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Achieving Fine-Grained and Flexible Access control on Blockchain-Based Data Sharing for the Internet of Things

China Communications 2022年第6期19卷 22-34页

作者： Ruimiao Wang Xiaodong Wang Wenti Yang Shuai Yuan Zhitao Guan School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China Department of Finance Operationsand Information SystemsBrock UniversityCanada

The traditional centralized data sharing systems have potential risks such as single point of failures and excessive working load on the central *** a distributed and collaborative alternative,approaches based upon blockchain have been explored recently for Internet of Things(IoTs).However,the access from a legitimate user may be denied without the pre-defined policy and data update on the blockchain could be costly to the *** this paper,we first address these issues by incorporating the Accountable Subgroup Multi-Signature(ASM)algorithm into the Attribute-based Access control(ABAC)method with Policy Smart Contract,to provide a finegrained and flexible ***,we propose a policy-based Chameleon Hash algorithm that allows the data to be updated in a reliable and convenient way by the authorized ***,we evaluate our work by comparing its performance with the *** results demonstrate significant improvement on the effectiveness and efficiency.

关键词： blockchain access control smart contract multi-signature chameleon-hash data sharing Internet of Things

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Enhanced cyber-physical system with semantic technologies and machine learning to support smart farming 24

Enhanced cyber-physical system with semantic technologies an...

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24th International Conference on control systems and computer Science, CSCS 2023

作者： Ciolofan, Sorin N. Dragoicea, Monica Popeanga, Daniel-Catalin Politehnica University of Bucharest Department of Computer Science Bucharest Romania Politehnica University of Bucharest Department of Automatic Control and Systems Engineering Bucharest Romania

ISBN: (纸本)9798350313390

An important aspect related to the effects of agricultural activities on the environment is represented by the nutrient loss in water and air (specifically nitrogen). The interactions between catchments hydrological processes, management of farm activities, climate changes and nitrogen losses constitute a complex phenomenon yet not well understood, being an important concern from the sustainable agriculture perspective. Nitrogen can be lost with water as leaching or runoff, or as gas as ammonia volatilization. Nitrous oxide (N2O) is particularly problematic because it is also a powerful greenhouse gas. The goal of the current article is to present innovative digital techniques to advance in understanding of this phenomena through an Information System that integrates Artificial Intelligence techniques such as Semantic Technologies and Machine Learning (ML) into Cyber-Physical systems (CPS) to support smart farming and sustainable agriculture. © 2023 IEEE.

关键词： Semantics

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Behavioural Swarm Optimisation for Stable Slung-Load Aerial Transportation

Behavioural Swarm Optimisation for Stable Slung-Load Aerial ...

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Chen, Jingyu Oyekan, John The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom University of York Department of Computer Science York United Kingdom

ISBN: (纸本)9798350314588

Collaboration of agents in a natural swarm enables the accomplishment of tasks that would be difficult or impossible for a single agent to complete alone. For example, a swarm of autonomous Unmanned Aerial Vehicles (UAVs) enables the collaborative sensing of bulky loads for transportation over impassable terrains when the load weighs several times more than each UAV. In this work, we propose a hierarchical algorithmic architecture that supports the search and coverage of various unknown payload profiles for subsequent transportation. The grasping formation of UAVs over the payload emerges from the synthetic behaviours in the architecture without any path planning. Experiments show that our proposed design can be successfully applied in searching and coverage of various loads and has been validated in the real world through the use of Crazyflie micro-UAVs. Furthermore, the proposed grasping formation satisfies static equilibrium thereby reducing orientation changes in the load-swarm system during transportation. © 2023 IEEE.

关键词： Motion planning

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Designing an Electronic Circuit of the Remotely Operated Underwater Vehicle Based on an Unified Element Base

Designing an Electronic Circuit of the Remotely Operated Und...

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2022 Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2022

作者： Galtsov, German A. Sakovich, Sergey Yu. Department of Automatic Control Systems and Onboard Computer Facilities Saint Petersburg Russia

ISBN: (纸本)9781665409933

This article presents a project of a small-sized remotely operated underwater vehicle (ROV) being designed and developed at SMTU. Paper describes a functional scheme of the underwater vehicle, motion control units with the proposed standard components, propulsion and steering system, system of remote control, and possible ROV modifications. © 2022 IEEE.

关键词： Remote control

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Benchmarking Semantic Communications for Image Transmission Over MIMO Interference Channels 16

Benchmarking Semantic Communications for Image Transmission ...

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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Wang, Yanhu Guo, Shuaishuai Dong, Anming Zhao, Hui School of Control Science and Engineering Shandong University China School of Computer Science and Technology Qilu University of Technology China Eurecom Communication Systems Department France

ISBN: (纸本)9798350390643

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input multiple-output (MIMO) interference channels, where we propose an interference-robust semantic communication (IRSC) scheme. This scheme involves the development of transceivers based on neural networks (NNs), which integrate channel state information (CSI) either solely at the receiver or at both transmitter and receiver ends. Moreover, we establish a composite loss function for training IRSC transceivers, along with a dynamic mechanism for updating the weights of various components in the loss function to enhance system fairness among users. Experimental results demonstrate that the proposed IRSC scheme effectively learns to mitigate interference and outperforms baseline approaches, particularly in low signal-tonoise (SNR) regimes. © 2024 IEEE.

关键词： Radio transceivers

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Some Use Cases of Security Constrained Economic Dispatch Problem for Outage Work Planning Collaboration System 13

Some Use Cases of Security Constrained Economic Dispatch Pro...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Toyoshima, Ichiro Tatekoji, Takashi Mizutani, Ryota Sato, Hiroaki Toshiba Energy Systems & Solutions Corporation Infrastructure Service Development & Design Department Tokyo Japan Toshiba Energy Systems & Solutions Corporation Power Grid System Solutions Engineering Depattment Kawasaki Japan Toshiba Energy Systems & Solutions Corporation Power Control Computer Systems Department Tokyo Japan

ISBN: (纸本)9798350355079

Outage work planning has been essential to maintain the power grid system. For the operators, the planning is troublesome. It is caused by too complex process. The past few years, we have been developing Outage Work planning Collaboration System (OWCS) with some mathematical optimization techniques. Especially, Security Constrained Economic Dispatch(SCED) is extened in some ways to handle various power grid situations. © 2024 IEEE.

关键词： Constrained optimization

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Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees 38

Learning Neural Contracting Dynamics: Extended Linearization...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Jaffe, Sean Davydov, Alexander Lapsekili, Deniz Singh, Ambuj K. Bullo, Francesco Center for Control Dynamical Systems and Computation University of California Santa Barbara United States Department of Computer Science University of California Santa Barbara United States

Global stability and robustness guarantees in learned dynamical systems are essential to ensure well-behavedness of the systems in the face of uncertainty. We present Extended Linearized Contracting Dynamics (ELCD), the first neural network-based dynamical system with global contractivity guarantees in arbitrary metrics. The key feature of ELCD is a parametrization of the extended linearization of the nonlinear vector field. In its most basic form, ELCD is guaranteed to be (i) globally exponentially stable, (ii) equilibrium contracting, and (iii) globally contracting with respect to some metric. To allow for contraction with respect to more general metrics in the data space, we train diffeomorphisms between the data space and a latent space and enforce contractivity in the latent space, which ensures global contractivity in the data space. We demonstrate the performance of ELCD on the high dimensional LASA, multi-link pendulum, and Rosenbrock datasets. © 2024 Neural information processing systems foundation. All rights reserved.

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Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets

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computers, Materials & Continua 2023年第2期74卷 4027-4041页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Fadwa Alrowais Sunil Kumar Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt School of Computer Science University of Petroleum and Energy StudiesDehradun248001India Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

In data mining and machine learning,feature selection is a critical part of the process of selecting the optimal subset of features based on the target *** are 2n potential feature subsets for every n features in a dataset,making it difficult to pick the best set of features using standard ***,in this research,a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm(ASSOA)has been *** using metaheuristics to pick features,it is common for the selection of features to vary across runs,which can lead to *** of this,we used the adaptive squirrel search to balance exploration and exploitation duties more evenly in the optimization *** the selection of the best subset of features,we recommend using the binary ASSOA search strategy we developed *** to the suggested approach,the number of features picked is reduced while maximizing classification accuracy.A ten-feature dataset from the University of California,Irvine(UCI)repository was used to test the proposed method’s performance *** other state-of-the-art approaches,including binary grey wolf optimization(bGWO),binary hybrid grey wolf and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hybrid GWO and genetic algorithm 4028 CMC,2023,vol.74,no.2(bGWO-GA),binary firefly algorithm(bFA),and *** results confirm the superiority and effectiveness of the proposed algorithm for solving the problem of feature selection.

关键词： Metaheuristics adaptive squirrel search algorithm optimization methods binary optimizer

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On a Structural Approach to the Complex systems Conceptual Modeling 4

On a Structural Approach to the Complex Systems Conceptual M...

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4th International Conference on control, Artificial Intelligence, Robotics and Optimization, ICCAIRO 2023

作者： Brodsky, Yury I. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Simulation Systems and Operation Research Department Moscow Russia

ISBN: (纸本)9798350300918

Conceptual modeling is gaining an essential role in designing large-scale systems, especially as the complexity of the latter increases. The design tool for such systems is the development of ontologies for their subject areas. A problem arises: in our activity, we consider more complex subject areas, and the complexity of ontologies is growing. Is there a limit to this complexity? The design of large-scale systems is already suffocating with complexity - it is difficult to describe the components of the domain, their synthesis is complicated, and even more difficult is the software implementation of the model within the framework of an imperative, object-oriented approach. Debugging the created software system is extremely difficult. The structural theory offers a unified way to describe the subject areas of a broad class of large-scale systems, realizing in this description the principle of 'One in everything and all in One.' Based on this, an end-to-end technology of reporting, synthesis, and software implementation of models of complex, large-scale systems, which is close to CAD methods, is being built. In implementing a software system, it is possible to remain within the framework of declarative programming, avoiding imperative programming, which significantly simplifies its debugging. © 2023 IEEE.

关键词： Large scale systems

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Reinforcement Learning-Based Output Stabilization control for Nonlinear systems With Generalized Disturbances 25

Reinforcement Learning-Based Output Stabilization Control fo...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Tang, Zezhi Rossiter, J Anthony Dong, Yi Panoutsos, George University Of Sheffield Department Of Automatic Control And Systems Engineering SheffieldS13JD United Kingdom University Of Southampton Department Of Electronics And Computer Science Southampton United Kingdom

ISBN: (纸本)9798350340266

This paper proposes a new disturbance observer (DO)-based reinforcement learning (RL) control approach for nonlinear systems with unmatched (generalized) disturbances. While a nonlinear disturbance observer (NDO) is utilized to measure the plant uncertainties, disturbances can exist in the plant via distinct channels from those of the control signals;so-called mismatched disturbances are theoretically difficult to attenuate within the channel of the system's states. A generalized disturbance observer-based compensator is implemented to address the uncertainty cancellation problem by removing the influence of uncertainties from the output channels. Con-currently, a composite actor-critic RL scheme is utilized for approximating the optimal control policy as well as the ideal value function pertaining to the compensated system by solving a Hamilton-Jacobi-Bellman (HJB) equation for both online and offline iterations simultaneously. Stability analysis verifies the convergence of the proposed framework. Simulation results are included to illustrate the effectiveness of the proposed scheme. © 2024 IEEE.

关键词： Nonlinear systems

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