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Aquaculture and Fisheries 2023年第2期8卷 180-189页

作者： Naresh Kumar Mehta banalata rout Amjad KBalange Binaya Bhusan Nayak Department of Fish Processing Technology and Engineering College of FisheriesCAU(I)LembucherraAgartalaTripura799210India Department of Post-Harvest Technology Central Institute of Fisheries EducationMumbai400061India

Changes in protein quality during ice storage affects the muscle structure,the textural quality,functional properties and the eating *** viscoelastic behaviour and gelling properties ofmeat proteinsin relation to histological changes in white leg shrimp muscles were assessed for 14 days in ice *** in Ca2+ATPase activity of fresh myofibrillar protein(MFP),fading of myosin banding pattern and increased gapping in myofibrils were clearly observed with progress of *** quality indices of the shrimp muscle were well correlated with histological and functional properties as a function of ice *** of fresh MFP was 86.76%which decreased to 77.06%on the 14th day of storage *** capacity found to increase during storage *** strength of white leg shrimp meat was low(81±14 g cm)and further,reduced nearly 60%compared to fresh sample at the end of *** considerable reductions(from 535.77 kPa to 246.56 kPa)in storage modulus values were evident of diminishing elasticity and gelling ability of the meat due to ice ***,this study usherd that the histological deterioration in myofibrils may be used as an indication of diminishing biochemical quality and gelling behaviour of the proteins.

关键词： White leg shrimp Myofibrillar proteins Quality Rheology Gel strength Functionality

Charting the course:India's health expenditure projections for 2035

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Global Health Journal 2024年第2期8卷 58-66页

作者： Pragyan Monalisa Sahoo Himanshu Sekhar rout Department of Analytical&Applied Economics Utkal UniversityBhubaneswarOdishaIndia Department of Analytical and Applied Economics&RUSA Centre of Excellence in Public Policy and Governance Utkal UniversityVani ViharBhubaneswarOdishaIndia

Objectives Understanding past trends and forecasting future changes in health spending is vital for planning and reducing reliance on out-of-pocket(OOP)*** current study analyzed health expenditure patterns in India and forecasted future trends and patterns until *** Data on health expenditure in India from 2000 to 2019 was collected from the Organisation for Economic Co-operation and Development(OECD)iLibrary and National Health Accounts 2019 *** domestic product(GDP)data from the World Bank was also *** statistics analyzed the composition and pattern,while the exponential smoothing model forecasted future health *** The findings revealed that expenditure made by OOP is the primary health financing source,followed by government and pre-paid private *** percentage of GDP allocated to total health expenditure remains stable,while the per capita health expenditure *** in expenditure among states are observed,with Karnataka relying heavily on pre-paid private *** projections suggest a decline in per capita and total health expenditure as a share of GDP,with a slight increase in the government’s ***-paid private expenditure per capita and OOP health expenditure as a share of the total is projected to remain relatively constant but still high in absolute *** The study highlights variations in health spending in India,characterized by high OOP spending,limited public coverage,and a need for investments,and reforms to improve healthcare access and equity.

关键词： Health expenditure Health spending Health financing Forecasting Exponential smoothing India

Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

Comparative Electrocatalytic Oxygen Evolution Reaction Studies of Spinel NiFe_(2)O_(4) and Its Nanocarbon Hybrids

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Transactions of Tianjin University 2022年第1期28卷 80-88页

作者： Pratik V.Shinde Rutuparna Samal Chandra Sekhar rout Centre for Nano and Material Sciences Jain UniversityBengaluruKarnataka 562112India

Electrocatalytic oxygen evolution reaction(OER)is one of the crucial reactions for converting renewable electricity into chemical fuel in the form of *** date,there is still a challenge in designing ideal cost-effective OER catalysts with excellent activity and robust *** hybridization of transition metal oxides and carbonaceous materials is one of the most effective and promising strategies to develop high-performance ***,this work synthesized hybrids of NiFe_2 O_4 spinel materials with two-dimensional(2D)graphene oxide and one-dimensional(1 D)carbon nanotubes using a facile solvothermal *** activities of NiFe_(2)O_(4) with 2 D graphene oxide toward OER were realized to be superior even to the 1 D carbon nanotube-based electro catalyst in terms of overpotential to reach a current density of10 mA/cm^(2) as well as Tafel *** NiFe_(2)O_(4) with 2 D graphene oxide hybrid exhibits good stability with an overpotential of 327 mV at a current density of 10 mA/cm^(2) and a Tafel slope of 103 mV/*** high performance of NiFe_(2)O_(4) with 2 D graphene oxide is mainly attributed to its unique morphology,more exposed active sites,and a porous structure with a high surface ***,an approach of hybridizing a metal oxide with a carbonaceous material offers an attractive platform for developing an efficient electrocatalyst for water electrochemistry applications.

关键词： Oxygen evolution reaction Metal oxide Graphene oxide Carbon nanotubes Stability

Neural Network and Fuzzy Control Based 11-Level Cascaded Inverter Operation

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Computers, Materials & Continua 2022年第2期70卷 2319-2346页

作者： Buddhadeva Sahoo Sangram Keshari routray Pravat Kumar rout Mohammed M.Alhaider Department of Electrical Engineering Siksha‘O’Anusandhan UniversityOdisha751030India Department of Electrical Electronics Engineering Siksha‘O’Anusandhan UniversityOdisha751030India College of Engineering atWadi Addawaser Prince Sattam bin Abdulaziz University11991Saudi Arabia

This paper presents a combined control and modulation technique to enhance the power quality(PQ)and power reliability(PR)of a hybrid energy system(HES)through a single-phase 11-level cascaded H-bridge inverter(11-CHBI).The controller and inverter specifically regulate the HES and meet the load *** track optimum power,a Modified Perturb and Observe(MP&O)technique is used for ***-capacitor(UCAP)based energy storage device and a novel current control strategy are proposed to provide additional active power support during both voltage sag and swell *** an improved PQ and PR,a two-way current control strategy such as the main controller(MC)and auxiliary controller(AC)is suggested for the 11-CHBI *** is used to regulate the active current component through the fuzzy controller(FC),and AC is used to regulate the dc-link voltage of CHBI through a neural network-based PI controller(ANN-PI).By tracking the reference signals fromMC and AC,a novel hybrid pulse widthmodulation(HPWM)technique is proposed for the 11-CHBI *** justify and analyze the MATLAB/Simulink software-based designed model,the robust controller performance is tested through numerous steady-state and dynamic state case studies.

关键词： Ultra-capacitor 11-level cascaded H-bridge inverter hybrid energy system modified perturb and observer neural network-based PI fuzzy controller

Human-Computer Interaction Using Deep Fusion Model-Based Facial Expression Recognition System

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Computer Modeling in Engineering & Sciences 2023年第5期135卷 1165-1185页

作者： Saiyed Umer Ranjeet Kumar rout Shailendra Tiwari Ahmad Ali AlZubi Jazem Mutared Alanazi Kulakov Yurii Department of Computer Science&Engineering Aliah UniversityKolkata700156India Department of Computer Science and Engineering National Institute of TechnologySrinagarJammu and Kashmir190006India Department of Computer Science&Engineering Thapar UniversityPatiala147004India Computer Science Department King Saud UniversityRiyadh11451Saudi Arabia Department of Computer Engineering National Technical University of UkraineIgor Sikorsky Kyiv Polytechnic InstituteKyiv03056Ukraine

A deep fusion model is proposed for facial expression-based human-computer Interaction ***,image preprocessing,i.e.,the extraction of the facial region from the input image is ***,the extraction of more discriminative and distinctive deep learning features is achieved using extracted facial *** prevent overfitting,in-depth features of facial images are extracted and assigned to the proposed convolutional neural network(CNN)*** CNN models are then ***,the performance of each CNN model is fused to obtain the final decision for the seven basic classes of facial expressions,i.e.,fear,disgust,anger,surprise,sadness,happiness,*** experimental purposes,three benchmark datasets,i.e.,SFEW,CK+,and KDEF are *** performance of the proposed systemis compared with some state-of-the-artmethods concerning each *** performance analysis reveals that the proposed system outperforms the competitive methods in terms of various performance ***,the proposed deep fusion model is being utilized to control a music player using the recognized emotions of the users.

关键词： Deep learning facial expression emotions recognition CNN

Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks

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World Journal of Clinical Cases 2022年第18期10卷 5957-5964页

作者： Madhusmita rout Bhumandeep Kour Sugunakar Vuree Sajitha S Lulu Krishna Mohan Medicherla Prashanth Suravajhala Department of Pediatrics University of Oklahoma Health Sciences CentreOklahoma CityOK 73104United States Department of Biotechnology and Bioinformatics Birla Institute of Scientific ResearchJaipur 302001RajasthanIndia Department of Biotechnology Lovely Professional UniversityPhagwara 144001PunjabIndia Department of Biotechnology Vellore Institute of TechnologyVellore 632014Tamil NaduIndia Amrita School of Biotechnology Amrita Vishwa VidyapeethamVallikavu POAmritapuriClappanaKollam 690525KeralaIndia

An emerging area of interest in understanding disease phenotypes is systems *** diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations.A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful,but understanding the candidate genes harboring those mutations is an unmet *** this perspective,using systems genomic approaches,we highlight the application of phenome-interactome networks in diabetes and provide deep ***01128,which we previously described as candidate for diabetes,is shown as an example to discuss the approach.

关键词： Type 1 diabetes Gestational diabetes mellitus Prostate cancer Phenome Type 2 diabetes Pleiotropy

Magnitude and Determinants of Mortalities Related to COVID-19:Evidence from 94 Countries Using Regression Techniques

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Fudan Journal of the Humanities and Social Sciences 2022年第4期15卷 475-499页

作者： Ashis Kumar Pradhan Ronny Thomas Sandhyarani rout Alok Kumar Pradhan Department of Humanities and Social Sciences Maulana Azad National Institute of TechnologyBhopalMadhya PradeshIndia Rajagiri Business School(RBS)and Rajagiri College of Social Sciences(RCSS) Rajagiri Valley CampusKakkanadKochiKeralaIndia Department of Social Science Fakir Mohan UniversityBalasoreOdishaIndia Indian Institute of Management Nagpur DahegaonIndia

This study attempts to investigate the factors determining COVID-19 deaths during the pandemic across countries by employing a rich dataset sourced from 94 countries updated till 6 February,*** empirical analysis,the study makes use of cross-sectional linear regression technique in the first part and after required diagnostic tests use 2SLS regression technique for correcting possible endogeneity bias in the second *** from the study indicate that factors like total reported cases,population size,population over 70 years of age,extreme poverty,and human development index play significant role in determining COVID-19-related ***,to check the robustness of the findings the present study employed LASSO *** from the study highlight the possibility of government intervention to devise appropriate policies to control COVID-related incidence and death.

关键词： COVID-19 deaths Mortality risks Infectious diseases LASSO regression Pandemic

A Pattern Classification Model for Vowel Data Using Fuzzy Nearest Neighbor

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Intelligent Automation & Soft Computing 2023年第3期35卷 3587-3598页

作者： Monika Khandelwal Ranjeet Kumar rout Saiyed Umer Kshira Sagar Sahoo NZ Jhanjhi Mohammad Shorfuzzaman Mehedi Masud Department of Computer Science and Engineering National Institute of Technology SrinagarHazratbal190006Jammu and KashmirIndia Department of Computer Science and Engineering Aliah UniversityKolkataIndia Department of Computer Science and Engineering SRM UniversityAmaravati522240APIndia School of Computer Science SCS Taylor’s UniversitySubang Jaya47500Malaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Classification of the patterns is a crucial structure of research and applications. Using fuzzy set theory, classifying the patterns has become of great interest because of its ability to understand the parameters. One of the problemsobserved in the fuzzification of an unknown pattern is that importance is givenonly to the known patterns but not to their features. In contrast, features of thepatterns play an essential role when their respective patterns overlap. In this paper,an optimal fuzzy nearest neighbor model has been introduced in which a fuzzifi-cation process has been carried out for the unknown pattern using k nearest neighbor. With the help of the fuzzification process, the membership matrix has beenformed. In this membership matrix, fuzzification has been carried out of the features of the unknown pattern. Classification results are verified on a completelyllabelled Telugu vowel data set, and the accuracy is compared with the differentmodels and the fuzzy k nearest neighbor algorithm. The proposed model gives84.86% accuracy on 50% training data set and 89.35% accuracy on 80% trainingdata set. The proposed classifier learns well enough with a small amount of training data, resulting in an efficient and faster approach.

关键词： Nearest neighbors fuzzy classification patterns recognition reasoning rule membership matrix

Sentiment Analysis with Tweets Behaviour in Twitter Streaming API

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Computer Systems Science & Engineering 2023年第5期45卷 1113-1128页

作者： Kuldeep Chouhan Mukesh Yadav Ranjeet Kumar rout Kshira Sagar Sahoo NZ Jhanjhi Mehedi Masud Sultan Aljahdali Computer Science and Engineering I.T.S Engineering CollegeGreater Noida201310India Computer Science and Engineering DPG Institute of Technology and ManagementGurgaon122004India Computer Science and Engineering National Institute of Technology SrinagarJammu and KashmirIndia Department of Computer Science and Engineering SRM UniversityAmaravatiAndhra Pradesh522240India School of Computer Science SCS Taylor’s UniversitySubang Jaya47500Malaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Twitter is a radiant platform with a quick and effective technique to analyze users’perceptions of activities on social *** researchers and industry experts show their attention to Twitter sentiment analysis to recognize the stakeholder *** sentiment analysis needs an advanced level of approaches including adoption to encompass data sentiment analysis and various machine learning *** assessment of sentiment analysis in multiple fields that affect their elevations among the people in real-time by using Naive Bayes and Support Vector Machine(SVM).This paper focused on analysing the distinguished sentiment techniques in tweets behaviour datasets for various spheres such as healthcare,behaviour estimation,*** addition,the results in this work explore and validate the statistical machine learning classifiers that provide the accuracy percentages attained in terms of positive,negative and neutral *** this work,we obligated Twitter Application Programming Interface(API)account and programmed in python for sentiment analysis approach for the computational measure of user’s perceptions that extract a massive number of tweets and provide market value to the Twitter account *** distinguish the results in terms of the performance evaluation,an error analysis investigates the features of various stakeholders comprising social media analytics researchers,Natural Language Processing(NLP)developers,engineering managers and experts involved to have a decision-making approach.

关键词： Machine learning Naive Bayes natural language processing sentiment analysis social media analytics support vector machine Twitter application programming interface