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A Latency-Aware and Fault-Tolerant Framework for Resource Scheduling and Data Management in Fog-Enabled Smart City Transportation Systems

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Computers, Materials & Continua 2025年第1期82卷 1377-1399页

作者： Ibrar Afzal Noor ul Amin Zulfiqar Ahmad Abdulmohsen Algarni Department of Computer Science and information Technology Hazara UniversityMansehra21300Pakistan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation *** computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end *** of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud *** smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system *** address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog *** framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation *** FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud *** simulation-based executions,tasks are allocated to the nearest available nodes with minimum *** the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of *** successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.

关键词： Fog computing smart cities smart transportation data management fault tolerance resource scheduling

An optimized texture-by-numbers synthesis method and its visual applications

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Science China(information Sciences) 2013年第5期56卷 50-63页

作者： FAN Jing SHI XiaoYing ZHOU Zhan TANG Ying School of Computer Science and Technology Zhejiang University of Technology Key laboratory of visual Media Intelligent processing Technology of Zhejiang Province School of information Engineering Zhejiang University of Technology

The framework of texture-by-numbers(TBN) synthesizes images of global-varying patterns with intuitive user *** TBN synthesis methods have difficulties in achieving high-quality synthesis results and efficiency *** paper proposes a fast TBN synthesis method based on texture optimization,which uses global optimization to solve the controllable non-homogeneous texture synthesis *** algorithm produces high quality synthesis results by combining texture optimization into TBN framework with two *** initialization process is adopted to generate the initial output of the global optimization algorithm,which speeds up the algorithm’s convergence rate and enhances synthesis *** distance metrics to measure image similarities are specifically designed for different images to better match human visual perception for structural patterns and a user study is conducted to verify the effectiveness of the *** further improve the synthesis speed,the algorithm is entirely implemented on GPU based on CUDA *** optimized TBN method is applied to various visual applications including not only traditional TBN applications,but also image in-painting and texture-based flow *** experimental results show that our method synthesizes images of higher or comparable qualities with higher efficiency than other state-of-art synthesis methods.

关键词： texture-by-number texture optimization feature synthesis CUDA

Rapid and robust medical image elastic registration using mean shift algorithm

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Chinese Optics Letters 2008年第12期6卷 950-952页

作者：杨烜裴继红 College of information Engineering Shenzhen University Intelligent information processing laboratory Shenzhen University

In landmark-based image registration, estimating the landmark correspondence plays an important role. In this letter, a novel landmark correspondence estimation technique using mean shift algorithm is proposed. Image corner points are detected as landmarks and mean shift iterations are adopted to find the most probable corresponding point positions in two images. Mutual information between intensity of two local regions is computed to eliminate mis-matching points to improve the stability of corresponding estimation correspondence landmarks is exact. The proposed experiments of various mono-modal medical images. Multi-level estimation （MLE） technique is proposed Experiments show that the precision in location of technique is shown to be feasible and rapid in the

关键词： Rapid and robust medical image elastic registration using mean shift algorithm MLE Mean

HSNR: A Network Representation Learning Algorithm Using Hierarchical Structure Embedding

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Chinese Journal of Electronics 2020年第6期29卷 1141-1152页

作者： YE Zhonglin ZHAO Haixing ZHU Yu XIAO Yuzhi College of Computer Qinghai Normal University Tibetan information processing and Machine Translation Key laboratory of Qinghai Province Key laboratory of Tibetan information processing Ministry of Education

Vertices in the same group tend to connect densely,and usually share common *** of different sizes reflect the relations of vertices in different ranges,and also reflect the features of different orders of the *** this work,we propose a novel network representation learning algorithm by introducing group features of vertices of different orders to learn more discriminative network representations,named as network representation learning algorithm using Hierarchical structure embedding(HSNR).HSNR algorithm firstly constructs hierarchical relations of network structures of different orders based on greedy algorithm and *** order to introduce hierarchical features into the network representation learning model,HSNR algorithm then introduces the idea of multi-relational modeling from knowledge representation,and converts the hierarchical relations into the triplet form between ***,HSNR proposes a joint learning model embedding vertex triplets into the network *** experimental results show that the HSRN algorithm presented has an excellent performance in network vertex classification task on three real-world datasets.

关键词： graph theory greedy algorithms knowledge representation learning (artificial intelligence) network vertex classification task HSRN algorithm joint learning model knowledge representation network representation learning model hierarchical features greedy algorithm network structures hierarchical relations HSNR algorithm discriminative network representations group features novel network representation vertices Hierarchical structure embedding network representation learning algorithm Network representation learning Network embedding Network vertex embedding Network data mining Network feature encoding

A maximum a posteriori super resolution algorithm based on multidimensional Lorentzian distribution

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第12期10卷 1705-1713页

作者： Wen CHEN Xiang-zhong FANG Yan CHENG Shanghai Key lab of Digital Media processing and Transmissions Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai 200240 China College of information Technology East China University of Political Science and Law Shanghai 201620 China

This paper presents a threshold-free maximum a posteriori (MAP) super resolution (SR) algorithm to reconstruct high resolution (HR) images with sharp edges. The joint distribution of directional edge images is modeled as a multidimensional Lorentzian (MDL) function and regarded as a new image prior. This model makes full use of gradient information to restrict the solution space and yields an edge-preserving SR algorithm. The Lorentzian parameters in the cost function are replaced with a tunable variable, and graduated nonconvexity (GNC) optimization is used to guarantee that the proposed multidimensional Lorentzian SR (MDLSR) algorithm converges to the global minimum. Simulation results show the effectiveness of the MDLSR algorithm as well as its superiority over conventional SR methods.

关键词： Edge preservation Multidimensional Lorentzian distribution (MDL) Super resolution Threshold

Novel multi-objective optimization algorithm

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系统工程与电子技术：英文版 2014年第4期25卷 697-710页

作者： Jie Zeng Wei Nie College of information Engineering Shenzhen University Modern Communication and information processing Key laboratory Shenzhen University

Many multi-objective evolutionary algorithms(MOEAs)can converge to the Pareto optimal front and work well on two or three objectives, but they deteriorate when faced with manyobjective problems. Indicator-based MOEAs, which adopt various indicators to evaluate the fitness values(instead of the Paretodominance relation to select candidate solutions), have been regarded as promising schemes that yield more satisfactory results than well-known algorithms, such as non-dominated sorting genetic algorithm(NSGA-II) and strength Pareto evolutionary algorithm(SPEA2). However, they can suffer from having a slow convergence speed. This paper proposes a new indicatorbased multi-objective optimization algorithm, namely, the multiobjective shuffled frog leaping algorithm based on the ε indicator(ε-MOSFLA). This algorithm adopts a memetic meta-heuristic,namely, the SFLA, which is characterized by the powerful capability of global search and quick convergence as an evolutionary strategy and a simple and effective ε-indicator as a fitness assignment scheme to conduct the search procedure. Experimental results, in comparison with other representative indicator-based MOEAs and traditional Pareto-based MOEAs on several standard test problems with up to 50 objectives, show that ε-MOSFLA is the best algorithm for solving many-objective optimization problems in terms of the solution quality as well as the speed of convergence.

关键词： evolutionary algorithm multi-objective optimization shuffled frog leaping algorithm(SFLA) convergence

Binocular fusion in Panum's limiting case of stereopsis obeys the uniqueness constraint

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Science China(Life Sciences) 2001年第1期44卷 40-48页

作者：王志宏吴新年倪睿汪云九 1. laboratory of visual information processing Institute of Biophysics 100101 Beijing China 2. Center for Brain and Mind Sciences Chinese Academy of Sciences 100101 Beijing China

In the information processing procedure of stereo vision, theuniqueness constraint has been used as one of the constraints to solve the "correspondence problem". While the uniqueness constraint is valid in most cases, whether it is still valid in some particular stimulus configuration (such as Panum's limiting case) has been a problem of widespread debate for a long time. To investigate the problem, we adopted the Panum's limiting case as its basic stimulus configuration, and delved into the phenomenon of binocular fusion from two distinct aspects: visual direction and orientation disparity. The results show that in Panum's limiting case binocular fusion does not comply with the rules governing regular binocular fusion as far as visual direction and orientation disparity are concerned. This indicates that double fusion does not happen in Panum's limiting case and that the uniqueness constraint is still valid.

关键词： uniqueness constraint, Panum's limiting case, visual direction, orientation disparity, correspondence problem, psychophysics.

Text Detection in Natural Scene Images Using Morphological Component Analysis and Laplacian Dictionary

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IEEE/CAA Journal of Automatica Sinica 2020年第1期7卷 214-222页

作者： Shuping Liu Yantuan Xian Huafeng Li Zhengtao Yu School of information Engineering and Automation and Key laboratory of Intelligent information processing Kunming University of Science and Technology

Text in natural scene images usually carries abundant semantic information. However, due to variations of text and complexity of background, detecting text in scene images becomes a critical and challenging task. In this paper, we present a novel method to detect text from scene images. Firstly, we decompose scene images into background and text components using morphological component analysis(MCA), which will reduce the adverse effects of complex backgrounds on the detection *** order to improve the performance of image decomposition,two discriminative dictionaries of background and text are learned from the training samples. Moreover, Laplacian sparse regularization is introduced into our proposed dictionary learning method which improves discrimination of dictionary. Based on the text dictionary and the sparse-representation coefficients of text, we can construct the text component. After that, the text in the query image can be detected by applying certain heuristic rules. The results of experiments show the effectiveness of the proposed method.

关键词： Dictionary learning Laplacian sparse regularization morphological component analysis(MCA) sparse representation text detection

Perception of illusory contours enhanced in motion

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Science China Life Sciences 2003年第6期46卷 570-583页

作者：倪睿王志宏吴新年汪云九李东光 Chinese Academy of Sciences Institute of Biophysics laboratory of visual information processing Beijing 100101 Beijing Institute of Technology National Key laboratory of Mechatronic Engineering and Control Beijing 100081 China

Investigation on illusory contours is important for understanding the mechanisms un- derlying the object recognition of human visual system. Numerous researches have shown that illusory contours formed in motion and stereopsis are generated by the unmatched features. Here we conduct three psychophysical experiments to test if Kanizsa illusory contours are also caused by unmatched information. Different types of motion (including horizontal translation, radial ex- panding and shrinking) are utilized in the experiments. The results show that no matter under what kind of motion, when figures or background move separately illusory contours are perceived stronger, and there is no significant difference between the perceived strength in these two types of motion. However, no such enhancement of perceived strength is found when figures and background move together. It is found that the strengthened unmatched features generate the enhancement effect of illusory contour perception in motion. Thus the results suggest that the process of unmatched information in visual system is a critical step in the formation of illusory contours.

关键词： illusory contours enhancement moving unmatched psychophysics.