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Correction: The role of electrochemical biosensors in SARS-CoV-2 detection: a bibliometrics-based analysis and review

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RSC advances 2022年第48期12卷 31441页

作者： Shuduan Mao Li Fu Chengliang Yin Xiaozhu Liu Hassan Karimi-Maleh Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province Interdisciplinary Research Academy (IRA) Zhejiang Shuren University Hangzhou 310015 China. Key Laboratory of Novel Materials for Sensor of Zhejiang Province College of Materials and Environmental Engineering Hangzhou Dianzi University Hangzhou 310018 China fuli@***. National Engineering Laboratory for Medical Big Data Application Technology Chinese PLA General Hospital Beijing China. Medical Big Data Research Center Medical Innovation Research Division of PLA General Hospital Beijing China. Department of Cardiology The Second Affiliated Hospital of Chongqing Medical University Chongqing 400010 China. School of Resources and Environment University of Electronic Science and Technology of China Xiyuan Ave 611731 Chengdu China. Department of Chemical Engineering Quchan University of Technology Quchan *** Iran. Department of Chemical Sciences University of Johannesburg Doornfontein Campus 2028 Johannesburg 17011 South Africa.

[This corrects the article DOI: 10.1039/D2RA04162F.].

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Software Defect Prediction Model Based On KPCA-SVM

Software Defect Prediction Model Based On KPCA-SVM

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Yan Zhou Chun Shan Shiyou Sun Shengjun Wei Sicong Zhang Beijing Key Laboratory of Software Security Engineering Technology School of Computer Science & Technology Beijing Institute of Technology Beijing China China Unicom Big Data Company Limited Beijing China

ISBN: (数字)9781728140346

ISBN: (纸本)9781728140353

Software defect prediction technology mainly relies on machine learning algorithm to learn the measurement data of existing software. There is some redundant data in the measurement element of software defect, which will reduce the accuracy of machine learning algorithm. This paper proposes a software defect prediction model based on ***, the dimension reduction pretreatment of software defect data sets is carried ***, This paper using support vector machines for *** accuracy of the model can be improved by keeping global features in the selection of the dimension reduction ***, the kernel principal component analysis (KPCA) algorithm was selected for dimensionality reduction. For the selection of classification algorithm, this paper considering that the defect prediction data set has small samples and non-linear characteristics, the support vector machine has better advantages in this kind of data set, so SVM is selected as the *** order to verify the performance of this model, this paper adopts the NASA MDP data set which is widely used in the field of software defect *** paper use the CM1, JM1, PC1 and KC1 dataset to contrast KPCA -SVM model with a single SVM and LLE - SVM. This paper proved that KPCA - SVM model can better solve the problem of data redundancy of defect prediction data *** can keep the global characteristics, and can have better prediction precision.

关键词： Support vector machines Predictive models Kernel data models Dimensionality reduction Prediction algorithms

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Geo-spatial ontology matching through compact evolutionary algorithm 2nd

Geo-spatial ontology matching through compact evolutionary a...

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2nd International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2018

作者： Xue, Xingsi Liu, Jianhua College of Information Science and Engineering Fujian University of Technology FuzhouFujian350118 China Intelligent Information Processing Research Center Fujian University of Technology FuzhouFujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology FuzhouFujian350118 China Fujian Key Lab for Automotive Electronics and Electric Drive Fujian University of Technology FuzhouFujian350118 China

ISBN: (纸本)9783030045845

Geo-spatial ontologies can provide a formal description of concepts, relationships, activities, features and rules in GIS domain. However, simply use them only allows to partially solve semantic conflicts, and does not completely solve heterogeneity issues that are caused by themselves. Geo-spatial ontology matching technique can find the correspondences between semantic identical entities, and solve the heterogeneous problem between two geo-spatial ontologies. Be inspired by the successful application of Evolutionary Algorithm (EA) in instance matching domain, in this paper, it is utilized to match the heterogeneous geo-spatial ontologies. To reduce the runtime and memory consumption required by EA, a compact version of it is presented, which does not work on the whole population but a probability representation on it. In addition, a geo-spatial similarity measure is presented to determine the identical geo-spatial entities, and an optimal model is constructed for geo-spatial ontology matching problem. The experimental results show that cEA-based geo-spatial ontology matching technique can efficiently determine the alignment. © Springer Nature Switzerland AG 2019.

关键词： Evolutionary algorithms

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Research on Intelligent Frequency Control of Permanent Magnet Synchronous Motor

Research on Intelligent Frequency Control of Permanent Magne...

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International Conference on Intelligent Computing, Automation and Systems (ICICAS)

作者： Kuo-Chi Chang Zhongxin Hu Kai-Chun Chu Fu-Hsiang Chang Hsiao-Chuan Wang Tsui-Lien Hsu Yuh-Chung Lin Yuwen Zhou Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan North Borneo University College Sabah Malaysia Fujian University of Technology Fuzhou China Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan

The development of PMSM is inseparable from the continuous improvement of the performance-to-price ratio of permanent magnet materials and the development of power electronic equipment. This is exactly the study of PMSM. Entered a new stage, PMSM plays an important role in military, industry and daily life. Dating vector control theory to the field of PMSM speed regulation is also a major breakthrough. Researchers combined the mathematical model of PMSM with the vector control model. It is based on this that the PMSM vector control double closed-loop model was established. Simulate in MATLAB software. There are current module, speed module and PMSM main module in the simulation diagram, and then analyze the simulation results.

关键词： Computational modeling Simulation Software Regulation Power electronics Mathematical model Machine vector control

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ANIMC: A soft approach for auto-weighted noisy and incomplete multi-view clustering

arXiv

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arXiv 2020年

作者： Fang, Xiang Hu, Yuchong Zhou, Pan Wu, Dapeng Oliver Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China School of Computer Science and Technology Key Laboratory of Information Storage System Ministry of Education of China Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Multi-view clustering has wide real-world applications because it can process data from multiple sources. However, these data often contain missing instances and noises, which are ignored by most multi-view clustering methods. Missing instances may make these methods difficult to use directly, and noises will lead to unreliable clustering results. In this paper, we propose a novel Auto-weighted Noisy and Incomplete Multi-view Clustering approach (ANIMC) via a soft auto-weighted strategy and a doubly soft regular regression model. Firstly, by designing adaptive semi-regularized nonnegative matrix factorization (adaptive semi-RNMF), the soft auto-weighted strategy assigns a proper weight to each view and adds a soft boundary to balance the influence of noises and incompleteness. Secondly, by proposing θ-norm, the doubly soft regularized regression model adjusts the sparsity of our model by choosing different θ. Compared with previous methods, ANIMC has three unique advantages: 1) it is a soft algorithm to adjust our approach in different scenarios, thereby improving its generalization ability;2) it automatically learns a proper weight for each view, thereby reducing the influence of noises;3) it performs doubly soft regularized regression that aligns the same instances in different views, thereby decreasing the impact of missing instances. Extensive experimental results demonstrate its superior advantages over other state-of-the-art methods. Impact Statement-As an effective method to process data from multiple sources, multi-view clustering has attracted more and more attention. However, most previous works ignore missing instances and noises in original multi-view data, which limits the applications of these works. By a soft approach, our proposed ANIMC can effectively reduce the negative influence of missing instances and noises. Moreover, ANIMC outperforms the stateof- the-art works by about 20% in representative cases. With satisfactory performance on multiple rea

关键词： Regression analysis

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Properties of SV-Style Homomorphic Encryption and Their Application

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Chinese Journal of Electronics 2017年第5期26卷 926-932页

作者： CHEN Hu HU Yupu LIAN Zhizhu State Key Laboratory of Integrated Service Networks Xidian University Jiangsu Key Laboratory of Education Big Data Science and Engineering Jiangsu Normal University

Several special properties of Smart and Vercauteren’s encryption scheme are put *** are all based on the special parameter,which is a recommended modulus *** properties not only show that the secret key is deduced from an N-dimensional vector into its any entry,but also produce the triplet(grade-i reduced plaintext space,grade-i reduced ciphertext space,grade-i reduced secret key) for each i,where grade-i reduced secret key can decrypt grade-i reduced ciphertexts and can be efficiently computed from grade-i delegated *** the same time,sequentially grade-(i + 1)delegated key can be efficiently computed from grade-i delegated *** work also discusses a sequential computation in opposite direction,i.e.,computing grade-i delegated key from grade-(i + 1) delegated *** the sequential computation in the opposite direction is difficult except at most the first steps of such sequential *** on the properties given,we then propose a simple hierarchical encryption scheme with relatively small key and ciphertext sizes.

关键词： Lattice-based cryptosystem Fully homomorphic encryption Hierarchical encryption

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Ghost imaging based on Y-net: A dynamic coding and conjugate-decoding approach

arXiv

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arXiv 2020年

作者： Zhu, Ruiguo Yu, Hong Tan, Zhijie Lu, Ronghua Han, Shensheng Huang, Zengfeng Wang, Jian Key Laboratory for Quantum Optics Center for Cold Atom Physics of CAS Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing10049 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou310024 School of Data Science Fudan-Xinzailing Joint Research Centre for Big Data Fudan University Shanghai200433 China

Ghost imaging incorporating deep learning technology has recently attracted much attention in the optical imaging field. However, deterministic illumination and multiple exposure are still essential in most scenarios. Here we propose a ghost imaging scheme based on a novel conjugate-decoding deep learning framework (Y-net), which works well under both deterministic and indeterministic illumination. Benefited from the end-to-end characteristic of our network, the image of a sample can be achieved directly from a pair of correlated speckles collected by the detectors, and the sample is illuminated only once in the experiment. The spatial distribution of the speckles encoding the sample in the experiment can be completely different from that of the simulation speckles for training, as long as the statistical characteristics of the speckles remain unchanged. This approach is particularly important to high-resolution x-ray ghost imaging applications due to its potential for improving image quality and reducing radiation damage. And the idea of conjugate-decoding network may also be applied to other learning-based imaging. Copyright © 2020, The Authors. All rights reserved.

关键词： Decoding

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Threshold and Deadline Effect in Crowdfunding

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Procedia Computer Science 2019年 162卷 339-346页

作者： Yan Song Xin Tian Chunlin Luo Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190China School of Information Technology Jiangxi University of Finance and Economics Nanchang Jiangxi 330013China

The deadline effect and threshold effect are common in product development and group buying. We consider these two effects also exist in crowdfunding, affecting the crowdfunding performance in the future. We conduct an empirical study using a dataset from *** to examine these two effects and their interactive relationship on the following crowdfunding performance. We find the threshold effect exists in crowdfunding and has a positive influence on the following contribution behaviour. The deadline effect also can stimulate the crowdfunding behaviour via limited fundraising time. Furthermore, we find the threshold effect and deadline effect are complements that increase the amount pledged.

关键词： crowdfunding performance threshold effect deadline effect interactive effect

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An Integrated Semantic-Syntactic SBLSTM Model for Aspect Specific Opinion Extraction 15th

An Integrated Semantic-Syntactic SBLSTM Model for Aspect Spe...

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15th Web Information Systems and Applications Conference, WISA 2018

作者： Han, Zhongming Jiang, Xin Li, Mengqi Zhang, Mengmei Duan, Dagao School of Computer and Information Engineering Beijing Technology and Business University Beijing100048 China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing China

ISBN: (纸本)9783030029333

Opinion Mining (OM) of Internet reviews is one of the key issues in Natural Language Processing (NLP) field. This paper proposes a stacked Bi-LSTM aspect opinion extraction model in which semantic and syntactic features are both integrated. The model takes embedded vector which is composed by word embedding, POS tags and dependency relations as its input while taking label sequence as its output. The experimental results show the effectiveness of this structural features embedded stacked Bi-LSTM model on cross-domain and cross-language datasets, and indicate that this model outperforms the state-of-the-art methods. © 2018, Springer Nature Switzerland AG.

关键词： Syntactics

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Leveled Homomorphic Encryption in Certificateless Cryptosystem

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Chinese Journal of Electronics 2017年第6期26卷 1213-1220页

To lower communication complexity, a Certificateless homomorphic encryption(CLHE) scheme based on the Learning with errors(LWE) problem is constructed by introducing a new technique called probabilistic encoding with weakly homomorphic property. This technique can conveniently convert an intended message into two elements in a ring, which will be respectively encrypted under both public keys of a user in certificateless *** knowing both elements simultaneously, the original message can be easily recovered. It is hidden perfectly by the probabilistic property of encoding. This CLHE removes evaluation keys by using the approximate eigenvector method given by Gentry et al., which makes it into a pure CLHE. It is proven to be semantic secure in the Random oracle model(ROM). The results indicate it is able to homomorphically evaluate any functions in a class functions with given multiplicative depth L.

关键词： Certificateless cryptosystem Lattice cryptography Fully homomorphic encryption Learning with errors Random oracle model

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