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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Zhang, Hanyu Tang, Lixin Song, Xiangman Xu, Te Northeastern University National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shen Yang110819 China Northeastern University Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shen Yang110819 China

ISBN: (纸本)9798350308365

Accurate segmentation of the microvascular component of the retinal fundus image is of great significance for the clinical diagnosis. Currently, deep learning-based methods are often employed for retinal fundus image segmentation. However, most deep learning models manually designed by experts are not suitable for task-specific applications. Therefore, we propose a novel retinal image segmentation method that integrates a neural architecture search framework with a non-subsampled multiscale decomposition (NSMD-NAS) technique. Specifically, the feature extraction layer includes the convolutional layer and the transformer layer. In addition, the non-subsampling filter bank is embedded into the convolutional and the transformer modules respectively to generate a new network module for exploring multiscale, multi-frequency, and multi-directional information. Unlike previous wavelet-based network modules, non-subsampling network modules have translation invariance. Subsequently, the components of the network are specified by the elaborated encoding strategy, and then the network with the highest adaptation is searched by a genetic evolutionary algorithm (GA) to finally obtain the best network structure. Experimental results demonstrate the effectiveness of each component in the proposed model on the public benchmark datasets. © 2024 IEEE.

关键词： Convolution

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AcArm: A Novel Semiconductor Wafer Handling Robot

AcArm: A Novel Semiconductor Wafer Handling Robot

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2023 China Semiconductor Technology International Conference, CSTIC 2023

作者： Chen, Donglin Tang, Lixin Cong, Dehong Qiao, Jingchao Northeastern University National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang110819 China Ministry of Education Shenyang110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China

ISBN: (纸本)9798350311006

In the field of semiconductor manufacturing, highly automated production methods have become an inevitable trend of development thanks to their precise, stable and reliable characteristics. This paper focuses on the handling link in the semiconductor production process, designed a novel handling robot. Minimum Snap method is used to plan the end-effector trajectory of the robot, the control method of the robot is based on the position control, and the experiment environment is the co-simulation environment of Simulink and Adams. All the simulation testing of the planning and the control method has been done on the virtual prototype. © 2023 IEEE.

关键词： Position control

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Efficiently Trimming the Fat: Streamlining Software Dependencies with Java Reflection and Dependency Analysis 24

Efficiently Trimming the Fat: Streamlining Software Dependen...

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44th ACM/IEEE International Conference on Software Engineering, ICSE 2024

作者： Song, Xiaohu Wang, Ying Cheng, Xiao Liang, Guangtai Wang, Qianxiang Zhu, Zhiliang Northeastern University Shenyang China Huawei Cloud Computing Technologies Co. Ltd. Beijing China Northeastern University National Frontiers Science Center for Industrial Intelligence and Systems Optimization Key Laboratory of Data Analytics and Optimization for Smart Industry Shenyang China

ISBN: (纸本)9798400702174

Numerous third-party libraries introduced into client projects are not actually required, resulting in modern software being gradually bloated. Software developers may spend much unnecessary effort to manage the bloated dependencies: keeping the library versions up-to-date, making sure that heterogeneous licenses are compatible, and resolving dependency conflict or vulnerability issues. However, the prior debloating techniques can easily produce false alarms of bloated dependencies since they are less effective in analyzing Java reflections. Besides, the solutions given by the existing approaches for removing bloated dependencies may induce new issues that are not conducive to dependency management. To address the above limitations, in this paper, we developed a technique, Slimming, to remove bloated dependencies from software projects reliably. Slimming statically analyzes the Java reflections that are commonly leveraged by popular frameworks (e.g., Spring Boot) and resolves the reflective targets via parsing configuration files (*. xml, *. ym1 and *. properties). By modeling string manipulations, Slimming fully resolves the string arguments of our concerned reflection APIs to identify all the required dependencies. More importantly, it helps developers analyze the debloating solutions by weighing the benefits against the costs of dependency management. Our evaluation results show that the static reflection analysis capability of Slimming outperforms all the other existing techniques with 97.0% of Precision and 98.8% of Recall. Compared with the prior debloating techniques, Slimming can reliably remove the bloated dependencies with a 100% test passing ratio and improve the rationality of debloating solutions. In our large-scale study in the Maven ecosystem, Slimming reported 484 bloated dependencies to 66 open-source projects. 38 reports (57.6%) have been confirmed by developers. © 2024 ACM.

关键词： Java programming language

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A Multi-Objective Evolutionary Machine Learning Method for the Yield Strength Prediction of Strip Steel in Continuous Annealing

A Multi-Objective Evolutionary Machine Learning Method for t...

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IISE Annual Conference and Expo 2024

作者： Liu, Chang Tang, Lixin Zhang, Kainan Guo, Jiajing National Frontiers Science Center for Industrial Intelligence and Systems Optimization North-eastern University Shenyang110819 China Ministry of Education Shenyang110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Shenyang110819 China

ISBN: (纸本)9781713877851

In the continuous annealing process, the yield strength is the key property index to evaluate the quality of strip steel and guide the production. It is difficult to perform online quality measurement for numerous products in the steel industry, this brings significant challenges for process monitoring and operation optimization. In this paper, a multiobjective evolutionary machine learning method is proposed for the yield strength prediction of strip steel in continuous annealing. First, the factors affecting the yield strength of strip steel are analyzed and the prediction model based on a hybrid kernel support vector regression (HKSVR) is established. To improve the prediction accuracy, a multi-objective evolutionary optimization algorithm with a knee solution strategy is used to optimize the key parameters of the HKSVR. It is verified by the actual production data that the proposed method has high prediction accuracy and can meet the actual production demand. Moreover, the proposed method can help practitioners to construct quality analytics models for many other similar production lines, providing assurance for quality control and optimization with a good generalization. © IISE Annual Conference and Expo *** rights reserved.

关键词： Prediction models

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Cosmology with fast radio bursts in the era of SKA

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Science China(Physics,Mechanics & Astronomy) 2023年第12期66卷 37-55页

作者： Ji-Guo Zhang Ze-Wei Zhao Yichao Li Jing-Fei Zhang Di Li Xin Zhang Department of Physics College of SciencesNortheastern UniversityShenyang 110819China Key Laboratory of Cosmology and Astrophysics(Liaoning) Northeastern UniversityShenyang 110819China National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Research Center for Intelligent Computing Platforms Zhejiang LaboratoryHangzhou 311100China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern UniversityShenyang 110819China

We present a forecast of the cosmological parameter estimation using fast radio bursts(FRBs)from the upcoming Square Kilometre Array(SKA),focusing on the issues of dark energy,the Hubble constant,and baryon *** simulate 105and 106localized FRBs from a 10-year SKA observation,and find that:(1)using 106FRB data alone can tightly constrain dark-energy equation of state parameters better than CMB+BAO+SNe,providing an independent cosmological probe to explore dark energy;(2)combining the FRB data with gravitational-wave standard siren data from 10-year observation with the Einstein Telescope,the Hubble constant can be constrained to a sub-percent level,serving as a powerful low-redshift probe;(3)using 106FRB data can constrain the baryon density?bh to a precision of~0.1%.Our results indicate that SKA-era FRBs will provide precise cosmological measurements to shed light on both dark energy and the missing baryon problem,and help resolve the Hubble tension.

关键词： fast radio burst cosmology dark energy the Hubble constant baryon density Square Kilometre Array

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Exploring neutrino mass and mass hierarchy in interacting dark energy models

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Science China(Physics,Mechanics & Astronomy) 2020年第2期63卷 55-63页

作者： Lu Feng Hai-Li Li Jing-Fei Zhang Xin Zhang College of Physical Science and Technology Shenyang Normal UniversityShenyang 110034China Department of Physics College of SciencesNortheastern UniversityShenyang 110819China Ministry of Education Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern UniversityShenyang 110819China Center for High Energy Physics Peking UniversityBeijing 100080China Center for Gravitation and Cosmology Yangzhou UniversityYangzhou 225009China

We investigate how the dark energy properties impact the constraints on the total neutrino mass in interacting dark energy（IDE）models. In this study, we focus on two typical interacting dynamical dark energy models, i.e., the interacting w cold dark matter（IwCDM） model and the interacting holographic dark energy（IHDE） model. To avoid the large-scale instability problem in IDE models, we apply the parameterized post-Friedmann approach to calculate the perturbation of dark energy. We employ the Planck 2015 cosmic microwave background temperature and polarization data, combined with low-redshift measurements on baryon acoustic oscillation distance scales, type Ia supernovae, and the Hubble constant, to constrain the cosmological parameters. We find that the dark energy properties could influence the constraint limits on the total neutrino mass. Once dynamical dark energy is considered in the IDE models, the upper bounds of ∑mν will be changed. By considering the values of χmin2 , we find that in these IDE models the normal hierarchy case is slightly preferred over the inverted hierarchy case; for example, ?χ2= 2.720 is given in the IHDE+∑mν model. In addition, we also find that in the Iw CDM+∑mν model β = 0 is consistent with current observational data inside the 1σ range, and in the IHDE+∑mν model β > 0 is favored at more than 2σ level.

关键词： neutrino mass mass hierarchies of neutrinos interacting dark energy cosmological observations cosmological constraints

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BERD+: A Generic Sequential Recommendation Framework by Eliminating Unreliable data with Item- and Attribute-level Signals

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ACM Transactions on Information Systems 2023年第2期42卷 1-33页

作者： Sun, Yatong Yang, Xiaochun Sun, Zhu Wang, Bin School of Computer Science and Engineering Northeastern University School of Computing Macquarie University China Australia Institute of High Performance Computing Centre for Frontier AI Research A*STAR Singapore School of Computer Science and Engineering Northeastern University China National Frontiers Science Center for Industrial Intelligence and Systems Optimization China Key Laboratory of Data Analytics and Optimization for Smart Industry [Northeastern University Ministry of Education China

A preliminary work of our study was published at IJCAI’21 [47], which is substantially extended in the following aspects: (1) In Section 1, we analyze the necessity of introducing item attributes for detecting unreliable instances, together with the problems and challenges that attributes may bring in. (2) In Section 2, we add discussions about the limitations of existing attribute-aware recommender systems (Section 2.2) and denoising methods (Section 2.3) in the context of detecting unreliable instances. (3) In Section 4.2, we further conduct an in-depth analysis at the attribute level to demonstrate the capability of attributes for rectifying instance loss and uncertainty, as well as the disturbance caused by attributes. (4) We generalize BERD to a generic framework BERD+ in Section 5.1, equipped with novel modules, i.e., HU-GCN (Section 5.2) and EPE (Section 5.4), which properly incorporate item attributes while reducing their disturbance for rectifying instance uncer tainty (Section 5.5) and loss (Section 5.6). The generic BERD+ can be flexibly plugged into existing SRSs for performance enhanced recommendation via eliminating unreliable data. (5) In Section 6.2, we apply our BERD+ framework to seven state-of-the-art SRSs on five real-world datasets to illustrate its superiority. (6) To avoid unfair comparison caused by item attributes, we build and compare with the baseline that combines the original BERD and an advanced attribute-aware recommender system, KSR [19]. (7) For more comprehensive comparison, in Section 6.2.2, we compare BRED+ with two state-of-the-art denoising approaches;in Section 6.2.3, to examine the efficacy of HU-GCN and EPE, we compare HU-GCN with various attribute embedding techniques, i.e., variants of graph neural networks, and compare EPE with different attribute fusing methods, i.e., adding, concatenation, and weighted sum. (8) In Section 6.2.4, a detailed ablation study is conducted to verify the effectiveness of each module of BERD+. (

关键词： Convolution

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AcArm: A Novel Semiconductor Wafer Handling Robot

AcArm: A Novel Semiconductor Wafer Handling Robot

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China Semiconductor Technology International Conference (CSTIC)

作者： Donglin Chen Lixin Tang Dehong Cong Jingchao Qiao National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China Ministry of Education Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Shenyang China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang China

关键词：

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Network pharmacology and single-cell transcriptomic analysis with molecular docking to elucidate the potential compounds and targets of Polygonum cuspidatum *** *** hepatocellular carcinoma

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iLIVER 2024年第3期3卷 41-51页

作者： Wenze Wu Yuzhu Shi Yongzi Wu Rui Zhang Xinyan Wu Weidi Zhao Zhiyuan Chen Gang Ye Key Laboratory of Bioresource Research and Development of Liaoning Province College of Life and Health SciencesNational Frontiers Science Center for Industrial Intelligence and Systems OptimizationKey Laboratory of Data Analytics and Optimization for Smart IndustryMinistry of EducationNortheastern UniversityShenyang 110169China College of Veterinary Medicine Sichuan Agricultural UniversityChengdu 625014China School of Physical Education Shanxi UniversityTaiyuan 030006China

Background and aims:Polygonum cuspidatum *** Zucc.(***)and its active components have been clinically proven to have anti-hepatocellular carcinoma ***,the potential targets of *** for these effects have not yet been ***:We used network pharmacology and single-cell transcriptomic analysis with molecular docking to elucidate the active components and targets of *** for hepatocellular ***:CDK1,ESR1,HSP90A11,and MAPK1 were shown to be the key targets of *** for hepatocellular *** was found to be likely correlated with the improved abnormal expression of CDK1 and ESR1 and the poor prognosis of HSP90AA1 and ***1 was identified as the most potential antihepatocellular carcinoma target of *** the active components of ***,physcion diglucoside was found to have the most potential to treat hepatocellular carcinoma by targeting ***:Our study provides novel insights into the anti-hepatocellular carcinoma pharmacological effects of ***,which could serve as a scientific basis for its development as a medicinal resource and the targeting of CDK1 for hepatocellular carcinoma treatment.

关键词： Hepatocellular carcinoma Network pharmacology Molecular dynamics simulation Molecular docking Polygonum cuspidatum Single-cell transcriptomic analysis

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Unraveling the early universe’s equation of state and primordial black hole production with PTA,BBN,and CMB observations

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Chinese Physics C 2024年第12期48卷 212-220页

作者： Qing-Hua Zhu Zhi-Chao Zhao Sai Wang Xin Zhang Department of Physics and Chongqing Key Laboratory for Strongly Coupled Physics Chongqing UniversityChongqing 401331China Department of Applied Physics College of ScienceChina Agricultural UniversityQinghua East RoadBeijing 100083China Theoretical Physics Division Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China Key Laboratory of Cosmology and Astrophysics(Liaoning)&College of Sciences Northeastern UniversityShenyang 110819China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern UniversityShenyang 110819China

Pulsar timing array(PTA)data releases show strong evidence for a stochastic gravitational-wave background in the nanohertz *** the signal is interpreted by a scenario of scalar-induced gravitational waves(SIGWs),we encounter overproduction of primordial black holes(PBHs).We wonder if varying the equation of state(EoS)of the early Universe can resolve this issue and thereby lead to a consistent interpretation of the PTA *** a data combination of PTA,big-bang nucleosynthesis,and cosmic microwave background,we find that an epoch with EoS w~O(10^(-2))between the end of inflation and the onset of radiation domination can significantly suppress the production of PBHs,leading to alleviation of the PBH-overproduction *** the inferred interval w=0.44_(-0.40)^(+0.52)at 95%confidence level,our scenario can interpret the PTA data just as well as the conventional scenario of SIGWs produced during the radiation domination.

关键词： physics of the early universe gravitational waves primordial black hole pulsar timing arrays

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