检索结果-内蒙古大学图书馆

5th Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2018

作者： Sun, Lu Liang, Yong-quan Fan, Jian-cong Princeton University PrincetonNJ08544 United States College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Provincial Key Laboratory for Information Technology of Wisdom Mining of Shandong Province Shandong University of Science and Technology Qingdao China Provincial Experimental Teaching Demonstration Center of Computer Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9783030037659

The traditional minimum spanning tree clustering algorithm uses a simple Euclidean distance metric method to calculate the distance between two entities. For the processing of noise data, the similarity can’t be well described. In this regard, first of all, we integrate fuzzy set theory to improve, and propose a method with indeterminacy fuzzy distance measurement. In the distance metric method, fuzzy set theory is introduced to measure the differences between two entities. Moreover, the attributes are fuzzy weighted on this basis, which overcomes the shortcomings of the simple Euclidean distance measurement method. So, it not only has a good tolerance for data noise to solve the misclassification of noise information in the actual data, but also takes into account the difference of distinguishability contribution degree of attributes in classification. Thus, the accuracy of clustering is improved, and it also has significance in practical project application. Then, the proposed distance metric is applied into the traditional MST clustering algorithm. Compared with the traditional MST clustering algorithm and other classical clustering algorithms, the results show that the MST algorithm based on the new distance metric is more effective. © Springer Nature Switzerland AG 2019.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

An exponential stability test for a messenger rna–micro rna ode model

引用

UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第4期82卷 11-16页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

In this paper we obtain a numerically tractable test (sufficient condition) for the exponential stability of the unique positive equilibrium point of an ODE system. The result (Theorem 3.1) is based on Lyapunov theory and Linear Ma-trix Inequalities techniques. The ODE model is related to the messengerRNA-microRNA interaction. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： RNA

来源：评论

学校读者我要写书评

暂无评论

An Algorithm for On-Line Image Segmentation of Multiple Paper Defects Based on Fast Two-Dimensional Threshold Method

引用

Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2020年第4期52卷 28-37页

作者： Qu, Yun-Hui Tang, Wei Feng, Bo Department of Electric and Control Engineering Shaanxi University of Science & Technology Shaanxi Xi’an710021 China Computer Teaching and Research Section Xi’an Medical University Shaanxi Xi’an710021 China

The two-dimensional threshold segmentation algorithm is time-consuming and cannot detect multiple paper defects. Considering these problems, a fast two-dimensional threshold method for on-line segmentation of multiple paper defects was proposed. The image subtraction operation was used first to segment the image with multiple paper defects. Then dividing two-dimensional threshold into two one-dimensional thresholds was used to accelerate the segmentation. At the same time, according to the gray distribution characteristics of the paper defect image after subtraction, the search range of the threshold was narrowed, and the selection of the optimal threshold was further accelerated. Experimental results showed that the algorithm proposed in this paper can accurately and quickly detect multiple paper defects, and could be effectively used for real-time detection of the paper production process. © 2020 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Understanding the development of interest and self-efficacy in active-learning undergraduate physics courses

arXiv

引用

arXiv 2022年

作者： Dou, Remy Brewe, Eric Potvin, Geoff Zwolak, Justyna P. Hazari, Zahra Department of Teaching and Learning Florida International University MiamiFL United States STEM Transformation Institute Florida International University MiamiFL United States Department of Physics Drexel University PhiladelphiaPA United States Department of Physics Florida International University MiamiFL United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD United States

Modeling Instruction (MI), an active-learning introductory physics curriculum, has been shown to improve student academic success. Peer-to-peer interactions play a salient role in the MI classroom. Their impact on student interest and self-efficacy – preeminent constructs of various career theories – has not been thoroughly explored. Our examination of three undergraduate MI courses (N = 221) revealed a decrease in students’ physics self-efficacy, physics interest, and general science interest. We found a positive link from physics interest to self-efficacy, and a negative relationship between science interest and self-efficacy. We tested structural equation models confirming that student interactions make positive contributions to self-efficacy. This study frames students’ classroom interactions within broader career theory frameworks and suggests nuanced considerations regarding interest and self-efficacy constructs in the context of undergraduate active-learning science courses. Copyright © 2022, The Authors. All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Web inspection algorithm for low contrast paper defects based on artificial bee colony optimization

引用

Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2020年第2期52卷 43-51页

作者： Qu, Yun-Hui Tang, Wei Feng, Bo Department of Electric and Control Engineering Shaanxi University of Science and Technology Xi'an Shaanxi710021 China Computer Teaching and Research Section Xi'An Medical University Xi'an Shaanxi710021 China

Traditional paper defect detection algorithms have the problems of low detection rate and poor anti-interference ability for low contrast paper defects such as cracks and folds. Considering these problems, an algorithm of low contrast paper defects based on artificial bee colony optimization was presented. Firstly, the Gabor filter was used to eliminate the texture elements and enhance the contrast. Then, the optimal segmentation threshold of 2-D OSTU was obtained by taking the trace of the dispersion matrix of the filtered paper disease image as the objective function of the artificial swarm optimization. Finally, according to the best segmentation threshold, the paper image was detected by 2-D OSTU method. The simulation results indicated that this algorithm has the advantages of high detection rate, accurate positioning and good anti-disturbance performance for low contrast paper defects. © 2020 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Robust Self-Expression Learning with Adaptive Noise Perception

SSRN

引用

SSRN 2023年

作者： Wang, Yangbo Zhou, Jie Lu, Jianglin Wan, Jun Gao, Can Lin, Qingshui College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518060 China SMILE Lab Department of ECE College of Engineering Northeastern University Boston02115 United States School of Information and Safety Engineering Zhongnan University of Economics and Law Wuhan430073 China Basic Teaching Department Liaoning Technical University Huludao125105 China

Self-expression learning methods often obtain a coefficient matrix to measure the similarity between pairs of samples. However, directly using the raw data to represent each sample under the self-expression framework may not be ideal, as noise points are inevitably involved in the process of representing clean samples. To address this issue, this work proposes a novel self-expression model called robust Self-Expression learning with adaptive Noise Perception (SENP). SENP decomposes each sample into a clean part and a noisy part, and samples with large self-expression losses can be recognized as the noise points. A reliable coefficient matrix can then be learned by using only the clean points to reconstruct the clean part of each sample. By simultaneously detecting the noisy part of each sample and noise points, and adaptively mitigating their negative impacts, the representative ability of the generated coefficient matrix is improved. Moreover, inspired by the solution of non-negative matrix factorization (NMF), an effective algorithm is formed to optimize SENP. Extensive experiments on well-known benchmark datasets demonstrate the superiority of SENP compared to several state-of-the-art methods. © 2023, The Authors. All rights reserved.

关键词： Non-negative matrix factorization

来源：评论

学校读者我要写书评

暂无评论

Third-order volterra model based on DUPSO for EEG signal denoising

Third-order volterra model based on DUPSO for EEG signal den...

引用

2019 International Conference on Video, Signal and Image Processing, VSIP 2019

作者： Wu, Xia Zhang, Yumei Wu, Xiaojun Key Laboratory of Modern Teaching Technology Ministry of Education Shaanxi Normal University China School of Computer Science Shaanxi Normal University Shaanxi China

ISBN: (纸本)9781450371483

In order to gain a high-performance analysis for electroencephalogram (EEG) signal, denoising has become a hot topic in this field. Due to the good performance of Volterra model, it has been widely applied to remove the noise in EEG signals. However, the inherent dimensionality problem of Volterra series makes the existing research mostly choose low order Volterra, which will sacrifice some accuracy. In addition, the realistic acquisition of EEG signals cannot satisfy the ideal conditions of phase space reconstruction, which makes it difficult to reconstruct phase space in the analysis process. For the purpose to solve these two questions, we introduce a third-order Volterra filter (TOVF) model to study the denoising problem of EEG and apply a dissipative uniform searching particle swarm optimization (DUPSO) algorithm to optimize the model's coefficients. Then a denoising model based on DUPSO third-order Volterra filter (DUPSO-TOVF) can be obtained. Simulating results show that the DUPSO-TOVF model has a significant increase in the SNR and decrease in the MSE when compared with UPSO second-order Volterra filter (UPSO-SOVF) and PSO-SOVF. Besides, the calculation time of DUPSO-TOVF model is not much different from the two compared models', which means the proposed model not only has the highest precision among the compared models but also can avoid the dimension disaster effectively. © 2019 Association for Computing Machinery.

关键词： Signal denoising

来源：评论

学校读者我要写书评

暂无评论

Icd: A New Interpretable Cognitive Diagnosis Model for Intelligent Tutor Systems

SSRN

引用

SSRN 2022年

作者： Qi, Tianlong Ren, Meirui Guo, Longjiang Li, Xiaokun Li, Jin Zhang, Lichen Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an710062 China Key Laboratory of Intelligent Computing and Service Technology for Folk Song Ministry of Culture and Tourism Xi’an710119 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi’an710119 China School of Computer Science Shaanxi Normal University Xi’an710119 China Xi’an Key Laboratory of Culture Tourism Resources Development and Utilization Xi’an710062 China Postdoctoral Program of Heilongjiang Hengxun Technology Co. Ltd Harbin150090 China

Cognitive diagnosis plays a crucial role in Intelligent Tutor Systems, which aims to diagnose learners' cognitive states according to learners' observable records, such as exercise records. However, this paper observes that the existing cognitive diagnosis models still have rooms for performance improvements: (1) they ignore the interaction between knowledge concepts;(2) they ignore the quantitative relation between exercises and concepts. In order to solve the aforementioned problems, this paper proposes a new interpretable cognitive diagnosis model named ICD based on a novel neural network designed by us, which can conduct answer records with different lengths. The neural network can fully utilize the interaction among concepts, the quantitative relation between exercises and concepts, and considers bias replacement by slip and guess, which makes the ICD more interpretable. The paper has conducted extensive experiments on four real publicity datasets, and the results show that both the performances and the interpretability of ICD are better than the latest state-of-the-art CDMs such as RCD, NCDM, and CDGK, and the classical CDMs such as DINA and MIRT. © 2022, The Authors. All rights reserved.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Time optimal control studies on COVID-19 incorporating adverse events of the antiviral drugs

arXiv

引用

arXiv 2021年

作者： Chhetri, Bishal Bhagat, Vijay M. Muthusamy, Swapna Ananth, V.S. Vamsi, D.K.K. Sanjeevi, Carani B. Department of Mathematics and Computer Science Sri Sathya Sai Institute of Higher Learning Prasanthi Nilayam Puttaparthi Anantapur District Andhra Pradesh515134 India Central Leprosy Teaching and Research Institute CLTRI Chennai India Sri Sathya Sai Institute of Higher Learning SSSIHL India

In this study, we first develop SIV model by incorporating the intercellular time delay and analyze the stability of the equilibrium points. The model dynamics admits disease-free equilibrium and the infected equilibrium with their stability, based on the value of basic reproduction number R0. We then frame an optimal control problem with antiviral drugs and second-line drugs as control measures and study their roles in reducing the infected cell count and the viral load. The comparative study done in the optimal control problem suggests that when the first line antiviral drugs shows adverse events, considering these drugs in reduced quantity along with the second line drug would be highly effective in reducing the infected cell and viral load in a COVID infected patients. Later, we formulate a time-optimal control problem with the objective to drive the system from any given initial state to the desired infection-free equilibrium state in minimal time. Using Pontryagin's Minimum Principle the optimal control strategy is shown to be of bang-bang type with possibility of switches between two extreme values of the optimal controls. Numerically, it is shown that the desired infection-free state is achieved in less time when the higher values of both the optimal controls are chosen. Copyright © 2021, The Authors. All rights reserved.

关键词： Bang bang control systems

来源：评论

学校读者我要写书评

暂无评论

Full spectrum of novelties in time-dependent urn models

引用

Physical Review Research 2025年第2期7卷 023127-023127页

作者： Alessandro Bellina Giordano De Marzo Vittorio Loreto Sapienza University of Rome Physics Department I-00185 Rome Italy Centro Ricerche Enrico Fermi I-00184 Rome Italy Sony Computer Science Laboratories–Rome Joint Initiative CREF-SONY Centro Ricerche Enrico Fermi 00184 Rome Italy Complexity Science Hub Vienna 1080 Vienna Austria Center for Data and Methods University of Konstanz Universitaetstrasse 10 78457 Konstanz Germany

Systems driven by innovation, a pivotal force in human society, present various intriguing statistical regularities, from the Heaps' law to logarithmic scaling or somewhat different patterns for the innovation rates. The urn model with triggering (UMT) has been instrumental in modeling these innovation dynamics. Yet a generalization is needed to capture the richer empirical phenomenology. Here we introduce a time-dependent urn model with triggering (TUMT), a generalization of the UMT that crucially integrates time-dependent parameters for reinforcement and triggering to offer a broader framework for modeling innovation in nonstationary systems. Through analytical computation and numerical simulations, we show that the TUMT reconciles various behaviors observed in a broad spectrum of systems from patenting activity to the analysis of gene mutations. We highlight how the TUMT features a “critical” region where both Heaps' and Zipf's laws coexist, for which we compute the exponents.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：