Chinese Science Bulletin

English vocabulary teaching strategies are the key to students' success in mastering a new language. The researcher selected four teachers at private and public schools by providing a questionnaire to find out the vocabulary teaching process. The findings suggest that educators use a variety of techniques to improve vocabulary learning, including visual aids, drilling exercises, pitch variations, repetitions, and interactive exercises. Assessment strategies include oral tests and interactive activities, which help measure vocabulary development and ensure practical applicability. The study hig

For the two-parameter (pq) deformed Heisenberg algebra in troduced recently and in which, instead of usual commutator of Hpq = aa Ip Iq Mostimportantistherealizability of the (pq) deformed Heisenberg algebra by means of the appropriate deformed oscillator algebra. Using the (pq)-derivative operator, we introduce the (pq)-deformed Heisenberg algebra HpqWe give a representation of Hpq

Artificial Intelligence (AI) has emerged as a powerful adjunct in critical care, capable of analyzing vast datasets at remarkable speed to enhance diagnostic accuracy, resource allocation, and treatment personalization. This review examines the current landscape of AI applications in Intensive Care Units (ICUs), focusing on predictive analytics, clinical decision support systems (CDSS), and computer vision. Predictive analytics models, leveraging machine learning and deep neural networks, identify early indicators of sepsis, organ failure, and other acute conditions, demonstrating reductions i

This study introduces an enhanced framework for student dropout prediction by integrating Binary Harris Hawks Optimization (BHHO) with boosting algorithms and Synthetic Minority Over-sampling Technique (SMOTE). We evaluated the framework using two datasets: a multi-class dataset of 6,847 student records and a binary dataset of 1,044 instances. The methodology combines BHHO for hyperparameter optimization of boosting algorithms (AdaBoost, Gradient Boosting, XGBoost, and CatBoost) with SMOTE for addressing class imbalance. Experimental results demonstrate the framework's superior performance com

Artificial Intelligence (AI) has emerged as a powerful adjunct in critical care, capable of analyzing vast datasets at remarkable speed to enhance diagnostic accuracy, resource allocation, and treatment personalization. This review examines the current landscape of AI applications in Intensive Care Units (ICUs), focusing on predictive analytics, clinical decision support systems (CDSS), and computer vision. Predictive analytics models, leveraging machine learning and deep neural networks, identify early indicators of sepsis, organ failure, and other acute conditions, demonstrating reductions i