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Practical fuzzy model approach for asymmetrical V-shaped microshield line by CADMFILT software

INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2021年第3期31卷

作者： Karpuz, Ceyhun Inan, Onur Urhan, Mehmet Pamukkale Univ Dept Elect & Elect Engn TR-20070 Denizli Turkey Mehmet Akif Ersoy Univ Bucak Emin Gulmez Tech Sci Vocat Sch Dept Biomed Device Technol Bucak Turkey

In this paper, practical fuzzy models depending on subtractive fuzzy clustering have been presented for asymmetrical V-shaped microshield line. In addition, a packet program has been introduced to run the proposed fuzzy models. In order to calculate the electrical parameters of each model, a linear equation system has been formed in each fuzzy model. Finally, the coefficients of each equation system have been found by means of fuzzy rules obtained by cluster extraction. The accuracy of each model has been confirmed by error analysis and the validity of the model results has been proven by comparing with the results of the quasi-static approach. At last, an object-oriented package program including theoretical solutions and fuzzy modeling has been presented. This computer-aided design program can be used for analysis, synthesis and modeling of transmission lines and microwave filters. It has been developed to calculate design processes with high speed and accuracy for researchers. It is expected that the introduced package program could be an alternative to commercial programs in the relevant field.

关键词： clustering algorithm fuzzy inference system fuzzy modeling software packages V-shaped microshield lines

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Research on optimization of setup time for product in the multi-product production system

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MICROPROCESSORS AND MICROSYSTEMS 2021年 80卷

作者： Li, Xiaoyan Tongji Univ Coll Econ & Management Shanghai Peoples R China

Consumers' consumption habits are more and more personalized and diversified, which makes the multi-product production system has been applied extensively in the factory worldwide. This brings a difficult problem to a large number of manufacturing enterprises: how to optimize the setup time of the product to achieve the purpose of improving the time efficiency. Based on this problem, this paper proposes the TCP technology for the optimization of setup time, that is, using the Times Series model, the clustering algorithm, and the Parallel Job technology in the Single Minute Exchange of Die (SMED), to form an application framework focusing on optimizing the product setup time. The validity of the technology is verified by a case study. This paper enriches the research field of setup time optimization, production planning, and the application of the clustering algorithm in the multi-product production system. It provides a new way for manufacturing enterprises to pursue an excellent efficiency of product setup time.

关键词： Multi-product production system Setup time clustering algorithm Time efficiency improvement

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Automated real-space lattice extraction for atomic force microscopy images

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MACHINE LEARNING-SCIENCE AND TECHNOLOGY 2023年第1期4卷 015015-015015页

作者： Corrias, Marco Papa, Lorenzo Sokolovic, Igor Birschitzky, Viktor Gorfer, Alexander Setvin, Martin Schmid, Michael Diebold, Ulrike Reticcioli, Michele Franchini, Cesare Univ Vienna Fac Phys Ctr Computat Mat Sci Kolingasse 14-16 A-1090 Vienna Austria Univ Vienna Vienna Doctoral Sch Phys Boltzmanngasse 5 A-1090 Vienna Austria TU Wien Inst Appl Phys Wiedner Hauptstr 8-10-134 A-1040 Vienna Austria Charles Univ Prague Fac Math & Phys Dept Surface & Plasma Sci 5 Holesovickach 2 Prague 8 18000 Czech Republic Univ Bologna Dipartimento Fis & Astron I-40127 Bologna Italy

Analyzing atomically resolved images is a time-consuming process requiring solid experience and substantial human intervention. In addition, the acquired images contain a large amount of information such as crystal structure, presence and distribution of defects, and formation of domains, which need to be resolved to understand a material's surface structure. Therefore, machine learning techniques have been applied in scanning probe and electron microscopies during the last years, aiming for automatized and efficient image analysis. This work introduces a free and open source tool (AiSurf: Automated Identification of Surface Images) developed to inspect atomically resolved images via scale-invariant feature transform and clustering algorithms. AiSurf extracts primitive lattice vectors, unit cells, and structural distortions from the original image, with no pre-assumption on the lattice and minimal user intervention. The method is applied to various atomically resolved non-contact atomic force microscopy images of selected surfaces with different levels of complexity: anatase TiO2(101), oxygen deficient rutile TiO2(110) with and without CO adsorbates, SrTiO3(001) with Sr vacancies and graphene with C vacancies. The code delivers excellent results and is tested against atom misclassification and artifacts, thereby facilitating the interpretation of scanning probe microscopy images.

关键词： machine learning clustering algorithm unsupervised learning computer vision atomic force microscopy scanning probe microscopy surface science

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Robust and interpretable mineral identification using laser-induced breakdown spectroscopy mapping

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SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY 2023年 206卷

作者： Capela, Diana Ferreira, Miguel F. S. Lima, Alexandre Dias, Filipa Guimara, Diana Jorge, Pedro A. S. Silva, Nuno A. INESC TEC Ctr Appl Photon Rua Campo Alegre 687 P-4169007 Porto Portugal Univ Porto Fac Ciencias Dept Fis & Astron Rua Campo Alegre 687 P-4169007 Porto Portugal Univ Porto Fac Ciencias Dept Geociencias Ambiente & Ordenamento Terr Rua Campo Alegre 687 P-4169007 Porto Portugal Pole Univ Porto ICT Inst Earth Sci P-4169007 Porto Portugal

Fast and precise identification of minerals in geological samples is of paramount importance for the study of rock constituents and for technological applications in the context of mining. However, analyzing samples based only on the extrinsic properties of the minerals such as color can often be insufficient, making additional analysis crucial to improve the accuracy of the methods. In this context, Laser-induced breakdown spectroscopy mapping is an interesting technique to perform the study of the distribution of the chemical elements in sample surfaces, thus allowing deeper insights to help the process of mineral identification. In this work, we present the development and deployment of a processing pipeline and algorithm to identify spatial regions of the same mineralogical composition through chemical information in a fast and automatic way. Furthermore, by providing the necessary labels to the results on a training sample, we can turn this unsupervised methodology into a classifier that can be used to generalize and classify minerals in similar but unseen samples. The results obtained show good accuracy in reproducing the expected mineral regions and extend the interpretability of previous unsupervised methods with a visualization tool for cluster assignment, thus paving for future applications in contexts requiring high-throughput mineral identification systems, such as mining.

关键词： LIBS Mineral identification Mapping clustering algorithm

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CH-Bin: A convex hull based approach for binning metagenomic contigs

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COMPUTATIONAL BIOLOGY AND CHEMISTRY 2022年 100卷 107734页

作者： Chandrasiri, Sunera Perera, Thumula Dilhara, Anjala Perera, Indika Mallawaarachchi, Vijini Univ Moratuwa Dept Comp Sci & Engn Moratuwa 10400 Sri Lanka Australian Natl Univ Sch Comp Canberra ACT 2600 Australia Flinders Univ S Australia Flinders Accelerator Microbiome Explorat Bedford Pk SA 5042 Australia

Metagenomics has enabled culture-independent analysis of micro-organisms present in environmental samples. Metagenomics binning, which involves the grouping of contigs into bins that represent different taxonomic groups, is an important step of a typical metagenomic workflow followed after assembly. The majority of the metagenomic binning tools represent the composition and coverage information of contigs as feature vectors consisting of a large number of dimensions. However, these tools use traditional Euclidean distance or Manhattan distance metrics which become unreliable in the high dimensional space. We propose CH-Bin, a binning approach that leverages the benefits of using convex hull distance for binning contigs represented by high dimensional feature vectors. We demonstrate using experimental evidence on simulated and real datasets that the use of high dimensional feature vectors to represent contigs can preserve additional information, and result in improved binning results. We further demonstrate that the convex hull distance based binning approach can be effectively utilized in binning such high dimensional data. To the best of our knowledge, this is the first time that composition information from oligonucleotides of multiple sizes has been used in representing the composition information of contigs and a convex hull distance based binning algorithm has been used to bin metagenomic contigs. The source code of CH-Bin is available at https://***/kdsuneraavinash/CH-Bin.

关键词： Convex hull Convex hull distance Metagenomic binning Multiple k values High dimensional data clustering clustering algorithm

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Stochastic Economic Dispatching Strategy of the Active Distribution Network Based on Comprehensive Typical Scenario Set

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IEEE ACCESS 2020年 8卷 201147-201157页

作者： Zhu, Huimin Yuan, Shun Li, Chunlai Shenyang Univ Technol Sch Elect Engn Shenyang 110870 Peoples R China

The increasing penetration of renewable energy resources in the distribution network has posed great uncertainties and challenges for the system security operation. To model various uncertain factors like the wholesale market price and renewable energy generation in the active distribution network (ADN), a similarity measurement method considering the amplitude, volatility and variation trend is proposed. The Latin hypercube sampling method and Graph Pyramid clustering algorithm are adopted to obtain the comprehensive typical scenario set. Furthermore, this study proposes a scenario-based stochastic day-ahead optimal economic dispatch approach based on typical scenario set. The energy trading between the distribution system and the wholesale energy market, various distributed generators, network topology and power flow model are jointly formulated in the proposed operation model. The effectiveness and scalability of the proposed approach are verified using the IEEE 33-bus system. Numerical simulation results under different implementation scenarios indicate that the proposed approach offers a high computational efficiency and promotes the security and economy of the distribution system operation, which has a promising industrial application value.

关键词： Active distribution network renewable energy resources stochastic optimization clustering algorithm typical scenario set

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A Single-Image Noise Estimation algorithm Based on Pixel-Level Low-Rank Low-Texture Patch and Principal Component Analysis

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SENSORS 2022年第22期22卷 8899页

作者： Li, Yong Liu, Chenguang You, Xiaoyu Liu, Jian Harbin Inst Technol Res Ctr Adv Microscopy & Instrumentat Harbin 150001 Peoples R China Harbin Inst Technol Res Ctr Basic Space Sci Harbin 150001 Peoples R China

Noise level is an important parameter for image denoising in many image-processing applications. We propose a noise estimation algorithm based on pixel-level low-rank, low-texture subblocks and principal component analysis for white Gaussian noise. First, an adaptive clustering algorithm, based on a dichotomy merge, adaptive pixel-level low-rank matrix construction method and a gradient covariance low-texture subblock selection method, is proposed to construct a pixel-level low-rank, low-texture subblock matrix. The adaptive clustering algorithm can improve the low-rank property of the constructed matrix and reduce the content of the image information in the eigenvalues of the matrix. Then, an eigenvalue selection method is proposed to eliminate matrix eigenvalues representing the image to avoid an inaccurate estimation of the noise level caused by using the minimum eigenvalue. The experimental results show that, compared with existing state-of-the-art methods, our proposed algorithm has, in most cases, the highest accuracy and robustness of noise level estimation for various scenarios with different noise levels, especially when the noise is high.

关键词： image processing image denoising noise level white Gaussian noise clustering algorithm

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Collaborative Evaluation Method of Multiple Team Membership: Case Study of Engineering Design Company

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JOURNAL OF MANAGEMENT IN ENGINEERING 2022年第6期38卷

作者： Jiang, Qi Qiang, Maoshan Lin, Chen Tsinghua Univ State Key Lab Hydrosci & Engn Inst Project Management & Construct Technol Beijing 100084 Peoples R China Beijing Inst Water Dept Technol & Qual Management Landscape Architecture Beijing 100048 Peoples R China

Team members' project collaborative process evaluation is the key link to improve the management effectiveness of an organization. However, there is a lack of evaluation methods from the perspective of multiple team membership (MTM). Based on the data in the project management system (PMS) of engineering design enterprises, this article studies the project participation evaluation method of team members from the perspective of MTM. Using a clustering algorithm, this article developed and verified the participation evaluation index of single projects and multiple projects, a classification and statistics method, and the centrality evaluation method of team members. The research revealed the distribution law of MTM quantity and the influence of team members' knowledge and ability on it. We found that this index can evaluate objectively team members' project participation, which can divided into three levels: high, medium, and low. Collaborative activities that contribute significantly to the project account for 20% of the total. The reasonable range for team members to invest in high participation projects is from 2 to 4. For medium participation projects, the number is from 6 to 8. For low participation projects, the number is from 18 to 25, or even unlimited. This study found four positive and four negative effects of personal characteristics on work efficiency. When individuals have these characteristics, team members can better play to their abilities under the project management mechanism, which provides a reference for enterprises to identify and cultivate team members.

关键词： Multiple team membership (MTM) Project participation Collaborative evaluation method clustering algorithm

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Free-Form Surface Partitioning and Simulation Verification Based on Surface Curvature

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MICROMACHINES 2022年第12期13卷

作者： Liu, Hongwei Zhang, Enzhong Sun, Ruiyang Gao, Wenhui Fu, Zheng Changchun Univ Technol Sch Mechatron Engn Changchun 130012 Peoples R China

To address the problem of low overall machining efficiency of free-form surfaces and difficulty in ensuring machining quality, this paper proposes a MATLAB-based free-form surface division method. The surface division is divided into two stages: Partition area identification and area boundary determination. In the first stage, the free-form surface is roughly divided into convex, concave, and saddle regions according to the curvature of the surface, and then the regions are subdivided based on the fuzzy c-means clustering algorithm. In the second stage, according to the clustering results, the Voronoi diagram algorithm is used to finally determine the boundary of the surface patch. We used NURBS to describe free-form surfaces and edit a set of MATLAB programs to realize the division of surfaces. The proposed method can easily and quickly divide the surface area, and the simulation results show that the proposed method can shorten machining time by 36% compared with the traditional machining method. It is proved that the method is practical and can effectively improve the machining efficiency and quality of complex surfaces.

关键词： regional division free-form surface surface curvature clustering algorithm Voronoi diagrams

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Cluster-CAM: Cluster-weighted visual interpretation of CNNs' decision in classification

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NEURAL NETWORKS 2024年 178卷 106473页

作者： Feng, Zhenpeng Ji, Hongbing Dakovic, Milos Cui, Xiyang Zhu, Mingzhe Stankovic, Ljubisa Xidian Univ Sch Elect Engn Xian Peoples R China Xidian Univ Sch Elect Engn Kunshan Innovat Inst Xian Peoples R China Univ Montenegro Fac Elect Engn Podgorica Montenegro

Despite the tremendous success of convolutional neural networks (CNNs) in computer vision, the mechanism of CNNs still lacks clear interpretation. Currently, class activation mapping (CAM), a famous visualization technique to interpret CNN's decision, has drawn increasing attention. Gradient -based CAMs are efficient, while the performance is heavily affected by gradient vanishing and exploding. In contrast, gradient -free CAMs can avoid computing gradients to produce more understandable results. However, they are quite time-consuming because hundreds of forward interference per image are required. In this paper, we proposed Cluster -CAM, an effective and efficient gradient -free CNN interpretation algorithm. Cluster -CAM can significantly reduce the times of forward propagation by splitting the feature maps into clusters. Furthermore, we propose an artful strategy to forge a cognition -base map and cognition -scissors from clustered feature maps. The final salience heatmap will be produced by merging the above cognition maps. Qualitative results conspicuously show that Cluster -CAM can produce heatmaps where the highlighted regions match the human's cognition more precisely than existing CAMs. The quantitative evaluation further demonstrates the superiority of Cluster -CAM in both effectiveness and efficiency.

关键词： Explainable artificial intelligence Class activation mapping clustering algorithm Image classification

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