Cardiovascular disease, the leading cause of death in the U.S., affects both the heart and blood vessels. Contrast-enhanced cardiac computed tomography angiography (CTA) is a prominent imaging modality for assessing h...
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The Internet has become an essential tool for people in the modern world. Humans, like all living organisms, have essential requirements for survival. These include access to atmospheric oxygen, potable water, protect...
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Breast cancer (BC) has been one of the significant causes of death worldwide, and its early detection can play a vital role in increasing the survival rate of this disease. This paper suggests a novel feature learning...
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Automating the documentation, explanation, and modification of source code has been an area of intense research interest for several decades. This paper proposes a novel framework for analyzing source codes to generat...
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Background: The development of medical treatments has traditionally relied on researchers leveraging scientific knowledge to hypothesize disease mechanisms and identify therapeutic agents. However, the depletion of no...
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The article presents a study on classifying wind turbine defects using the SqueezeNet neural network. Wind turbines are critical for renewable energy, but defects such as corrosion, erosion, and cracks can significant...
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While the wireless word moves towards higher frequency bands, new challenges arises, due to the inherent characteristics of the transmission links, such as high path and penetration losses. Penetration losses causes b...
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The multi-hopping mechanism features in the wireless network environment, in which all nodes contain the information of link and connectivity in any infrastructure less manner. When mobile devices either jump from the...
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The mainstream of diagnostic approaches of printed circuit board assemblies is optimised for large-scale industrial production, and is less suited for repair and maintenance during later stages of the product life-cyc...
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Humans immediately understand any long text by processing or searching the Part-of-Speech (POS). Optimal AI classifier and a unique POS tagging approach guarantee the success of natural language processing. Improved U...
Humans immediately understand any long text by processing or searching the Part-of-Speech (POS). Optimal AI classifier and a unique POS tagging approach guarantee the success of natural language processing. Improved Urdu text classification depends upon the choice of algorithm and an optimal tagging system. Support Vector Machine (SVM) and its latest hyper-tuned variants are effective classifiers because the decision function or support vectors have training points. For more improved results and novelty different variants and hyperparameters will be used. SVM variants, Random Forest, and an ensemble model are tested on the same corpus dataset with and without the proposed unique POS tagger. The POS tagging is a kind of feature engineering for better results. The corpus dataset is divided into four categories: sports, entertainment, science and technology, and business and economics. The results are dramatically improved by using customized POS taggers. The average accuracy, precision, recall, and F1-score of the SVM variants using POS tagging are above 92%. Random Forest classifiers give over 95% results for all matrices. It gives an average of above 98% results for all four matrices. POS tagging significantly improves the performance of models. There is a special focus on improved POS based text categorization for Quick and lightweight models deployment. Recent emerging discriminative and generative AI algorithms with improved architecture may better utilize POS taggers for more complex natural language text classification. Rule-Based POS Taggers Uses handcrafted linguistic rules and Machine learning based taggers Learns patterns from annotated corpora.
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