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Scheduling Bi-Objective Lot-Streaming Hybrid Flow Shops with Consistent Sublots via an Enhanced Artificial Bee Colony Algorithm

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Complex System Modeling and Simulation 2025年第1期5卷 46-67页

作者： Benxue Lu Kaizhou Gao Peiyong Duan Adam Slowik School of Computer Science Liaocheng UniversityLiaocheng 252000China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Information and Automation Engineering Qilu University of TechnologyJinan 250353China Department of Electronics and Computer Science Koszalin University of TechnologyKoszalin 75-453Poland

This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots(Bi-HFSP_CS).The objectives are to minimize the makespan and total energy ***,the Bi-HFSP_CS is formalized,followed by the establishment of a mathematical ***,enhanced version of the artificial bee colony(ABC)algorithms is proposed for tackling the Bi-HFSP_***,fourteen local search operators are employed to search for better *** different Q-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration ***,the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm,its three variants,and three effective algorithms in resolving 95 instances of 35 different *** experimental results and analysis showcase that the enhanced ABC algorithm combined with Q-learning(QABC1)demonstrates as the top performer for solving concerned *** study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength,offering beneficial perspectives for exploration and research in relevant domains.

关键词： hybrid flow shop scheduling Q-learning lot streaming local search

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Change Categories Based on Mutable Artifacts in PLC Control Software Projects

Change Categories Based on Mutable Artifacts in PLC Control ...

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Industrial Cyber-Physical systems (ICPS)

作者： Yizhi Wang Birgit Vogel-Heuser Eva-Maria Neumann Michael Gnadlinger Ziming Wen Jan Wilch Bernhard Rupprecht Institute of Automation and Information Systems TUM School of Engineering and Design Technical University of Munich Garching Germany

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

Automated Production systems are highly complex mechatronic systems. The increasing complexity of automation software is a main challenge for companies to remain competitive. Added functionality entails software changes, which may cause side effects. Static code analysis and change impact analysis are key methods in computer science for assessing software regarding side effects. However, the requirements of real-time capability, reliability, and mixing different Programmable Logic Controller programming languages in the automation software lead to new requirements for code analysis and change management. This paper introduces a set of change categories designed to provide understandable and comprehensive classifications of changes in automation software. Mutable (i.e., changed or modified between versions) software artifacts serve to differentiate change categories. Aiming for unambiguousness and completeness, this set of categories supports the further work of the change analysis, such as automatic change detection and visualization. The change categories are evaluated through an industrial software project programmed in Siemens TIA Portal comprising 262 program organization units in the health sector.

关键词： Visualization Production systems automation Codes Mechatronics Programmable logic devices Software

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Drogue detection for autonomous aerial refueling via hybrid pigeon-inspired optimized color opponent and saliency aggregation

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Chinese Journal of Aeronautics 2024年第5期37卷 27-38页

作者： Tongyan WU Haibin DUAN Yanming FAN State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China AVIC Shenyang Aircraft Design and Research Institute Shenyang 110035China

Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and *** detection based on image intrinsic cues can achieve fast detection,but with poor *** studies reveal that optimization-based methods provide accurate and quick solutions for saliency *** paper presents a hybrid pigeon-inspired optimization method,the optimized color opponent,that aims to adjust the weight of color opponent channels to detect the drogue *** can optimize the weights in the selected aerial refueling scene offline,and the results are applied for drogue detection in the scene.A novel algorithm aggregated by the optimized color opponent and robust background detection is presented to provide better precision and *** results on benchmark datasets and aerial refueling images show that the proposed method successfully extracts the saliency region or drogue and exhibits superior performance against the other saliency detection methods with intrinsic *** algorithm designed in this paper is competent for the drogue detection task of autonomous aerial refueling.

关键词： Autonomous aerial refueling Drones Hybrid pigeon-inspired optimization Color opponent Saliency detection Saliency aggregation

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Data-Filtered Prediction with Decomposition and Amplitude-Aware Permutation Entropy for Workload and Resource Utilization in Cloud Data Centers

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IEEE Internet of Things Journal 2025年第12期12卷 19189-19201页

作者： Yuan, Haitao Hu, Qinglong Wang, Meijia Wang, Shen Bi, Jing Buyya, Rajkumar Shi, Shuyuan Yang, Jinhong Zhang, Jia Zhou, MengChu Beihang University School of Automation Science and Electrical Engineering Beijing100191 China City University of Hong Kong Department of Computer Science Hong Kong999077 Hong Kong Beijing University of Technology School of Software Engineering The Faculty of Information Technology Beijing100124 China Lab School of Computing and Information Systems MelbourneVIC3010 Australia Beihang University School of Integrated Circuit Science and Engineering Beijing China CSSC Systems Engineering Research Institute Beijing China Southern Methodist University Department of Computer Science The Lyle School of Engineering DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

In recent years, cloud computing has witnessed widespread applications across numerous organizations. Predicting workload and computing resource data can facilitate proactive service operation management, leading to substantial improvements in quality of service and cost efficiency. However, these data often exhibit non-linearity, high volatility, and interdependencies across different categories, presenting challenges for accurate forecasting. Consequently, there is a critical need to develop a method that thoroughly and comprehensively analyzes all available data to forecast future trends effectively. This work proposes a novel integrated data-enhanced prediction model named SVAPI for achieving high-accuracy workload prediction in cloud computing systems. SVAPI employs the Savitzky-Golay filter, Variational mode decomposition, and the mode selection based on Amplitude-aware Permutation entropy for feature processing, whose features are subsequently utilized by Informer for multivariate joint analysis of the enhanced data, achieving high-precision prediction. Ablation and comparative experiments with advanced prediction models are conducted on the Google cluster trace and other typical datasets. Realistic data-driven results indicate that SVAPI improves the prediction accuracy by 37.7% compared to the original Informer, with each module contributing to the performance enhancement. Furthermore, compared with Autoformer, SVAPI enhances the prediction accuracy of workload, CPU, and memory by 65.6%, 66.9%, and 70.8%, respectively, demonstrating that SVAPI owns strong abilities in noise filtering, feature processing, and multivariate joint analysis for achieving higher prediction accuracy. © 2014 IEEE.

关键词： Quality of service

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Measurement Methods for Software Execution Time on Heterogeneous Edge Devices

Measurement Methods for Software Execution Time on Heterogen...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Bernhard Rupprecht Birgit Vogel-Heuser Eva-Maria Neumann Institute of Automation and Information Systems School of Engineering and Design Technical University of Munich

Due to emerging data-driven approaches in factory automation in the course of Industry 4.0, automated Production systems must incorporate additional algorithms for data collection and processing tasks. However, strict real-time requirements, resource constraint devices, such as Programmable Logic Controllers or low-power edge devices, and network bandwidth limitations pose a challenge to selecting suitable algorithms for specific edge devices and vice-versa, also known as software-hardware co-design. Measuring the execution time of an algorithm or code snippet is therefore a crucial part of algorithm and hardware assessment and is incorporated in numerous benchmarks. However, this is not trivial since most existing time measurement methods are designed with specific devices in mind with limited portability to different hardware platforms. Thus this paper provides an overview of the properties of selected execution time measurement methods to support their feasible deployment in edge computing, including legacy systems. A time measurement code snippet for Beckhoff Programmable Logic Controllers and recommendations for implementing software-based timing functions for heterogeneous devices help shorten development times. Besides, comparing execution time measurement methods highlights the challenges of creating a generic cross-platform benchmark in future research.

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Optimization design of Network Attack and Defense Scenarios in Intelligent Clusters 9

Optimization Design of Network Attack and Defense Scenarios ...

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9th IEEE International Conference on Data Science in Cyberspace, DSC 2024

作者： Wang, Chengyue Liu, Yang Qiao, Yaojun Han, Daoqi Lu, Yueming Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing China Beijing Institute of Technology The Beijing Institute of Astronautical Systems Engineering School of Automation Beijing China Beijing University of Posts and Telecommunications School of Cyberspace Security Beijing China

ISBN: (纸本)9798350391367

Intelligent cluster networks are crucial infrastructures with a high susceptibility to cyber threats, necessitating the optimization of existing security protocols and resource allocation schemes to dynamically mitigate these risks. This optimization serves as the cornerstone for next-generation security measures. In the realm of defense strategy research, accurately depicting network attack and defense scenarios is pivotal. However, much of the existing research in this domain primarily focuses on theoretical scenarios, lacking a thorough analysis of real-world characteristics, thereby hindering the efficacy of algorithmic applications. To address this gap, we utilize incomplete information and zero-sum game theory to establish and refine attack and defense models within intelligent cluster networks. Leveraging these models, a game simulation system is constructed using the Gym toolkit to enhance the realism of network security simulation scenarios. Additionally, we design six typical attack strategies to more precisely simulate common attacks within intelligent networks, thereby facilitating the development of novel defensive strategies. Experimental results demonstrate that the proposed network attack and defense simulation model is well-designed, and the performance of the attack strategies closely mirrors real-world attacks. This provides a simulation environment closely resembling actual scenarios, thereby offering a robust platform for the exploration of defense strategies within intelligent cluster networks. © 2024 IEEE.

关键词： Resource allocation

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Research on maximizing throughput of high-speed railway system by allocating train-to-train communication resources 24

Research on maximizing throughput of high-speed railway syst...

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8th International Conference on Electronic information Technology and Computer engineering, EITCE 2024

作者： Lv, Qianhui Gao, Yunbo Xie, Jianli Cheng, Xuan Ban, Yuhao School of Automation and Electrical Engineering Lanzhou Jiaotong University Gansu Lanzhou China School of Electronics and information engineering Lanzhou Jiaotong University Gansu Lanzhou China Lanzhou Railway Design Institute Co. LTD Gansu Lanzhou China

ISBN: (纸本)9798400710094

The realization of train-to-train (T2T) communication in 5G-R systems can effectively reduce the communication delay of trains and improve the safety and efficiency of train operation, but in this communication process, due to the coexistence of T2T communication and train-to-ground (T2G) communication, the problem of co-frequency interference will inevitably exist. To address this problem, this paper firstly proposes the Weighted Bifurcation Graph-based Resource Allocation (WBGRA) algorithm to reasonably allocate channel resources, which divides the channel resource allocation process into two parts, i.e., allocating channel resources for T2G users and reusing T2G users’ resources by T2T users, and the reuse process takes into account whether the reuse conditions are satisfied;and then the game theory is used to control the power. Simulation of the proposed algorithm shows that it gives the optimal solution of the optimization objective. © 2024 Copyright held by the owner/author(s).

关键词： Railroads

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Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

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Online instantaneous angular speed estimation from vibration on low-power embedded systems evaluated on a gas foil bearing use case

Online instantaneous angular speed estimation from vibration...

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作者： Kliemank, Martin Leonhard Rupprecht, Bernhard Ahmadzadeh, Majid Brederlow, Ralf Stahl, Karsten Liebich, Robert Vogel-Heuser, Birgit Gühmann, Clemens Chair of Electronic Measurement and Diagnostic Technology Technische Universität Berlin Germany Institute of Automation and Information Systems TUM School of Engineering and Design Technical University of Munich Germany Chair of Engineering Design & Product Reliability Technische Universität Berlin Germany Chair of Circuit Design TUM School of Computation Information and Technology Technical University of Munich Germany Institute of Machine Elements TUM School of Engineering and Design Technical University of Munich Germany

This study presents an algorithm for estimating the instantaneous angular speed (IAS) from vibrations in low-power embedded systems, evaluated on the use-case of a gas foil bearing. While there are numerous methods for IAS estimation, they have thus far only been evaluated using industrial-grade sensors and data acquisition systems with high computational resources. To boost the application of IAS estimation methods in embedded applications, like sensor-integrating machine elements, this paper highlights and evaluates an algorithm for low-power embedded systems. Theoretical analysis and benchmarks on various low-power microcontrollers demonstrate its feasibility for real-time application. Furthermore, evaluation with lower sampling rates and ADC resolutions confirms compatibility with small-scale sensors typical in embedded systems. For good performance, a typical Cortex-M4-based MCU (e.g. 1.12 ms estimation time using 1024 data points) and a sensor with 8-bit resolution and 6400 Hz sampling rate would suffice. These findings establish the algorithm's readiness for diverse embedded applications. © 2024

关键词： Microcontrollers

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TJ-FlyingFish:An Unmanned Morphable Aerial-Aquatic Vehicle System

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无人系统（英文） 2024年第2期12卷 409-428页

作者： Xuchen Liu Minghao Dou Ruixin Yan Dongyue Huang Songqun Gao Biao Wang Jinqiang Cui Qinyuan Ren Lihua Dou Zhi Gao Jie Chen Ben M.Chen Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghaiP.R.China Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongP.R.China Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongP.R.China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjingJiangsuP.R.China Peng Cheng Laboratory ShenzhenGuangdongP.R.China College of Control Science and Engineering Zhejiang UniversityHangzhouZhejiangP.R.China School of Automation Beijing Institute of TechnologyBeijingP.R.China School of Remote Sensing and Information Engineering Wuhan UniversityWuhanHubeiP.R.China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghaiP.R.China

In this paper,we present in this work a fairly complete process for developing an unmanned aerial-aquatic vehicle system,TJ-FlyingFish,which includes an innovative design methodology of the aerial-aquatic platform and the cross-medium localization,dynamics modeling,and flight control *** development faces the challenge how to manipulate locomotion effectively in both water and air which presents substantial differences in fluid ***,there are difficulties in perception and navigation because of the discontinuity of *** cope with these challenges,we designed an innovative unmanned aerial-aquatic vehicle with an optimized dual-speed and tilting propulsion *** rotors/propellers operate in different ranges of rotating speed in the two different mediums,providing sufficient thrust and ensuring output ***,thrust vectoring is achieved by rotating each propulsion unit around its mounted arm,facilitating agile underwater *** key component of our approach is a sophisticated multi-sensor-based cross-medium localization system that combines SLAM,sensor synchronization,and data capture mechanisms,enabling seamless transitions between aerial and aquatic environments,and supporting autonomous *** results are fully validated through actual flight experiments.

关键词： Unmanned aerial-vehicles cross-medium locomotion cross-medium localization

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