through image analysis. This technology has the potential to assist and empower medical professionals in making timely and informed decisions. Deep learning has proven to be highly effective when ample high-quality

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Plant Diseases Diagnosis with Artificial Intelligence (AI),iagnosis. In the realm of computer vision, deep learning has also become increasingly important for providing improved performance results for identifying plant diseases. There has been significant progress in the machine learning and computer vision fields as a result of the application of deep lea

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Analyzing the Frontier of AI-Based Plant Disease Detection: Insights and Perspectives,l professionals, and policymakers in their search for disease-control strategies that are both more successful and more permanent. This study not only identifies the AI methods that hold the most promise for PDD but also brings to light some of the challenges and problems that remain unresolved that

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