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Deep Transfer Learning Models for Mobile-Based Ocular Disorder Identification on Retinal Images

Computers, Materials & Continua 2024年第7期80卷 139-161页

作者： Roseline Oluwaseun Ogundokun joseph bamidele awotunde Hakeem Babalola Akande Cheng-Chi Lee Agbotiname Lucky Imoize Department of Multimedia Engineering Kaunas University of TechnologyKaunas44249Lithuania Department of Computer Science Landmark UniversityOmu Aran251103Nigeria Department of Computer Science Faculty of Information and Communication SciencesUniversity of IlorinIlorin240003Nigeria Department of Telecommunication Science University of IlorinIlorin230003Nigeria Department of Library and Information Science Fu Jen Catholic UniversityNew Taipei City24205Taiwan Department of Computer Science and Information Engineering Fintech and Blockchain Research CenterAsia UniversityTaichung City41354Taiwan Department of Electrical and Electronics Engineering Faculty of EngineeringUniversity of LagosAkokaLagos100213Nigeria Department of Electrical Engineering and Information Technology Institute of Digital CommunicationRuhr UniversityBochum44801Germany

Mobile technology is developing *** phone technologies have been integrated into the healthcare industry to help medical ***,computer vision models focus on image detection and classification ***2 is a computer vision model that performs well on mobile devices,but it requires cloud services to process biometric image information and provide predictions to *** leads to increased *** biometrics image datasets on mobile devices will make the prediction faster,but mobiles are resource-restricted devices in terms of storage,power,and computational ***,a model that is small in size,efficient,and has good prediction quality for biometrics image classification problems is *** pre-trainedCNN(PCNN)MobileNetV2 architecture combined with a SupportVectorMachine(SVM)compacts the model representation and reduces the computational cost and memory *** proposed novel approach combines quantized pre-trained CNN(PCNN)MobileNetV2 architecture with a Support Vector Machine(SVM)to represent models efficiently with low computational cost and *** contributions include evaluating three CNN models for ocular disease identification in transfer learning and deep feature plus SVM approaches,showing the superiority of deep features from MobileNetV2 and SVM classification models,comparing traditional methods,exploring six ocular diseases and normal classification with 20,111 images postdata augmentation,and reducing the number of trainable *** model is trained on ocular disorder retinal fundus image datasets according to the severity of six age-related macular degeneration(AMD),one of the most common eye illnesses,Cataract,Diabetes,Glaucoma,Hypertension,andMyopia with one class *** the experiment outcomes,it is observed that the suggested MobileNetV2-SVM model size is *** testing accuracy forMobileNetV2-SVM,InceptionV3,andMobileNetV2 is 90.11%,86.88%,and 89

关键词： Retinal images ocular disorder deep transfer learning disease identification mobile device

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An Ensemble-Based Hotel Reviews System Using Naive Bayes Classifier

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 131-154页

作者： joseph bamidele awotunde Sanjay Misra Vikash Katta Oluwafemi Charles Adebayo Department of Computer Science Faculty of Information and Communication SciencesUniversity of IlorinIlorin240003Nigeria Department of Computer Science and Communication Otfold University CollegeHaldenNorway

The task of classifying opinions conveyed in any form of text online is referred to as sentiment *** emergence of social media usage and its spread has given room for sentiment analysis in our daily *** media applications and websites have become the foremost spring of data recycled for reviews for sentimentality in various *** subject matter can be encountered on social media platforms,such as movie product reviews,consumer opinions,and testimonies,among others,which can be used for sentiment *** rapid uncovering of these web contents contains divergence of many benefits like profit-making,which is one of the most vital of them *** to a recent study,81%of consumers conduct online research prior to making a *** the reviews available online are too huge and numerous for human brains to process and ***,machine learning classifiers are one of the prominent tools used to classify sentiment in order to get valuable information for use in companies like hotels,game companies,and so *** the sentiments of people towards different commodities helps to improve the services for contextual promotions,referral systems,and market ***,this study proposes a sentiment-based framework detection to enable the rapid uncovering of opinionated contents of hotel reviews.A Naive Bayes classifier was used to process and analyze the dataset for the detection of the polarity of the *** dataset from Datafiniti’s Business Database obtained from Kaggle was used for the experiments in this *** performance evaluation of the model shows a test accuracy of 96.08%,an F1-score of 96.00%,a precision of 96.00%,and a recall of 96.00%.The results were compared with state-of-the-art classifiers and showed a promising performance andmuch better in terms of performancemetrics.

关键词： Sentiment analysis hotel reviews Naive Bayes algorithm consumer opinions web 2.0 machine learning

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FAIR Machine Learning Model Pipeline Implementation of COVID-19 Data

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Data Intelligence 2022年第4期4卷 971-990,1036页

作者： Sakinat Folorunso Ezekiel Ogundepo Mariam Basajja joseph awotunde Abdullahi Kawu Francisca Oladipo Abdullahi Ibrahim Department of Mathematical Sciences Olabisi Onabanjo UniversityP.M.B 2002Ago-IwoyeOgun StateNigeria 120005Nigeria Data Science Nigeria Lagos 105102Nigeria Leiden University 1011NCAmsterdamthe Netherlands Department of Computer Science University of IlorinIlorinKwara State240103Nigeria Department of Computer Science Ibrahim Badamosi UniversityLapaiNiger State911101Nigeria Kampala International University 260101Uganda Federal University Lokoja Nigeria Virus Outbreak Data Network-Africa

Research and development are gradually becoming data-driven and the implementation of the FAIR Guidelines(that data should be Findable, Accessible, Interoperable, and Reusable) for scientific data administration and stewardship has the potential to remarkably enhance the framework for the reuse of research data. In this way, FAIR is aiding digital transformation. The ‘FAIRification’ of data increases the interoperability and(re)usability of data, so that new and robust analytical tools, such as machine learning(ML) models, can access the data to deduce meaningful insights, extract actionable information, and identify hidden patterns. This article aims to build a FAIR ML model pipeline using the generic FAIRification workflow to make the whole ML analytics process FAIR. Accordingly, FAIR input data was modelled using a FAIR ML model. The output data from the FAIR ML model was also made FAIR. For this, a hybrid hierarchical k-means (HHK) clustering ML algorithm was applied to group the data into homogeneous subgroups and ascertain the underlying structure of the data using a Nigerian-based FAIR dataset that contains data on economic factors, healthcare facilities, and coronavirus occurrences in all the 36 states of Nigeria. The model showed that research data and the ML pipeline can be FAIRified, shared, and reused by following the proposed FAIRification workflow and implementing technical architecture.

关键词： FAIRification Semantic data model Cluster analysis FAIR data Metadata Machine learning model

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Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Coinfection with Malaria in Selected States in Nigeria

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Advances in Infectious Diseases 2024年第2期14卷 442-455页

作者： Oluwagbemiga Olanrewaju Aina Olufemi Samuel Amoo Kazeem Adewale Osuolale Adewale Kayode Ojogbede Azuka Patrick Okwuraiwe David Ayoola Oladele Adesola Zaidat Musa Tajudeen Akanji bamidele Celestina Onyinye Okoyenta Abideen Olurotimi Salako Toyosi Yekeen Raheem Ifeoma Eugenia Idigbe Fehintola Anthonia Ige joseph Ojonugwa Shaibu Gregory Aigbe Ohihoin Kikelomo Wright Bisola Adebayo Hussein Abdu-Razzaq Abdulrahman Ahmad Mustapha Imam Bashir Bello Tambuwal Muhammad Shuaibu Gobir Richard Ikwuogu Christian Tetsola Gloria Patrick-Ferife Nathaniel Enamuotor Mildred Okowa William Nwachukwu Cornelius Ohonsi Magdalene Egede Chinwe Ochu Ehimario Igumbor Oliver Chukwujekwu Ezechi Babatunde Lawal Salako Rosemary Ajuma Audu Biochemistry and Nutrition Department Nigerian Institute of Medical Research Lagos Nigeria Centre for Human Virology and Genomics Microbiology Department Nigerian Institute of Medical Research Lagos Nigeria Monitoring and Evaluation Unit Nigerian Institute of Medical Research Lagos Nigeria Public Health and Epidemiology Department Nigerian Institute of Medical Research Lagos Nigeria Clinical Sciences Department Nigerian Institute of Medical Research Lagos Nigeria Molecular Biology and Biotechnology Department Nigerian Institute of Medical Research Lagos Nigeria Department of Community Health & Primary Health Care Lagos State University College of Medicine Lagos State University Teaching Hospital Lagos Nigeria Research Unit Lagos State Ministry of Health Lagos Nigeria Sokoto State Ministry of Health Sokoto Nigeria Department of Medical Biochemistry Usmanu Danfodiyo University Sokoto Nigeria Centre for Advanced Medical Research and Training Usmanu Danfodiyo University Sokoto Nigeria Delta State Ministry of Health Asaba Nigeria Nigeria Centre for Disease Control Abuja Nigeria Center for Infectious Disease Research Nigerian Institute of Medical Research Lagos Nigeria

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Plasmodium species are the causative agents of coronavirus disease 2019 (COVID-19) and malaria respectively with similar clinical presentations. The objective of this study is to determine the burden of co-infection of SARS-CoV-2 and malaria in the general population. Five (5 mLs) of blood samples were collected for SARS-CoV-2 and malaria parasite test. The malaria test was performed using a commercially available one-step malaria antigen Plasmodium falciparum histidine-rich protein 2 (Pf HRP-II) rapid test kit. The results of the study showed that the participants that were coinfected with SARS-CoV-2 IgG and malaria were 13 (2.5%) in Lagos, 1114 (39.1%) in Delta and 49 (2.3%) in Sokoto States. The prevalence of coinfection of SARS-CoV-2 and malaria in urban areas in Lagos, Delta and Sokoto States were 7 (2.2%), 1373 (48.1%), and 5 (0.2%) respectively. In rural areas, the prevalence of coinfection of SARS-CoV-2 and malaria in Lagos, Delta and Sokoto States were 6 (0.3%), 365 (12.8%), and 44 (2.1%) respectively in this study. This suggests that participants in the urban areas were more prone to co-infections than the rural areas in Lagos and Delta states, while it was otherwise in Sokoto State. In conclusion, the co-infection of SARS-CoV-2 and malaria was very high in Delta State compared to the other States. It is important for clinics to screen for both diseases when patients present with symptoms of malaria. This is because the infections have similar symptoms and the public is quick to assume malaria infection without diagnosing for COVID-19 and vice versa.

关键词： SARS-CoV-2 Malaria Coinfection

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Microbial Contents and Antibiotics Susceptibilities from Hand Washing Stations during COVID-19 Pandemic in Lagos, Nigeria

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Advances in Infectious Diseases 2023年第1期13卷 54-65页

作者： Tajudeen Akanji bamidele bamidele Tolulope Odumosu Princess Temitope Adenola James Ameh joseph Anejo-Okopi Adesola Zaidat Musa Babatunde Osoba Oliver Chukwujekwu Ezechi Babatunde Lawal Salako Nigerian Institute of Medical Research Yaba Nigeria University of Lagos Akoka Nigeria University of Queensland School of Veterinary Science Brisbane Australia Microbiology Department Federal University of Health Sciences Otukpo Nigeria Ministry of Health Lagos Nigeria

The COVID-19 pandemic put every government in the globe on red alert;safety protocol and long-standing infection prevention and control (IPC) measures such as hand and oral hygiene, social/ physical distancing, use of face mask were rigorously enforced. This study evaluated microbial (bacterial, fungal) contents of rinsate, bowl water, water from tap, and the neighborhood drainage in selected hand washing stations in Agege, Alimosho, Mainland, Island and Shomolu local government areas (LGAs) in Lagos, Nigeria. The identities of bacterial isolates were confirmed with 16S rRNA sequencing while the fungi were identified by colonial appearances. The antibiotics susceptibility testing (AST) of the bacteria against structurally unrelated antibiotics was performed and interpreted according to standard guidelines. Sixty-seven (67) bacterial and fifty-one (51) fungal isolates were recovered from mainly water bucket with tap and rinsates across all the LGAs. There were marked microbial loads (some too numerous to count at 10-3 dilution) across Alimosho, Lagos Island and Mainland. Forty (40) representative bacterial isolates were selected for 16S rRNA sequencing. The occurrence of microbial isolates in the samples was at varying degrees;Klebsiella spp. (37.5%), Bacillus spp. (32.5%), Enterobacter spp. (17.5%), were the predominant bacteria while Aspergillus spp. (46.2%), yeasts (34.6%), Sporothrix schenckii (11.5%) and Penicillium spp. (7.7%) constituted the fungal isolates. The biological weapon, B. anthracis was recovered from a water bucket with tap in Alimosho. The antibiotics susceptibility testing of the bacteria showed high degrees of resistance profile;45 (69.2%) to ampicillin, 41.5% amoxicillin/clavulanate while 47.6% were resistant to two (2) or more antibiotics. This study demonstrated high microbial load during the pandemic at the study LGAs, presence of environmental commensals reputed for debilitating opportunistic infections in man and risk of passing

关键词： Microbial Antibiotics Handwashing COVID-19 Rinsates

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Predictive modelling of COVID-19 confirmed cases in Nigeria

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Infectious Disease Modelling 2020年第1期5卷 543-548页

作者： Roseline O.Ogundokun Adewale F.Lukman Golam B.M.Kibria joseph B.awotunde Benedita B.Aladeitan Department of Computer Science Landmark University Omu AranNigeria Department of Physical Sciences Landmark University Omu AranNigeria Department of Mathematics and Statistics Florida International UniversityFloridaUSA Department of Computer Science University of IlorinIlorinNigeria

The coronavirus outbreak is the most notable world crisis since the *** pandemic that originated from Wuhan,China in late 2019 has affected all the nations of the world and triggered a global economic crisis whose impact will be felt for years to *** necessitates the need to monitor and predict COVID-19 prevalence for adequate *** linear regression models are prominent tools in predicting the impact of certain factors on COVID-19 outbreak and taking the necessary measures to respond to this *** data was extracted from the NCDC website and spanned from March 31,2020 to May 29,*** this study,we adopted the ordinary least squares estimator to measure the impact of travelling history and contacts on the spread of COVID-19 in Nigeria and made a *** model was conducted before and after travel restriction was enforced by the Federal government of *** fitted model fitted well to the dataset and was free of any violation based on the diagnostic checks *** results show that the government made a right decision in enforcing travelling restriction because we observed that travelling history and contacts made increases the chances of people being infected with COVID-19 by 85%and 88%*** prediction of COVID-19 shows that the government should ensure that most travelling agency should have better precautions and preparations in place before re-opening.

关键词： COVID-19 Pandemic Linear regression model Prediction Ordinary least squares estimator Diagnostic checks

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Effect of Some Plating Variables on Zinc Coated Low Carbon Steel Substrates

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Journal of Minerals and Materials Characterization and Engineering 2011年第13期10卷 1255-1262页

作者： bamidele M. Durodola joseph A.O. Olugbuyiro Department of Chemistry College of Science and Technology Covenant University Ota Ogun state Nigeria

This work examined the effect of plating variables on zinc coated low carbon steel substrates. The electrodeposition of steel substrates was carried out in zinc electrolyte bath. Time, voltage, distance from the anode to the cathode and the immersion depth served as plating variables. The results showed that weight gained increases as the plating time increases for the constant depth of immersion while the weight gained per unit time by varying immersion depth is irregular. Also, the study demonstrated that sample plated for 20 minutes;20cm from the anode, 45cm depth of immersion at 0.8V exhibited the best plating properties with homogeneity of diffuse plating efficiency.

关键词： Variables Zinc-coated low carbon steel substrates Depth of immersion Electrodeposition

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Outcome of Symptom-Based RT-PCR Testing for SARS-CoV-2: Experience from a Large Public Testing Centre in Nigeria

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Advances in Infectious Diseases 2022年第4期12卷 799-812页

作者： Aigbe Gregory Ohihoin Kazeem Adewale Osuolale Patrick Azuka Okwuraiwe Adesola Zaidat Musa Ayorinde Babatunde James Chika Kingsley Onwuamah Olufemi Samuel Amoo joseph Ojonugwa Shaibu Fehintola Ige Esther Ngozi Ohihoin Emelda Chukwu Ngozi Mirabel Otuonye Tajudeen bamidele Adeola Olukosi Olusola Ajibaye Yekeen Raheem David Oladele Agatha Nkiru David Babatunde Adewale Rosemary Audu Oliver Ezechi Nkiruka Nnonyelum Odunukwe Richard Adegbola Babatunde Lawal Salako Clinical Sciences Department Nigerian Institute of Medical Research Yaba Lagos Grants and M/E Unit (Biostatistics) Nigerian Institute of Medical Research Yaba Lagos Centre for Human Virology and Genomics Microbiology Department Nigerian Institute of Medical Research Yaba Lagos Department of Biochemistry and Nutrition Nigerian Institute of Medical Research Yaba Lagos Centre of Infectious Disease Research Microbiology Department Nigerian Institute of Medical Research Yaba Lagos Central Research Laboratory Nigerian Institute of Medical Research Yaba Lagos Department of Molecular Biology and Biotechnology Nigerian Institute of Medical Research Yaba Lagos Clinical Diagnostic Laboratory Nigerian Institute of Medical Research Yaba Lagos Department of Public Health Nigerian Institute of Medical Research Yaba Lagos

Background: Access to testing for SARS-CoV-2 in Nigeria is still highly restricted. Only patients who are symptomatic for SARS-CoV-2 are selected for testing. This pattern of testing will miss a large proportion of individuals with the infection who are asymptomatic and presymptomatic. This study reports the experience of a symptom-based study from a large testing centre in Nigeria. Methods: A cross-sectional study, reviewing data collected from respondents presenting at the Nigerian Institute of Medical Research (NIMR) modified drive-through center for COVID-19 test between the period March 31st and August 31st, 2020 were included in the analysis. Results: A total of 9891 participants were recruited into the study and 2465 participants (24.9%) had a positive PCR result for SARS-CoV-2. The majority of the respondents were above 18 years old, n = 9163 (93.4%). The average age of the respondents was 36.7 years (sd 13.8 years). The age of the participants has a significant effect on SARS-CoV-2 status (AOR = 1.009, CI, 1.005 to 1.012, p = 0.0001). There was a male preponderance, n = 5652 (57.6%). The odds of having a positive status for SARS-CoV-2 were 0.9 times lower for female participants. The majority of the respondents had a history of travel, n = 6788 (68.6%). Cough was the commonest symptom, n = 1062 (10.7%) followed by fever, n = 979 (9.9%). The mortality rate was 0.1%. Among the participants with comorbidity, 31 (51.7%) had positive results for SARS-CoV-2 while 29 (48.3%) had negative results. Conclusion: Symptom-based approach to testing for SARS-CoV-2 in Nigeria revealed a high positivity rate, while mortality from those tested in the study is low. Age and gender appear to play a significant role in the dynamics of the disease.

关键词： SARS-CoV-2 COVID-19 Symptoms RT-PCR Nigeria

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Microbial Contents and Antibiotics Susceptibilities from Hand Washing Stations during COVID-19 Pandemic in Lagos, Nigeria

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Advances in Infectious Diseases（传染病进展） 2023年第1期

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Determinants of Adoption of Sawah Rice Technology among Farmers in Ashanti Region of Ghana

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Journal of Agricultural Science and Technology(B) 2013年第7期3卷 459-468页

作者： Cornelius Idowu Alarimal Comfort Oyekale Adamu joseph Mubo awotunde Mary Nuako Bandoh Tsugiyuki Masunaga Toshiyuki Wakatsuki Soil and Ecological Engineering Laboratory Faculty of Life and Environmental Sciences Shimane University Matsue 690-8504 Japan Department of Agricultural Extension and Rural Development University of Agriculture Abeokuta Nigeria Crop Research Institute P.O. Box 3785 Fumesua Kumasi Ghana

The purpose of this study is to identify the determinants of adoption of sawah technology in Ashanti region of Ghana. It identifies those independent variables that explain adoption and can also facilitate further dissemination and adoption of sawah technology. Sawah refers to leveled rice field surrounded by banks with inlet and outlet for irrigation and drainage. This study uses data from 108 farmers randomly selected from 198 sawah farmers in the study area. Regression analysis showed that age, educational level and year of experience in rice production were the personal factors that determined the adoption of sawah technology among the respondents. The result further showed that contact with extension agents, attendance in previous sawah trainings, land tenure arrangement, yield from sawah farm and attributes of sawah technology determined adoption. This study suggested that adoption of sawah technology should be targeted at young, educated and experienced farmers. Also, security of land must be ascertained by farmers in order to enhance adoption, continuous and sustained use of sawah technology.

关键词：技术属性农民水稻加纳土地使用权独立变量研究区域回归分析

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