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Improved Synthesis of Nondeterministic Publicly-Known Edit Functions for Opacity Enforcement

IEEE Transactions on Automatic control 2025年

作者： Liu, Rongjian Hadjicostis, Christoforos N. Chongqing Normal University National Center for Applied Mathematics in Chongqing Chongqing401331 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus

In this paper, we investigate the synthesis problem of edit functions for opacity enforcement in systems modelled as partially-observed finite-state automata. For better plausible deniability for the edit functions, in cases where the intruder may learn/know their existence, a synthesis problem for nondeterministic edit functions under a publicly-known setting was introduced in the literature, but not yet fully solved. In light of this, we revisit the publicly-known edit mechanism by proposing a sound and complete approach for solving the synthesis problem of nondeterministic publicly-known edit functions. For practical applications, the edit function is assumed to have limited erasure and insertion ability. Our approach is based on a new labelled finite-state structure, and results in wider applicability than previously-proposed in the literature. © 1963-2012 IEEE.

关键词： Discrete event simulation

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Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks

arXiv

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arXiv 2022年

作者： Davydov, Alexander Jafarpour, Saber Abate, Matthew Bullo, Francesco Coogan, Samuel The Center for Control Dynamical Systems and Computation University of California Santa Barbara United States The School of Electrical and Computer Engineering Georgia Institute of Technology United States

We use interval reachability analysis to obtain robustness guarantees for implicit neural networks (INNs). INNs are a class of implicit learning models that use implicit equations as layers and have been shown to exhibit several notable benefits over traditional deep neural networks. We first establish that tight inclusion functions of neural networks, which provide the tightest rectangular over-approximation of an input-output map, lead to sharper robustness guarantees than the well-studied robustness measures of local Lipschitz constants. Like Lipschitz constants, tight inclusions functions are computationally challenging to obtain, and we thus propose using mixed monotonicity and contraction theory to obtain computationally efficient estimates of tight inclusion functions for INNs. We show that our approach performs at least as well as, and generally better than, applying state-of-the-art interval bound propagation methods to INNs. We design a novel optimization problem for training robust INNs and we provide empirical evidence that suitably-trained INNs can be more robust than comparably-trained feedforward networks. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep neural networks

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Event-triggered leader-following formation control for multi-agent systems under communication faults: application to a fleet of unmanned aerial vehicles

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Journal of Systems engineering and Electronics 2021年第5期32卷 1014-1022页

作者： VAZQUEZ TREJO Juan Antonio GUENARD Adrien ADAM-MEDINA Manuel PONSART Jean-Christophe CIARLETTA Laurent ROTONDO Damiano THEILLIOL Didier Research Center for Automatic Control of Nancy University of LorraineNancy F-54000France Electronic Engineering Department National Institute of Technology of MexicoCuernavaca Morelos 62490Mexico Lorraine Research Laboratory in Computer Science and Its Applications University of LorraineNancy F-54000France University of Stavanger Department of Electrical and Computer EngineeringStavanger 4021Norway

The main contribution of this paper is the design of an event-triggered formation control for leader-following consensus in second-order multi-agent systems(MASs)under communication *** the agents must follow the trajectories of a virtual leader despite communication faults considered as smooth time-varying delays dependent on the distance between the *** matrix inequalities(LMIs)-based conditions are obtained to synthesize a controller gain that guarantees stability of the synchronization *** on the closed-loop system,an event-triggered mechanism is designed to reduce the control law update and information exchange in order to reduce energy *** proposed approach is implemented in a real platform of a fleet of unmanned aerial vehicles(UAVs)under communication faults.A comparison between a state-of-the-art technique and the proposed technique has been provided,demonstrating the performance improvement brought by the proposed approach.

关键词： event-triggered leader-following consensus communication fault formation control unmanned aerial vehicle(UAV) experimental result

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Forecasting Slow-Wave Sleep Deficiency Through Stress-Related Markers in Forehead EEG

Forecasting Slow-Wave Sleep Deficiency Through Stress-Relate...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Su, Cheng-Hua Ko, Li-Wei Jung, Tzyy-Ping Onton, Julie Tzou, Shey-Cherng Juang, Jia-Chi Hsu, Chung-Yao Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Department of Biomedical Science and Environmental Biology Kaohsiung807 Taiwan Institute for Neural Computation Institute of Engineering in Medicine University of California San Diego La Jolla CA92093 United States College of Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute for Neural Computation University of California San Diego La Jolla CA92093 United States Kaohsiung Medical University Hospital Sleep Disorders Center Department of Neurology Kaohsiung807 Taiwan College of Medicine Kaohsiung Medical University Department of Neurology Kaohsiung807 Taiwan

ISBN: (纸本)9781665410205

Sleep quality is critical for human well-being. Lack of sleep and poor sleep quality impair daily cognitive functions and health. While stress has been recognized as a detrimental factor on sleep quality, the relationship between pre-sleep stress level, resting EEG and subsequent sleep structure remains to be explored. This study presents a novel approach that evaluates pre-sleep stress levels using a 2-channel EEG to predict slow-wave sleep (SWS) deficiency. We recorded forehead EEG immediately before sleep onset, then utilized power spectra and entropy analysis to extract stress-related neurological features, including beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn), and spectral entropy (SpEn). We found that individuals with SWS deficiency exhibited signs of stress, such as a robust beta/delta correlation, higher alpha asymmetry, and increased FuzzEn. Conversely, individuals with ample SWS displayed weak beta/delta correlation and reduced FuzzEn in EEG recordings. Finally, we tested the robustness of the selected neuro markers with two supervised learning models and found that the selected markers predict SWS deficiency with an accuracy above 70%. Our study demonstrated that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. The proposed method can be integrated with a portable EEG device and sleep-improving interventions to develop a personalized sleep-improvement solution. © 2024 IEEE.

关键词： Sleep research

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Comparative Analysis of Different Sliding Mode control Approaches for Load Frequency control in Edge of the Grid System

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IET Generation, Transmission and Distribution 2025年第1期19卷

作者： Aich, Pritom Ahmed, Anis Shah, Rakibuzzaman Islam, Md Rabiul Roy, Naruttam Kumar Nasir, Ali Department of Electrical and Electronic Engineering Daffodil International University Dhaka Bangladesh Department of Electrical and Electronic Engineering Khulna University of Engineering & Technology Khulna Bangladesh Federation University Australia Mt HelenVIC Australia School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW Australia Control and Instrumentation Engineering Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Intelligent Manufacturing and Robotics King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

The integration of renewable energy sources (RESs) at the edge of the grid plays a contributory role in advancing the transition to a sustainable energy future. However, this transition introduces significant variability, which challenges the maintenance of frequency stability in power systems. To address the impacts of RES variability, various robust control strategies have been developed. This paper compares the performance of different advanced sliding mode control (SMC) approaches, i.e., super twisting (ST) algorithm-based second order sliding mode control (STSOSMC), second order sliding mode control (SOSMC), double integral sliding mode control (DISMC) and integral sliding mode control (ISMC) with conventional sliding mode control (SMC) for load frequency control with stochastic RESs such as biogas generators (BG) and wind-based doubly fed induction generators (DFIG). The impact of the advanced sliding mode controllers on the voltage and rotor angle stability of the system is also explored. The efficacy of the controllers is tested under different load disturbances, considering nonlinearities such as communication delay (CD), sensor inaccuracy (SI), governor dead band (GDB), and generation rate constraint (GRC). The results demonstrate that STSOSMC achieves superior frequency regulation with minimal chattering and outperforms other controllers in terms of settling time, overshooting, and undershooting in frequency deviation. The result also demonstrates the effectiveness of STSOSMC in managing the variability and disturbances of RESs. Therefore, it could be considered the most robust control mechanism from the edge of the grid system with high penetration of RESs. © 2025 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Robust control

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Spleen-preserving distal pancreatectomy from multi-port to reducedport surgery approach

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World Journal of Gastrointestinal Surgery 2023年第7期15卷 1501-1511页

作者： Ching-Lung Hsieh Tung-Sheng Tsai Cheng-Ming Peng Teng-Chieh Cheng Yi-Jui Liu Department of Computer Science and Information Engineering Feng Chia UniversityTaichung 40724TaiwanChina Department of Surgery Chung Shan Medical University HospitalTaichung 40201TaiwanChina PhD Program of Electrical and Communications Engineering Feng Chia UniversityTaichung 40724Taiwan School of Medicine Chung Shan Medical UniversityTaichung 40201Taiwan Da Vinci Minimally Invasive Surgery Center Chung Shan Medical University HospitalTaichung 40201Taiwan Department of Automatic Control Engineering Feng Chia UniversityTaichung 407Taiwan

BACKGROUND Minimally invasive pancreatic surgery via the multi-port approach has become a primary surgical method for distal pancreatectomy(DP)due to its advantages of lower wound pain and superior cosmetic *** studies have applied reduced-port techniques for DP in an attempt to enhance cosmetic outcomes due to the minimally invasive *** recent review studies have compared multi-port laparoscopic DP(LDP)and multi-port robotic DP(RDP);most of these studies concluded multi-port RDP is more beneficial than multi-port LDP for spleen ***,there have been no comprehensive reviews of the value of reduced-port LDP and reduced-port *** To search for and review the studies on spleen preservation and the clinical outcomes of minimally invasive DP that compared reduced-port DP surgery with multi-port DP *** The PubMed medical database was searched for articles published between 2013 and *** search terms were implemented using the following Boolean search algorithm:(“distal pancreatectomy”OR“left pancreatectomy”OR“peripheral pancreatic resection”)AND(“reduced-port”OR“single-site”OR“single-port”OR“dual-incision”OR“single-incision”)AND(“spleen-preserving”OR“spleen preservation”OR“splenic preservation”).A literature review was conducted to identify studies that compared the perioperative outcomes of reduced-port LDP and reduced-port *** Fifteen articles published in the period from 2013 to 2022 were retrieved using three groups of search *** studies were added after manually searching the related ***,10 papers were selected after removing case reports(n=3),non-English language papers(n=1),technique papers(n=1),reviews(n=1),and animal studies(n=1).The common items were defined as items reported in more than five papers,and data on these common items were extracted from all *** ten studies included a total of 337 patients(females/males:231/106)who underwent *** total,166 patients(females/male

关键词： Minimally invasive surgery Robotic distal pancreatectomy Laparoscopic distal pancreatectomy Spleen preservation Reduced-port Multi-port

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A Modified Dempster Shafer Approach to Classification in Surgical Skill Assessment

A Modified Dempster Shafer Approach to Classification in Sur...

引用

Iranian Conference on electrical engineering (ICEE)

作者： Arash Iranfar Mohammad Soleymannejad Behzad Moshiri Hamid D. Taghirad School of Electrical and Computer Engineering University College of Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is.

关键词：

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Unified Temporal Erasable Itemset Mining with a Lower-Bound Strategy

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

引用

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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Convergence of energy-based learning in linear resistive networks

arXiv

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arXiv 2025年

作者： Huijzer, Anne-Men Chaffey, Thomas Besselink, Bart van Waarde, Henk J. Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands CogniGron - Groningen Cognitive Systems and Materials Center Netherlands Control Group Department of Engineering University of Cambridge United Kingdom School of Electrical and Computer Engineering University of Sydney Australia

Energy-based learning algorithms are alternatives to backpropagation and are well-suited to distributed implementations in analog electronic devices. However, a rigorous theory of convergence is lacking. We make a first step in this direction by analysing a particular energy-based learning algorithm, Contrastive Learning, applied to a network of linear adjustable resistors. It is shown that, in this setup, Contrastive Learning is equivalent to projected gradient descent on a convex function, for any step size, giving a guarantee of convergence for the *** Codes 65K10, 68T05, 93B30, 93D99 © 2025, CC BY-SA.

关键词： Contrastive Learning

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On the Complexity of Computing the Minimum Mean Square Error of Causal Prediction

On the Complexity of Computing the Minimum Mean Square Error...

引用

American control Conference (ACC)

作者： Holger Boche Volker Pohl H. Vincent Poor School of Computation Information and Technology Technical University of Munich Munchen Germany Munich Center for Quantum Science and Technology (MCQST) Munchen Germany Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper gives a complete characterization of the complexity of computing the minimum mean square pre-diction error for wide-sense stationary stochastic processes. It shows that if the spectral density of the stationary process is a strictly positive, computable continuous function then the minimum mean square error (MMSE) is always a computable number. It is also shown that the computation of the MMSE is a $\neq P_computation$ complete problem on the set of strictly positive, polynomial-time computable, continuous spectral densities. This means that if, as widely assumed, $FP_computation\neq\neq P_computation$ , then there exist strictly positive, polynomial-time computable continuous spectral densities for which the computation of the MMSE is not polynomial-time computable. So under the widely accepted assumptions of complexity theory, the computation of the MMSE is generally much harder than $NP_computation$ complete problems.

关键词： Stochastic processes Mean square error methods Complexity theory

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