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Encryption and steganography-based text extraction in IoT using the EWCTS optimizer

IMAGING SCIENCE JOURNAL 2021年第1-4期69卷 38-56页

作者： Pandey, Binay Kumar Pandey, Digvijay Nassa, Vinay Kumar Ahmad, Tanveer Singh, Chaitanya George, A. Shaji Wakchaure, M. A. Govind Ballabh Pant Univ Agr & Technol Coll Technol Dept IT Pantnagar India Dr APJ Abdul Kalam Tech Univ Dept Tech Educ IET Lucknow India South Point Grp Inst Dept Comp Sci Engn Sonepat India Amity Univ Amity Inst Informat Technol Dept Comp Sci & Engn Lucknow India Shivajirao Kadam Inst Technol & Management Dept Comp Sci & Engn Indore India Crown Univ Intl Chartered Inc CUICI Dept Informat & Commun Technol Santa Cruz Argentina Amrutvahini Coll Engn Dept Comp Engn Sangamner India

This paper develops an effective encryption and steganography-based text extraction in IoT using deep learning method. Initially, the input text and cover images are separately pre-processed. DCT (discrete cosine transform) is utilized to transfer the image from spatial domain to frequency domain. Then, the original text is encrypted using new optimized equilibrium-based homomorphic encryption (OEHE) approach. Next, the extended wavelet convolutional transient search (EWCTS) optimizer with quotient multi-pixel value differencing (QMPVD) is developed to embed the secret text in cover images. Then, at receiver side, the reverse process for encryption and steganography is executed with secret key provided by the sender. Finally, the accurate text is extracted at receiver side using steganalysis process. The developed approach is executed in MATLAB software. The various evaluation metrics are used to authorize the effectiveness of suggested approach. Simulation outcomes proved that the suggested technique provides better outcomes than other existing approaches.

关键词： Text encryption and decryption optimization algorithm wavelet image steganography convolution IoT embedding & extraction

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Trimming Analysis Method of Quad Tilt Rotor Based on Aerodynamic Interference Model

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JOURNAL OF AIRCRAFT 2021年第2期58卷 253-265页

作者： Wang, Zhigang Wang, Qiannan Yu, Hongrui Duan, Dengyan Ding, Zhiwei Li, Jianbo Yangzhou Collaborat Innovat Res Inst Shenyang Aircraft Design & Res Inst Yangzhou 225000 Jiangsu Peoples R China Nanjing Univ Aeronaut & Astronaut Natl Key Lab Rotorcraft Aeromech Nanjing 210016 Peoples R China

The quad tilt rotor (QTR) has complex aerodynamic characteristics and strong aerodynamic interference. The flight dynamic model is the basis of control. To effectively account for the aerodynamic interference between the multiple aerodynamic surfaces of the QTR unmanned aerial vehicle, a hybrid optimization trimming analysis method based on Immune algorithm/Levenberg-Marquardt (IA/LM) and lattice Boltzmann method (LBM) is proposed. The aerodynamic characteristics between the wing and the rotor calculated by the LBM are compensated into the flight dynamics model. The IA/LM algorithm is used to reduce the dependence on the initial trimming value. The effectiveness of the hybrid optimal trimming analysis method is verified through the analysis of trimming simulation results.

关键词： Tiltrotor Aircraft Aerodynamic Characteristics LBM UAV Aircraft Flight Dynamics Fuselages Helicopters CFD optimization algorithm Lift to Drag Ratio

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MADCR:Mobility Aware Dynamic Clustering-Based Routing Protocol in Internet of Vehicles

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China Communications 2021年第7期18卷 69-85页

作者： Sankar Sennan Somula Ramasubbareddy Sathiyabhama Balasubramaniyam Anand Nayyar Chaker Abdelaziz Kerrache Muhammad Bilal Deparment of of Computer Science and Engineering Sona College of TechnologySalem 636005India Deparment of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabad 500090India. Graduate School Duy Tan UniversityDa Nang 550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang 550000Vietnam Laboratoire d’Informatique et de Mathématiques UniversitéAmar Telidji de LaghouatLaghouatAlgeria. Department of Computer Engineering Hankuk University of Foreign Studies17035Yongin-SiSouth Korea

Internet of Vehicles(IoV)is an evolution of the Internet of Things(IoT)to improve the capabilities of vehicular ad-hoc networks(VANETs)in intelligence transport *** network topology in IoV paradigm is highly *** is one of the promising solutions to maintain the route stability in the dynamic ***,existing algorithms consume a considerable amount of time in the cluster head(CH)selection ***,this study proposes a mobility aware dynamic clustering-based routing(MADCR)protocol in IoV to maximize the lifespan of networks and reduce the end-to-end delay of *** MADCR protocol consists of cluster formation and CH selection processes.A cluster is formed on the basis of Euclidean *** CH is then chosen using the mayfly optimization algorithm(MOA).The CH subsequently receives vehicle data and forwards such data to the Road Side Unit(RSU).The performance of the MADCR protocol is compared with that ofAnt Colony optimization(ACO),Comprehensive Learning Particle Swarm optimization(CLPSO),and Clustering algorithm for Internet of Vehicles based on Dragonfly Optimizer(CAVDO).The proposed MADCR protocol decreases the end-toend delay by 5–80 ms and increases the packet delivery ratio by 5%–15%.

关键词： clustering protocol Internet of things Internet of vehicles optimization algorithm Mayfly algorithm

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Machining stability enhancement in multi-axis milling of titanium hollow blade by introducing multiple damping and rigid supporters

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JOURNAL OF MANUFACTURING PROCESSES 2021年 64卷 198-208页

作者： Hou, Junming Zhao, Zhengcai Fu, Yucan Qian, Ning Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing 210016 Peoples R China Nanjing Inst Technol Ind Ctr Nanjing 211167 Peoples R China

Hollow blades, which are important components of aeroengines, have thin-walled structures and are subjected to vibrations in the machining process owing to its low rigidity and damping. This paper proposes an approach to enhance the machining stability of titanium hollow blades by introducing multiple damping and rigid supporters to the blade machining system in multi-axis milling process. A theoretical prediction model, considering the influence of original system, transmission and supporter, is established to predict the dynamic parameters of blade with a single damping or rigid supporter. Then, the model is applied in multi-supporter system and an optimization algorithm is used to determine reasonable positions of multiple supporters. The stability lobe diagrams of blade system with no supporter, optimized damping supporters and optimized rigid supporters are analysed and validated by blade machining experiment. The conclusion can be achieved that the sound signal is suppressed up to 40 % by adding optimized supporters and the machining stability is enhanced effectively.

关键词： Hollow blade Dynamic parameters optimization algorithm Multiple supporters

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Bearing fault diagnosis method based on unsupervised pseudo-labels adapted for Locality Preserving Projections

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NONDESTRUCTIVE TESTING AND EVALUATION 2025年

作者： Xi, Rui Xu, Youzhi Wu, Shutao Ji, Aihong Zhao, Biao Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing Peoples R China

Currently, the detection of anomalous machine operations and the identification of faulty machine components are essential for maintaining the stability of manufacturing processes and ensuring product quality. In engineering applications, variations in environmental and operating conditions significantly influence the performance and efficiency of fault monitoring models. A bearing fault diagnosis method based on unsupervised domain adaptation with popular embeddings is proposed to address the dual challenges of unsupervised data environments and diverse engineering requirements while meeting demands for model costs, speed, and accuracy. Initially, an optimal convolutional neural network architecture is selected to extract significant feature data. Subsequently, an unsupervised manifold learning approach is utilized for dimensionality reduction, and a heuristic optimization algorithm is employed for hyperparameter optimization, thereby enhancing the model's performance and generalization capability. Furthermore, a robust classifier developed from source domain data and an accuracy calculation method based on decision fusion are designed to significantly improve the model's robustness. Finally, experiments on datasets with varying noise levels demonstrate that the proposed model achieves up to 20% higher accuracy in bearing fault diagnosis compared to other monitoring methods, showcasing its excellent practical utility in bearing anomaly detection and fault diagnosis.

关键词： Deep learning unsupervised domain adaptation optimization algorithm

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Erratum to“Designing thermal demultiplexer:Splitting phonons by negative mass and genetic algorithm optimization”

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Chinese Physics B 2021年第9期30卷 653-653页

作者： Yu-Tao Tan Lu-Qin Wang Zi Wang Jiebin Peng Jie Ren Center for Phononics and Thermal Energy Science China-EU Joint Center for NanophononicsShanghai Key Laboratory of Special Artificial Microstructure Materials and TechnologySchool of Physics Science and EngineeringTongji UniversityShanghai 200092China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 200092China

Equations(8)and(9)in the original paper[***.B 30036301(2021)]are corrected.

关键词： phonon transport thermal demultiplexer optimization algorithm

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optimization of Elastic Properties of Composite Laminates Using Fiber-Optic Strain Sensors

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APPLIED COMPOSITE MATERIALS 2020年第5期27卷 491-509页

作者： Tashkinov, Mikhail A. Matveenko, Valeriy P. Perm Natl Res Polytech Univ Komsomolsky Ave 29 Perm 614990 Russia Russian Acad Sci Inst Continuous Media Mech Academician Korolev St 1 Perm 614013 Russia

The paper is devoted to combined computational and experimental approach for estimation of the elastic mechanical properties of structures made of laminate polymer composite materials (PCM). The computational component of the technique is connected with numerical simulation of mechanical behavior during quasistatic deformation of structures made of PCM. The experimental component is based on measurement of strains by fiber-optic strain sensors (FOSS) with Bragg gratings (FBG sensors), embedded in composite laminates or attached to them. The principle of the proposed method is based on the comparison of the data from FBG sensors, placed in the predetermined control points in the composite structure, with the data of numerical finite element modelling of the same structure. To refine the elastic constants in accordance with the information received from the FBG sensors, an algorithm is proposed, according to which the inverse problems are solved in order to ensure that the numerical and experimental results coincide with the specified accuracy. The implementation of the algorithm is demonstrated on the example case studies.

关键词： Mechanical characteristics Fiber-optic strain sensors Bragg gratings optimization algorithm Finite element method

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Novel Rewinding-Time Technique Applied for Enhancing Meta-heuristic algorithms

Novel Rewinding-Time Technique Applied for Enhancing Meta-he...

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International Conference on Advanced Mechanical Engineering, Automation and Sustainable Development, AMAS 2021

作者： Dat, Nguyen Tien Kien, Cao Van Anh, Ho Pham Huy 268 Ly Thuong Kiet Street District 10 Ho Chi Minh Viet Nam Linh Trung Ward Thu Duc District Ho Chi Minh Viet Nam

ISBN: (纸本)9783030996659

This paper proposes a new rewinding-time algorithm applied in meta-heuristic optimization techniques including PSO, JAYA to quickly and robustly obtain accurate and stable identified result. In standard optimization algorithms, initiated population are installed to look for the optimum solution with the fitness function value is responded to output requirements. With the proposed rewinding-time technique, the state of each generation, included all of information of population and gradient of fitness function, is stored. During optimize process, the rollback event will be triggered when gradient of fitness function satisfied the jumping condition. The current state is return to the previous state which is chosen if the rollback event active. The proposed technique is fully tested on benchmark test-functions including Shubert, Rosenbrock, Griewank, Salomon, Ackley and Michalewicz. The simulation results indicate that the proposed technique yield a competitive performance in both of precision and stability criteria compared to the standard algorithms. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Benchmark function JAYA optimization technique Novel rewinding-time algorithm optimization algorithm Particle Swarm optimization (PSO)

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Data-Driven Method for Response Control of Nonlinear Random Dynamical Systems

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JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME 2021年第4期88卷 041012页

作者： Tian, Yanping Jin, Xiaoling Wu, Lingling Yang, Ying Wang, Yong Huang, Zhilong Hangzhou Dianzi Univ Coll Mech Engn Hangzhou 310018 Peoples R China Zhejiang Univ Dept Engn Mech Hangzhou 310027 Peoples R China Arizona State Univ Sch Engn Matter Transport & Energy Tempe AZ 85287 USA

The response control of nonlinear random dynamical systems is an important but also difficult subject in scientific and industrial fields. This work merges the decomposition technique of feedback control and the data-driven identification method of stationary response probability density, converts the constrained functional extreme value problem associated with optimal control to an unconstrained optimization problem of multivariable function, and determines the optimal coefficients of preselected control terms by an optimization algorithm. This data-driven method avoids the difficulty of solving the stochastic dynamic programming equation or forward-backward stochastic differential equations encountered in classical control theories, the miss of the conservative mechanism in the nonlinear stochastic optimal control strategy, and the difficulty of judging the integrability and resonance of the controlled Hamiltonian systems encountered in the direct-control method. The application and efficacy of the data-driven method are illustrated by the random response control problems of the Duffing oscillator, van der Pol system, and a two degrees-of-freedom nonlinear system.

关键词： random response control nonlinear dynamical system data-driven method decomposition technique of feedback control optimization algorithm vibration

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Application of a novel grey Bernoulli model to predict the global consumption of renewable energy

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ENERGY REPORTS 2021年 7卷 7200-7211页

作者： Duan, Huiming Wang, Siqi He, Chenglin Huang, Jiangbo Chongqing Univ Posts & Telecommun Sch Sci Chongqing 400065 Peoples R China

Accurate prediction of renewable energy can provide an important basis for national energy security and the government to formulate policies. Therefore, according to the non-linearity of energy prediction system, this paper proposes a new nonlinear grey Bernoulli optimization model by the grey Bernoulli extended model, which is a nonlinear grey prediction model, and studies the properties of the new model. The order and nonlinear coefficient of the new model are optimized by Particle Swarm optimization. Then, through the consumption of global renewable energy, such as solar, wind and hydropower as empirical analyses, the results of the four evaluation indicators show that the new model works better than the original model, which has higher prediction accuracy than before and makes the prediction model more applicable. At the same time, the model results were compared with the weighted grey model, Verhulst and the discrete grey model, and the new model has the highest accuracy. Finally, the new model is used to forecast the global consumption of wind, solar and hydropower energy in 2019-2023. The results will provide important forecasting information for global energy conservation and emission reduction policies. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Grey prediction model Bernoulli model Renewable energy consumption optimization algorithm Forecasting

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