KNN

Latest Nature Sub-Journal from Beijing University of Science and Technology: Achieving Ultra-High Piezoelectric Performance in (K,Na)NbO₃ System Based on Lattice Softening and Grain Orientation Strategies

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Latest Nature Sub-Journal from Beijing University of Science and Technology: Achieving Ultra-High Piezoelectric Performance in (K,Na)NbO₃ System Based on Lattice Softening and Grain Orientation Strategies

| Welcome to submit, please contact: MatResFron001 (WeChat ID) First Author (or Co-First Author): Zhu Lifeng, Liu Dong, Shi Xiaoming Corresponding Authors (or Co-Corresponding Authors): Deng Shiqing, Zhang Boping, Zhang Shujun, Li Jingfeng Affiliated Institutions: Beijing University of Science and Technology; Tsinghua University; University of Wollongong, Australia Paper DOI: https://doi.org/10.1038/s41467-025-56074-8 1. Overview: Potassium Sodium Niobate((K,Na)NbO3) … Read more

Enhancement Mechanisms of Piezoelectric, Dielectric, and Thermal Stability in (K, Na)NbO₃

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Enhancement Mechanisms of Piezoelectric, Dielectric, and Thermal Stability in (K, Na)NbO₃

| Welcome to submit articles, please contact: MatResFron001 (WeChat ID) Introduction: (K, Na)NbO3 (KNN) based piezoelectric ceramics are the most promising lead-free system to replace lead zirconate titanate (PZT) in the piezoelectric field due to their suitable piezoelectric coefficient and high Curie temperature. Currently, the research on the performance regulation of KNN has matured, and … Read more

A New Method for Identifying Bank Credit Risk: SVM-KNN Combined Model

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A New Method for Identifying Bank Credit Risk: SVM-KNN Combined Model

Authors: Shen Qing, Zhang Lianzheng Affiliation: Nankai University, School of Finance Source: Journal of Financial Regulation Research, Issue 7, 2020 Original Title: A New Method for Identifying Bank Credit Risk: SVM-KNN Combined Model Research Background Since 2019, the Baoshang Bank incident has attracted widespread attention from both academia and industry, sparking renewed discussions on credit … Read more

Impact of Grain Size on Piezoelectric Ceramic Performance

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Impact of Grain Size on Piezoelectric Ceramic Performance

Introduction Piezoelectric ceramics are an important functional ceramic that realize the conversion between electrical and mechanical energy through the piezoelectric effect. They are widely used in fields such as information sensing, medical health, military defense, and aerospace. To date, the most studied piezoelectric materials are piezoelectric ceramics with a perovskite structure. However, due to the … Read more

Application of Lead-Free Ferroelectric Films in pMUT

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Application of Lead-Free Ferroelectric Films in pMUT

Research Background: Micro piezoelectric ultrasonic transducers (pMUTs) have significant applications in fields such as medical imaging, fingerprint recognition, distance detection, and gesture recognition. The emission sensitivity of the device is one of the most important indicators for evaluating the pMUT emitter, in which the piezoelectric layer plays a critical role. In recent years, the piezoelectric … Read more

Unveiling the Ecological Footprint of Lead-Free Piezoelectric Ceramics

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Unveiling the Ecological Footprint of Lead-Free Piezoelectric Ceramics

Research Background Piezoelectric ceramics can achieve the conversion between mechanical energy and electrical energy, making them key materials in important fields such as information communication, biomedical, defense industry, and consumer electronics. Since the discovery of lead zirconate titanate (PZT) in 1955, its excellent piezoelectric properties have led to its rapid application in sensors, actuators, and … Read more

Statistical Learning Methods Using Python

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Python Algorithm Implementation from scipy import stats from pylab import * def knnClassify(Target_feature, dataSet, p, k): dataSet_x = dataSet[:, 0:-1] dataSet_y = dataSet[:, -1] L_p = [] for i in range(len(dataSet_x)): l_p = 0 for x_i in range(len(dataSet_x[i])): l_p = (abs(dataSet_x[i][x_i] – Target_feature[x_i]))**p+l_p l_p =math.pow(l_p, 1/p) L_p.append(l_p) L_p = np.array(L_p) y_i = L_p.argsort() y = … Read more

An Efficient Secure KNN Classification Protocol

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An Efficient Secure KNN Classification Protocol

The new issue of high-level papers is here This issue introduces the paper An efficient secure k nearest neighbor classification protocol with high-dimensional features Published in the INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS The authors are Yang Ruidi and her advisor, Professor Sun Maohua Part 01 Author Introduction Sun MaohuaINTERVIEW Born in 1986 in Shandong, China. … Read more

Prediction Model for Greenhouse Tomato Growth Based on KNN-SVM Algorithm

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Prediction Model for Greenhouse Tomato Growth Based on KNN-SVM Algorithm

Author：Tang You1,2, Zhang Wei1 Affiliation：1. School of Information and Control Engineering, Jilin Chemical Technology College; 2. School of Electrical and Information Engineering, Jilin Agricultural Science and Technology College Abstract：Tang You, male, from Longjiang, Heilongjiang, professor, PhD, engaged in research on bioinformatics and agricultural informatization. Fund Project：Jilin Provincial Science and Technology Development Plan Project (YDZJ202201ZYTS-692). Source：《Anhui … Read more

Research on PM2.5 Concentration Prediction Model Based on Weighted KNN-BP Neural Network

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Research on PM2.5 Concentration Prediction Model Based on Weighted KNN-BP Neural Network

Source: Journal of Environmental Engineering Technology, January 2019 Issue Authors: Zhao Wenyi, Xia Lisha, Gao Guangkuo, Cheng Li Affiliation: School of Management, University of Shanghai for Science and Technology Funding Projects: National Social Science Fund Project; Shanghai University of Science and Technology Humanities and Social Sciences “Climbing Plan” Project; Shanghai Municipal College Student Innovation and … Read more