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A Parallel Color Image Encryption Algorithm Based on a 2-D Logistic-Rulkov Neuron Map

IEEE Internet of Things Journal 2025年第11期12卷 18115-18124页

作者： Gao, Suo Zhang, Zheyi Iu, Herbert Ho-Ching Ding, Siqi Mou, Jun Erkan, Uğur Toktas, Abdurrahim Li, Qi Wang, Chunpeng Cao, Yinghong Dalian Polytechnic University School of Information Science and Engineering Dalian116034 China The University of Western Australia School of Electrical Electronic and Computer Engineering PerthWA6009 Australia Dalian University of Technology School of Mathematical Sciences Dalian116024 China Karamanoglu Mehmetbey University Faculty of Engineering Department of Computer Engineering Karaman70200 Turkey Ankara University Engineering Faculty Department of Artificial Intelligence and Data Engineering Ankara06830 Turkey Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan250000 China

Images are widely used in social networks, necessitating efficient and secure transmission, especially in bandwidth-constrained environments. This article aims to develop a color image encryption algorithm that enhances security while optimizing computational efficiency. A novel parallel color image encryption algorithm based on the 2-D logistic-Rulkov neuron map (2D-LRNM) is proposed. In this approach, the three channels of the color image are first separated. Cross-channel information interaction is introduced to form three new channels, which are then processed in parallel. During the encryption process of each channel, a block-wise parallel encryption mechanism is applied, ensuring simultaneous encryption of each block. This block-wise strategy effectively leverages parallel computing resources and balances the task load. To meet the demand for a large number of keystreams during encryption, the 2D-LRNM is introduced. It combines the simplicity and chaotic properties of the Logistic map with the multitimescale dynamics and neurodynamic behaviors of the Rulkov map. By overcoming the dimensional limitations inherent in the single Logistic map, this approach extends the system to a 2-D framework, significantly increasing the complexity of chaotic behavior and improving its unpredictability. Experimental results demonstrate that the proposed encryption algorithm achieves high security and reduces computation time by approximately 83.3%. © 2014 IEEE.

关键词： Encryption algorithms

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Study on the characteristics of inductively coupled plasma discharge at different frequencies under air background

Study on the characteristics of inductively coupled plasma d...

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2024 International Conference on Aerospace, Mechanical and Materials engineering, AMME 2024

作者： Lei, Fan Wu, Hongzhi Zhang, Zhaoyang School of Electrical and Control Engineering Shaanxi University of Science & Technology Shaanxi Xi'an710021 China

Simulation of the two-dimensional axisymmetric inductively coupled plasma (ICP) discharge model under air background is carried out through the finite element simulation software COMSOL Multiphysics based on the hydrodynamic equations. The changes and distribution characteristics of plasma parameters are obtained and analyzed during the discharge process, including the electron density, the electronic temperature, and the macro-gas temperature of the plasma. The influence of different frequencies on flow field characteristics of ICP in the background of air is studied. The model fixed the input discharge power of 1000W and the pressure of 20Pa. The research results indicate that the plasma appears in the middle of the discharge chamber and gradually dissipates along the direction of the chamber wall. The macro-gas temperature near the inductive coil is higher than in other areas. In addition, rising discharge frequencies will lead to a decrease in plasma conductivity, which will cause the research object of plasma to gradually decrease. The proportion of O2 not only affects the relevant feature parameters of plasma, but also has an impact on the distribution of the spatial space of plasma. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Inductively coupled plasma

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Signal Conducting System with Effective Optimization Using Deep Learning for Schizophrenia Classification

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computer Systems science & engineering 2023年第5期45卷 1869-1886页

作者： V.Divya S.Sendil Kumar V.Gokula Krishnan Manoj Kumar School of Electrical and Electronics Engineering Sathyabama Institute of Science and TechnologyChennaiTamilnaduIndia Department of Electrical and Electronics Engineering S A Engineering CollegeChennaiTamilnaduIndia Department of Computer Science and Information Technology CVR College of EngineeringMangalpallyHyderabadTelanganaIndia School of Computer Science University of Petroleum and Energy StudiesDehradunIndia

Signal processing based research was adopted with Electroencephalogram(EEG)for predicting the abnormality and cerebral *** proposed research work is intended to provide an automatic diagnostic system to determine the EEG signal in order to classify the brain function which shows whether a person is affected with schizophrenia or *** detection and intervention are vital for better ***,the diagnosis of schizophrenia still depends on clinical observation to *** reliable biomarkers,schizophrenia is difficult to detect in its early phase and hence we have proposed this *** this work,the EEG signal series are divided into non-linear feature mining,classification and validation,and t-test integrated feature selection *** this work,19-channel EEG signals are utilized from schizophrenia class and normal ***,the datasets initially execute the splitting process based on raw 19-channel EEG into 6250 sample point’s *** this process,1142 features of normal and schizophrenia class patterns can be *** other hand,157 features from each EEG patterns are utilized based on Non-linear feature extraction process where 14 principal features can be identified in terms of considering the essential *** last,the Deep Learning(DL)technique incorporated with an effective optimization technique is adopted for classification process called a Deep Convolutional Neural Network(DCNN)with mayfly optimization *** proposed technique is implemented into the platform of MATLAB in order to obtain better results and is analyzed based on the performance analysis framework such as accuracy,Signal to Noise Ratio(SNR),Mean Square Error,Normalized Mean Square Error(NMSE)and *** comparison,the proposed technique is proved to a better technique than other existing techniques.

关键词： Deep learning optimization algorithm signal conducting system schizophrenia convolutional neural network mayfly optimization algorithm

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Efficient Real-Time Recognition Model of Plant Diseases for Low-Power Consumption Platform

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2040-2054页

作者： Deng, Songyun Wu, Wanneng Zou, Kunlin Qin, Hai Cheng, Lekai Liang, Qiaokang Hunan University College of Electrical and Information Engineering Changsha410082 China Changsha University of Science and Technology School of Electrical and Information Engineering Changsha410114 China Hunan University National Engineering Research Center for Robot Vision Perception and Control College of Electrical and Information Engineering Changsha410082 China

Recognition and early warning of plant diseases is one of the keys to agricultural disaster prevention and mitigation. Deep learning-based image recognition methods give us a new idea for plant disease identification. Due to the harsh conditions in agricultural environment, recent research has focused on exploring ways to lightweight the recognition model for deployment on low-power devices. In this article, we propose an efficient and feature-guided real-time plant disease recognition model with a multiclassifier architecture, specifically designed for low-power devices. By comparing with other advanced methods, our model reaches the state of the art in the combined metrics of recognition accuracy, the number of parameters, and inference speed. First, we propose AMI-NanoNet based on Roofline theory to significantly reduce the number of parameters and computational complexity. This model can achieve 99.8343% accuracy on PlantVillage by using a feature-guided curriculum learning with stepwise training strategy. Moreover, we design another training strategy suitable for lightweight ensemble models. Based on this strategy, our model only needs to integrate the classifiers at the end of the network to achieve 99.8708% identification accuracy, and it hardly increases the number of operations and parameters of the network. Extensive evaluations on this dataset demonstrate the effectiveness of our ensemble learning method. Furthermore, we tested our proposed methods on another dataset from other domains to validate its applicability to different scenarios. Overall, our research provides a basis for rapid and intelligent identification of plant diseases. © 2023 IEEE.

关键词： Real time systems

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Artificial Intelligence Enabled Cognitive Computing for AlN/β-Ga2O3 HEMT 2

Artificial Intelligence Enabled Cognitive Computing for AlN/...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Verma, Yogesh Kumar Bhatia, Kamal Khushboo Bhanot, Aastha Roy, Trijeeta Sinha, Supriya Laksh School of Electronics and Electrical Engineering Lovely Professional University Jalandhar India School of Computer Science and Engineering Lovely Professional University Jalandhar India

ISBN: (纸本)9798331530389

HEMT devices have potential to handle the fast processing in applications such as real-time diagnostics utilizing the artificial-intelligence (AI) enhanced abilities. Along-with this HEMT devices can be extensively used in radar and defense systems to obtain faster response time and threat detection. This integration of AI and cognitive computing enables pattern-recognition and adaptive learning. The cognitive computing techniques integrated with HEMT enables the real-time analysis and predictions. For precise sensor data the amplification should be done at either no or very less noise levels. © 2025 IEEE.

关键词： Gallium compounds

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Neutrosophic Overlap Function and Its Derived Neutrosophic Residual Implication

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Neutrosophic Sets and Systems 2023年 56卷 5-19页

作者： Zhang, Xingna Hu, Qingqing Zhang, Xiaohong School of Mathematics and Data Science Shaanxi University of Science & Technology Xi'an710021 China School of Electrical and Control Engineering Shaanxi University of Science & Technology Xi'an710021 China

A new concept of neutrosophic overlap function is given, furthermore a neutrosophic residual implication derived from it is also introduced. Firstly, we give new concept of neutrosophic overlap function and some classical examples which are introduced on the lattice. Secondly, the concept of representable neutrosophic overlap function and its pertinent examples are given, meanwhile the general method of constructing representable neutrosophic overlap function by using intuitionistic overlap function is given. Finally, neutrosophic residual implication induced by neutrosophic overlap function and its basic properties are studied. © (2023). All Rights Reserved.

关键词： lattice neutrosophic overlap function neutrosophic residual implication representable neutrosophic overlap function

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AR-Light: Enabling Fast and Lightweight Multi-User Augmented Reality via Semantic Segmentation and Collaborative View Synchronization

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IEEE Transactions on computers 2025年第6期74卷 2073-2086页

作者： Wen, Yu Shah, Aamir Bader Cao, Ruizhi Zhang, Chen Chen, Jiefu Wu, Xuqing Xie, Chenhao Fu, Xin University of Houston Department of Electrical and Computer Engineering HoustonTX77204 United States Beihang University School of Computer Science and Engineering Beijing100191 China University of Houston Department of Information Science Technology HoustonTX77204 United States

Multi-user Augmented Reality (MuAR) allows multiple users to interact with shared virtual objects, facilitated by exchanging environment information. Current MuAR systems rely on 3D point clouds for real-world analysis, view synchronization, object rendering, and movement tracking. However, the complexity of 3D point clouds leads to significant processing delays, with approximately 80% of overhead in commercial frameworks. This hampers usability and degrades user experience. Our analysis reveals that maintaining the facing side of the real-world scene in a stable environment provides sufficient information for virtual object placement and rendering. To address this, we introduce a lightweight quadtree structure, representing 2D scenes through semantic segmentation and geometry, as an alternative to 3D point clouds. Additionally, we propose a novel correction method to handle potential shifts in virtual object placement during view synchronization among users. Combining all designs, we implement a fast and lightweight MuAR framework named AR-Light and test our framework on commercial AR devices. The evaluation results on real-world applications demonstrate that AR-Light can achieve high performance in various real-world scenes while maintaining a comparable virtual object placement accuracy. © 1968-2012 IEEE.

关键词： Semantic Segmentation

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Sliding-mode-based preassigned-time control of a class of memristor chaotic systems

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Chinese Physics B 2024年第11期33卷 161-166页

作者： Jinrong Fan Qiang Lai Qiming Wang Leimin Wang College of Computer Science South-Central Minzu UniversityWuhan 430074China School of Electrical and Automation Engineering East China Jiaotong UniversityNanchang 330013China School of Automation China University of GeosciencesWuhan 430074China

This paper addresses the preassigned-time chaos control problem of memristor chaotic systems with time *** the introduction of memristor,the presented models are nonlinear systems with chaotic ***,the TS fuzzy method is adopted to describe the chaotic ***,a sliding-model-based control approach is proposed to achieve the preassigned-time stabilization of the presented models,where the upper bound of stabilization time can be arbitrarily specified in ***,simulation results demonstrate the validity of presented control approach and theoretic results.

关键词： memristor chaotic system TS fuzzy method preassigned-time stabilization sliding-mode control

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Irrigation Optimization in Agricultural Fields Using Deep Reinforcement Learning Approaches 29

Irrigation Optimization in Agricultural Fields Using Deep Re...

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29th International computer Conference, computer Society of Iran, CSICC 2025

作者： Heidari, Parsa Esfidi, Ali Ahmadi Mehrvarz, Ali Khodaei, Elaheh Khonsari, Ahmad School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran School of Math and Computer Science Amirkabir University of Technology Tehran Iran School of Electrical and Computer Engineering University of Waterloo Waterloo Canada Faculty of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9798331523114

In recent years, due to the world population growth, the demand for agricultural products has also increased. Global crises such as climate change, destruction of water resources, pollution and destruction of aquatic ecosystems, have limited the access to clean water to irrigate the agricultural fields in a global scale. Meanwhile, according to the reports of Food and Agriculture Organization of the United Nations (FAO), about 70% of global water consumption is allocated to agricultural activities. Therefore, it is necessary to minimize water consumption during agricultural irrigation while maximizing crop yield by the end of the season. Most IoT frameworks used in irrigation systems collect data from the soil and weather, then send it to the user, leaving the final decision on irrigation to the user. This approach may cause water wastage or even water stress for the plants as the amount of water irrigated in fields may be low. In this paper, we will use deep reinforcement learning approaches to reach this goal. We propose a novel approach to minimize water usage while keeping the yield produced at the highest level. Our approach utilizes DQN and A2C networks. The findings demonstrate that our methods reduce water wastage compared to previous approaches, making it more flexible and practical in varying weather and soil conditions. © 2025 IEEE.

关键词： Fruits

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A trajectory summarisation gener

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IET Cyber-Systems and Robotics 2023年第1期5卷 154-164页

作者： Weifeng Liu Liwen Ma Shaoyong Qu Zhangming Peng School of Electrical and Control Engineering Shaanxi University of Science and TechnologyXi'anChina School of Artificial Intelligence Hangzhou Dianzi UniversityHangzhouChina School of Mechanical Engineering Hangzhou Dianzi UniversityHangzhouChina

The semantic representation of the trajectory is conducive to enrich the content oftrajectory data mining. A trajectory summarisation generation method based on themobile robot behaviour analysis was proposed to realize the abstract expression andsemantic representation of the spatio-temporal motion features of the robot and itsenvironmental interaction state. First, the behavioural semantic modelling and representationof the mobile robot are completed by modelling the sub-trajectory andcalculating the topological behaviour (TOP). Second, Chinese word segmentation andsemantic slot filling methods are used to combine with hierarchical clustering to performbasic word extraction and classification for describing trajectory sentences. Then, thedescription language frame is extracted based on the TOP, and the final trajectorysummarisation is generated. The result shows that the proposed method can semanticallyrepresent robot behaviours with different motion features and topological features,extract two verb-frameworks for describing the sentences according to their topologicalfeatures, and dynamically adjust the syntactic structure for the different topological behavioursbetween the target and the environment. The proposed method can generatesemantic information of relatively high quality for spatio-temporal data and help tounderstand the higher-order semantics of moving robot behaviour.

关键词： behaviour analysis behaviour semantics natural language processing semantic trajectory trajectory summarisation

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