Search

To overcome the problem of current control effect being reduced by unideal factors in a motor control system, such as motor parameter variation, inverter dead time, nonlinearity of the system, etc., a sliding mode disturbance observer for an interior permanent magnet synchronous motor is proposed in this paper. The model of an interior permanent magnet synchronous motor with unideal factors is designed, and the unideal factors are unified into lumped disturbances of motor stator voltage. Then, the observer for lumped disturbance is designed. A recursive integral sliding surface is used to replace the terminal sliding surface to avoid the noise sensitivity and singularity problem of the traditional terminal sliding mode observer. The observer can estimate the lumped disturbance of the current loop without relying on the accurate system model in finite time. Moreover, the structure of the current loop does not need to be adjusted while using the observer to observe and compensate for disturbances. Experiments are carried out to verify the effectiveness of the proposed observer. [ABSTRACT FROM AUTHOR]

The computer‐aided diagnostic (CAD) method to detect human brain tumors relies heavily on automated tumor characterization. Although CAD method has been extensively researched, significant obstacles still exist. Magnetic resonance imaging (MRI) classifiers brain tumors into glioma, meningioma, and pituitary tumors. However, accurately distinguishing between these tumor types remains a complex challenge in medical imaging. The recently developed deep learning and machine learning (ML) techniques have shown immense potential in image classification. However, the low numbers of medical image archives also pose a problem for medical image classification. As a result, fewer medical images are available to use in deep learning research and development. To address this issue, we use three highly effective ML classifiers with deep convolutional learned features for medical image classification. The MRI images of the three distinct types of brain tumors may be found in an open dataset on Figshare, which tests the automated approach's efficacy. Features are extracted from brain MRI scans using the DenseNet169 model. Extracted features are fed into a multiclass three ML classifiers (RF, SVM, XGBoost) for improved performance. Results from testing and evaluation of the entire framework are promising, especially compared to the field's state‐of‐the art technique. The suggested model outperformed the state‐of‐the‐art technique, with an overall classification accuracy of 95.10%. To verify the enhanced performance of the proposed system, extensive tests are conducted on the brain MRI dataset available on Figshare. The optimal hyper‐parameter fading classifier is seen to outperform the Softmax classifier for the features when there is limited training data. [ABSTRACT FROM AUTHOR]

Objectives: Esketamine is an S (+) enantiomer of ketamine with greater potency and similar psychomimetic effects compared to racemic ketamine. We aimed to explore the safety of esketamine in different doses as an adjuvant to propofol in patients undergoing endoscopic variceal ligation (EVL) with or without injection sclerotherapy. Methods: One hundred patients were randomized to receive sedation with propofol 1.5 mg/kg in combination with sufentanil 0.1 μg/kg (group S), esketamine 0.2 mg/kg (group E0.2), esketamine 0.3 mg/kg (group E0.3), or esketamine 0.4 mg/kg (group E0.4) for EVL (n = 25 each). Hemodynamic and respiratory parameters were recorded during the procedure. The primary outcome was the incidence of hypotension; secondary outcomes included the incidence of desaturation, positive and negative syndrome scale (PANSS) after the procedure, pain score after the procedure, and secretion volume. Results: The incidence of hypotension was significantly lower in groups E0.2 (36%), E0.3 (20%), and E0.4 (24%) than in group S (72%). The incidence of SpO2 ≤94% was significantly lower in group E0.4 (4%) than in group S (32%). No significant intergroup difference was found in the PANSS assessment. Conclusions: Combining 0.4 mg/kg esketamine with propofol sedation was optimal to facilitate EVL with stable hemodynamic status and better respiratory function during the procedure, without significant psychomimetic side‐effects. Trial registration: Chinese Clinical Trial Registry (Trial ID: ChiCTR2100047033, http://www.chictr.org.cn/showproj.aspx?proj=127518). [ABSTRACT FROM AUTHOR]

In order to solve the coordinated optimization problem of distributed generation (DG), on‐load tap changer (OLTC) and capacitor banks, a dynamic reactive power optimization (DRPO) method based on fuzzy time clustering is proposed. In the method, fuzzy time clustering algorithm is used to cluster the static optimal switching sequence of OLTC and capacitor banks. The time decoupling of control variables is realized and it meets the constraints of the maximum switching times. Next, the influencing factors of DG reactive power limit are analysed. Considering the control ability of OLTC, capacitor banks and DG in voltage and reactive power optimization, a coordinated optimization method is proposed. Since the adjustment of OLTC tap position directly affects the voltage and reactive power distribution of the whole line, the switching time and tap position of OLTC are determined based on the static optimization results of each time and fuzzy time clustering algorithm. Then, the switching time of capacitor banks is determined by fuzzy time clustering algorithm. At last, the switching capacity of capacitor banks and DG reactive power are jointly optimized to get the final control scheme. The proposed method demonstrated good performance in the modified IEEE33 node system and two actual power grid examples. [ABSTRACT FROM AUTHOR]