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IEEE Conference on Decision and control

作者： Filippos Fotiadis Kyriakos G. Vamvoudakis Zhong-Ping Jiang School of Aerospace Engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical and Computer Engineering Control and Networks Lab Tandon School of Engineering New York University Brooklyn USA

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

In this work, we consider an actuator redundant system, i.e., a system with more actuators than the number of effective control inputs, and bring together connections between control allocation, actuator selection, and learning. In this kind of systems, the actuator commands can be chosen to meet a given control objective while still having leftover degrees of freedom to use towards minimizing the overall actuation energy. We show that this energy can be further minimized by optimally selecting the actuators themselves, which we perform in two different scenarios; first, in the case where the control objective is not known beforehand; and second, in the case where the control objective is defined to be a stabilizing state feedback controller. To relax the requirement for knowledge of the system’s plant matrix, we compose a novel learning mechanism based on policy iteration, which computes the anti-stabilizing solution to an associated algebraic Riccati equation using trajectory data. Simulations are performed that demonstrate our approach.

关键词： Actuators State feedback Computational modeling Riccati equations Optimal control Mathematical models Real-time systems

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On the synergetic relationship between Circular Economy and Resilience: findings from a systematic literature review

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IFAC-PapersOnLine 2022年第10期55卷 2869-2874页

作者： Giovanni Francesco Massari Alessandro Annarelli Simonetta Primario Gloria Puliga Department of Mechanics Mathematics and Management Polytechnic University of Bari Italy Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Industrial Engineering University of Naples Federico II Italy School of Industrial Engineering LIUC - Cattaneo University Italy

Nowadays, industrial firms are increasingly required to develop resilient supply chains to better face turbulent environments by adapting to unforeseen and frequent disruptions. In this regard, researchers strongly agree that fostering innovation toward circular business models can influence resilience capability development. Findings, however, are still fragmented and sparse. To this aim, a systematic literature review of previous studies is conducted. The results of content analyses are presented, and their implications discussed.

关键词： Circular Economy resilience circular business model risk

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DIFFUSION MODELS FOR EARTH OBSERVATION USE-CASES: FROM CLOUD REMOVAL TO URBAN CHANGE DETECTION

arXiv

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arXiv 2023年

作者： Sanguigni, Fulvio Czerkawski, Mikolaj Papa, Lorenzo Amerini, Irene Le Saux, Bertrand Φ-lab ESRIN European Space Agency FrascatiI-00044 Italy Department of Computer Control and Management Engineering AlcorLab Sapienza University of Rome Via Ariosto 25 Rome00185 Italy

The advancements in the state of the art of generative Artificial Intelligence (AI) brought by diffusion models can be highly beneficial in novel contexts involving Earth observation data. After introducing this new family of generative models, this work proposes and analyses three use cases which demonstrate the potential of diffusion-based approaches for satellite image data. Namely, we tackle cloud removal and inpainting, dataset generation for change-detection tasks, and urban replanning. © 2023, CC BY.

关键词： Observatories

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Adaptive Marginalized Semantic Hashing for Unpaired Cross-Modal Retrieval

arXiv

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arXiv 2022年

作者： Luo, Kaiyi Zhang, Chao Li, Huaxiong Jia, Xiuyi Chen, Chunlin The Department of Control Science and Intelligence Engineering Nanjing University Nanjing210093 China The School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210014 China

In recent years, Cross-Modal Hashing (CMH) has aroused much attention due to its fast query speed and efficient storage. Previous literatures have achieved promising results for Cross-Modal Retrieval (CMR) by discovering discriminative hash codes and modality-specific hash functions. Nonetheless, most existing CMR works are subjected to some restrictions: 1) It is assumed that data of different modalities are fully paired, which is impractical in real applications due to sample missing and false data alignment, and 2) binary regression targets including the label matrix and binary codes are too rigid to effectively learn semantic-preserving hash codes and hash functions. To address these problems, this paper proposes an Adaptive Marginalized Semantic Hashing (AMSH) method which not only enhances the discrimination of latent representations and hash codes by adaptive margins, but also can be used for both paired and unpaired CMR. As a two-step method, in the first step, AMSH generates semantic-aware modality-specific latent representations with adaptively marginalized labels, which enlarges the distances between different classes, and exploits the labels to preserve the inter-modal and intra-modal semantic similarities into latent representations and hash codes. In the second step, adaptive margin matrices are embedded into the hash codes, and enlarge the gaps between positive and negative bits, which improves the discrimination and robustness of hash functions. On this basis, AMSH generates similarity-preserving hash codes and robust hash functions without strict one-to-one data correspondence requirement. Experiments are conducted on several benchmark datasets to demonstrate the superiority and flexibility of AMSH over some state-of-the-art CMR methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Hash functions

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Mapping cultural heritage sites at risk: A support tool for heritage sites management

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Journal of Urban Management 2025年

作者： Brandano, Maria Giovanna Conti, Chiara Modica, Marco Urso, Giulia Gran Sasso Science Institute – Social Sciences Viale Luigi Rendina 26-28 L'Aquila 67100 Italy Department of Computer Control and Management Engineering “Antonio Ruberti” of the University La Sapienza Italy

Under the threat of climate change, the world has become increasingly unsafe, with extreme weather events causing devastation and high economic costs. These impacts are heterogeneous because of the interaction between different regional climate changes and the varying socio-economic characteristics of affected places. Climate change also impacts the management of cultural heritage sites. We then propose a method to identify heritage sites at risk from climate change issues, considering the single components of risk, namely both the natural hazard and the resilient/vulnerable local characteristics that may increase or mitigate the potential damage. The link between the natural and human spheres is, in fact, crucial for the development of suitable mitigation and prevention strategies, particularly relevant for developing countries that suffer from scarce economic resources. Overall, this work aims to provide a method to detect heritage sites at risk and a decision support tool for strategically managing cultural sites. We focus on Italy since it is one of the countries with a higher endowment of cultural heritage. However, thanks to its high replicability, this tool might be exported and adopted in different contexts and scenarios. © 2025 The Authors

关键词： Climate change Cultural heritage Impacts Risks

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Depth Image Restoration for High-Level Vision Tasks

Depth Image Restoration for High-Level Vision Tasks

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Artificial Intelligence, Human-computer Interaction and Robotics (AIHCIR), International Conference on

作者： Ying Gao Shaojing Song Xie Ding Yu Wang Xiang Sun Shaoqiu Zheng School of Computer and Information Engineering Shanghai Polytechnic University Shanghai China Data Intelligence Product Department Wonders Information Co. Ltd Shanghai China School of Intelligent Manufacturing and Control Engineering Shanghai Polytechnic University Shanghai China

High-level computer vision tasks often necessitate large-scale, high-quality depth images. However, real-world depth images are unsuitable for direct application in experimental studies due to their inherent noise and presence of holes. Consequently, image restoration becomes imperative. Large-scale hole repair often proves ineffective in the face of realistic and complex degraded scenes. To address this issue, our research introduces the fast Fourier convolution and a Multi-Scale Attention mechanism into an unsupervised learning network. This integration expands the network's sensory field and enhances perception of spatial feature details within the depth image. Its objective is to improve the restoration performance of depth images that possess substantial regions of missing depth values. Our experimental results demonstrate significant enhancements achieved by our restoration algorithm. Specifically, relative to the original depth images, the algorithm improves PSNR and SSIM by 25% and 60%. On average, improvements exceed the baseline by 9% and 15%, respectively. Moreover, our algorithm outperforms the original depth images in target detection, with the average precision values for human pose recognition tasks increasing by 24% and 25%, respectively. Compared to the baseline, these AP values experience additional enhancements of 11% and 18%, respectively. The restoration algorithm presented in this paper not only achieves visually pleasing results in terms of image quality but also significantly enhances the performance of downstream advanced vision tasks.

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Range-Limited Pursuit-Evasion

Range-Limited Pursuit-Evasion

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Isaac E. Weintraub Alexander Von Moll Meir Pachter Air Force Research Laboratory Control Science Center Wright-Patterson AFB OH USA Electrical and Computer Engineering Air Force Institute of Technology Wright-Patterson AFB OH USA

In pursuit-evasion the objective of the pursuer is to capture the evader. In this work, the faster pursuer is modeled to have limited range and therefore optimal strategies for the pursuer and evader change. Depending upon the range limits of the pursuer the evader may evade capture by the pursuer. This paper describes the optimal strategies and nuances that appear for point-capture or when the pursuer is endowed with a non-zero capture radius.

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Optimizing Membrane Distillation Configuration for Superior Heat and Mass Transfer

Optimizing Membrane Distillation Configuration for Superior ...

引用

Emerging Trends in Smart Technologies (ICETST), 2020 International Conference on

作者： Muhammad Arslan Xian Haizhen M. Nouman Khalid Khan Kashif Ali Zaid Bin Tariq Baig School of energy power and mechanical engineering North China Electric Power University Beijing China School of Mechanical Engineering University of Engineering & Technology Lahore Pakistan School of renewable and clean energy North China Electric Power University Beijing China Department of Control and Computer Science North China Electric Power University Beijing China

ISBN: (数字)9798331515850

ISBN: (纸本)9798331515867

Membrane distillation (MD) has emerged as a promising technique for desalination and water purification, offering potential advantages in terms of energy efficiency and operational flexibility. However, challenges related to heat and mass transfer inefficiencies limit its widespread adoption. This study explores the use of innovative materials and optimized configurations to enhance heat and mass transfer in direct contact membrane distillation (DCMD) systems. By integrating advanced hybrid membranes with nano-coating techniques and evaluating their performance through simulation-based methodologies, we demonstrate significant improvements in thermal conductivity, mass transfer efficiency, and fouling resistance. The results indicate that the newly developed hybrid membranes not only enhance heat and mass transfer rates but also maintain high separation efficiency, ultimately leading to improved overall system performance. These findings provide a foundation for the further development of MD technologies and suggest pathways for overcoming existing limitations, paving the way for more sustainable and efficient water treatment solutions.

关键词： Temperature distribution Visualization Correlation Three-dimensional displays Thermal resistance Simulation Water heating Conductivity Feeds Heat transfer

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Automated Optical Inspection for Quality control in PCBA assembly lines: a case study for Point of Sale Devices Production Lines

Automated Optical Inspection for Quality Control in PCBA ass...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Kerem Aras Syed Saad Saif Alessandro Giuseppi Vedat Coskun R&D Center Token Financial Technologies Istanbul Türkiye Dept. of Computer Control and Management of Rome La Sapienza Rome Italy Dept. of Software Engineering Istanbul Atlas University Istanbul Turkiye

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

This paper reports on the design and development of a customized Automated Optical Inspection (AOI) solution aimed at detecting defects in a production line related to the correct mounting of integrated circuits. Contrary to most solutions avail- able on the market, the developed system relies on deep learning to be able to perform detailed real-time visual inspections of components without the need to compare the captured photos with any reference images/golden sample. The proposed solution was designed to also provide good generalization capabilities, accommodating visual changes in the environment and in the structure of the component being produced. A custom testing machine was built in order to perform real-time inferences and validate the simulation results in a real-world setting.

关键词： Visualization Production Optical fiber networks Optical imaging Adaptive optics Real-time systems Automatic optical inspection

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Joint Data Compression and Task Scheduling for LEO Satellite Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： He, Lijun Li, Shiyin Jia, Ziye Wang, Juncheng Han, Zhu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Xidian University State Key Laboratory of Integrated Services Networks Shaanxi Xi'an710071 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing210000 China Hong Kong Baptist University Department of Computer Science China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

We investigate a joint data compression and task scheduling problem for Low Earth Orbit Satellite Networks (LEOSNs), to maximize the sum weights of tasks while simultaneously minimizing the total data loss. First, we propose a novel Multi-Resource Conflict Graph (MRCG) model to characterize the intertwined communication and computation allocation conflicts inherent in typical data offloading processes of LEOSNs. Leveraging the proposed MRCG model, we then formulate the studied problem for LEOSNs as a linear integer program, to maximize the normalized weighted sum of both the sum task weight and the total data loss. We further explore the intrinsic structure of the linear integer program to propose an efficient solution using the Semi-Definite Relaxation (SDR) technique. Finally, the simulation results underscore that the synergistic optimization of data compression and task scheduling significantly facilitates the data offloading efficiency of LEOSNs, and the performances surpass existing benchmarks across a broad range of system parameters. © 1967-2012 IEEE.

关键词： Integer programming

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