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Paddy Leaf Disease Detection Using an Optimized Deep Neural Network

Computers, Materials & Continua 2021年第7期68卷 1117-1128页

作者： Shankaranarayanan Nalini Nagappan Krishnaraj Thangaiyan Jayasankar Kalimuthu Vinothkumar antony sagai francis britto Kamalraj Subramaniam Chokkaligam Bharatiraja Department of Computer Science&Engineering University College of EngineeringBIT CampusAnna UniversityTiruchirappalli620024India School of Computing SRM Institute of Science and TechnologyKattankulathur603203India Department of Electronics and Communication Engineering University College of EngineeringBIT CampusAnna UniversityTiruchirappalli620024India Department of Electronics&Communication Engineering SSM Institute of Engineering and TechnologyDindigul624002India Department of Mechanical Engineering Rohini College of Engineering and TechnologyPalkulam629401India Department of ECE Karpagam Academy of Higher EducationCoimbatore641021India Department of Electrical and Electronics Engineering SRM Institute of Science and TechnologyChennai603203India

Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the *** diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming *** of diseases from the plant images is an active research topic which makes use of machine learning(ML)approaches.A novel deep neural network(DNN)classification model is proposed for the identification of paddy leaf disease using plant image *** errors were minimized by optimizing weights and biases in the DNN model using a crow search algorithm(CSA)during both the standard pre-training and fine-tuning *** DNN-CSA architecture enables the use of simplistic statistical learning techniques with a decreased computational workload,ensuring high classification *** leaf images were first preprocessed,and the areas indicative of disease were initially extracted using a k-means clustering *** was then applied to eliminate regions not indicative of ***,a set of features were extracted from the previously isolated diseased ***,the classification accuracy and efficiency of the proposed DNN-CSA model were verified experimentally and shown to be superior to a support vector machine with multiple cross-fold validations.

关键词： Leaf classification paddy leaf deep learning metaheuristics optimization crow search algorithm

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Modelling and Characterization of Basalt/Vinyl Ester/SiC Micro-and Nano-hybrid Biocomposites Properties Using Novel ANN–GA Approach

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Journal of Bionic Engineering 2024年第2期21卷 938-952页

作者： Yesudhasan Thooyavan Lakshmi Annamali Kumaraswamidhas Robinson Dhas Edwin Raj Joseph Selvi Binoj Bright Brailson Mansingh antony sagai francis britto Alamry Ali Department of Mechanical Engineering Indian Institute of Technology Dhanbad(ISM)DhanbadJharkhand826004India Gati Shakti Vishwavidyalaya(GSV-A Central University Funded By GoI in the Ministry of Railways) LalbaugVadodaraGujarat390004India Institute of Mechanical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityChennaiTamilnadu602105India Metal Joining Research Centre Department of Mechanical EngineeringSri Ramakrishna Engineering CollegeCoimbatoreTamilnadu641022India Department of Mechanical Engineering Rohini College of Engineering and TechnologyPalkulamTamil Nadu629401India Department of Mechanical Engineering College of Engineering in Al-KharjPrince Sattam Bin Abdulaziz University11942Al-KharjSaudi Arabia

Basalt fiber reinforcement in polymer matrix composites is becoming more and more popular because of its environmental friendliness and mechanical qualities that are comparable to those of synthetic *** fiber strengthened vinyl ester matrix polymeric composite with filler addition of nano-and micro-sized silicon carbide(SiC)element spanning from 2 weight percent to 10 weight percent was studied for its mechanical and wear *** application of Artificial Neural Network(ANN)to correlate the filler addition composition for optimum mechanical properties is required due to the non-linear mechanical and tribological features of *** stuffing blend and composition of the composite are optimized using the hybrid model and Genetic Algorithm(GA)to maximize the mechanical and wear-resistant *** predicted and tested ANN–GA optimal values obtained for the composite combination had a tensile,flexural,impact resilience,hardness and wear properties of 202.93 MPa,501.67 MPa,3.460 J/s,43 HV and 0.196 g,respectively,for its optimum combination of filler and *** can be noted that the nano-sized SiC filler particle enhances most of the properties of the composite which diversifies its *** predicted mechanical and wear values of the developed ANN–GA model were in closer agreement with the experimental values which validate the model.

关键词： Hybrid polymer composite Prediction Process modelling Artificial neural networks Genetic algorithm

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Segmentation of Brain Tumor Magnetic Resonance Images Using a Teaching-Learning Optimization Algorithm

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Computers, Materials & Continua 2021年第9期68卷 4191-4203页

作者： J.Jayanthi M.Kavitha T.Jayasankar A.sagai francis britto N.B.Prakash Mohamed Yacin Sikkandar C.Bharathiraja Department of Computer Science and Engineering Sona College of TechnologySalem636005TamilnaduIndia Department of Electronics and Communication Engineering K.Ramakrishnan College of TechnologyTrichy621112India Department of Electronics and Communication Engineering University College of EngineeringAnna UniversityTiruchirappalli620024India Department of Mechanical Engineering Rohini College of Engineering and TechnologyPalkulam629401India Department of Electrical and Electronics Engineering National Engineering CollegeKovilpatti628503India Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAlMajmaah11952Kingdom of Saudi Arabia Department of Electrical and Electronics Engineering SRM Institute of Science and TechnologyChennai603203India

Image recognition is considered to be the pre-eminent paradigm for the automatic detection of tumor diseases in this *** various cancers identified so far,glioma,a type of brain tumor,is one of the deadliest cancers,and it remains challenging to the medicinal *** only consoling factor is that the survival rate of the patient is increased by remarkable percentage with the early diagnosis of the *** diagnosis is attempted to be accomplished with the changes observed in the images of suspected parts of the brain captured in specific interval of *** the captured image,the affected part of the brain is analyzed using magnetic resonance imaging(MRI)*** of different modalities in the captured MRI image demands the best automated model for the easy identification of malignant *** of image processing techniques are available for processing the images to identify the affected *** study concentrates and proposes to improve early diagnosis of glioma using a preprocessing boosted teaching and learning optimization(P-BTLBO)algorithm that automatically segments a brain tumor in an given MRI *** involves contrast enhancement and skull stripping procedures through contrast limited adaptive histogram equalization *** traditional TLBO algorithm that works with the perspective of teacher and the student is here improved by using a boosting *** results obtained using this P-BTLBO algorithm is compared on different benchmark images for the validation of its *** experimental findings show that P-BTLBO algorithm approach outperforms other existing algorithms of its kind.

关键词： Brain tumor TLBO algorithm skull stripping preprocessing segmentation

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Artificial Intelligence Based Solar Radiation Predictive Model Using Weather Forecasts

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Computers, Materials & Continua 2022年第4期71卷 109-124页

作者： Sathish Babu Pandu A.sagai francis britto Pudi Sekhar P.Vijayarajan Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Mesfer Al Duhayyim Department of Electrical and Electronics Engineering University College of EngineeringPanruti607106India Department of Mechanical Engineering Rohini College of Engineering&TechnologyPalkulam629401India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyAndra Pradesh530046India Department of Electrical and Electronics Engineering University College of EngineeringBIT CampusTiruchirappalli620024India Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia&Faculty of Computer and ITSana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Solar energy has gained attention in the past two decades,since it is an effective renewable energy source that causes no harm to the *** Irradiation Prediction(SIP)is essential to plan,schedule,and manage photovoltaic power plants and grid-based power generation *** models have been proposed for SIP in the literature while such studies demand huge volumes of weather data about the target location for a lengthy period of *** this scenario,commonly available Artificial Intelligence(AI)technique can be trained over past values of irradiance as well as weatherrelated parameters such as temperature,humidity,wind speed,pressure,and ***,in current study,the authors aimed at developing a solar irradiance prediction model by integrating big data analytics with AI models(BDAAI-SIP)using weather forecasting *** order to perform long-term collection of weather data,Hadoop MapReduce tool is *** proposed solar irradiance prediction model operates on different ***,data preprocessing take place using various sub processes such as data conversion,missing value replacement,and data ***,Elman Neural Network(ENN),a type of feedforward neural network is also applied for predictive *** is divided into input layer,hidden layer,loadbearing layer,and output *** overcome the insufficiency of ENN in choosing the value of weights and hidden layer neuron count,Mayfly Optimization(MFO)algorithm is *** order to validate the performance of the proposed model,a series of experiments was *** experimental values infer that the proposed model outperformed other methods used for comparison.

关键词： Solar irradiation prediction weather forecast artificial intelligence Elman neural network mayfly optimization

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Land Cover Dynamics in the Kirisia Forest Ecosystem, Samburu County, Kenya

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Advances in Remote Sensing 2016年第3期5卷 168-182页

作者： Fiesta Warinwa francis Mwaura John Warui Kiringe antony Oduya Ndubi African Wildlife Foundation (AWF) Nairobi Kenya Department of Geography & Environmental Studies University of Nairobi Nairobi Kenya Habitat Planners & Environmental Consultants Ltd Nairobi Kenya Regional Centre for Mapping of Resources for Development (RCMRD) SERVIR Eastern and Southern Africa Project Nairobi Kenya

The study characterized the status and trend of land cover transformation in Kirisia forest ecosystem between 1973 and 2015 using remote sensing and GIS. The dominant land cover types consisted of indigenous forest followed by shrub land and bush land. The findings showed a major increase in the built environment by 55.4% and an overall reduction in forest cover by 21.3%. Up to 83.9 km2 of the original indigenous forest was lost between 1973 and 1986 due to severe fires. Thereafter, 23.7 km2 of the remaining indigenous forest was lost between 1986 and 2000 mainly through charcoal burning, illegal timber logging and livestock forage harvesting. A slight recovery occurred between 2000 and 2015 with a 5% increase in indigenous forest cover mostly through natural succession by shrub land and bush land in the burnt forest areas especially following the 1998 El Nino period. The land cover change in the forest ecosystem was not exceptional in Kenya but mirrors similar changes that have been documented in other valued dry land watershed ecosystems in the country including the national water towers. The continued loss of forest cover is likely to affect the water recharge capacity in the watershed thereby creating severe water scarcity for the people in Mararal town as well as nearly 142,954 other individuals in the Kirisia region. Appropriate interventions are therefore needed to mitigate the negative land cover change in Kirisia forest and restore its hydrological functions and water recharge capacity.

关键词： Kirisia Watershed Ecosystem Forest Cover Water Supply

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Case of COVID-19 presenting with gastrointestinal symptoms

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World Journal of Virology 2020年第1期9卷 1-4页

作者： Ravi Kant Lakshya Chandra Mc Anto antony Vipin Verma Division of Endocrinology Diabetes and MetabolismMedical University of South Carolina/AnMed CampusAndersonSC 29621United States Department of Medicine Bon Secours Saint Francis Health SystemGreenvilleSouth CarolinaSC 29601United States Department of Medicine Medical University of South Carolina/AnMed CampusAndersonSC 29621United States

Patients with coronavirus disease 2019(COVID-19)predominantly present with the pulmonary symptoms such as fever,cough,and shortness of *** present a case of an 83 years old patient with COVID-19 who presented with only gastrointestinal symptoms without respiratory *** case raises the concern regarding our current lack of understanding of extrapulmonary manifestations of *** genetic homology between 2019 severe acute respiratory syndrome coronavirus(SARS-CoV)2 and SARS-CoV,our case underscores the urgent need for further studies to understand the role of the gastrointestinal system in 2019 SARS-CoV-2 transmission and COVID-19 pathogenesis.

关键词： COVID-19 SARS-CoV-2 Coronavirus Gastrointestinal Diarrhea Pandemic

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Various Metal Sandwich Layer Oriented Efficiency Enhancement Superiority on CuInGaSe2 Thin Film Solar Cells

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Advances in Chemical Engineering and Science 2019年第2期9卷 176-181页

作者： R. Kabilan R. Ravi A. antony Christian Raja T. Prem Kumar Department of Electronics and Communication Engineering Francis Xavier Engineering College Tirunelveli Tamilnadu India Department of Computer Science and Engineering Francis Xavier Engineering College Tirunelveli Tamilnadu India Department of Physics Francis Xavier Engineering College Tirunelveli Tamilnadu India Physics Department S.N. College Perungudi Madurai Tamilnadu India

The good quality CuInGaSe2 (CIGS) thin film solar cells were fabricated on molybdenum metal coated soda lime glass substrate. Three-stage co-evaporation method was utilized for the fabrication of high quality p-type CIGS thin film absorber layer. Further, n-type CdS layer, high resistive intrinsic ZnO layer and transparent conducting AlZnO layers were fabricated by CBD method and vacuum sputtering methods. We made three various top metal sandwich grid patterns, i.e. Al, Al/Cu and Cu/Al which were utilized to investigate the metal sandwich layer oriented efficiency enhancement superiority on CuInGaSe2 thin film solar cells. The investigated specific CIGS solar cell device efficiency with respect to various top metal grid sandwich patterns is presented and discussed.

关键词： CIGS Solar Cells Metal Sandwich Thin Film Efficiency CBD Method Sputtering Method Co-Evaporation Method e-Beam Evaporation

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城市中心历史街区更新——以希腊雅典交通影响事前评价为例

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城市交通 2015年第5期13卷 85-95页

作者： Konstantinos Kepaptsoglou Matthew G.Karlaftis Ilias Gkotsis Eleni Vlahogianni antony Stathopoulos 耿雪雅典国家技术大学交通规划与工程系希腊雅典10682 中国城市规划设计研究院北京100037

现代城市地区城市更新项目通常与交通系统结构和运营的重要变化相结合。采用事前评价方法从城市范围层面探讨希腊雅典中心区一条主要干路改造为步行街项目的交通影响。通过构建几种情景,展现项目实施后的交通状况。研究结果显示,尽管短... 详细信息

现代城市地区城市更新项目通常与交通系统结构和运营的重要变化相结合。采用事前评价方法从城市范围层面探讨希腊雅典中心区一条主要干路改造为步行街项目的交通影响。通过构建几种情景,展现项目实施后的交通状况。研究结果显示,尽管短期交通状况会恶化,但项目带来的潜在交通消散将显著改善中心区交通和环境状况。

关键词：事前评价步行街交通消散城市更新

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Gut microbiota interactions with anti-diabetic medications and pathogenesis of type 2 diabetes mellitus

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World Journal of Methodology 2022年第4期12卷 246-257页

作者： Ravi Kant Lakshya Chandra Vipin Verma Priyanshu Nain Diego Bello Siddharth Patel Subash Ala Rashmi Chandra Mc Anto antony Department of Endocrinology Diabetes and MetabolismMedical University of South CarolinaAndersonSC 29621United States Department of Endocrinology Diabetes and MetabolismAnMed HealthAndersonSC 29621United States Department of Internal Medicine St Francis HospitalGreenvilleSC 29601United States Department of Internal Medicine Medical University of South CarolinaAndersonSC 29621United States Department of Internal Medicine AnMed HealthAndersonSC 29621United States Department of Graduate Medical Education Maulana Azad Medical CollegeDelhi 110002India Department of Surgery AnMed HealthAndersonSC 29621United States Department of Internal Medicine Decatur Morgan HospitalDecaturAL 35601United States

Microorganisms including bacteria,viruses,protozoa,and fungi living in the gastrointestinal tract are collectively known as the gut *** is the imbalance in microbial composition on or inside the body relative to healthy *** Firmicutes to Bacteroidetes ratio and decreased abundance of Akkermansia muciniphila are the predominant gut dysbiosis associated with the pathogenesis of type 2 diabetes mellitus(T2DM)and metabolic *** mechanisms linking gut dysbiosis,and metabolic diseases and their complications include altered metabolism of short-chain fatty acids and bile acids,interaction with gut hormones,increased gut microbial metabolite trimethylamine-N-oxide,bacterial translocation/Leaky gut syndrome,and endotoxin production such as *** association between the gut microbiota and glycemic agents,however,is much less understood and is the growing focus of research and *** studies suggest that the gut microbiota and anti-diabetic medications are interdependent on each other,meaning that while anti-diabetic medications alter the gut microbiota,the gut microbiota also alters the efficacy of anti-diabetic *** increasing evidence regarding the significance of gut microbiota,it is imperative to review the role of gut microbiota in the pathogenesis of *** review also discusses the interaction between gut microbiota and the various medications used in the treatment of T2DM.

关键词： Metabolic disease Gut microbiota Cardiovascular disease Short chain fatty acid Dysbiosis Trimethylamine-N-oxide

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