BURSA
发表于 2025-3-28 16:56:50
Guido Becke,Stephanie Pöser,Cora Zenzledge for the purpose of building Food Composition Tables. The latter can therefore be used for food recommendation, ingredient substitution, etc. To demonstrate the relevance of the knowledge extracted, we invited one domain expert for validation. On the other hand, we compared an excerpt of the kn
内向者
发表于 2025-3-28 19:30:43
https://doi.org/10.1007/978-3-662-65598-6integrity and protect sensitive information in the proposed blockchain. Extensive simulations and real-world trials assess the algorithm‘s efficiency and efficacy. Data sharing speed, transaction throughput, and security are compared to typical VANET data sharing methods. The biometric blockchain al
松紧带
发表于 2025-3-29 00:11:32
https://doi.org/10.1007/978-3-662-65598-6sed on fungal diseases and some researchers only focused on bacterial diseases. In this research, The aim is to detect 13 different fungal and bacterial mango leaf diseases using CNN techniques. The photographs were captured in the Andhra Pradesh state’s Chittoor district, which is home to India’s l
forthy
发表于 2025-3-29 05:17:16
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抵押贷款
发表于 2025-3-29 08:39:56
Alexander Klamar,Sebastian Fischerleads as a significant indicator of environmental impact, explores potential alternatives, and provides a comparison of CO2 emissions. Our work focuses specifically on assessing the environmental consequences of food production, primarily through the measurement of CO2 emissions. We consider key fac
证明无罪
发表于 2025-3-29 12:50:15
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咒语
发表于 2025-3-29 16:36:31
ESG and IoT: Ensuring Sustainability and Social Responsibility in the Digital Age,monitored, and trigger real time alarms when needed. As the adoption of IoT continues to grow, it will be important to monitor and evaluate its impacts on ESG, and to identify and implement best practices for ensuring that IoT can contribute positively to environmental, social, and governance outcom
avarice
发表于 2025-3-29 23:08:03
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蛛丝
发表于 2025-3-30 03:08:52
Leaf Disease Detection Using Transfer Learning,sification abilities. The paper also examines the practical implications of the models for real-time leaf disease detection. Factors such as inference time and computational resource requirements are considered to assess their suitability for deployment in real-world scenarios. The analysis tries to
分散
发表于 2025-3-30 06:49:05
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