The state of charge (SOC) is a critical metric for effective operation and assessment of electric vehicle batteries. Various models are reported for estimating the SOC, among which the general nonlinear (GNL) model is...
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ISBN:
(数字)9798350390193
ISBN:
(纸本)9798350390209
The state of charge (SOC) is a critical metric for effective operation and assessment of electric vehicle batteries. Various models are reported for estimating the SOC, among which the general nonlinear (GNL) model is notable for its ability to capture essential batteries' electrical characteristics, particularly the self-discharge effect. Nevertheless, identifying the parameters in GNL model presents significant challenges. Genetic algorithm (GA) methods exhibit good performance in this parameterization due to their global searching capability. Unfortunately, the undefined initial values and unconstrained searching space in existing methods for GNL models limit the derivation speed and necessitate a large resource. To address this issue, this paper proposes a physics-informed GA method for estimating the SOC. Specifically, the initial parameter set is obtained by averaging the measured values from multiple on-site battery tests, while the corresponding searching spaces are determined based on their upper and lower limits. Using the LiFePO4 C102F Blade battery as a case study, the results demonstrate the effectiveness of the proposed method, which can reduce the iterations by more than 10 times. Additionally, the influences of with/without initialization as well as different searching space sizes are discussed for clarity.
This paper proposes a belief-updating scheme in a human-machine collaborative decision-making network to com-bat Byzantine attacks. A hierarchical framework is used to realize the network where local decisions from ph...
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The incorporation of mmWave technology in vehicular networks has unlocked a realm of possibilities, propelling the advancement of autonomous vehicles, enhancing interconnectedness, and facilitating communication for i...
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Antibiotic-resistant Neisseria gonorrhoeae, the bacterium responsible for gonococcal gonorrhea, is an increasing public health problem. If left untreated, gonorrhea can result in complications such as infertility and ...
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ISBN:
(数字)9798331519094
ISBN:
(纸本)9798331519100
Antibiotic-resistant Neisseria gonorrhoeae, the bacterium responsible for gonococcal gonorrhea, is an increasing public health problem. If left untreated, gonorrhea can result in complications such as infertility and pelvic inflammatory disease; the rising resistance to antibiotics complicates infection control. We performed our experiments with different models such as Logistic Regression, Decision Trees, Random Forests, and Support Vector Machine (SVM) over more complex Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) and Gated recurrent units (GRU). We used Explainable AI (XAI) to lighten the black box and infer what decisions these models make. In general, deep learning models were more successful in capturing the data patterns, with XAI being a key mechanism to provide knowledge on operability that can guide the treatment strategies.
A biomimetic artificial compound eye is constructed as an array of pixels each consisting of in-pixel circuits made of several metal-oxide thin-film transistors, a hydrogenated amorphous silicon photodiode and a struc...
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During the COVID-19 pandemic, medical imaging techniques like computed tomography (CT) scans have demonstrated effectiveness in combating the rapid spread of the virus. Therefore, it is crucial to conduct research on ...
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In this work, we, for the first time, demonstrate a comprehensive model of the multi-level Spin-Orbit torque (SOT)-MRAM. Scalability, stochasticity, and variations of the multi-level SOT-MRAM are captured within a uni...
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Deep learning algorithms have been widely used for various healthcare research because it helps eliminate the need for manual feature extraction which requires specialist expertise and is time-consuming. However, deep...
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This paper proposes a joint user cooperation and scheduling (JUCS) method to minimize the maximum transmission time among users in the synchronous federated learning (FL) architecture, since the user with the worst qu...
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Arithmetic operations and expression evaluations are fundamental in computing models. This paper firstly designs arithmetic membranes without priority rules for basic arithmetic operations, and then proposes an algori...
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Arithmetic operations and expression evaluations are fundamental in computing models. This paper firstly designs arithmetic membranes without priority rules for basic arithmetic operations, and then proposes an algorithm to construct expression P systems based on several of such membranes after designing synchronous and asynchronous transmission strategies among the membranes. For any arithmetic expression, an expression P system can be built to evaluate it effectively. Finally, we discuss different parallelism strategies through which different expression P systems can be built for an arithmetic expression.
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