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RISS 인기검색어
- 검색키워드
- 저자 : Ch. Mallikarjuna, Rao (검색결과 2 건)
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Facile synthesis of Cu@TiO<sub>2</sub> core shell nanowires for efficient photocatalysis
Babu, B.,Mallikarjuna, K.,Reddy, Ch.V.,Park, J. North-Holland 2016 Materials letters Vol.176 No.-
Metallic copper is a dependable co-catalyst for improving photoactivity of TiO<SUB>2</SUB> photocatalysis. Cu@TiO<SUB>2</SUB> core shell nanowires (NWs) were prepared by wet chemical synthesis and characterized. The microscopy images clearly show core shell morphology in nano regime. X-ray diffraction studies reveal the metallic copper and anatase TiO<SUB>2</SUB> crystallinity. The optical absorption spectra exhibit ultraviolet and visible light harvesting properties. X-ray photoelectron spectroscopy confirms the presence of oxidation states of metallic copper and titanium. The photocatalytic efficiency was investigated by degrading the methyl orange (MO) and 3wt% Cu@TiO<SUB>2</SUB> core shell NWs shows highest degradation rate (k=0.02905min<SUP>-1</SUP>) with superior photocatalytic activity. This material could be surely meet the necessities to harvest solar energy for many energy-related applications.
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A Comprehensive Literature Study on Precision Agriculture: Tools and Techniques
Bh., Prashanthi,A.V. Praveen, Krishna,Ch. Mallikarjuna, Rao International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.12
Due to digitization, data has become a tsunami in almost every data-driven business sector. The information wave has been greatly boosted by man-to-machine (M2M) digital data management. An explosion in the use of ICT for farm management has pushed technical solutions into rural areas and benefited farmers and customers alike. This study discusses the benefits and possible pitfalls of using information and communication technology (ICT) in conventional farming. Information technology (IT), the Internet of Things (IoT), and robotics are discussed, along with the roles of Machine learning (ML), Artificial intelligence (AI), and sensors in farming. Drones are also being studied for crop surveillance and yield optimization management. Global and state-of-the-art Internet of Things (IoT) agricultural platforms are emphasized when relevant. This article analyse the most current publications pertaining to precision agriculture using ML and AI techniques. This study further details about current and future developments in AI and identify existing and prospective research concerns in AI for agriculture based on this thorough extensive literature evaluation.
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