• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.201-209
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• 2024

The COVID-19 pandemic has significantly impacted the aviation industry, leading to worldwide changes in travel restrictions and security measures. This study analyzes 59,818 reviews of 147 airlines from the SKYTRAX website between 2016 and 2023 to understand the changes in airline service satisfaction before and after the pandemic. Using sentiment analysis, the study compares overall satisfaction, review sentiment, and attributes influencing satisfaction. The results show a statistically significant (p<0.001) decrease in overall satisfaction post-COVID-19, with reduced positive sentiment and increased negative sentiment for all airline selection attributes, except cabin and in-flight services. Flight operation services had the most significant impact on overall satisfaction during both periods. This quantitative analysis of global major airlines' satisfaction attributes before and after COVID-19 contributes to enhancing future service satisfaction in the airline industry.