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1.
2nd Asian Conference on Innovation in Technology, ASIANCON 2022 ; 2022.
Artigo em Inglês | Scopus | ID: covidwho-2136098

RESUMO

The variations in the price of crude oil are very erratic, nonlinear, and dynamic with a high degree of uncertainty making it much more difficult to predict accurately. As a result, the opacity and intricacy in determining the crude oil price have been a significant topic of interest for researchers. This paper develops an efficient Genetic Algorithm(GA) based fine-tuned Support Vector Regression(SVR) model for predicting crude oil prices. The strategy utilizes key economic factors that ascertain the price per barrel, which serves as the input. The NASDAQ dataset used in this work encompasses ten years of daily data. The GA technique fine-tunes the parameters of the SVR model to boost the model's ability to foresee crude oil price fluctuations. The proposed model's performance is evaluated by employing various major criteria that compare our model to its counterparts, such as SVR and Long Short-Term Memory (LSTM) approaches. In light of these criteria, the findings of root mean square error (RMSE) and mean absolute percentage error (MAPE) indicate that this model surpasses others in predicting crude oil prices more accurately. Finally, this study also analyzes the impact of persistent uncertainness concerning the COVID-19 outbreak on crude oil price trends. © 2022 IEEE.

2.
International Journal of Health Sciences ; 6:3686-3700, 2022.
Artigo em Inglês | Scopus | ID: covidwho-1995072

RESUMO

COVID-19 has significantly affected the teaching-learning continuum in India. Most of the educational institutes had adopted online mode for the delivery of content and pedagogies enabled by digital technology, devices, and platforms. The pandemic has adversely affected English language learning in India, for learners used to learning ESL in a real-life situation through regular face-to-face mode experienced challenges in earning ESL through virtual mode. Learning English to develop the required language skills in virtual classrooms was anything but easy. Nonetheless, Indian students, as this study finds, took up the challenge by their stride and survived the altered learning conditions forced by the pandemic. This student-centric study aims to explore the impact of COVID-19 on language learning, the problems and challenges faced by student-learners, and the strategies to overcome them. An online survey was conducted to collect data from a group of students (n=400) using a survey questionnaire and mixed methods were used for data analysis and interpretation. The results indicate that the students experienced moderate to high-level difficulty in language learning and their coping strategies worked out. © 2022 International Journal of Health Sciences.

3.
INTERNATIONAL JOURNAL OF EARLY CHILDHOOD SPECIAL EDUCATION ; 14(4):1225-1235, 2022.
Artigo em Inglês | Web of Science | ID: covidwho-1966000

RESUMO

The man-made brainpower (AI) methods overall and convolutional brain organizations (CNNs) specifically have achieved victories in clinical picture examination and grouping. A profound CNN design partakesprojected into this research article for the analysis of OMICRONgroundedonto clinical radiography analysis (X-ray). As matter of the fact, thenon-availability in adequate scope and excellent X-ray picture database, a compelling and exact Convolutional NN (CNN) characterization remained anexamination. Managingthose intricacies, for example, accessibility with avery-little measured and contrastdatabaseof picture resolutionchallenges, the database has been pre-processed into various stages utilizing various strategies to accomplish a powerful preparation databaseof the appliedConvolutional NN (CNN)prototypical to achieve itsfinest presentation. Preprocessing phases in the database acted intoresearch incorporate database adjusting, clinical specialists' picture investigation, and information expansion. The exploratory outcomes reveal general precision up to 98.08% that exhibits its great capacity of the prototypicalConvolutional NN (CNN)systemof the ongoing application space. Convolutional NN (CNN)prototype has been tried into 2 (two) situations. The primary situation explains that it hasbeen tried utilizing the 7762 X-ray pictures as database,it accomplished a precision of 98.08 percent. To the subsequent situation, the prototypical hastried been utilizing the autonomous database of Omicron X-ray pictures from Kaggle. The execution intocurrentassessment the situation remained just about 98.08%. It additionally demonstrates that the prototypicalsystem beats different systems, asa similar examination has finished been thru a portion of AIcalculations. The proposed model has superseded every one of the models by and large and explicitly when the model testing was finished utilizing a free testing set.

4.
Indian Journal of Otolaryngology and Head and Neck Surgery ; 2020.
Artigo em Inglês | Scopus | ID: covidwho-891926

RESUMO

To find out incidence, prevalence, various modes and pattern of cutthroat injury during COVID-19 pandemic and compare with prior non pandemic period. To find out the various factor influencing the suicidal cutthroat and establish the temporal association of suicidal cutthroat with COVID-19 pandemic. It is a retrospective study of cutthroat patients who were managed in ENT Dept. VIMSAR, Burla, Sambalur, Odisha, India from 1st September 2019 to 31st August 2020. Source of information are casualty, IPD and OT registers and online data. Total cases were divided into group-A (prior to COVID-19 pandemic) and group-B (during COVID-19 pandemic) and analysed. Total 24 cutthroat injury cases were treated over 1 year in department of ENT, VIMSAR, Burla, which was 0.054% of total cases attended at casualty and 2.371% of total IPD patients treated. In GROUP-A, total 10 cases with M:F = 9:1,suicidal 4 cases (40%), homicidal 6 cases (60%), and no accidental cases were recorded. While in GROUP-B, total 14 case with M:F = 14:0, suicidal 9 cases (64.28%), homicidal 3 cases (21.42%) and accidental 2 (14.28%) cases were recorded. In our study majority of cases were male with M:F = 23:1. Common age group belongs to 20–30 years with LSES and farmer by occupation. Zone II injury had incidence of 70.83%. Homicide cases proportionally high during non-COVID period while suicide cases high during COVID-19 pandemic. Association of COVID-19 pandemic with suicidal cut throat injury is seems to be significant. Among predisposing risk factors for suicidal, depression during COVID-19 pandemic had seen in 53.84% of total suicidal cases. Incidence and prevalence of Cut throat injury is comparatively high in western odisha which again increases during months of July and August parallel to COVID-19 pandemic. The common mode of cutthroat injury is homicidal, which suddenly changes to suicidal during COVID-19 pandemic. More vulnerable groups were young unemployed male, farmers and labours. Cutthroat injury cases definitely increases during COVID-19 pandemic with most common mode of injury being suicidal attempt, which may be due to economical and psychological imbalances, due to loss of job and fear and social stigma for COVID-19 diseases. © 2020, The Author(s).

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