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9th International Conference on Fuzzy Systems and Data Mining, FSDM 2023

作者： Xia, Changhai Peng, Zhiping Cui, Delong Li, Qirui Sun, Lihui School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China Jiangmen Polytechnic College Jiangmen City529090 China School of Computer Science Guangdong University of Petrochemical Technology Maoming City525000 China

ISBN: (纸本)9781643684703

This study presents a cutting-edge soft sensing approach for coke-making diagnostics, aimed at tackling the challenges posed by multifaceted, nonlinear, non-Gaussian, and noisy operational data prevalent in coke-making ovens. Our proposed method leverages a Bayesian t-distributed mixed regression model, effectively capturing the intricate nature of multivariate, nonlinear, and non-Gaussian data. The utilization of the t-distribution ensures the model's resilience to interference, with model parameter estimation achieved within a Bayesian framework. Conducting simulation experiments and real industrial experiments, as well as comparative analysis with PLSR, GMR, and GPR models, we demonstrate the model's good robustness, excellent prediction accuracy, and robustness, further confirming its potential application in coking diagnosis. © 2023 The authors and IOS Press.

关键词： Coke

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Real-Time Notifier for Blockchain Events

Real-Time Notifier for Blockchain Events

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Roedunet International Conference (RoEduNet)

作者： Cristian Tănase-Paris Costin Carabaș Nicolae Țăpuș Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

Blockchain technology gained much traction in the last few years. These decentralized databases offer security, immutability, and scalability across various applications. Decentralized applications generate vast amounts of data, known as events, that are recorded on the blockchain and are public to anyone. Some people may see opportunities for financial gains in these events and would like to know when they occur. This paper proposes a solution to process and deliver those events as real-time alerts to the users. It uses existing technologies such as message queues, multithreading, and asynchronous processing and integrates them into a scalable architecture. The results we achieved in this paper show that for an evenly distributed network traffic, which does not entirely consists of transaction bursts, the proposed solution offers reliability, efficiency, and a suitable delivery time to those wishing to integrate it into their projects. With time, this solution, or improved architectures, may form the basis of the following big-data architectures for processing blockchain events.

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Gradient Projection Differential Neural Solution for Quadratic Optimization with Quadratic Constraints: An ACP Perspective

Gradient Projection Differential Neural Solution for Quadrat...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Liufu, Ying Liu, Mei Jin, Long Wang, Feiyue School of Information Science and Engineering Lanzhou University Lanzhou China College of Computer Qinghai Normal University Xining China Institute of Automation The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350337020

In recent years, quadratic optimizations have become increasingly popular in engineering. However, conventional methods that investigate this problem from the perspective of a canonical form with linear constraints are not effective in dealing with the significant challenges posed by quadratic constraints in practice. This paper proposes a solution framework for the quadratic optimization with quadratic constraints (QOQC) based on innovative artificial societies, computational experiments, and parallel execution (ACP) framework. Then, a gradient projection differential neural solution (GPDNS) is proposed to address this. To illustrate the effectiveness of the GPDNS model in solving the QOQC system, numerical simulations are provided. Overall, this paper presents the potential of innovative approaches like the ACP framework to enhance our capabilities in addressing challenging optimization systems. © 2023 IEEE.

关键词： ACP constraints differential neural solution numerical simulation Quadratic optimization with quadratic

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Robustness challenges in Reinforcement Learning based time-critical cloud resource scheduling: A Meta-Learning based solution

Robustness challenges in Reinforcement Learning based time-c...

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作者： Liu, Hongyun Chen, Peng Ouyang, Xue Gao, Hui Yan, Bing Grosso, Paola Zhao, Zhiming Informatics Institute University of Amsterdam Amsterdam1098 XH Netherlands Graduate School of Informatics University of Amsterdam Amsterdam1098 XH Netherlands School of Computer and Software Engineering Xihua University Chengdu610039 China School of Computer Science National University of Defense Technology Changsha410073 China College of Electrical and Control Engineering Shaanxi University of Science and Technology Xi'an710021 China School of Electrical and Electronic Engineering University of Adelaide Adelaide South Australia5005 Australia

Cloud computing attracts increasing attention in processing dynamic computing tasks and automating the software development and operation pipeline. In many cases, the computing tasks have strict deadlines. The cloud resource manager (e.g., orchestrator) effectively manages the resources and provides tasks Quality of Service (QoS). Cloud task scheduling is tricky due to the dynamic nature of task workload and resource availability. Reinforcement Learning (RL) has attracted lots of research attention in scheduling. However, those RL-based approaches suffer from low scheduling performance robustness when the task workload and resource availability change, particularly when handling time-critical tasks. This paper focuses on both challenges of robustness and deadline guarantee among such RL, specifically Deep RL (DRL)-based scheduling approaches. We quantify the robustness measurements as the retraining time and investigate how to improve both robustness and deadline guarantee of DRL-based scheduling. We propose MLR-TC-DRLS, a practical, robust Meta Deep Reinforcement Learning-based scheduling solution to provide time-critical tasks deadline guarantee and fast adaptation under highly dynamic situations. We comprehensively evaluate MLR-TC-DRLS performance against RL-based and RL advanced variants-based scheduling approaches using real-world and synthetic data. The evaluations validate that our proposed approach improves the scheduling performance robustness of typical DRL variants scheduling approaches with 97%–98.5% deadline guarantees and 200%–500% faster adaptation. © 2023 The Author(s)

关键词： Reinforcement learning

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A Loopless Distributed Algorithm for Personalized Bilevel Optimization

A Loopless Distributed Algorithm for Personalized Bilevel Op...

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IEEE Conference on Decision and control

作者： Youcheng Niu Ying Sun Yan Huang Jinming Xu College of Control Science and Engineering Zhejiang University Hangzhou China School of Electrical Engineering and Computer Science The Pennsylvania State University State College PA

This paper studies a class of personalized distributed bilevel optimization problems over networks, where nodes aim at jointly optimizing the sum of outer-level objectives that depend on the solution of inner-level optimization problems. The existing algorithms for distributed bilevel optimization problems usually require extra computation loops for estimating hypergradients. To facilitate computational efficiency, we develop a loopless distributed algorithm that employs certain steps to approximate the optimal solution of innerlevel optimization problems, and track Hessian-inverse-vector products in a recursive manner. We prove that for stochastic nonconvex-strongly-convex problems, the proposed algorithm achieves the state of the art O(∊ −2 ) communication cost, while improving the computational cost by O(1og(1/∊)). Numerical experiments validate our theoretical findings.

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Boolean matrix compressed sensing

Boolean matrix compressed sensing

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

作者： Liu, Qiang Soleymani, Mahdi Mahdavifar, Hessam National Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Halıcıoğlu Data Science Institute University of California La Jolla San DiegoCA92093 United States Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States

ISBN: (纸本)9798350368741

In real-world datasets, leveraging the low-rank and sparsity properties enables developing efficient algorithms across a diverse array of data-related tasks, including compression, compressed sensing, matrix completion, etc. Notably, these two properties often coexist in certain real-world datasets, especially in Boolean datasets and quantized real-valued datasets. To harness the advantages of low-rank and sparsity simultaneously, we adopt a technique inspired by compressed sensing and Boolean matrix completion. Our approach entails compressing a low-rank sparse Boolean matrix by performing inner product operations with a randomly generated Boolean matrix. We then propose a decoding algorithms based on message-passing techniques to recover the original matrix. Our experiments demonstrate superior recovery performance of our proposed algorithms compared to Boolean matrix completion, with equal measurement requirements. © 2025 IEEE.

关键词： Belief Propagation Boolean Matrix Compressed Sensing Matrix Completion

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Image Visibility Graph Analysis of the Eye Disease Images 16

Image Visibility Graph Analysis of the Eye Disease Images

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16th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2023

作者： Wu, Dandan Ma, Zhiyi Yang, Xiaodong Jiang, Guangkang Yan, Chen Ma, Lu China University of Mining and Technology School of Computer Science and Technology Xuzhou221116 China China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Suzhou Vocational and Technical College Suzhou234000 China

ISBN: (纸本)9798350330755

Visibility graph algorithm is a widely used time series complex network transformation algorithm. It has been mainly applied to one-dimensional or multidimensional time series, while many real-life objects, such as images, cannot be represented by sequences. In this paper, we focus on two-dimensional images and propose a novel method of image visibility graph network (IVGN) with redefined node-degree features. We use the staining images of corneal ulcer of eye as the research object and demonstrate the application of IVGN to medical images. Our method consists of the following steps: (1) We construct a novel IVGN by treating each pixel as a node and connecting the visible pixels. We compute the average node degree of the IVGN for ocular pathology image analysis. (2) Based on the IVGN, we extract the node-degree features of the visible images and map them to a new degree topology, which is used for image enhancement. (3) By doing so, we build a gray co-occurrence matrix based on the degree topology and extract its four parameters, showing the role of the degree topology in image texture extraction. (4) As a result, we use the proposed contrast-based descriptors to achieve effective detection of eye staining images with different categories and severity levels. © 2023 IEEE.

关键词： Pixels

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C4F6 Etching Characteristics for High-Aspect-Ratio Etching of SiO2 Films Using an Inductively Coupled Plasma Etching System With Low-Frequency Bias Power

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Plasma Processes and Polymers 2025年第6期22卷

作者： Wei, Jiachen Woo, Byungjun Lee, DaeKug Jeong, Ki-Hyeok Kwon, Kwang-Ho Department of Control and Instrumentation Engineering Korea University-Sejong Campus Sejong Korea Republic of Department of Computer and Information Science Korea University-Sejong Campus Sejong Korea Republic of

In this study, the etching characteristics of C4F6 gas are investigated using inductively coupled plasma (ICP) etching equipment to apply a high-aspect-ratio etching process to SiO2. The use of a CF4 + C4F6 + He gas mixture in the ICP etching system provides a lower F atom density, a higher polymerization capacity with increasing C4F6 gas proportion, and better SiO2/amorphous carbon layer selectivity. With an increase in the C4F6 gas mixing ratio, the bowing phenomenon is alleviated, and a vertically etched profile is formed regardless of the source and bias power. The etching characteristics demonstrate that ICP etching using C4F6 gas is an excellent alternative to capacitively coupled plasma (CCP) etching for the development of next-generation high-aspect-ratio-contact etching processes. © 2025 Wiley-VCH GmbH.

关键词： Aspect ratio

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Unified Temporal Erasable Itemset Mining with a Lower-Bound Strategy

Unified Temporal Erasable Itemset Mining with a Lower-Bound ...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Hong, Tzung-Pei Li, Jia-Xiang Tsai, Yu-Chuan Huang, Wei-Ming National University of Kaohsiung Department of Computer Science and Information Engineering Kaohsiung Taiwan National Sun Yat-Sen University Department of Computer Science and Engineering Kaohsiung Taiwan National University of Kaohsiung Library and Information Center Kaohsiung Taiwan China Steel Inc Department of Electrical and Control Kaohsiung Taiwan

ISBN: (纸本)9781665480451

Erasable itemset mining has been a valuable mining problem for manufacturers. It can extract less profitable materials from a product dataset and provide managers with good decision-making and a trade-off between cost and profit. However, the traditional erasable itemset mining methods seldom consider the time factor. For time-sensitive industries such as agro-processors, the time range is important in determining which materials are less profitable. Hong et al. first proposed the concept of temporal erasable itemset mining and seven lifespan options. They also proposed a unified temporal erasable (UTE) mining algorithm for getting incomplete temporal erasable itemsets. Howerever, the UTE algorithm does not satisfy the property of downward closure. In this work, we propose an improved algorithm to improve the performance of the UTE algorithm based on a lower-bound strategy and satisfying the property of downward closure. The proposed algorithm uses a hash table to store information that will be reused during the mining process to avoid scanning a dataset multiple times. The designed lower-bound strategy can preserve the downward closure property, narrowing the search space of candidate itemsets. In numerical experiments, we compare the performance using several metrics between the proposed method and the previous work. From the results of experiments, our proposed method outperforms the existing method on various metrics, such as execution time and the number of candidate erasable itemsets. © 2022 IEEE.

关键词： Data mining

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Home Care Assistance Solution based on a Software Multi-Agents System 24

Home Care Assistance Solution based on a Software Multi-Agen...

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24th International Conference on control Systems and computer science, CSCS 2023

作者： Rasras, Mohammad Marin, Iuliana Radu, Serban University Politehnica of Bucharest Doctoral School of Automatic Control and Computers Bucharest Romania University Politehnica of Bucharest Dept. of Engineering in Foreign Languages Bucharest Romania University Politehnica of Bucharest Dept. of Computer Science Bucharest Romania

ISBN: (纸本)9798350313390

A smart home allows automated technology to control systems and appliances to assist daily life activities. In the current work, a prototype of a designed smart home health-aware system is presented. Three predefined ruled agents have been used to gather data, communicate between themselves, interpret the data based on several machine learning algorithms to predict abnormality for cardiac conditions. The paper also compares results obtained by running five machine learning algorithms. The agents function in accordance with predefined dataset describing residents ' age, gender, height, weight, systolic and diastolic blood pressure, cholesterol, and glucose levels, smoking and alcohol consumption habits, and lastly, physical activity. Our plan is to simplify ubiquitous health monitoring for smart home's residents. The proposed solution aims to monitor parametric measurements to alert health specialists in case of emergencies. © 2023 IEEE.

关键词： Multi agent systems

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