This paper provides an analysis method of a robust invariant set for discrete-time linear switched systems with peak-bounded disturbances. In the case of a switched linear system, it is challenging to analyse the robu...
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This paper introduces an alternative technique for diagnosing Acute Ischemic Stroke within the IoMT environment. In the proposed approach, the collected data is transmitted to a cloud-based center where the technique ...
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Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and ma...
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Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning *** study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal *** information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering *** learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding *** ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different ***,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased *** analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered ***,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.
electrical circuit networks consist of various electrical components connected in different arrangements that are used to process electrical signals, such as voltages and currents. Moreover, they are widely used in ma...
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ISBN:
(数字)9798331508180
ISBN:
(纸本)9798331508197
electrical circuit networks consist of various electrical components connected in different arrangements that are used to process electrical signals, such as voltages and currents. Moreover, they are widely used in many engineering and physical systems, such as control, embedded and communication systems. In this work, we propose to use higher-order-logic theorem proving for formally analyzing electrical circuit networks using network topology matrices. In particular, we formalize in the Is-abellelHOL theorem prover incidence and circuit (loop) matrices, which are widely used topology matrices. Our formalization is based on modeling the system as a network using the notion of directed graphs that are algebraically represented by matrices. Next, we use this formalization to formally analyze various network topologies, such as Δ- $Y$ and ∏ - $L$ topologies, where we perform Kirchhoff's current and voltage laws based analysis in a generic way.
As disassembly lines evolve, keeping workers safe from all potential dangers has become paramount. This work proposes an improved approach, Proximal Policy Optimization for Disassembly Line(PPO-DL), to address Multi-o...
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This article proposes an active fault detection method combining the Total Measurable Fault Information Residual (ToMFIR) and auxiliary signals to address the incipient faults of autonomous underwater vehicle (AUV) th...
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In robotics applications, ensuring reliable performance in the presence of actuator faults is essential for maintaining system safety and reliability. This paper presents a tolerant tracking control method for permane...
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The Internet of Things (IoT) devices' proliferation underscores the critical importance of fortifying nanoscale circuit security against evolving cyber threats. This paper introduces an unprecedented paradigm to e...
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Pediatric bone age prediction is a crucial task in clinical practice that can help diagnose endocrine disorders and provide insight into a child's growth and development. However, conventional bone age prediction ...
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Greenhouse gas emission reduction is underway worldwide to mitigate the effects of global warming. Among the new initiatives, electrification of passenger airplanes could yield enormous economic and environmental bene...
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