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Wave profile analysis of a couple of(3+1)-dimensional nonlinear evolution equations by sine-Gordon expansion approach

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Journal of Ocean Engineering and Science 2022年第3期7卷 272-279页

作者： Md.Rezwan Ahamed Fahim purobi rani kundu Md.Ekramul Islam M.Ali Akbar M.S.Osman Department of Mathematics Pabna University of Science and TechnologyBangladesh Department of Applied Mathematics University of RajshahiBangladesh Department of Mathematics Faculty of ScienceCairo UniversityGiza 12613Egypt Department of Mathematics Faculty of Applied ScienceUmm Alqura UniversityMakkah 21955Saudi Arabia

The(3+1)-dimensional Kadomtsev-Petviashvili and the modified KdV-Zakharov-Kuznetsov equations have a significant impact in modern science for their widespread applications in the theory of long-wave propagation,dynamics of shallow water wave,plasma fluid model,chemical kinematics,chemical engineering,geochemistry,and many other *** this article,we have assessed the effects of wave speed and physical parameters on the wave contours and confirmed that waveform changes with the variety of the free factors in *** a result,wave solutions are extensively analyzed by using the balancing condition on the linear and nonlinear terms of the highest order and extracted different standard wave configurations,containing kink,breather soliton,bell-shaped soliton,and periodic *** extract the soliton solutions of the high-dimensional nonlinear evolution equations,a recently developed approach of the sine-Gordon expansion method is used to derive the wave solutions *** sine-Gordon expansion approach is a potent and strategic mathematical tool for instituting ample of new traveling wave solutions of nonlinear *** study established the efficiency of the described method in solving evolution equations which are nonlinear and with higher dimension(HNEEs).Closed-form solutions are carefully illustrated and discussed through diagrams.

关键词： Sine-Gordon expansion approach Kadomtsev-Petviashvili equation modified KdV-Zakharov-Kuznetsov equation soliton solutions

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Disease detection,severity prediction,and crop loss estimation in MaizeCrop using deep learning

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Artificial Intelligence in Agriculture 2022年第1期6卷 276-291页

作者： Nidhi kundu Geeta rani Vijaypal Singh Dhaka Kalpit Gupta Siddaiah Chandra Nayaka Eugenio Vocaturo Ester Zumpano Department of Computer and Communication Engineering Manipal University JaipurJaipurIndia ICAR DOS in Biotechnology University of Mysore ManasagangotriMysore 570005India DIMES(Department of Computer Engineering ModelingElectronics and Systems)University of CalabriaItaly Nanotec Italian National Research Council87036 RendeCSItaly

The increasing gap between the demand and productivity of maize crop is a point of concern for the food industry,and ***'susceptibility to diseases such as Turcicum Leaf Blight,and Rust is a major cause for reducing its *** detection,and classification of these diseases,calculation of disease severity,and crop loss estimation is a time-consuming ***,it requires expertise in disease ***,there is a need to find an alternative for automatic disease detection,severity prediction,and crop loss *** promising results of machine learning,and deep learning algorithms in pattern recognition,object detection,and data analysis motivate researchers to employ these techniques for disease detection,classification,and crop loss estimation in maize *** research works available in literature,have proven their potential in automatic disease detection using machine learning,and deep learning ***,there is a lack none of these works a reliable and real-life labelled dataset for training these ***,none of the existing works focus on severity prediction,and crop loss *** authors in this manuscript collect the real-life dataset labelled by plant *** propose a deep learning-based framework for pre-processing of dataset,automatic disease detection,severity prediction,and crop loss *** uses the K-Means clustering algorithm for extracting the region of ***,they employ the customized deep learning model‘MaizeNet’for disease detection,severity prediction,and crop loss *** model reports the highest accuracy of 98.50%.Also,the authors perform the feature visualization using the ***,the proposed model is integrated with a web application to provide a userfriendly *** efficacy of the model in extracting the relevant features,a smaller number of parameters,low training time,high accuracy favors its importance as an assisting tool for plant pathology experts.T

关键词： Disease detection Crop loss Severity Deep learning Maize

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Nurses’ Experiences in Service Provision a COVID-19 Dedicated Tertiary Public Hospital

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Open Journal of Nursing 2022年第11期12卷 725-737页

作者： Suniti Halder Poly rani kundu Auparna Biswas Senior Staff Nurse Dhaka Medical College Hospital Dhaka Bangladesh Senior Staff Nurse Sadar Hospital Narail Narail Bangladesh Senior Staff Nurse National Institute of Cancer Research and Hospital Dhaka Bangladesh

Objectives: To assess the nurses’ experiences in service provision a COVID-19 dedicated tertiary public hospital. Materials and Methods: This descriptive cross-sectional study was conducted in one tertiary level public hospital namely Dhaka Medical College Hospital (DMCH), Dhaka, Bangladesh from January to December 2021. Data were collected through face-to-face interview using a structured questionnaire containing demographic details and experiences faced by the nurses in service provision during COVID-19. Data was analysed by using SPSS (Statistical Package for Social Science) software version 23. Results: The findings revealed that the mean age of the respondents was 32.35 ± 7.248 years, the minimum age was 23 years and maximum age was 58 years. About half of the respondents 52.1% were in 21 - 30 years. The majorities 89% were female. More than half of the respondents 72.6% were Muslim and 63.83% of respondents have completed Diploma in nursing. About 32.2% respondents were living with senior citizen, 33% respondents were infected by COVID-19, 24.23% respondent mentioned nurse-Patient ratio in general ward was 1:7 and 71.08% mentioned nurse-patient ratio in I.C.U/C.C.U. was 1:3 (December 2021). PPE were available among 88.0% respondents and N95 mask were available among 84.0% respondent. About 34.8% respondents got COVID-19 guideline training and 32.4% got donning and doffing training. More than half of the respondents 76% stated that equipment is adequate, 56.38% respondents mention that insufficient of nurses and 53.7% were mentioned insufficient of subordinate staff. About 22.6% respondents faced social stigma and majorities 96.5% respondents mentioned they got proper family support. There was a significant association found between Professional educational qualification and satisfaction of current designation (p value = 0.001 Conclusion: The most important findings of this study was lack of training, insufficient of manpower especially nurses and subordinate s

关键词： Nurses’ Experiences Service Provision COVID-19 Tertiary Public Hospital

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