Alzheimer's Disease is a complex and currently one of the most prevalent illnesses. Due to these factors there is a growing emphasis on the early diagnosis of Alzheimer's Disease and our approach involves leve...
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In recent times, Synthetic-Aperture Radar (SAR) images have gained significant importance due to their extensive use in both military and civilian applications. However, these images are often compromised by speckle n...
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In this study, we develop an innovative federated framework for erasable itemset mining to address the challenges of horizontal federated learning in data mining and resolve the shortcomings of the previous algorithm....
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Plant diseases pose severe risks to agricultural production and global food security. For prompt intervention and mitigation, early and precise disease detection is crucial. Due to the development of trustworthy compu...
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Creating resilient machine learning (ML) systems has become necessary to ensure production-ready ML systems that acquire user confidence seamlessly. The quality of the input data and the model highly influence the suc...
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Recommender systems are techniques designed to enhance user experience in various domains. They suggest relevant items to users based on their behavior and preferences (Linyuan et al. Feb 2012). These systems are bein...
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Twitter and other social media platforms have evolved into crucial sources of information and communication for billions of people across the world. The massive amount of data collected on these platforms enables insi...
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Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)...
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Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be defined by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.
Patients with medical implants may have contraindications when undergoing an MRI scan due to the accumulation of heat in tissues surrounding the implants. The heating of local tissue is due to the RF-fields from the M...
The evolution of traditional power systems into smart grids has been pivotal in enhancing grid efficiency, stability, and sustainability. This study presents a comprehensive load flow analysis and optimization framewo...
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