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1.
5th International Conference on Communication, Device and Networking, ICCDN 2021 ; 902:223-232, 2023.
Article in English | Scopus | ID: covidwho-2048169

ABSTRACT

Now a days in EFL procedure of education the ability of reading became as significant belief and personal-efficacy reading as a basic understanding for students. By monitoring the acknowledged participates under the ballpark figure of large studying and methods of understanding, the impact of their observation is premeditated on reading of each one’s personal-efficacy. On a daily routine all these things are comparatively considered which are put into effect by teachers of handful in number. Approach towards exhibiting Extensive reading (ER) is inspected to be “more expensive, difficult, and time-consuming”. Method of recognition of elements in a various way for effective impact in putting its efforts to utilize for its empowerment. Paper has been segregated into two contexts: Association with attitude is considered as primary one and attitude is considered as secondary one. Whether knowledge work is understood by student or not is considered as the impact of ER by the first review. Procedure which are convenient is taken as the observations of student and is analysed as second one. The examinations are quantifiable to utilize the observations as information in terms of subjective way taken from students who belong to first academic year of reading course in a systematic way and 603 details of undergraduate students from KLEF of Guntur were chosen as participants for extant examination. In ER programme of includes and excludes “comprehension reading work” is treated as fundamental in the proposal of disclosures. In case of any, “the programme appeared to positively affect contributing students”. Techniques of classification like “decision tree and Mixed Model Database Miner (MMDBM)” are employed in this paper which leads to improvements of post-test to pre-test in ER group. Observations of students in ER results as optimistic and algorithm of MMDBM which leads to accuracy in higher rate in pre-test and post-test detection. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

2.
12th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2022 ; : 477-481, 2022.
Article in English | Scopus | ID: covidwho-1788635

ABSTRACT

The novel corona virus (COVID-19) has turned out to be the biggest challenge of 21 century. Since, it is spreading at a very high pace all over the world, fast and accurate detection of this virus becomes a necessity. However, the human annotation of images is time-consuming;it is not a good strategy for dealing with big amounts of medical imaging data. This work looks at the experimental examination of features that are well-suited for examining X-ray pictures in COVID19. This investigation encompasses the series of steps, including data augmentation, pre-processing, feature extraction using GLCM followed by feature selection using PCA, and finally classification is performed by Light Gradient Boosting Machine. The proposed method was validated by comparing it to COVID-19 X-ray dataset, with an accuracy achieved is 92.40%. © 2022 IEEE.

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