Modernization and intense industrialization have led to a substantial improvement in people’s quality of life. However, the aspiration for achieving an improved quality of life results in environmental contamination....
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The corrosion degradation of organic coatings in tropical marine atmospheric environments results in substantial economic losses across various *** complexity of a dynamic environment,combined with high costs,extended...
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The corrosion degradation of organic coatings in tropical marine atmospheric environments results in substantial economic losses across various *** complexity of a dynamic environment,combined with high costs,extended experimental periods,and limited data,places a limit on the comprehension of this *** study addresses this challenge by investigating the corrosion de-gradation of damaged organic coatings in a tropical marine environment using an atmospheric corrosion monitoring sensor and a random forest(RF)*** damage simulation,a polyurethane coating applied to a Fe/graphite corrosion sensor was intentionally scratched and exposed to the marine atmosphere for over one *** correlation analysis was performed for the collection and filtering of en-vironmental and corrosion current *** to the RF model,the following specific conditions contributed to accelerated degrada-tion:relative humidity(RH)above 80%and temperatures below 22.5℃,with the risk increasing significantly when RH exceeded 90%.High RH and temperature exhibited a cumulative effect on coating degradation.A high risk of corrosion occurred in the *** RF model was also used to predict the coating degradation process using environmental data as input parameters,with the accuracy show-ing improvement when the duration of influential environmental ranges was considered.
The application of contrastive learning (CL) to collaborative filtering (CF) in recommender systems has achieved remarkable success. CL-based recommendation models mainly focus on creating multiple augmented views by ...
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The scheduling of final exams at a university is a problem which can be improved with artificial intelligence techniques. In this paper we explain and compare two algorithms used to solve the exam scheduling problem a...
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Automatic image captioning is a multidisciplinary effort that combines machine learning, natural language processing, and computer vision in creating meaningful and context-rich captions for images. Within a short tim...
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As an important computer vision task that can be used in many areas, facial expression recognition (FER) has been widely studied which much progress has been obtained especially when deep learning (DL) approaches have...
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Human activity recognition (HAR) techniques pick out and interpret human behaviors and actions by analyzing data gathered from various sensor devices. HAR aims to recognize and automatically categorize human activitie...
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Heart failure is common and often fatal that occurs when the heart is not able to pump enough blood to fulfill the body’s needs. Early prognosis and cure of heart failure can significantly improve patient outcomes, a...
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Agriculture, the backbone of many economies, faces challenges like lack of information, outdated practices, and limited access to technology, hindering farmer productivity. This work proposes a user-friendly, multilin...
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Agriculture, the backbone of many economies, faces challenges like lack of information, outdated practices, and limited access to technology, hindering farmer productivity. This work proposes a user-friendly, multilingual platform leveraging Generative AI to address farmers' diverse needs. The platform encompasses various features to enhance agricultural practices. An LLM-powered Government Scheme Advisor functions as a multilingual chatbot offering intelligent guidance on government agricultural schemes and subsidies. The Disease Detection module utilizes AI technology for real-time identification and treatment recommendations, minimizing crop diseases and yield losses. The Soil Testing Centre feature locates nearby soil testing centers, providing essential information based on geographical data to assist farmers in optimizing soil quality. A Crop Recommendation feature employs Machine Learning algorithms to offer personalized crop recommendations, considering various factors and aiding informed decision-making. The Crop Planning Tool, with its intuitive user interface, simplifies planning planting schedules and managing resources. Additionally, the platform includes an MSP Center Locator to find nearby Minimum Support Price (MSP) centers based on location. By integrating these innovative solutions, this platform bridges the gap between conventional agricultural techniques and contemporary technology, equipping farmers with the resources and expertise essential for advancing productivity and sustainability. Multilingual support ensures accessibility for a wider audience, breaking down language barriers and promoting inclusivity in the agricultural sector. This work proposes an innovative, multilingual platform powered by Generative AI to address these issues. Key features include an LLM-driven chatbot for government scheme guidance, AI-based real-time disease detection, and location-based tools for soil testing and MSP center identification. Additionally, the platf
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