Analysis and Optimization of Asymmetric Wireless Power Transfer in Concrete

Tian, Zhen; Liu, Dairong; Chen, Wei; Wang, Wenqing; Pan, Shan Ling; Guo, Ni

doi:10.1155/2020/8841210

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…With the explosive growth of power distribution data brought about by the large-scale popularization and application of smart meters and the lean management of the power grid, accurate classification and characteristic analysis of power users have become an important task for power grid companies [1,2]. Mastering the characteristics of user demand response helps to fully tap the potential of user demand response and improve the implementation efficiency of demand response, which is the basis for formulating a demand-side management scheme and electricity price package.…”

Section: Introductionmentioning

confidence: 99%

Data Mining Algorithm for Power User Network Based on Multi-Information Fusion

Huang

2022

International Transactions on Electrical Energy Systems

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In order to solve the problem of accurately mining the power consumption characteristic data of power users, this paper proposes a research on power user network data mining algorithms based on multi-information fusion. In the past, the mining methods based on neural networks and cure algorithms were affected by noise data, resulting in low mining accuracy. To solve this problem, this paper proposes a user-complex power consumption feature mining method based on the K-means clustering algorithm. In the K-means clustering algorithm, the principle of mining complex power consumption characteristics of users is studied, and the data are cleaned, integrated, and preprocessed by protocol transformation to avoid noise interference. The information entropy principle is used to cluster the matrix to regularize the feature points. According to the complex power consumption characteristics, the power consumption feature points are determined through the cluster, the distance between the clusters is calculated, the power consumption feature information gain is obtained, and the user complex power consumption feature mining is completed. The experimental results show that the mining accuracy of this method is up to 99%, providing users with better quality services. Conclusion. The automatic control performance of the system is good, and the acquisition results are accurate and reliable.

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Section: Introductionmentioning

confidence: 99%

Data Mining Algorithm for Power User Network Based on Multi-Information Fusion

Huang

2022

International Transactions on Electrical Energy Systems

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“…By comparing the postoperative VAS scores and trend changes of patients in the resting state and in the exercise state, the results showed that the median postoperative VAS score in group F was 2 (1) at 8 h, 12 h, and 24 h after the operation in the exercise state. ,2), 3(2,3) and 4(2,4) and the median VAS scores of group S 2(2,2), 3(2,3) and 4(3,5) compared with group C VAS e median scores of 3(2,3), 4(4,5) and 5 (3,6) were significantly reduced (p < 0.05). Table 5 shows the comparison of the VAS scores of the three groups of patients in the postoperative exercise state.…”

Section: Comparison Of Postoperative Analgesia In Patientsmentioning

confidence: 87%

“…e medical IoT is the application of advanced IoT technology to medical enterprises. As my country's medical and health system evolves from clinical information to regional, medical, and health information, the IoT technology has matured: to solve people's concerns about their own health, the situation requires further promotion of medical care, and the development of the health information industry [4][5][6][7].…”

Section: Medical Iot and Its Data Fusion Technologymentioning

confidence: 99%

Observation and Analysis of the Postoperative Analgesic Effect of Subanaesthetic Dose of Ketamine in Kashin–Beck Disease Patients after Total Knee Arthroplasty

Xie

Zhu

et al. 2022

Journal of Healthcare Engineering

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With the transformation of modern medical models, the medical needs of patients have changed from treatment to safe, comfortable, and painless treatment. Therefore, it is clinically important to find an ideal analgesia model to reduce the pain after total knee arthroplasty and minimize the impact of surgical trauma on the body pressure. This article aims to study the effects of lower limb nerve block combined with local infiltration analgesia of the joint cavity on the hemodynamics and postoperative analgesia effects of knee joint replacement in elderly patients by comparing the effects of the subanaesthetic dose of ketamine on the hemodynamics and postoperative analgesia effect of knee joint replacement in elderly patients’ intraoperative analgesia program. This article proposes that 90 patients requiring unilateral total knee replacement were randomly divided into 3 groups, with 30 patients in each group, age 65–85 years, average age 75 years, ASA I ∼ II grade, and body mass index 13.89 ∼ 37.26. Use a multifunctional monitor to monitor the patient’s continuous blood pressure (SBP/DBP) and mean arterial pressure (MAP), heart rate (HR), electrocardiogram (ECG), intraoperative pulse oxygen saturation (SpO2), and end-tidal carbon dioxide (PETCO2). The following are monitored: record the heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure before induction of anesthesia (T0), before the upper tourniquet (T1), and after the upper tourniquet (T2), before tourniquet withdrawal (T3), and after tourniquet withdrawal (T4), mean arterial pressure (MAP). The three groups of patients had different degrees of itching, vomiting, nausea, and other adverse reactions. The experimental results in this article show that, in elderly patients with epidural anesthesia, the use of propofol and dexmedetomidine to maintain the patient’s BIS value between 60 and 70 can meet the depth of sedation required for surgery without important surgical operation knowledge.

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“…The target of disaster relief is natural disaster farmers, and the target of the minimum agricultural security system is poor farmers who have not yet solved their clothing deficiencies [16]. The prosperity of rural society is a public welfare activity, which is a guarantee provided to certain special farmer groups, such as the elderly and the disabled [17], as well as vulnerable groups in rural areas. Its main purpose is to provide financial and material assistance to the elderly who cannot take care of themselves and the elderly without children in rural areas to ensure their basic living standards [18].…”

Section: Design and Implementation Methods Of A Rural Social Security System Based On Deep Learningmentioning

confidence: 99%

Design and Implementation of a Rural Social Security System Based on Deep Learning

Zhao

2021

Wireless Communications and Mobile Computing

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After the reform and opening up, my country’s economic level and total national strength have achieved unprecedented growth. The building of a well-off society in an all-round way is moving towards a harmonious society. The development of social security is also an important part of the development and improvement of a socialist harmonious society. This article is aimed at designing a rural social security system based on deep learning algorithms, using sample collection and statistical analysis methods, collecting samples, simplifying the algorithm, and establishing a new rural social security system. The data collected by the system shows that the proportion of farmers who choose very satisfied, satisfied, average, dissatisfied, and very dissatisfied with the satisfaction of the new rural insurance is 8.94%, 45.53%, 34.96%, 8.13%, and 2.44%. It can be seen that the proportion of farmers who choose to be satisfied is the largest, and more than 10.0% of farmers choose to be dissatisfied or very dissatisfied. Investigate the factors that farmers worry about participating in the new rural insurance, and the questionnaire options can also be set to multiple choices. The survey results show that 29.27% of the farmers think that the individual payment for participating in the new rural insurance is higher; 26.02% of the farmers believe that they do not understand the new rural insurance system; 9.76% of the farmers believe that it is unnecessary to pay for the new rural insurance; 22.76% of farmers choose to rely on themselves or their children in the future; 27.64% of farmers think that the system is unstable. It has basically realized the design of a brand new rural social security system starting from the deep learning of semantic computing.

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Analysis and Optimization of Asymmetric Wireless Power Transfer in Concrete

Cited by 6 publications

References 23 publications

Data Mining Algorithm for Power User Network Based on Multi-Information Fusion

Data Mining Algorithm for Power User Network Based on Multi-Information Fusion

Observation and Analysis of the Postoperative Analgesic Effect of Subanaesthetic Dose of Ketamine in Kashin–Beck Disease Patients after Total Knee Arthroplasty

Design and Implementation of a Rural Social Security System Based on Deep Learning

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