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Sigmoidal Particle Swarm Optimization for Twitter Sentiment Analysis

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Computers, Materials & Continua 2023年第1期74卷 897-914页

作者： sandeep kumar Muhammad Badruddin Khan Mozaherul Hoque Abul Hasanat Abdul Khader Jilani Saudagar Abdullah AlTameem Mohammed AlKhathami Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

Social media,like Twitter,is a data repository,and people exchange views on global issues like the COVID-19 *** media has been shown to influence the low acceptance of *** work aims to identify public sentiments concerning the COVID-19 vaccines and better understand the individual’s sensitivities and feelings that lead to *** work proposes a method to analyze the opinion of an individual’s tweet about the COVID-19 *** paper introduces a sigmoidal particle swarm optimization(SPSO)***,the performance of SPSO is measured on a set of 12 benchmark problems,and later it is deployed for selecting optimal text features and categorizing *** proposed method uses TextBlob and VADER for sentiment analysis,CountVectorizer,and term frequency-inverse document frequency(TF-IDF)vectorizer for feature extraction,followed by SPSO-based feature *** Covid-19 vaccination tweets dataset was created and used for training,validating,and *** proposed approach outperformed considered algorithms in terms of ***,we augmented the newly created dataset to make it balanced to increase performance.A classical support vector machine(SVM)gives better accuracy for the augmented dataset without a feature selection *** shows that augmentation improves the overall accuracy of tweet *** the augmentation performance of PSO and SPSO is improved by almost 7%and 5%,respectively,it is observed that simple SVMwith 10-fold cross-validation significantly improved compared to the primary dataset.

关键词： Twitter data analysis sentiment analysis social media analytics swarm intelligence COVID-19 vaccine

Effect of exogenous progesterone on cumulus characteristics of buffalo oocytes by allowing passage of more number of sperm through cumulus but not essentially fertilization

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Asian pacific Journal of Reproduction 2018年第2期7卷 79-86页

作者： Madhusmita Panda Asmita sandeep kumar Purusottam Mishra Mahesh Chandra Sahu Sachinandan De Tirtha kumar Datta Rakesh kumar Nodal Officer Chief District Veterinary OfficeKadambedaBhadrak756100OdishaIndia Institute of Microbial Technology Council of Scientific and Industrial ResearchChandigarhIndia BSL-4 National Institute of VirologySus RoadPashanPune-411021India Goat Breeding Farm AT/PO-SalapadaDistrict-KeonjharPin code-758020State-OdishaIndia Directorate of Medical Research IMS and SUM HospitalSiksha'O'Anusandhan UniversityK8Kalinga NagarBhubaneswar-751003OdishaIndia Animal Biotechnology Centre National Dairy Research InstituteKarnal132001HaryanaIndia

Objective:To understand the level of progesterone (P4) in different quality of buffalo cumulus oocyte complexes (COCs) and further to evaluate the effect of exogenous P4 supplementation on maturation and subsequent developmental ability of poor quality brilliant cresyl blue (BCB-)***: Progesterone secreted by different quality of buffalo oocytes was estimated by enzyme linked immunosorbent assay and the concentration differences were translated into P4 doses to be incorporated in the maturation medium of BCB-ve COCs followed by expression analysis of genes involved in the cumulus expansion, extracellular matrix disintegration and progesterone receptor signalling. In addition, the study also evaluated the effect of exogenous P4 on sperm-cumulus interaction. Results: More than 10-fold up-regulated expression of progesterone receptor in P4 supplemented oocytes signified that P4 might be acting predominantly through this receptor. Also, exogenous P4 supplementation had significant effect on transcatheter arterial chemoembolization protease regulated by P4-progesterone receptor pathway which in turn had an important role in extracellular matrix disintegration. On the contrary, cumulus expansion genesHAS2,TNFAIP6,AREG were not altered upon P4 supplementation. Also, it was observed that P4 addition did facilitate passage of significantly more number of spermatozoa through P4 treated cumulus cells. Further, incorporation of different doses of P4 did not improve significantly the cleavage and blastocyst rates of BCB-ve ***: Different qualities of buffalo COCs secrete substantially diverse levels of P4, and its supplementation has a role in oocyte maturation via modulation of cumulus characteristics but perhaps not fertilization.

关键词： BCB screening Progesterone Sperm cumulus interaction Fertilizing ability

Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India

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Big Data Mining and Analytics 2021年第2期4卷 65-75页

作者： Rajani kumari sandeep kumar Ramesh Chandra Poonia Vijander Singh Linesh Raja Vaibhav Bhatnagar Pankaj Agarwal Department of Information Technology and Computer Application JECRC UniversityJaipurRajasthan 303905India Bangalore Karnataka 560029India with Amity University Rajasthan JaipurRajasthan 303002India University Jaipur Rajasthan 303007India

The novel coronavirus outbreak was first reported in late December 2019 and more than 7 million people were infected with this disease and over 0.40 million worldwide lost their lives. The first case was diagnosed on30 January 2020 in India and the figure crossed 0.24 million as of 6 June 2020. This paper presents a detailed study of recently developed forecasting models and predicts the number of confirmed, recovered, and death cases in India caused by COVID-19. The correlation coefficients and multiple linear regression applied for prediction and autocorrelation and autoregression have been used to improve the accuracy. The predicted number of cases shows a good agreement with 0.9992 R-squared score to the actual values. The finding suggests that lockdown and social distancing are two important factors that can help to suppress the increasing spread rate of COVID-19.

关键词： COVID-19 regression correlation machine learning prediction

Unstructured Oncological Image Cluster Identification Using Improved Unsupervised Clustering Techniques

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Computers, Materials & Continua 2022年第7期72卷 281-299页

作者： S.Sreedhar kumar Syed Thouheed Ahmed Qin Xin S.sandeep M.Madheswaran Syed Muzamil Basha Dr.T.Thimmaiah Institute of Technology VTUKGFKarnatakaIndia School of Computing&Information Technology REVA UniversityBengaluruIndia Faculty of Science and Technology University of the Faroe IslandsFaroe IslandsDenmark K S School of Engineering BengaluruIndia Muthayammal Engineering College RasipuramTamil NaduIndia

This paper presents,a new approach of Medical Image Pixels Clustering(MIPC),aims to trace the dissimilar patterns over the Magnetic Resonance(MR)image through the process of automatically identify the appropriate number of distinct clusters based on different improved unsupervised clustering schemes for enrichment,pattern predication and deeper *** proposed MIPC consists of two stages:clustering and *** the clustering stage,the MIPC automatically identifies the distinct number of dissimilar clusters over the gray scale MR image based on three different improved unsupervised clustering schemes likely improved Limited Agglomerative Clustering(iLIAC),Dynamic Automatic Agglomerative Clustering(DAAC)and Optimum N-Means(ONM).In the second stage,the performance of MIPC approach is estimated by measuring Intra intimacy and Intra contrast of each individual cluster in the result of MR image based on proposed validation method namely Shreekum Intra Cluster Measure(SICM).Experimental results showthat the MIPC approach is better suited for automatic identification of highly relative dissimilar clusters over the MR cancer images with higher Intra closeness and lower Intra contrast based on improved unsupervised clustering schemes.

关键词： Magnetic resonance image unsupervised clustering scheme intra intimacy intra contrast iLIAC shreekum intra cluster measure medical image clustering

Potassium recovery from muscovite using NaCl-roasting followed by H_(2)SO_(4)-leaching

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Journal of Central South University 2022年第6期29卷 1881-1894页

作者： sandeep kumar JENA Baijayantimala MOHANTY Geetikamayee PADHY Jogeshwara SAHU Sapan kumar KANDI CSIR-Institute of Minerals and Materials Technology BhubaneswarOdisha-751013India

The present study aims at the recovery of potassium from muscovite mica(which contains K_(2)O;~10 wt%)using NaCl-roasting coupled with H_(2)SO_(4)-leaching *** preliminary acid leaching studies applying different mineral acids resulted in a potassium recovery of 8%−18%.The optimum leaching conditions for the maximum recovery were 4 mol/L H_(2)SO_(4),60 min leaching time and liquid-solid ratio 4 mL/g at 90℃.However,the roasting of muscovite with additive NaCl(muscovite:NaCl mass ratio of 1:1.00,900℃,45 min)followed by H_(2)SO_(4)-leaching(95℃,60 min)extracted potassium to the tune of 98%.Under similar roasting conditions,the H_(2)O-leaching process extracted only 60%of *** effects of various roasting and leaching parameters such as temperature,time,NaCl concentration,acid concentration,liquid-solid ratio on potassium extraction were *** appearance of the sylvite(KCl)mineral phase in the NaCl-roasted muscovite and its disappearance in the acid/water leached residue confirmed the physical and chemical distortions of the muscovite crystal *** possible mechanism of potassium release from the complex muscovite structure was elucidated based on available literature substantiated by characterizations using X-ray diffraction(XRD)and scanning electron microscopy with energy dispersive X-rays spectroscopy(SEM-EDX).

关键词： muscovite roasting acid leaching potassium recovery sylvite

Vaccine development for leptospirosis:A systematic review

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Asian Pacific Journal of Tropical Medicine 2023年第12期16卷 533-545页

作者： Yocyny Surendran Mahalingam Nandikha Syafinaz Amin-Nordin sandeep kumar Dhanda Mohamad Ridhuan Mohd Ali Narcisse MS Joseph Department of Medical Microbiology Faculty of Medicine and Health SciencesUniversiti Putra Malaysia43400Malaysia Department of Biomedical Science Faculty of MedicineQuest International University30250Malaysia Department of Oncology St Jude Children’s Research Hospital Memphis38105USA Institute for Medical Research Ministry of HealthMalaysia

Objective:To assess the efficacy of various types of vaccines developed for ***:A comprehensive search was conducted in three databases:PubMed,Scopus,and Cochrane *** authors(YS and MN)selected the articles based on manual *** study eligibility criteria are all Leptospira species regardless of any cluster(pathogenic,intermediate and non-pathogenic).This study recorded articles with positive and negative results and showed a comparison among various membrane proteins as vaccine *** studies on the effectiveness of outer membrane protein as vaccine candidates were also *** articles obtained in the databases were imported into the WPS spreadsheet,and duplicate documents were removed ***:A total of 24 studies were included in the review,which evaluated various types of leptospirosis *** vaccines were developed and tested;however,the heterogeneity of Leptospira species pose a *** an effective approach,an epitope based vaccine shows quite a promising ***,sufficient validation,testing and clinical trials are ***:Developing an effective vaccine for leptospirosis remains a global health *** significant progress has been made in recent years,there is a need for further research to optimize vaccine development and to ensure that vaccines are accessible and effective for high-risk populations.

关键词： Leptospira Vaccine candidate Outer membrane protein

Multilayer Neural Network Based Speech Emotion Recognition for Smart Assistance

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Computers, Materials & Continua 2023年第1期74卷 1523-1540页

作者： sandeep kumar MohdAnul Haq Arpit Jain C.Andy Jason Nageswara Rao Moparthi Nitin Mittal Zamil S.Alzamil Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAP522502India Department of Computer Science College of Computer and Information SciencesMajmaah University11952Al-MajmaahSaudi Arabia Department of Computer Science and Engineering Teerthanker Mahaveer UniversityMoradabadUttar Pradesh244001India Department of Electronics and Communication Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia

Day by day,biometric-based systems play a vital role in our daily *** paper proposed an intelligent assistant intended to identify emotions via voice message.A biometric system has been developed to detect human emotions based on voice recognition and control a few electronic peripherals for alert *** proposed smart assistant aims to provide a support to the people through buzzer and light emitting diodes(LED)alert signals and it also keep track of the places like households,hospitals and remote areas,*** proposed approach is able to detect seven emotions:worry,surprise,neutral,sadness,happiness,hate and *** key elements for the implementation of speech emotion recognition are voice processing,and once the emotion is recognized,the machine interface automatically detects the actions by buzzer and *** proposed system is trained and tested on various benchmark datasets,i.e.,Ryerson Audio-Visual Database of Emotional Speech and Song(RAVDESS)database,Acoustic-Phonetic Continuous Speech Corpus(TIMIT)database,Emotional Speech database(Emo-DB)database and evaluated based on various parameters,i.e.,accuracy,error rate,and *** comparing with existing technologies,the proposed algorithm gave a better error rate and less *** rate and time is decreased by 19.79%,5.13 *** the RAVDEES dataset,15.77%,0.01 s for the Emo-DB dataset and 14.88%,3.62 for the TIMIT *** proposed model shows better accuracy of 81.02%for the RAVDEES dataset,84.23%for the TIMIT dataset and 85.12%for the Emo-DB dataset compared to Gaussian Mixture Modeling(GMM)and Support Vector Machine(SVM)Model.

关键词： Speech emotion recognition classifier implementation feature extraction and selection smart assistance

Monitoring of TDS and conductivity in groundwater in the seismically active region in NW Himalayas,India

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Earthquake Science 2010年第3期23卷 295-299页

作者： Arvind kumar Surinder Singh Bikramjit Singh Bajwa sandeep Mahajan Rajeev Kalia Sunil Dhar Department of Physics Guru Nanak Dev University Department of Geology Govt.CollegeDharamsala

The earthquake precursors and earthquake prediction are the burning issue among the community of earth scientists and engineers. Studies of earthquake precursory phenomena since the last several decades have shown that significant geophysical and geochemical changes may occur prior to intermediate and large earthquakes （Hartmann and Levy, 2005; Yang et al, 2005; Einarsson et al, 2008; Italiano et al, 2008; kumar et al, 2009）. Among the more intensely investigated geochemical phenomena there have been changes in the concentrations of dissolved ions and gases in groundwater as well as variations in the concentrations of crustal and mantle volatiles in ground gases.

关键词： TDS (total dissolved solids) conductivity earthquake precursor NW Himalayas

Modeling the impacts of temperature and precipitation changes on soil CO_2 fluxes from a Switchgrass stand recently converted from cropland

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Journal of Environmental Sciences 2016年第5期28卷 15-25页

作者： Liming Lai sandeep kumar Rajesh Chintala Vance N. Owens David Clay Joseph Schumacher Abdul-Sattar Nizami Sang Soo Lee Rashad Rafique Department of Plant Science South Dakota State University Brookings South Dakota 57007 USA. North Central Sun Grant Center South Dakota State University Brookings South Dakota 57007 USA Center of Excellence in Environmental Studies (CEES) King Abdulaziz University Abdullah Sulayman Jeddah 22254 Saudi Arabia kangwon National University Chuncheon 200-701 South Korea Joint global Change Research Institute Pacific Northwest National Lab College Park Maryland 20740 USA

Switchgrass（Panicum virgatum L.） is a perennial C_4 grass native to North America and successfully adapted to diverse environmental conditions. It offers the potential to reduce soil surface carbon dioxide（CO_2） fluxes and mitigate climate change. However, information on how these CO_2 fluxes respond to changing climate is still lacking. In this study, CO_2 fluxes were monitored continuously from 2011 through 2014 using high frequency measurements from Switchgrass land seeded in 2008 on an experimental site that has been previously used for soybean（Glycine max L.） in South Dakota, USA. DAYCENT, a process-based model, was used to simulate CO_2 fluxes. An improved methodology CPTE[Combining Parameter estimation（PEST） with ＂Trial and Error＂ method] was used to calibrate DAYCENT. The calibrated DAYCENT model was used for simulating future CO_2 emissions based on different climate change scenarios. This study showed that：（i） the measured soil CO_2 fluxes from Switchgrass land were higher for 2012 which was a drought year, and these fluxes when simulated using DAYCENT for long-term（2015–2070） provided a pattern of polynomial curve;（ii） the simulated CO_2 fluxes provided different patterns with temperature and precipitation changes in a long-term,（iii） the future CO_2 fluxes from Switchgrass land under different changing climate scenarios were not significantly different, therefore, it can be concluded that Switchgrass grown for longer durations could reduce changes in CO_2 fluxes from soil as a result of temperature and precipitation changes to some extent.

关键词： Carbon dioxide Switchgrass DAYCENT Climate change