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TDCA: Improved Optimization Algorithm with Degree Distribution and Communication Traffic for the Deployment of Software Components Base on AUTOSAR Architecture

Research Square

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Research Square 2021年

作者： Zhang, Kunpeng Liu, Yanheng Zhang, Jindong Zhang, Guanhua Jin, Jingyi Li, Yunhao Tang, Fengmin College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbol Computation and Knowledge Engineering The Ministry of Education Jilin University Changchun China State Key Laboratory of Automobile Simulation and Control Jilin University Changchun China College of Mechanical Engineering Hebei University of Technology Tianjin300132 China China Automotive Technology and Research Center Tianjin300300 China

AUTOSAR (Automotive Open System Architecture), as an open, standardized framework for automotive electronic software development, has gradually become the standard followed by major automotive manufacturers and automotive electronic device suppliers. The electronic software system problem improves the development efficiency and portability of the system by reducing the development cost of automotive electronic software while ensuring the quality of products and services, which is beneficial for subsequent upgrades and updates of the system. In order to improve the reliability of the software component deployment algorithm based on AUTOSAR architecture, we proposed the TDCA algorithm. During the execution of the algorithm, communication volume and communication degree are introduced to improve the accuracy of the deployment plan by optimizing the bus load and ECU balancing. Algorithm comparison experiments show that comparing heuristic and linear optimization algorithms, the TDCA algorithm proposed in this paper has significant advantages in reducing bus load and ECU utilization. The algorithm can reduce the communication between cores and balance ECU load according to the constraints of AUTOSAR architecture. © 2021, CC BY.

关键词： Equalizers

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Curvature regularization to prevent distortion in graph embedding

arXiv

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arXiv 2020年

作者： Pei, Hongbin Wei, Bingzhe Zhang, Chunxu Chang, Kevin Chen-Chuan Yang, Bo College of Computer Science and Technology Jilin University China Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign United States Department of Computer Science University of Illinois at Urbana-Champaign United States Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education China

Recent research on graph embedding has achieved success in various applications. Most graph embedding methods preserve the proximity in a graph into a manifold in an embedding space. We argue an important but neglected problem about this proximity-preserving strategy: Graph topology patterns, while preserved well into an embedding manifold by preserving proximity, may distort in the ambient embedding Euclidean space, and hence to detect them becomes difficult for machine learning models. To address the problem, we propose curvature regularization, to enforce flatness for embedding manifolds, thereby preventing the distortion. We present a novel angle-based sectional curvature, termed ABS curvature, and accordingly three kinds of curvature regularization to induce flat embedding manifolds during graph embedding. We integrate curvature regularization into five popular proximity-preserving embedding methods, and empirical results in two applications show significant improvements on a wide range of open graph datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Topology

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High-Resolution Natural Image Matting by Refining Low-resolution Alpha Mattes

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IEEE transactions on image processing : a publication of the IEEE Signal Processing Society 2025年 PP卷 PP页

作者： Xianmin Ye Yihui Liang Mian Tan Fujian Feng Lin Wang Han Huang College of Data Science and Information Engineering Guizhou Minzu University Guiyang China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China Guizhou Key Laboratory of Pattern Recognition and Intelligent System and the College of Data Science and Information Engineering Guizhou Minzu University Guiyang China School of Software Engineering South China University of Technology Guangzhou China Key Laboratory of Big Data and Intelligent Robot (SCUT) MOE of China Guangzhou China Guangdong Engineering Center for Large Model and GenAI Technology Guangzhou China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

High-resolution natural image matting plays an important role in image editing, film-making and remote sensing due to its ability of accurately extract the foreground from a natural background. However, due to the complexity brought about by the proliferation of resolution, the existing image matting methods cannot obtain high-quality alpha mattes on high-resolution images in reasonable time. To overcome this challenge, we introduce a high-resolution image matting framework based on alpha matte refinement from low-resolution to high-resolution (HRIMF-AMR). The proposed framework transforms the complex high-resolution image matting problem into low-resolution image matting problem and high-resolution alpha matte refinement problem. While the first problem is solved by adopting an existing image matting method, the latter is addressed by applying the Detail Difference Feature Extractor (DDFE) designed as a part of our work. The DDFE extracts detail difference features from high-resolution images by measuring the image feature difference between high-resolution images and low-resolution images. The low-resolution alpha matte is refined according to the extracted detail difference feature, providing the high-resolution alpha matte. In addition, the Matte Detail Resolution Difference (MDRD) loss is introduced to train the DDFE, which imposes an additional constraint on the extraction of detail difference features with mattes. Experimental results show that integrating HRIMF-AMR significantly enhances the performance of existing matting methods on high-resolution images of Transparent-460 and Alphamatting. Project page: https://***/yexianmin/HRAMR-Matting.

关键词： Feature extraction Image resolution Image color analysis Optimization Remote sensing Clustering algorithms Accuracy Visualization Transforms Training

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Motion Deblur of QR Code Based on Generative Adversative Network 19

Motion Deblur of QR Code Based on Generative Adversative Net...

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Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence

作者： Benzhi Wang Jingben Xu Junke Zhang Guancheng Li Xin Wang College of Computer Science and Technology Jilin University Changchun Jilin China College of Computer Science and Technology Jilin University Changchun China and Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781450372619

Aiming at the problem that the QR codes cannot be recognized due to factors such as motion blur caused by the hand tremor and environmental noise in the QR codes of the packaged product, this paper proposes an algorithm based on the Generative Adversative Network to remove QR codes motion blur. Compared with the traditional deblurring algorithm, this method eliminates the process of blur kernel estimation, directly restores the motion blurred image. Gradient L1 regularization is added on the basis of the traditional GAN, which enhances the edge features of the restored image and adds the perceptual loss term, so that the image generated by the generator is closer to the global structure of the target clear image. The results show that the generator can remove the blur and generate a QR code with high recognition rate.

关键词： Motion Blur QR Code Generative Adversative Network Perceived Loss Function

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An unmanned aerial vehicle pose estimation system based on SLAM 2

An unmanned aerial vehicle pose estimation system based on S...

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2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation, AMIMA 2019

作者： Dou, Xinglei Huo, Yuzhou Liu, Yongchang Wang, Xin College of Software Engineering Jilin University Changchun Jilin130012 China College of Computer Science and Technology Jilin University Changchun Jilin130012 China Key Laboratory of Symbolic Computation and Knowledge Engineer Ministry of Education Jilin University Changchun Jilin130012 China

This paper presents an unmanned aerial vehicle (UAV) pose estimation system based on monocular simultaneous localization and mapping (SLAM) guided by the desired shot. The system enables UAV to automatically adjust the pose to achieve a shot close to the desired shot provided by the user. The SLAM module in the system includes ORB feature-based visual odometry and Levenberg-Marquardt method-based optimizer. To ensure the reliability of the camera pose estimation result, the bag of words model is used to select an image which has enough good matches with the desired shot. The experimental results prove that the system is valid and effective. © Published under licence by IOP Publishing Ltd.

关键词： Antennas

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Affine-periodic solutions by averaging methods

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Science China Mathematics 2018年第3期61卷 439-452页

作者： Jiamin Xing Xue Yang Yong Li College of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University School of Mathematics and Statistics Northeast Normal University Center for Mathematics and Interdisciplinary Sciences Northeast Normal University

This paper concerns the existence of affine-periodic solutions for perturbed affine-periodic *** kind of affine-periodic solutions has the form of x(t+T)≡Qx(t) with some nonsingular matrix Q,which may be quasi-periodic when Q is an orthogonal matrix. It can be even unbounded but x(t)/|x(t)| is quasi-periodic,like a helical line. for example x(t)=e^(at)(cos ωt, sin ωt), when Q is not an orthogonal matrix. The averaging method of higher order for finding affine-periodic solutions is given by topological degree.

关键词： affine-periodic solutions averaging method topological degree

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Deep neural architecture search with deep graph bayesian optimization

arXiv

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arXiv 2019年

作者： Ma, Lizheng Cui, Jiaxu Yang, Bo College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education

Bayesian optimization (BO) is an effective method of finding the global optima of black-box functions. Recently BO has been applied to neural architecture search and shows better performance than pure evolutionary strategies. All these methods adopt Gaussian processes (GPs) as surrogate function, with the handcraft similarity metrics as input. In this work, we propose a Bayesian graph neural network as a new surrogate, which can automatically extract features from deep neural architectures, and use such learned features to fit and characterize black-box objectives and their uncertainty. Based on the new surrogate, we then develop a graph Bayesian optimization framework to address the challenging task of deep neural architecture search. Experiment results show our method significantly outperforms the comparative methods on benchmark tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Evolutionary algorithms

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Movie Score Prediction Model Based on Movie Plots

Movie Score Prediction Model Based on Movie Plots

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2019国际计算机前沿大会

作者： Hui Xie Haomeng Wang Chen Zhao Zhe Wang College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education (Jilin University)

With the rapid development of the movie industry, it is vital to evaluate and predict a movie's quality. In this paper, a movie score prediction model is proposed based on the movie plots. Movie data was processed with the word2 vec method, and the linear regression model and back propagation neural network algorithm were employed to establish the movie score prediction model. The high-quality classic movie plots of high-scoring movies summed up by big data contributed to a high synthesis of the wonderful content of the *** results show that it is effective in terms of movie evaluation and prediction, and helpful in understanding people's preferences for movie plots.

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Optimal control approach to stability criteria on Hill's equations

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Applied Mathematics(A Journal of Chinese Universities) 2018年第3期33卷 253-273页

作者： ZU Jian LI Yong School of Mathematics and Statistics & Center for Mathematics and Interdisciplinary Sciences North-east Normal University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University College of Mathematics Jilin University

This paper gives a tutorial on how to prove Lyapunov type criteria by optimal control methods. Firstly, we consider stability criteria on Hill’s equations with nonnegative potential. By optimal control methods developed in 1990s, we obtain several stability criteria including Lyapunov’s criterion, Neǐgauz and Lidskiǐ’s criterion. Secondly, we present stability criteria on Hill’s equations with sign-changing potential in which Brog’s criterion and Krein’s criterion are included.

关键词： stability criteria optimal control method Hill's equation Lyapunov inequality

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Application of Monocular Direct Vision Odometry in Augmented Reality

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Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zuoming Zhang Zixuan Wang Hanwen Wang Xin Wang College of Software Engineering Jilin University Changchun Jilin 130000 China Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun Jilin 130000 China

In recent years, the unlabeled augmented reality system has been gradually applied to various mobile devices, among which stable, accurate, and fast registration is the key to realizing this function. For this technique, this paper introduces camera exposure parameters and puts the data association and pose estimation into a unified nonlinear optimization problem. Moreover, the direct monocular vision odometer is transplanted into the augmented reality system through the position adjustment module. We compare it with the traditional visual odometry method that matches the feature points. The results show that this improved method can be used to track more quickly and build a more visual semi-dense point cloud map, which can be used to support the registration and tracking of virtual objects in augmented reality.

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