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A Data Transmission Approach Based on Ant Colony Optimization and Threshold Proxy Re-encryption in WSNs

Journal of Artificial Intelligence and Technology 2022年第1期2卷 23-31页

作者： Jing Liu Zenghui Liu Chenyu Sun Junxi Zhuang College of Computer Science Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of EducationBeijing 100124China College of Automation Engineering Beijing PolytechnicBeijing 100176China

Wireless sensor networks(WSNs)have become increasingly popular due to the rapid growth of the Internet of *** open wireless transmission media are easy to attack,security is one of the primary design concerns for *** solutions consider routing and data encryption as two isolated issues,providing incomplete ***,in this paper,we divide the WSN communication process into a data path selection phase and a data encryption *** propose an improved transmission method based on ant colony optimization(ACO)and threshold proxy re-encryption for WSNs,and we named it as *** method resists internal and external attacks and ensures safe and efficient data *** the data path selection stage,the ACO algorithm is used for network *** improvement of the pheromone concentration is *** order to resist attacks from external attackers,proxy re-encryption is extended to WSN in the data encryption *** threshold secret sharing algorithm is introduced to generate a set of re-encryption key fragments composed of random numbers at the source *** confirm the performance of our model via simulation studies.

关键词： wireless sensors network ant colony optimization pheromone proxy re-encryption threshold

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Set-theoretic fault-diagnosis for a nonlinear real-word fluidic benchmark

Set-theoretic fault-diagnosis for a nonlinear real-word flui...

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European Control Conference (ECC)

作者： Florin Stoican Janetta Culiţă Sorin Olaru Faculty of Automation Control and Computer Science University Politehnica of Bucharest Romania L2S lab of CentraleSupelec Gif sur Yvette France

Fault diagnosis is essential in managing abnormal changes in system characteristics which affect its functioning and control abilities. The manuscript provides a set-based fault diagnosis for a fluidic benchmark. Invariant sets are employed to characterize the steady-state behavior of the open-loop stable dynamics for sensor faults. It is shown that the set-based fault diagnosis theory integrates this model and is able to handle efficiently persistent fault events.

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Advanced Analysis of Electro-Oculographic Signal using Deep Neural Networks for Safety Purposes in automation and Production Systems

Advanced Analysis of Electro-Oculographic Signal using Deep ...

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International Conference on computer and automation Engineering, ICCAE

作者： Ivan Kuric Vladimír Stenchlák Ivan Zajačko Martin Bohušík Dorota Więcek Department of Automation and Production Systems University of Žilina Žilina Slovakia Faculty of Mechanical Engineering and Computer Science University of Bielsko-Biala Bielsko-Biala Poland

This article deals with the problematics of obtaining and processing the EOG signals. This research describes the ways in which it is possible to measure and evaluate the measured bio-electrical signals of brain and muscle activity in more detail. The work also describes the analysis of the current state of this problematics and individual models of artificial intelligence are also described in the work - artificial neural networks that can be used for such advanced analysis. The experimental part of this work is performed in the MATLAB environment using the Deep Neural Network Toolbox. The experimental part of the work is focused on the analysis and processing of bio-electrical activity eye-motor muscles in the area of eye-tracking with the help of the OLIMEX EEG-SMT device. The information provided in this research can be used for improving safety and reliability and elimination of potential risks connected to an epilepsy disease and epilepsy seizures in automated production systems.

关键词： Deep learning Safety devices Production systems Voltage measurement automation Tracking Current measurement

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Evaluation of Convolutional Neural Network Model Architecture Performance

Evaluation of Convolutional Neural Network Model Architectur...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Musthofa Galih Pradana Hilda Khoirunnisa I Wayan Rangga Pinastawa Faculty of Computer Science Universitas Pembangunan Nasional Veteran Jakarta Jakarta Indonesia Department of Automation Engineering and Mechatronics Bandung Polytechnic for Manufacturing Bandung Indonesia

The identification of image types can be facilitated through the use of algorithms and automation in their detection. In this research, detection is performed on fashion images, which encompass various types and categorizations. The process of identification and detection can utilize the Neural Network algorithm known as Convolutional Neural Network (CNN). The Convolutional Neural Network (CNN) algorithm consists of multiple layers, and its application involves setting values for pixels as well as arranging the sequence of layers within it. In this study, two Convolutional Neural Network (CNN) algorithm models are employed for image classification in the fashion dataset. These two models differ in the order of layers within the Convolutional Neural Network (CNN) and in the values of strides applied for modification. Model 1 employs ZeroPadding2D in the first layer with a smaller stride value of 1 compared to Model 2, which places the Conv2D layer in the first layer and applies strides with 1, 2, and 3 values. This research indicates that Model 1 outperforms Model 2, achieving the highest accuracy in epoch 20 with an accuracy value of 0.9711. This is attributed to the fact that the strides value in the Conv2D layer of Model 1 is set to a smaller value compared to Model 2.

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Distance-based Formation-Motion Control for Unicycle Agents

Distance-based Formation-Motion Control for Unicycle Agents

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American Control Conference (ACC)

作者： Jin Chen Bayu Jayawardhana Hector Garcia de Marina Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen The Netherlands Department of Computer Engineer Automation and Robotics and With CITIC The University of Granada Spain

We present a distance-based distributed formation-motion control law for unicycle agents that are required to move together at a constant reference speed. The distributed control law consists of the standard distance-based formation gradient control law, which is projected to the longitudinal and angular velocity inputs of the unicycle, and of a linear term that depends on the reference speed. The main contribution of this paper is to realize the consistency of unicycle agents’ orientations without orientation measurement, thereby reducing the possibility of significant orientation measurement errors in real-world applications. We prove and show numerically the local exponential convergence of the unicycle agents to the desired formation, where they eventually move in unison at a constant reference speed.

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Scaling up the formation of agents with heterogeneous sensing: mixed distance and bearing-only

arXiv

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arXiv 2023年

作者： Chen, Jin Jayawardhana, Bayu de Marina, Hector Garcia The Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Netherlands Department of Computer Engineer Automation and Robotics CITIC The University of Granada Spain

Unlike the case with identical neighboring agents whose actions are mirrored, the problem of distributed formation control design with heterogeneous sensing is not straightforward. In this paper, we consider the problem of distributed formation control where each agent can only control distances or bearings with its neighbors. We firstly develop a rigidity theory with heterogeneous sensing to ensure that the desired shape is well-posed. Secondly, we propose an iterative method that allows us to scale up the number of agents with heterogeneous sensing. Finally, numerical simulations show the effectiveness of our method. © 2023, CC BY.

关键词： Iterative methods

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Energy efficient indoor localisation for narrowband internet of things

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1150-1163页

作者： Ismail Keshta Mukesh Soni Mohammed Wasim Bhatt Azeem Irshad Ali Rizwan Shakir Khan Renato RMaaliw III Arsalan Muhammad Soomar Mohammad Shabaz Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia Department of CSE University Centre for Research and Development Chandigarh UniversityMohaliPunjabIndia Department of Computer Science and Engineering National Institute of TechnologySrinagarIndia Asghar Mall College Rawalpindi Higher Education Department(HED)Govt.of the PunjabRawalpindiPakistan Department of Industrial Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Automation Electronics and Electrical EngineeringGdansk University of TechnologyGdańskPoland Arba Minch University Arba MinchEthiopia

There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops *** high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these *** maximise the data rate fairness of Narrow Band IoT devices,a multi‐dimensional indoor localisation model is devised,consisting of transmission power,data scheduling,and time slot scheduling,based on a network model that employs non‐orthogonal multiple access via a *** on this network model,the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors,while taking into account the Narrow Band IoT network:The multidimensional indoor localisation optimisation model of equipment tends to minimize data rate,energy constraints and EH relay energy and data buffer constraints,data scheduling and time slot *** a result,each Narrow Band IoT device's data rate needs are met while the network's overall performance is *** investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT *** current work primarily considers the NOMA Narrow Band IoT network under a single EH ***,the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference,which impacts NOMA's performance *** simulation,the proposed approach is successfully *** improvements have boosted the network's energy efficiency by 44.1%,data rate proportional fairness by 11.9%,and spectrum efficiency by 55.4%.

关键词： artificial inteligence detection of moving objects internet of things

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On the Complexity of Computing the Maximal Positive Invariant Set

On the Complexity of Computing the Maximal Positive Invarian...

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European Control Conference (ECC)

作者： Bogdan Gheorghe Florin Stoican Ionela Prodan Faculty of Automation Control and Computer Science National University of Science and Technology Politehnica Bucharest Romania Grenoble INP LCIS Univ. Grenoble Alpes Institute of Engineering and Management Univ. Grenoble Alpes Valence France

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Computing the maximal (robust) positive invari-ant (M(R)PI) set for linear dynamics and a polyhedral constraint set is well-known in the literature but, the effects and limitations of the different methods employed are not sufficiently clear, especially for high dimensional systems. In this paper we propose a systematic analysis of the existing techniques as well as the application of new ideas to accelerate the computation of the MPI set. This includes new stop conditions for the set recurrence that spans it. We analyze and compare these variations over a dynamical system whose dimension can be arbitrarily increased to draw conclusions about their relative strengths and weaknesses.

关键词： Systematics Europe Complexity theory Dynamical systems Predictive control

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Classification of skin lesions using morpho-granulometry features derived from color clusters

Classification of skin lesions using morpho-granulometry fea...

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International Conference on System Theory, Control, and Computing (ICSTCC)

作者： Gigi Tăbăcaru Simona Moldovanu Marian Barbu Department of Automatic Control and Electrical Engineering Faculty of Automation Computers Electrical Engineering and Electronics "Dunarea de Jos" University of Galati Galati Romania Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics The Modelling & Simulation Laboratory "Dunarea de Jos" University of Galati Galati Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

The skin lesion can be thought of as a biological system, so the morpho-granulometry of significant color clusters found in skin lesions is one of the elements that reproduce in a natural way the structure of the lesion, this novelty is highlighted in this study. Important features of skin lesions can be modulated by fusing neural networks (NN) and machine learning (ML). By choosing the nevus and melanoma classes, the primary goal was accomplished, and three databases were used to test the methodology. The characteristics based on morpho-granulometry allowed for the identification of microstructure within the images, which can be very helpful in characterizing the biological system. Based on random forest (RF) and extreme gradient boosting (XGboost) classifiers, this work aimed to improve the classification performance of important feature selection. The selected features from three free image databases with three NNs were classified. In a binary classification of nevus vs. melanoma, the results showed that the pattern recognition neural network (PRNN), according to the PH2 database, provided an accuracy of 0.923 and an F1-score of 0.876. The classification is interpretable if it is not validated. In our study, the best results were verified with a logistic regression (LR) classifier.

关键词： Accuracy Recurrent neural networks Image color analysis Melanoma Biological systems Artificial neural networks Feature extraction Skin Lesions Classification tree analysis

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Multi-Expert Adaptive Selection: Task-Balancing for All-in-One Image Restoration

arXiv

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arXiv 2024年

作者： Yu, Xiaoyan Zhou, Shen Li, Huafeng Zhu, Liehuang School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China

The use of a single image restoration framework to achieve multi-task image restoration has garnered significant attention from researchers. However, several practical challenges remain, including meeting the specific and simultaneous demands of different tasks, balancing relationships between tasks, and effectively utilizing task correlations in model design. To address these challenges, this paper explores a multi-expert adaptive selection mechanism. We begin by designing a feature representation method that accounts for both the pixel channel level and the global level, encompassing low-frequency and high-frequency components of the image. Based on this method, we construct a multi-expert selection and ensemble scheme. This scheme adaptively selects the most suitable expert from the expert library according to the content of the input image and the prompts of the current task. It not only meets the individualized needs of different tasks but also achieves balance and optimization across tasks. By sharing experts, our design promotes interconnections between different tasks, thereby enhancing overall performance and resource utilization. Additionally, the multi-expert mechanism effectively eliminates irrelevant experts, reducing interference from them and further improving the effectiveness and accuracy of image restoration. Experimental results demonstrate that our proposed method is both effective and superior to existing approaches, highlighting its potential for practical applications in multi-task image restoration. The source code of the proposed method is available at https://***/zhoushen1/MEASNet. Copyright © 2024, The Authors. All rights reserved.

关键词： Restoration

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