Over the years, there have been ongoing efforts to use clothing as a vehicle for distributing digital capabilities. Information technology (IT) is being incorporated into garments to enable people to work more quickly...
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Atrial fibrillation (AF) is the most common arrhythmia. Although the exact cause is unclear, electropathology of atrial tissue is one contributing factor. Electropathological characteristics derived from intra-operati...
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Heart disease is one of the most common diseases in Jordan. It is a major reason of death among Jordanian adult citizens. Worldwide, an average of 56,000 people dies each day or one death every 1.5 seconds. Hence, thi...
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ISBN:
(数字)9798331540012
ISBN:
(纸本)9798331540029
Heart disease is one of the most common diseases in Jordan. It is a major reason of death among Jordanian adult citizens. Worldwide, an average of 56,000 people dies each day or one death every 1.5 seconds. Hence, this research is interested in the early prediction of this disease among Jordanian people. To achieve this main objective, Machine Learning (ML) is utilized through a large number of classification models and considering five well-known evaluation metrics. These classification models have been trained on a primary dataset that has been collected for the purpose of the research. The results revealed that RandomForest and RandomCommittee are the best classification models to handle the task of the early prediction of Heart disease in Jordan.
This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic...
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This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic *** traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent *** introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local *** the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is *** simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.
Machine learning has been widely used as part of financial markets investment strategies, whether for forecasting the financial assets exchange rate, managing market volatility, or solving different classification pro...
Machine learning has been widely used as part of financial markets investment strategies, whether for forecasting the financial assets exchange rate, managing market volatility, or solving different classification problems that help with decision-making. Building an investment strategy using a scientific approach requires a massive amount of data, good computational power, and some expertise in the finance industry. Machine learning applications to the financial field, such as price exchange rate prediction, market pattern recognition, or other trading strategy tasks, are considered optimization problems. As they require an efficient algorithm dedicated to finding a global optimum, they can be solved using metaheuristics. In this survey, we study how metaheuristic optimization techniques contribute to building a robust learning model dedicated to financial investment strategy applications.
Feature noise and label noise are ubiquitous in practical scenarios, which pose great challenges for training a robust machine learning model. Most previous approaches usually deal with only a single problem of either...
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This study presents a hybrid optimization framework combining Non-dominated Sorting Genetic Algorithm III (NSGA-III) and Multi-Objective Ant Colony Optimization (MOACO) to optimize time, cost, quality, and carbon foot...
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This study examines improvements in stegano-graphic models by redesigning three main components: the encoder, decoder, and evaluator, each optimized for better performance. The encoder is designed to embed data effect...
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Marianna Ruggieri, Andrea Scapellato; Preface of the Symposium “Qualitative Properties of Solutions of Differential Equations”, AIP Conference Proceedings, Volu
Marianna Ruggieri, Andrea Scapellato; Preface of the Symposium “Qualitative Properties of Solutions of Differential Equations”, AIP Conference Proceedings, Volu
Software accuracy and dependability become very important issues now-a-days. It is more difficult to identify software program errors due to the growing size and complexity of programs. Traditional fault localization ...
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