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African Bison Optimization Algorithm:A New Bio-Inspired Optimizer with Engineering Applications

computers, Materials & Continua 2024年第10期81卷 603-623页

作者： Jian Zhao Kang Wang Jiacun Wang Xiwang Guo Liang Qi School of Science University of Science and Technology LiaoningAnshan114051China Team of Artificial Intelligence Theory and Application University of Science and Technology LiaoningAnshan114051China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Information and Control Engineering College Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China

This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foraging behavior prompts the bison to seek a richer food source for *** bison find a food source,they stick around for a while by bathing *** jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating *** eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent *** above behaviors are translated into ABO by mathematical *** assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with *** findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.

关键词： Optimization metaheuristics African bison optimization engineering problems

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Higher Accuracy Yolov5 Based Safety Helmet Detection 5th

Higher Accuracy Yolov5 Based Safety Helmet Detection

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5th EAI International Conference on 6G for Future Wireless Networks, 6GN 2022

作者： Wang, Zizhen Sun, Yuegong Wang, Zhening Li, Ao School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9783031360107

For the construction site with high-risk possibility, object detection based on safety helmet and reflective clothing will greatly reduce the risk of workers. At present, the algorithm based on deep learning is the mainstream algorithm of object detection. Among them, the YOLO algorithm is fast and widely used in real-time safety helmet detection. However, for the problems of small objects such as safety helmets and relatively dense detection scene objects, the detection effect is not ideal. For these problems, this paper proposes an improvement of the safety helmet detection algorithm based on YOLOv5s. The DenseBlock module is used in the improved algorithm to replace the Focus structure in the backbone network, which has an improved feature extraction capability for the network;secondly, Soft-NMS is used to retain more category frames when removing redundant frames. After the experiments, it is shown that the accuracy is improved on the homemade safety helmet dataset, which indicates the effectiveness of the improved algorithm. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Object detection

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COMPrompter: reconceptualized segment anything model with multiprompt network for camouflaged object detection

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science China(Information sciences) 2025年第1期68卷 189-203页

作者： Xiaoqin ZHANG Zhenni YU Li ZHAO Deng-Ping FAN Guobao XIAO Zhejiang Province Key Laboratory of Intelligent Informatics for Safety and Emergency Wenzhou University Nankai International Advanced Research Institute (SHENZHEN FUTIAN) College of Computer Science Nankai University School of Computer Science and Technology Tongji University

We rethink the segment anything model(SAM) and propose a novel multiprompt network called COMPrompter for camouflaged object detection(COD). SAM has zero-shot generalization ability beyond other models and can provide an ideal framework for COD. Our network aims to enhance the single prompt strategy in SAM to a multiprompt strategy. To achieve this, we propose an edge gradient extraction module, which generates a mask containing gradient information regarding the boundaries of camouflaged objects. This gradient mask is then used as a novel boundary prompt, enhancing the segmentation process. Thereafter, we design a box-boundary mutual guidance module, which fosters more precise and comprehensive feature extraction via mutual guidance between a boundary prompt and a box prompt. This collaboration enhances the model's ability to accurately detect camouflaged objects. Moreover, we employ the discrete wavelet transform to extract high-frequency features from image embeddings. The high-frequency features serve as a supplementary component to the multiprompt ***, our COMPrompter guides the network to achieve enhanced segmentation results, thereby advancing the development of SAM in terms of COD. Experimental results across COD benchmarks demonstrate that COMPrompter achieves a cutting-edge performance, surpassing the current leading model by an average positive metric of 2.2% in COD10K. In the specific application of COD, the experimental results in polyp segmentation show that our model is superior to top-tier methods as well. The code will be made available at https://***/guobaoxiao/COMPrompter.

关键词： segment anything model camouflaged object detection boundary prompt

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Spatio-temporal knowledge embedding via circular correlation: insights into functional urban area travel pattern mining

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Neural Computing and Applications 2024年第30期36卷 19075-19095页

作者： Pan, Qihong Chen, Yao Shen, Guojiang Yang, Yao Kong, Xiangjie College of Computer Science and Technology Zhejiang University of Technology Hangzhou310023 China Zhejiang Lab Hangzhou China

In recent urban studies, understanding the flow patterns of urban residents has become crucial for effective transportation planning and business district design. Traditional data-driven approaches have provided insights but often lead to random and uninterpretable results due to their sole reliance on data features, lacking a deeper contextual and semantic analysis of the underlying patterns. To overcome these limitations, our work introduces a novel framework that fuses holographic knowledge embedding with graph deep learning to predict urban population travel patterns. This dual-driven approach of data and knowledge uniquely integrates traffic geographic information, vehicle trajectory data, and Points of Interest (POI) into a comprehensive urban traffic knowledge graph. Our method not only captures the spatial-temporal dependencies of big data traffic but also models the relationships between geographic, semantic POI information, and urban travel behaviors. The knowledge graph is then processed through a graph deep learning model, enhancing the embedding features and enabling sophisticated link prediction. Compared with conventional data-driven methods, our approach demonstrates significant advancements in harnessing semantic information, leading to more accurate and interpretable predictions of travel patterns. Experimental validation on real-world datasets confirms the effectiveness of our method in capturing complex urban dynamics. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Embeddings

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A Practical Multi-Protocol Collaborative Quantum Key Distribution Networking Scheme for Consumer Electronics Devices

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IEEE Transactions on Consumer Electronics 2024年第1期71卷 1190-1200页

作者： Yao, Jia-Meng Li, Qiong Mao, Hao-Kun El-Latif, Ahmed A. Abd Harbin Institute of Technology Department of the School of Computer Science and Technology Harbin150001 China Prince Sultan University Center of Excellence in Quantum and Intelligent Computing Riyadh11586 Saudi Arabia Menoufia University Faculty of Science Department of Mathematics and Computer Science Shibin El Kom6132501 Egypt

The development of emerging consumer technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud computing brings convenience but also raises critical concerns about securing communication data. Quantum computing threatens the security of classical public key cryptography, making post-quantum data protection essential. Quantum Key Distribution (QKD) networks offer a solution, but the dependence on trusted relays raises security concerns. The existing QKD networks mainly consist of two types: measurement-device-dependent protocol based QKD networks which have a high dependence on trusted relays, and measurement-device-independent protocol based QKD networks which have a weak dependence on trusted relays but communication capability is limited. This paper proposes a Multi-Protocol Collaborative (MPC) networking cell combining both types of QKD protocol, which can reduce the dependence on trusted relays while maintaining a high communication capacity, and consequently has an enhanced practicality. An optimal topology method is also designed to further enhance the performance of the networks. Results show that communication capacity is improved 37 times compared to measurement-device-independent protocol based QKD networks. In addition, 23% reduction in the dependence on trusted relays compared to measurement-device-dependent protocol based QKD networks. By overcoming the trade-off between trust and capacity, this work significantly advances the practicalization of QKD networks in consumer electronics. © 1975-2011 IEEE.

关键词： Quantum computers

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Finite-Time Stability and Instability of Nonlinear Impulsive Systems

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Advances in Applied Mathematics and Mechanics 2023年第1期15卷 49-68页

作者： Guihua Zhao Hui Liang College of Science University of Shanghai for Science and TechnologyShanghai200093China School of Science Harbin Institute of TechnologyShenzhenGuangdong 518055China

In this paper,the finite-time stability and instability are studied for nonlinear impulsive *** are mainly four concerns.1)For the system with stabilizing impulses,a Lyapunov theorem on global finite-time stability is presented.2)When the system without impulsive effects is globally finite-time stable(GFTS)and the settling time is continuous at the origin,it is proved that it is still GFTS over any class of impulse sequences,if the mixed impulsive jumps satisfy some mild conditions.3)For systems with destabilizing impulses,it is shown that to be finite-time stable,the destabilizing impulses should not occur too frequently,otherwise,the origin of the impulsive system is finite-time instable,which are formulated by average dwell time(ADT)conditions respectively.4)A theorem on finite-time instability is provided for system with stabilizing *** each GFTS theorem of impulsive systems considered in this paper,the upper boundedness of settling time is given,which depends on the initial value and impulsive *** numerical examples are given to illustrate the theoretical analysis.

关键词： Impulsive systems finite-time stability finite-time instability nonlinear systems

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SEOE:an option graph based semantically embedding method for prenatal depression detection

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Frontiers of computer science 2024年第6期18卷 245-258页

作者： Xiaosong HAN Mengchen CAO Dong XU Xiaoyue FENG Yanchun LIANG Xiaoduo LANG Renchu GUAN College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun 130012China Department of Electrical Engineering and Computer Science and Christopher S.Bond Life Sciences Center University of MissouriColumbiaMO 65211USA Department of Computer Science and Technology Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationZhuhai College of Science and TechnologyZhuhai 519041China Jilin Provincial Institute of Population Science and Technology Changchun 130000China

Prenatal depression,which can affect pregnant women’s physical and psychological health and cause postpartum depression,is increasing ***,it is essential to detect prenatal depression early and conduct an attribution *** studies have used questionnaires to screen for prenatal depression,but the existing methods lack *** diagnose the early signs of prenatal depression and identify the key factors that may lead to prenatal depression from questionnaires,we present the semantically enhanced option embedding(SEOE)model to represent questionnaire *** can quantitatively determine the relationship and patterns between options and *** first quantifies options and resorts them,gathering options with little difference,since Word2Vec is highly dependent on *** resort task is transformed into an optimization problem involving the traveling salesman ***,all questionnaire samples are used to train the options’vector using ***,an LSTM and GRU fused model incorporating the cycle learning rate is constructed to detect whether a pregnant woman is suffering from *** verify the model,we compare it with other deep learning and traditional machine learning *** experiment results show that our proposed model can accurately identify pregnant women with depression and reach an F1 score of *** most relevant factors of depression found by SEOE are also verified in the *** addition,our model is of low computational complexity and strong generalization,which can be widely applied to other questionnaire analyses of psychiatric disorders.

关键词： questionnaire analyses text classification graph representation learning traveling salesman problem prenatal depression

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Adversarial Threats to Automatic Modulation Open Set Recognition in Wireless Networks

Adversarial Threats to Automatic Modulation Open Set Recogni...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Yang, Yandie Zhang, Sicheng Li, Kuixian Tian, Qiao Lin, Yun Harbin Engineering University College of Information and Communication Engineering Harbin China Harbin Engineering University College of Computer Science and Technology Harbin China

ISBN: (纸本)9798350351255

Automatic Modulation Open Set Recognition (AMOSR) is a crucial technological approach for cognitive radio communications, wireless spectrum management, and interference monitoring within wireless networks. Numerous studies have shown that AMR is highly susceptible to minimal perturbations carefully designed by malicious attackers, leading to misclassification of signals. However, the adversarial security issue of AMOSR has not yet been explored. This paper adopts the perspective of attackers and proposes an Open Set Adversarial Attack (OSAttack), aiming at investigating the adversarial vulnerabilities of various AMOSR methods. Initially, an adversarial threat model for AMOSR scenarios is established. Subsequently, by analyzing the decision criteria of both discriminative and generative open set recognition, OSFGSM and OSPGD are proposed to reduce the performance of AMOSR. Finally, the influence of OSAttack on AMOSR is evaluated utilizing a range of qualitative and quantitative indicators. The results indicate that despite the increased resistance of AMOSR models to conventional interference signals, they remain vulnerable to attacks by adversarial examples. © 2024 IEEE.

关键词： Signal modulation

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ZVEFusion: Zero-Shot Visual Enhancement Fusion for Infrared and Visible Images in Low Light

ZVEFusion: Zero-Shot Visual Enhancement Fusion for Infrared ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Liu, Duo Shi, Yiqi Zhang, Guoyin Li, Sizhao Zhang, Liguo School of Computer Science and Technology Harbin Engineering University China

ISBN: (纸本)9798350368741

Infrared and visible image fusion (IVIF) aims to generate fused images with prominent targets and rich scene information. However, in low-light conditions, visible images lose accurate texture and color, reducing their ability to provide detailed scene information for fusion. Existing IVIF methods often overlook illumination degradation and cause color distortion when incorporating infrared information. To address these problems, we propose a novel visually enhanced IVIF method tailored for low-light environments. Our method combines low-light image enhancement (LLIE) and IVIF into a single module. First, we adaptively enhance the low-light visible image, ensuring rich texture and color for fusion. Additionally, we introduce a three-channel fusion coefficient map to transform infrared information into visible image, preventing color distortion and highlighting key targets while maintaining details of the fused image. Since infrared and visible images are from different modalities, we map them into the same high-dimensional feature space. We then propose the feature difference to integrate complementary information, producing a fused image with complete content and no redundancy. Notably, our method is zero-shot, requiring only a pair of test infrared and visible images for training. This better meets the complexity of IVIF in various low-light scenes. Extensive experiments show that in low-light conditions, our method surpasses other state-of-the-art (SOTA) methods by providing more natural colors, richer textures, and better alignment with human visual perception. © 2025 IEEE.

关键词： Image Fusion Low Light Visually Enhanced Zero-Shot

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Achieving high strength-ductility synergy in TiB_(w)/near α-Ti composites by ultrafine grains and nanosilicides via low-temperature severe plastic deformation

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Journal of Materials science & technology 2024年第35期202卷 253-266页

作者： Changjiang Zhang Xiaojian Liang Yonggang Sun Shuzhi Zhang Ruipeng Guo Hong Feng Fantao Kong Peng Cao College of Materials Science and Engineering Taiyuan University of TechnologyTaiyuan 030024China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China School of Materials Science and Engineering Yanshan UniversityQinhuangdao 66004China Department of Chemical and Materials Engineering The University of AucklandPrivate Bag 92019Auckland 1142New Zealand

The common problem of low strength-ductility matching prevails in near-αhigh-temperature titanium matrix composites(TMCs).In this work,the design strategy of ultrafine grains and dispersed(Ti,Zr)_(6)Si_(3) nanoprecipitates in the microstructure of TiB_(w)/nearα-Ti composites via low-temperature isothermal mul-tidirectional forging(IMDF),is expected to break the trade-offdilemma between strength and *** results show that with the decrease in the temperature of IMDF,the grain scale decreased from 0.98 to 0.59μm,and the location of silicide precipitation shifted from phase boundaries and grain boundaries toα-grain boundaries and intracrystalline *** experiments confirm that the local segregation of Si and the temperature of thermomechanical deformation are the key factors affecting the precipitation behavior of *** the decrease of the deformation temperature,the precipitation mechanism of silicides changes from a single diffusion-controlled precipitation to the coupling of two mechanisms,namely,elemental diffusion and dislocation-assisted nucleation,which facilitates the successive precip-itation of nanometer-sized silicides at the grain boundaries and in the inner *** ultimate ten-sile strength(UTS)and elongation of the composites were substantially increased after IMDF at 950 and 800℃,especially the excellent performance at 800℃,where the strength reached 1320.3 MPa and the elongation was 5.8%.The room and high-temperature strengthening and failure mechanisms of the com-posites are analyzed and discussed,and the yield strength(YS)increments provided by various strength-ening mechanisms at room temperature are quantified,aiming to provide a potential preparation strategy for the synergistic strengthening of near-αTMCs with ultrafine grains and nanoparticles.

关键词： Titanium matrix composites High temperature titanium alloy Severe plastic deformation Ultrafine grain Silicides Strengthening mechanisms

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