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作者： Nabiaek, M. Postawa, P. Pietrusiewicz, P. Razak, K.A. Walters, S. Stambuaa, S. Jez, B. Department of Physics Faculty of Production Engineering and Materials Technology Czestochowa University of Technology al. Armii Krajowej 19 Czestochowa42-200 Poland Department of Technology and Automation Faculty of Mechanical Engineering and Computer Science Czestochowa University of Technology al. Armii Krajowej 19c Czestochowa42-200 Poland Center of Excellence Geopolymer and Green Technology Universiti Malaysia Perlis TamanMuhibbah Arau Perlis02600 Malaysia Advanced Engineering Centre University of Brighton BrightonBN2 4GJ United Kingdom

Structural relaxations play a large role in forming the properties of magnetic materials. In amorphous alloys, which are metastable materials, obtaining a relatively stable structure requires a properly designed thermal treatment process. Samples should be annealed above the Curie temperature and below the crystallization temperature. With the process designed in such a way, the domain structure is not interfered with and the formation of crystal grains does not occur. By analyzing the so-called Holstein-Primakoff paraprocess, it is possible to determine the in uence of magnetic atoms on the magnetization process in strong magnetic elds above the eld of effective anisotropy. © 2025 Polska Akademia Nauk. All rights reserved.

关键词： Amorphous alloys

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The stratified K-folds cross-validation and class-balancing methods with high-performance ensemble classifiers for breast cancer classification

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Healthcare Analytics 2023年 4卷 100247-100247页

作者： T R, Mahesh V, Vinoth Kumar V, Dhilip Kumar Geman, Oana Margala, Martin Guduri, Manisha Department of Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore 562112 India School of Computer Science Engineering & Information Systems (SCORE) Vellore Institute of Technology (VIT) 632014 India School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai 600062 India Department of Computers Electronics and Automation Faculty of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava 720229 Romania School of Computing and Informatics University of Louisiana at Lafayette United States

Breast cancer is one of the most common causes of death among women, and early diagnosis is vital for reducing the fatality rate. This study evaluates the most widely used machine-learning breast cancer prediction and diagnosis methods. We use synthetic minority over-sampling to handle imbalanced data in the breast cancer diagnosis dataset obtained from the Wisconsin Machine Learning Repository. We use a variety of machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Classification and Regression Tree (CART), Naive Bayes (NB), and well-known ensembles methods like Majority-Voting, eXtreme Gradient Boosting algorithm (XGBoost), and Random Forest (RF) for the breast cancer classification. The findings show that the Majority-Voting ensemble method, built on the top three classifiers (LR, SVM, and CART), outperforms all other individual classifiers and offers the highest accuracy of 99.3%. © 2023 The Author(s)

关键词： Breast cancer Class-balancing Cross-validation Diagnostic analytics Ensemble method Machine learning

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Essential proteins identification based on weak consensus model and neighborhood aggregation centrality

Essential proteins identification based on weak consensus mo...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Zhipeng Hu Gaoshi Li Jingli Wu Xinlong Luo Jiafei Liu Wei Peng Xiaoshu Zhu Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin China Guangxi Key Lab of Multi-Source Information Mining & Security Guangxi Normal University Guilin China College of Computer Science and Engineering Guangxi Normal University Guilin China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China School of Computer and Information Security & School of Software Engineering Guilin University of Electronic Science and Technology Guilin China

Essential proteins play an essential role in cell survival and replication. Currently, more and more computational methods are developed to identify essential proteins, which overcome the time-consuming, costly and inefficient shortcomings with biological experimental methods. In order to improve the recognition rate, some new methods by fusing multiple features are developed, but they seldom consider the connection among features. After analyzing a large number of methods based on multi-feature fusion, a weak consensus model to fuse features is proposed in this paper. Then, this paper uses the weak consensus model to fuse protein-protein interaction network, gene expression data, and orthologous data, thus proposing a new method, WOL. Then experiments are performed on one *** dataset. The results show that compared with WDC, PeC, ION, JDC, NCCO and E_POC, WOL has a higher recognition rate.

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Jet mixing enhancement with Bayesian optimization, deep learning, and persistent data topology

arXiv

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arXiv 2023年

作者： Li, Yiqing Noack, Bernd R. Wang, Tianyu Cornejo Maceda, Guy Y. Pickering, Ethan Shaqarin, Tamir Tyliszczak, Artur School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen518055 China Department of Mechanical Engineering Tafila Technical University Tafila66110 Jordan Faculty of Mechanical Engineering and Computer Science Czestochowa University of Technology Czestochowa42-201 Poland

We optimize the jet mixing using large eddy simulations (LES) at a Reynolds number of 3000. Key methodological enablers consist of Bayesian optimization, a surrogate model enhanced by deep learning, and persistent data topology for physical interpretation. The mixing performance is characterized by an equivalent jet radius (Req) derived from the streamwise velocity in a plane located 8 diameters downstream. The optimization is performed in a 22-dimensional actuation space that comprises most known excitations. The plant benefits from a 22-dimensional actuation space that comprises most known excitations. This search space parameterizes distributed actuation imposed on the bulk flow and at the periphery of the nozzle in the streamwise and radial directions. The momentum flux measures the energy input of the actuation. The optimization quadruples the jet radius Req with a 7-armed blooming jet after around 570 evaluations. The control input requires 2% momentum flux of the main flow, which is one order of magnitude lower than an ad hoc dual-mode excitation. Intriguingly, a pronounced suboptimum in the search space is associated with a double-helix jet, a new flow pattern. This jet pattern results in a mixing improvement comparable to the blooming jet. A state-of-the-art Bayesian optimization converges towards this double helix solution. The learning is accelerated and converges to another better optimum by including surrogate model trained along the optimization. Persistent data topology extracts the global and many local minima in the actuation space. These minima can be identified with flow patterns beneficial to the mixing. © 2023, CC BY-NC-ND.

关键词： Flow patterns

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UGNA-VPR: A Novel Training Paradigm for Visual Place Recognition Based on Uncertainty-Guided NeRF Augmentation

arXiv

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arXiv 2025年

作者： Shen, Yehui Zhang, Lei Li, Qingqiu Zhao, Xiongwei Wang, Yue Lu, Huimin Chen, Xieyuanli College of Intelligence Science and Technology National University of Defense Technology China Faculty of Robot Science and Engineering Northeastern University China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University China SIASUN Robot& Automation Co. Ltd China School of Computer Science Fudan University China

Visual place recognition (VPR) is crucial for robots to identify previously visited locations, playing an important role in autonomous navigation in both indoor and outdoor environments. However, most existing VPR datasets are limited to single-viewpoint scenarios, leading to reduced recognition accuracy, particularly in multi-directional driving or feature-sparse scenes. Moreover, obtaining additional data to mitigate these limitations is often expensive. This paper introduces a novel training paradigm to improve the performance of existing VPR networks by enhancing multi-view diversity within current datasets through uncertainty estimation and NeRF-based data augmentation. Specifically, we initially train NeRF using the existing VPR dataset. Then, our devised self-supervised uncertainty estimation network identifies places with high uncertainty. The poses of these uncertain places are input into NeRF to generate new synthetic observations for further training of VPR networks. Additionally, we propose an improved storage method for efficient organization of augmented and original training data. We conducted extensive experiments on three datasets and tested three different VPR backbone networks. The results demonstrate that our proposed training paradigm significantly improves VPR performance by fully utilizing existing data, outperforming other training approaches. We further validated the effectiveness of our approach on self-recorded indoor and outdoor datasets, consistently demonstrating superior results. Our dataset and code have been released at https://***/nubot-nudt/UGNA-VPR. Copyright © 2025, The Authors. All rights reserved.

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A loading path planning method for co-loading in automatic harvesting system

A loading path planning method for co-loading in automatic h...

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International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Xiaoxiong Wang Zhuo Wang Xiaoping Bai Zhikang Ge Jian Wang Zhihong Man Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Faculty of Science Engineering and Technology Swinburne University of Technology Melbourne Australia

In this paper, a path planning method is developed for co-loading in master-slave automatic harvesting. It is shown that, the adjustment of the unloading port position relative to the grain tank can be performed jointly by the longitudinal relative position between the vehicles and the angle of the unloading arm. Then the loading path based on the Hamiltonian circuit is designed to guide the motion of the unloading port during the loading process. By improving the loading uniformity, the loading path proposed can maximize the capacity utilization of grain tank which can reduce the round-trip frequency of the transport vehicle and improve the energy and time efficiency of the harvesting operation. Simulation results are provided to validate the excellent performance of presented path planning method.

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Lyapunov-Function Based Control Technique for a Single-Phase Grid-Connected Five-Level Active Neutral Point Clamped Flying Capacitor Inverter with LCL Filter

Lyapunov-Function Based Control Technique for a Single-Phase...

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Compatibility in Power Electronics (CPE)

作者： Ugur Fesli Sertac Bayhan Naki Guler Hasan Komurcugil Electronic and Automation Department Technical Sciences Vocational School Gazi University Ankara Turkey Qatar Environment and Energy Research Institute Hamad Bin Khalifa University Doha Qatar Department of Electrical-Electronic Engineering Technology Faculty Gazi University Ankara Turkey Department of Computer Engineering Eastern Mediterranean University Via Mersin 10 Famagusta Turkey

This paper presents Lyapunov-function based control technique for a grid-connected five-level active neutral point clamped flying capacitor (ANPC-FC) inverter with LCL filter. The control technique used in this study ensures global stability of the closed-loop system and almost zero steady-state error in the grid current. A proportional resonant (PR) controller is also employed in the control scheme to generate the required reference value for the inverter current. In addition, a simple phase shift pulse width modulation (PSPWM) technique is used for resolving voltage imbalances between dc-link capacitors and floating capacitors without the use of complicated circuitry or sensors. Simulation results validate the performance of the proposed system. Studies conducted at steady state and in dynamic mode demonstrate excellent results.

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Innovation Approaches in CAD Systems Training Program

Innovation Approaches in CAD Systems Training Program

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Electronic engineering, Information Technology & Education (EEITE), International Conference in

作者： Volodymyr Shanaida Valeriy Lazaryuk Andrii Blavitskyi Justyna Żylińska Stanisłw Tkaczyk Volodymyr Hutsaylyuk Design of Machine Tools Instruments and Machines Department Ternopil Ivan Puluj National Technical University Ternopil Ternopil Ukraine Department of Mechanical Engineering Technology Ternopil Ivan Puluj National Technical University Ternopil Ukraine Department Automation and Computer integrated Technologies Ternopil Ivan Puluj NationalTechnical University Ternopil Ternopil Ukraine Faculty of Management and Logistics Helena Chodkowska University of Technology and Economics Warsaw Poland Faculty of Engineering Helena Chodkowska University of Technology and Economics Warsaw Warsaw Poland

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

The advancements in information technology and computer-aided design have paved the way for virtual modeling and exploration of real-life objects. In the realm of CAD systems, there are subgroups of specialized software (CADCAM- CAE systems) that are designed to accomplish specific object-oriented tasks. Such software is primarily used for mathematical computations, analytic studies of schematic technical objects, and 2D and 3D systems for engineering design practices.

关键词： Training Technological innovation Solid modeling Three-dimensional displays Object oriented modeling Software algorithms Solids

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A Robust Adaptive Terminal Sliding Mode Control for Lane-keeping in Road Vehicles

A Robust Adaptive Terminal Sliding Mode Control for Lane-kee...

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International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Zhikang Ge Zhuo Wang Xiaoping Bai Xiaoxiong Wang Zhihong Man Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Faculty of Science Engineering and Technology Swinburne University of Technology Melbourne Australia

In this paper, a novel adaptive terminal sliding-mode control (ATSMC) method is developed for road vehicles with uncertain dynamics. It is shown that the designed adaptive laws can recursively update the controller parameters based on the estimation values of the unknown parameter bound in the Lyapunov sense, and then the lateral position error can be driven to zero in a finite time. In comparison to the conventional sliding-mode-based vehicle lateral control method, the proposed ATSMC not only ensures fast error convergence, but also eliminates the requirement for known bounded information in controller design. Simulation results are presented to demonstrate the good performance of the proposed ATSMC scheme.

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Practical Aspects of Creating a Teacher's Information Space 5

Practical Aspects of Creating a Teacher's Information Space

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5th International Conference on Information Technologies in engineering Education, Inforino 2020

作者： Muzyleva, Inna Yazykova, Liubov Martynova, Anzhelika Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia Lipetsk State Technical University Institute of Mechanical Engineering Lipetsk Russia

ISBN: (纸本)9781728148106

The article discusses one of the aspects of digitalization of education, in terms of digitalization of the educational process itself. The methodology of creating a personal information space of a teacher is presented. The form of this space is a teaching site with teaching materials. A method for structuring methodological content is proposed. The methodology of posting structured content on a WordPress blog is described. A method for creating media content for special disciplines of technical areas of training is considered. The analysis of educational video content presented on the Internet is carried out. A step-by-step methodology for creating a video lesson in the Camtasia Studio program based on the Power Point presentation is described. There is an example of its application, successfully implemented in the educational process. © 2020 IEEE.

关键词： Studios

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