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Effect of Alkali Carbonate/Bicarbonate on Citral Hydrogenation over Pd/Carbon Molecular Sieves Catalysts in Aqueous Media

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Modern Research in Catalysis 2016年第1期5卷 1-10页

作者： racharla krishna Chowdam Ramakrishna Keshav Soni Thakkallapalli Gopi Gujarathi Swetha Bijendra Saini S. Chandra Shekar Defense R & D Establishment Gwalior India

The efficient citral hydrogenation was achieved in aqueous media using Pd/CMS and alkali additives like K2CO3. The alkali concentrations, reaction temperature and the Pd metal content were optimized to enhance the citral hydrogenation under aqueous media. In the absence of alkali, citral hydrogenation was low and addition of alkali promoted to ~92% hydrogenation without reduction in the selectivity to citronellal. The alkali addition appears to be altered the palladium sites. The pore size distribution reveals that the pore size of these catalysts is in the range of 0.96 to 0.7 nm. The palladium active sites are also quite uniform based on the TPR data. The catalytic parameters are correlated well with the activity data.

关键词： Alkali Carbonates Citral Hydrogenation CMS Supported Pd Catalyst

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Hybrid Multi-Strategy Aquila Optimization with Deep Learning Driven Crop Type Classification on Hyperspectral Images

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Computer Systems Science & Engineering 2023年第10期47卷 375-391页

作者： Sultan Alahmari Saud Yonbawi Suneetha racharla ELaxmi Lydia Mohamad Khairi Ishak Hend Khalid Alkahtani Ayman Aljarbouh Samih M.Mostafa King Abdulaziz City for Science and Technology P.O Box 6086Riyadh 11442Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of AIML Aditya Engineering CollegeSurempallemAndhra PradeshIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed *** spatial information and spectral signatures of hyperspectral images(HSIs)present greater potential for detecting and classifying fine *** accurate classification of crop kinds utilizing hyperspectral remote sensing imaging(RSI)has become an indispensable application in the agricultural *** is significant for the prediction and growth monitoring of crop *** the deep learning(DL)techniques,Convolution Neural Network(CNN)was the best method for classifying HSI for their incredible local contextual modeling ability,enabling spectral and spatial feature *** article designs a Hybrid Multi-Strategy Aquila Optimization with a Deep Learning-Driven Crop Type Classification(HMAODL-CTC)algorithm *** proposed HMAODL-CTC model mainly intends to categorize different types of crops on *** accomplish this,the presented HMAODL-CTC model initially carries out image preprocessing to improve image *** addition,the presented HMAODL-CTC model develops dilated convolutional neural network(CNN)for feature *** hyperparameter tuning of the dilated CNN model,the HMAO algorithm is ***,the presented HMAODL-CTC model uses an extreme learning machine(ELM)model for crop type classification.A comprehensive set of simulations were performed to illustrate the enhanced performance of the presented HMAODL-CTC *** comparison studies reported the improved performance of the presented HMAODL-CTC algorithm over other compared methods.

关键词： Crop type classification hyperspectral images agricultural monitoring deep learning metaheuristics

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