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arXiv 2025年

作者： Li, Zi Yang, Fan Yang, Qingcheng Shanghai Key Laboratory of Mechanics in Energy Engineering School of Mechanics and Engineering Science Shanghai Institute of Applied Mathematics and Mechanics Shanghai University Shanghai China School of Aerospace Engineering and Applied Mechanics Tongji University Shanghai China Key Laboratory of AI-Aided Airworthiness of Civil Aircraft Structures Civil Aviation Administration of China Tongji University Shanghai China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Dalian China Shanghai Institute of Aircraft Mechanics and Control Shanghai China

To mitigate the substantial computational costs associated with modeling the mechanical behavior of large-scale architected lattice structures, this work introduces a concurrent multiscale approach: the Generalized Non-local Quasicontinuum (GNQC) method. GNQC generalizes the classical nonlocal Quasicontinuum framework by eliminating the assumption of affine or high-order deformation patterns for accurate energy sampling in coarse-grained regions and by ensuring consistency with general finite element shape functions used for coarse-graining. The introduced GNQC method offers three key features: (1) a constitutive-model-consistent framework that employs the same lattice constitutive relationship in both the locally full-resolution region and the coarse-grained domain, similar to existing nonlocal QC approaches;(2) a shape-function consistent energy sampling mechanism that aligns with the interpolation order of the generally employed shape functions, differing significantly from existing Quasicontinuum works and substantially reducing computational costs;and (3) consistent interfacial compatibility, which enables seamless energy and force transfer across interfaces between regions of different resolutions without cumbersome interfacial treatments. The performance of GNQC is validated through a series of numerical test cases—including tension, clamped bending, three-point bending, and crack propagation problems—that demonstrate good accuracy. Additionally, the error analysis and convergence behavior of GNQC are investigated. Copyright © 2025, The Authors. All rights reserved.

关键词： Constitutive models

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A Crossover Algebra for Solving Minimum Spanning Tree in Network Design with Diameter Constraints

A Crossover Algebra for Solving Minimum Spanning Tree in Net...

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作者： Ziyi Wang Kai Shi Fuqiang Qiao Huanran Li School of Computer Science and Engineering Tianjin University of Technology College of Software and Communications Tianjin Sino-German University of Applied Sciences Tianjin

The minimum spanning tree problem with diameter constraint is an important problem for many applications such as network design and reliability. The diameter constraint makes it be different from the common minimum spanning tree problem, it is difficult to get the optimal solution, even the feasible solution can not be obtained by the traditional method. To address this problem, in this paper, a new crossover algebra is designed to ensure that the crossover tree still satisfies the diameter constraint. During the crossover process, structure of the subtree will be retained, thus avoiding the problem that the new generated tree is not a feasible solution. Experimental results show the effectiveness of the improved algorithm.

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Optimization Design and Implementation of Intelligent Diagnosis System for AFC Equipment Fault Detection

Optimization Design and Implementation of Intelligent Diagno...

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作者： Zhao-cheng WANG School of Software and Applied Science and Technology Zhengzhou University

In view of the problems faced by the operation and maintenance of subway AFC system, such as the distribution of stations, the large number of equipment repairs and the difficulty of fault analysis and diagnosis. On the basis of the research and analysis, taking the operation and maintenance services as the main line, taking the parameters such as influencing the service life and maintenance cycle of the main equipment components of AFC as the characteristic data, and based on the optimization model of the combination of BP neural network and genetic algorithm. After simulation verification, an intelligent fault detection diagnosis system is designed and implemented. It has high application value in system optimization design, equipment physical quantity characteristic detection and intelligent diagnosis, and also has a certain reference guidance role in other design of preventive operation and maintenance systems related to equipment failure.

关键词： AFC system BP neural network Genetic algorithm Fault detect Intelligent diagnosis

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Intelligent predictor using cancer-related biologically information extraction from cancer transcriptomes 4

Intelligent predictor using cancer-related biologically info...

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4th IEEE International Symposium on Recent Advances in Electrical Engineering and Computer sciences, RAEE and CS 2020

作者： Shehzadi, Tahira Majid, Abdul Hameed, Madiha Farooq, Aqeel Yousaf, Aqsa Pakistan Institute of Engineering and Applied Sciences Department of computer science Islamabad Pakistan Swinburne University of Technology School of Software and Electrical Engineering VIC3122 Australia

ISBN: (纸本)9780738131092

This research includes cancer transcriptome which comprises of modifications in envoi RNAs while cancer genome involves DNA based alterations such as gene duplication and point mutations. Collectively, genome and transcriptome provide an overall view of individual patient's cancer that would impact on clinical decision making. This development has motivated to develop ML-based intelligent models for cancer detection. In this paper, we built predictor to extract cancer-related information using RNA sequences. Here, in this work, an effective RNA bio-sequencing is used and a novel feature extraction technique is applied accordingly. The features are trained on different learning models namely XGBoost, SVM, AdaBoost, Bagging, Random Forest, Naive Bayes, and Linear Regression to extract cancer-related biological information from cancer transcriptomic data. The XGBoost classifier gives the best performance as it provides accuracy 91.67% and sensitivity 96.89% on a standard dataset and independent dataset. These models are useful for precision medicine, drug discovery and clinical oncology. © 2020 IEEE.

关键词： Feature Selection RNA mutation Sequence-Based Features XGBoost

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Intrusion Detection Mechanism Based on Modular Neural Network 2

Intrusion Detection Mechanism Based on Modular Neural Networ...

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2nd International Conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2020

作者： Luo, Hongyu Shi, Kai Qiao, Fuqiang Li, Yinghao Tianjin University of Technology School of Computer Science and Engineering Tianjin China Tianjin Sino-German University of Applied Sciences College of Software and Communications Tianjin China

ISBN: (纸本)9781728196381

Nowadays, the complexity and diversity of network security issues have caused intrusion detection to become an important research topic. Aiming at the problems of traditional intrusion detection mechanisms, the modular neural network intrusion detection mechanism based on K-means similarity judgment is proposed. The method uses the Meanshift-Kmeans clustering algorithm to calculate the clustering center and data classification, then uses the similarity to determine the dynamic allocation of sub-modules, and finally uses the classifiers trained according to different types of intrusion to achieve intrusion detection. Through experiments on two different intrusion data sets, the experimental results prove the good detection efficiency and model stability of the model. © 2020 IEEE.

关键词： Intrusion detection

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Developing Eye Tracking Exercise System for Treatment of Lazy Eye

Developing Eye Tracking Exercise System for Treatment of Laz...

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Medical Technologies National Conference (TIPTEKNO)

作者： Kaan Kurtel Melahat Kizil Umuthan Ercan Suzan E. Ozsimsek Hasan Baris Mihci Department of Software Engineering Izmir University of Economics Balcova Izmir Turkey Izmir University of Economics Paramedic Program Vocational School of Health Services Luleå University of Technology MSc. Student in Applied Artificial Intelligence E-commerce Project Manager Macquarie University MSc. Student in Data Science

The aim of this study is to develop a fun and effective computer application game for children with amblyopia and to prevent eye strain in people whose work or lifestyle involves constantly looking at screens. The main motivation is to use children’s enthusiasm for playing video games for the treatment of amblyopia. For this, hardware and software products were brought together, and a software was developed according to software engineering principles. The system was tested with a group of volunteers and necessary alterations were made.

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〈qo|op〉: A quantum object optimizer

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softwareX 2024年 26卷

作者： Hai, Vu Tuan Viet, Nguyen Tan Ho, Le Bin Faculty of Software Engineering University of Information Technology Ho Chi Minh 70000 Viet Nam Vietnam National University Ho Chi Minh 70000 Viet Nam Nara Institute of Science and Technology 8916–5 Takayama-cho Ikoma Nara630-0192 Japan FPT University Hanoi Viet Nam Frontier Research Institute for Interdisciplinary Sciences Tohoku University Sendai 980-8578 Japan Department of Applied Physics Graduate School of Engineering Tohoku University Sendai 980-8578 Japan

The quantum object optimizer (〈qo|op〉) is a Python library that offers a framework for optimizing quantum circuits to represent quantum objects such as quantum states and Hamiltonians. This optimizer is a quantum compilation process in which an ansatz is trained to compile the information from a given quantum object. The software generates shallow circuits that can be implemented on various quantum computers and reduces the time required to process data and simulation. It also allows users to customize the algorithm for practical and proactive solutions to quantum circuit design. In this way, 〈qo|op〉 has the potential to impact both scientific research and practical applications in quantum technology significantly. © 2024 The Authors

关键词： Python

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Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack Tree and Fuzzy Logic

Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack T...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Nitin Naik Paul Jenkins Paul Grace Dishita Naik Jingping Song Shaligram Prajapat Durgesh Mishra Longzhi Yang Tossapon Boongoen Natthakan Iam-On School of Informatics and Digital Engineering Aston University United Kingdom Cardiff School of Technologies Cardiff Metropolitan University United Kingdom Birmingham City University United Kingdom Software College Northeastern University China International Institute of Professional Studies Devi Ahilya University India School of Computer Science & Information Technology Symbiosis University of Applied Sciences India Department of Computer and Information Sciences Northumbria University United Kingdom Department of Computer Science Aberystwyth University United Kingdom

Organisations and users have been experiencing significant rises in cyberattacks and their severity, which means that they require a greater awareness and understanding of the anatomy of cyberattacks, to prevent and mitigate their effects. In analysing cyberattacks, there are a number of different approaches that may be used to assess their potential risks and effects. However, these are utilised in specific types of cyberattacks and their analysis, which means they cannot be applied in every situation or cyberattack. Moreover, several other factors may influence the decision to use these approaches, such as cost, complexity, skills and adaptability. As a result, continuous research to design and enhance these approaches is undertaken to produce a generic, cost-effective, easy and adaptable approach. This paper presents one such approach to assess the risk of cyberattacks utilising an attack tree and fuzzy logic. An attack tree is a systematic and illustrative method for describing an attack on a system and analysing its taxonomy and other aspects. Subsequently, the probability and risk of each leaf node in the attack tree are calculated using the proposed formulas. Finally, fuzzy logic enables decision making based on imprecise data and heuristics to obtain the overall risk of attack. This proposed approach comprises systematic steps to accomplish an assessment of any cyberattack and its associated risks in an uncomplicated and effective manner, enabling its prevention and mitigation to be determined. The paper illustrates an application of the proposed approach to assess the risk of an information theft attack on an organisation, which can then be utilised to assess the risk of other cyberattacks.

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Assessing the magnetic order dependent γ-surface of Cr-Co-Ni alloys

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Journal of Materials science & technology 2021年第21期80卷 66-74页

作者： Zhibiao Yang Song Lu Yanzhong Tian Zijian Gu Huahai Mao Jian Sun Levente Vitos Shanghai Key Laboratory of Advanced High-Temperature Materials and Precision Forming School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China Applied Materials Physics Department of Materials Science and EngineeringRoyal Institute of TechnologyStockholm SE-10044Sweden Key Laboratory for Anisotropy and Texture of Materials(Ministry of Education) School of Materials Science and EngineeringNortheastern UniversityShenyang 110819China Unit of Structures Department of Materials Science and EngineeringKTHSE-10044StockholmSweden Thermo-Calc Software Råsundav.18SE-16767SolnaSweden Division of Materials Theory Department of Physics and Materials ScienceUppsala UniversityP.O.Box 516Uppsala SE-75120Sweden Research Institute for Solid State Physics and Optics Wigner Research Center for PhysicsBudapest H-1525P.O.Box 49Hungary

In order to efficiently explore the nearly infinite composition space in multicomponent solid solution alloys for reaching higher mechanical performance,it is important to establish predictive design strategies using computation-aided ***,using ab initio calculations we systematically study the effects of magnetism and chemical composition on the generalized stacking fault energy surface(γ-surface) of Cr-Co-Ni medium entropy alloys and show that both chemistry and the coupled magnetic state strongly affect the γ-surface,consequently,the primary deformation *** relations among various stable and unstable stacking fault energies are revealed and *** present findings are useful for studying the deformation behaviors of Cr-Co-Ni alloys and facilitate a density functional theory based design of transformation-induced plasticity and twinning-induced plasticity mechanisms in Cr-Co-Ni alloys.

关键词： Cr-Co-Ni alloys Stacking fault energy Transformation-induced plasticity Twinning-induced plasticity Ab initio

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Fusion Dilated CNN for Encrypted Web Traffic Classification

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International Journal of Network Security 2022年第4期24卷 733-740页

作者： Appiah, Benjamin Sackey, Anthony Kingsley Kwabena, Owusu-Agyemang Kanpogninge, Ansuura JohnBosco Aristotle Buah, Peter Antwi Department of Computer Science Ho Technical University1 Ho Volta Region Ghana School of Information and Software Engineering University of Electronic Science and Technology of China China C. K. Tedam University of Technology Applied Sciences Ghana Department of Civil Engineering Southwest Jiaotong University China

A Growing number of conventional Convolutional neural network (CNN) models have been employed for encrypted web traffic characterization. However, the application of CNN models is confronted with two significant challenges;a) they possess short reflective fields that don’t gather much-encrypted traffic information for effective and accurate predictions. b) these models are not adaptive to the diverse nature of traffic flow because of their singlehead architecture. This paper alleviates these problems using the fusion of dilated Convolutional neural networks dubbed FDCNN. FDCNN architecture supports exponentially large receptive fields and captures local dependencies in encrypted traffic data. The experimental results on public datasets, ISCX VPNnon-VPN Traffic datasets, indicate that FDCNN architecture is practical and achieves higher accuracy. © Institute of Mathematical Statistics, 2022

关键词： Convolution

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