Weather forecasting in countries like Bangladesh poses unique challenges, given its diverse geographical features. The region experiences varying weather patterns influenced by factors such as monsoons, river systems,...
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This paper proposes a design for a visualization system for underwater multi-target tracking based on the Gaussian Mixture Probability Hypothesis Density (GMPHD) filter using Unity 3D engine. Traditional analysis meth...
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Very recently, a memory-efficient version (called MeZO) of simultaneous perturbation stochastic approximation (SPSA), one well-established zeroth-order optimizer from the automatic control community, has shown competi...
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Face recognition under occlusion presents a persistent challenge in computer vision, primarily due to difficulties in capturing and effectively integrating visible and obscured facial features. This paper introduces a...
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The proliferation of IoT devices necessitates secure and efficient mechanisms for data encryption and retrieval. This paper presents an optimized framework that leverages AES encryption integrated with memory modules ...
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Objective Hypertension is a critical medical condition that increases the risks of many fatal *** detection of hypertension can be crucial to lead a healthy *** learning(ML)can be useful for the early prediction of a ...
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Objective Hypertension is a critical medical condition that increases the risks of many fatal *** detection of hypertension can be crucial to lead a healthy *** learning(ML)can be useful for the early prediction of a patient’s likelihood of having a blood pressure abnormality and preventing *** artificial intelligence(XAI)is a state-of-the-art ML toolset that helps us understand and explain the prediction of an ML *** research aims to build an automatic blood pressure anomaly detection system with maximum accuracy using the fewest features and learn why a model arrived at a particular result using *** This study utilized the“Blood Pressure Data for Disease Prediction”dataset from *** were collected from medical reports of random participants in 2019 based on the presence of blood pressure abnormality,chronic kidney disease,and adrenal and thyroid *** have used several ML algorithms(extreme gradient boosting(XGBoost),random forest(RF),support vector machine(SVM),decision tree(DT),and logistic regression(LR))to predict blood pressure abnormality based on patient’s *** component analysis(PCA)and recursive feature elimination(RFE)algorithms were used as feature *** outcome metrics included receiver operating characteristic(ROC)curve analysis and *** performance measurement techniques,such as precision,recall,specificity,F1-score,and kappa were calculated to identify the model with the best ***,several XAI methods,namely permutation feature importance(PFI),partial dependence plots(PDP),Shapley additive explanations(SHAP),and local interpretable model-agnostic explanations(LIME)were implemented for additional exploration of our best *** The combination of RFE and XGBoost provides the most significant *** results of the study show that the algorithm has an AUC of 0.95,indicating good discriminatory power in detecting abnormal blood pressur
In recent years, YouTube has become the leading platform for Bangla movies and dramas, where viewers express their opinions in comments that convey their sentiments about the content. However, not all comments are rel...
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Advances in immunological research are essential for elucidating immune responses and developing targeted therapeutic approaches. This study proposes an automated method for immune cell classification leveraging machi...
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In recent years, neural network-based differential distinguishers have demonstrated significant advantages in accuracy and effi-ciency over traditional differential distinguishers in symmetric cipher differential anal...
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Potholes, waterlogging, and possible electrical hazards have a significant impact on urban traffic safety, especially during the monsoon season. Road damage, traffic jams, car accidents, and even potentially fatal ele...
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