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Security algorithm of Internet of Things based on ZigBee protocol

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6-Sup期22卷 14759-14766页

作者： Wang, Yongkang Chen, Chunxia Jiang, Qijie Civil Aviat Flight Univ China Sch Aviat Transportat Management Guanghan Peoples R China Chengdu Technol Univ Sch Econ & Management Chengdu Sichuan Peoples R China Univ Nottingham Sch Business Nottingham England

To study the application of ZigBee protocol in the security algorithm of Internet of Things, the relevant development status at home and abroad is firstly summarized and ZigBee technology is introduced in detail. Then, the principle of AES-128 algorithm is analyzed, and the steps of decryption algorithm are adjusted, so that the decryption algorithm is symmetric in structure and encryption algorithm. In addition, the encryption and decryption algorithm of AES-128 is implemented by using C language. Based on the characteristics of simplicity and low cost of ZigBee technology, the two optimization algorithms are designed and implemented from the analysis of simplicity and efficiency based on the performances of security algorithm. The analysis and test results show that the two optimization algorithms are better than the UN optimized algorithm in terms of speed and complexity. To sum up, in the result comparison, it is found that the speed and complexity of the round operation optimization algorithm is better than that of the column obfuscation optimization algorithm.

关键词： ZigBee protocol Security AES-128 algorithm optimization

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Efficient 2-D MUSIC algorithm for super-resolution moving target tracking based on an FMCW radar

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Geodesy and Geodynamics 2024年第5期15卷 504-515页

作者： Xuchong Yi Shuangxi Zhang Yuxuan Zhou School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China Key Laboratory of Geospace Environment and Geodesy Ministry of EducationWuhan 430079China

Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental ***,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution *** paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW ***,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching ***,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target *** two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and *** experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.

关键词： 2D-MUSIC FMCW radar Moving target tracking Super-resolution algorithm optimization

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Optimal implicit single-step time integration methods with equivalence to the second-order-type linear multistep methods for structural dynamics: Accuracy analysis based on an analytical framework

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2024年第PartA期418卷

作者： Zhang, Jie Jinan Univ Sch Mech & Construct Engn MOE Key Lab Disaster Forecast & Control Engn Guangzhou 510632 Peoples R China

This paper presents a comprehensive study of the second-order-type time integration methods family encompassing the linear multistep (LMS) methods, the single-step methods, and the LMS equivalent single-step methods for structural dynamics. An analytical accuracy framework for algorithm design, convergence, and optimization is developed, where the obstacles encountered in algorithms construction, convergence accuracy, algorithms equivalence, accuracy measurement, and accuracy optimization in traditional accuracy frameworks are well addressed. Rigorous accuracy analysis successively to the second-order-type LMS (LMS2) methods, the single-step methods, and the LMS2 equivalent single-step methods aims to reveal optimal algorithms with desirable numerical properties. First, independent implicit algorithms including the velocity type and the acceleration type LMS2 methods except the displacement type ones are newly revealed in the LMS2 methods family with second-order convergence and A-stability, and three error constants that can play essential roles in the accuracy measurement and algorithm optimization are developed. Second, a single-step methods family where the displacement, velocity, and acceleration can achieve the same order of accuracy simultaneously is revealed in a generalized 16 -parameters methods family, which contains numerous conventional single-step single-solve methods as subfamily methods. It is found that the unit consistent and non-consistent represen-tations show a significant difference in the local truncation error, stability, and convergence performances. Third, a family of accuracy-improved single-step methods with algorithmic equivalence, which is stricter than the traditional spectral equivalence, to the LMS2 methods is revealed. It is clarified that the difference between the methods with equivalence can significantly influence their convergence accuracy, and the error constants concept of the LMS2 methods can be extended to the single-step m

关键词： Accuracy analysis algorithm optimization Controllable numerical dissipation Stability Time integration Structural dynamics

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Fish sonar image recognition algorithm based on improved YOLOv5

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2024年第1期21卷 1321-1341页

作者： Xing, Bowen Sun, Min Ding, Minyang Han, Chuang Shanghai Ocean Univ Coll Engn Sci & Technol Shanghai 201306 Peoples R China Marine Design & Res Inst China Shanghai 200011 Peoples R China Harbin Univ Sci & Technol Heilongjiang Prov Key Lab Laser Spect Technol & Ap Harbin 150080 Peoples R China

Fish stock assessment is crucial for sustainable marine fisheries management in rangeland ecosystems. To address the challenges posed by the overfishing of offshore fish species and facili-tate comprehensive deep-sea resource evaluation, this paper introduces an improved fish sonar image detection algorithm based on the you only look once algorithm, version 5 (YOLOv5). Sonar image noise often results in blurred targets and indistinct features, thereby reducing the precision of object detection. Thus, a C3N module is incorporated into the neck component, where depth-separable convo-lution and an inverse bottleneck layer structure are integrated to lessen feature information loss during downsampling and forward propagation. Furthermore, lowercase shallow feature layer is introduced in the network prediction layer to enhance feature extraction for pixels larger than 4 x 4. Additionally, normalized weighted distance based on a Gaussian distribution is combined with Intersection over Union (IoU) during gradient descent to improve small target detection and mitigate the IoU's scale sensitivity. Finally, traditional non-maximum suppression (NMS) is replaced with soft-NMS, reducing missed detections due to occlusion and overlapping fish targets that are common in sonar datasets. Experiments show that the improved model surpasses the original model and YOLOv3 with gains in precision, recall and mean average precision of 2.3%, 4.7% and 2.7%, respectively, and 2.5%, 6.3% and 6.7%, respectively. These findings confirm the method's effectiveness in raising sonar image de-tection accuracy, which is consistent with model comparisons. Given Unmanned Underwater Vehicle advancements, this method holds the potential to support fish culture decision-making and facilitate fish stock resource assessment.

关键词： sonar fish detection YOLOv5 deep learning algorithm optimization

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Application of big data optimized clustering algorithm in cloud computing environment in traffic accident forecast

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2021年第4期14卷 2511-2523页

作者： Tian, Zhun Zhang, Shengrui Changan Univ Coll Transportat Engn Xian 710064 Shaanxi Peoples R China Xian Univ Architecture & Technol Sch Civil Engn Xian 710055 Shaanxi Peoples R China Changan Univ Key Lab Transport Ind Management Control & Cycle Xian 710064 Shaanxi Peoples R China

As the usage rate of cars is getting higher and higher, the injuries and losses caused by traffic accidents are also getting bigger and bigger. If some traffic accidents can be predicted, then such losses can be greatly solved. Although there are abundant research results on intelligent transportation, there are not many research results on how to predict traffic accidents. For this issue, the main aim of this paper is to propose a continuous non-convex optimization of the K-means algorithm in order to solve the model problem in the traffic prediction process. First, this paper uses clustering algorithm for feature analysis and big data for the establishment of simulation model in cloud environment. Through this paper an equivalent model, using matrix optimization theory to analyze and process K-means problem, and design efficient and theoretically guaranteed algorithms for big data. By simulating the traffic situation in Shanghai city within three years, the outcomes display that the model endorsed in the given paper can predict traffic accidents at a rate of 93.88% and the accuracy rate of traffic accident processing time is 78%, which fully illustrates the effectiveness of the model established in this paper.

关键词： Cloud computing Big data Clustering algorithm Traffic accident prediction algorithm optimization

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Low-complexity MP3 decoder based on Broadcom embedded platform

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Journal of Beijing Institute of Technology 2011年第1期20卷 94-99页

作者：冉川沈庭芝 School of Information and Electronics Beijing Institute of Technology

A low complexity MP3 decoder based on Broadcom embedded platform was proposed. C code level optimization algorithms on inverse quantization, stereo decoding and alias reduction based on PC were proposed to further reduce the amount of memory usage and the computational complex ity. Furthermore, the executable file of the optimized MP3 decoder was generated under the Linux environment, and transplanted to the set top box based on Broadcom embedded platform. Experi ment results showed that the total time for decoding was reduced on the embedded platform, and the goal of real time and fluent playing of audio files was fulfilled, which demonstrated the effectiveness of the proposed MP3 decoder. The proposed MP3 decoder could be applied in fields such xs the set top box based on Broadcom embedded platform and other portable devices.

关键词： MP3 decoder algorithm optimization Linux Broadcom

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COMPLEX SURFACE APPROXIMATION WITH DEVELOPABLE STRIPS

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JOURNAL OF THE INTERNATIONAL ASSOCIATION FOR SHELL AND SPATIAL STRUCTURES 2016年第2期57卷 133-143页

作者： Anastas, Yousef Gillet, Margaux Rowenczyn, Laurie Baverel, Olivier Univ Paris Est Lab GSA Geometrie Struct Architecture Ecole Natl Super Architecture Paris Malaquais 14 Rue Bonaparte F-75006 Paris France TESS 7 Cite Paradis F-75010 Paris France UPE CNRS IFSTTAR NAVIERUMR 8205Ecole Ponts F-77455 Champs Sur Marne 2 Marne La Vallee France

Unfolding double-curvature surfaces is a problem that is widely encountered in engineering and increasingly met in architecture and digital fabrication processes. In the context of building construction, the process used to unfold the complex surface matters more than the unfolded result. Mastering the process of developable surfaces is fundamental to the construction method in order to keep the resulting geometry faithful to the initial one, to increase structural efficiency and material savings. The interest in unfolding a surface lies in its feasibility, in order to build surfaces with materials that can be elastically bent. This study is based on geodesic curves on surfaces and involves a process including parameters such as the number of geodesics and the division of these geodesics depending on the curvature of the surface, to be as close as possible to the initial surface. The algorithm approximates the initial surface by building developable strips between two successive geodesic curves.

关键词： Complex surface approximation unfolding strips geodesic curves algorithm optimization

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Stratified waveguide grating coupler for normal fiber incidence

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OPTICS LETTERS 2005年第8期30卷 845-847页

作者： Wang, B Jiang, JH Chambers, DM Cai, JB Nordin, GP Univ Alabama Nano & Micro Devices Ctr Huntsville AL 35899 USA

We propose a new stratified waveguide grating coupler (SWGC) to couple light from a fiber at normal incidence into a planar waveguide. SWGCs are designed to operate in the strong coupling regime without intermediate optics between the fiber and the waveguide. Two-dimensional finite-difference time-domain simulation in conjunction with microgenetic algorithm optimization shows that similar to 72% coupling efficiency is possible for fiber (core size of 8.3 mu m and Delta = 0.36%) to slab waveguide (1.2-mu m core and Delta = 3.1%) coupling. We show that the phase-matching and Bragg conditions are simultaneously satisfied through the fundamental leaky mode. (c) 2005 Optical Society of America.

关键词： Fiber slab waveguide algorithm optimization strong coupling waveguide grating couplers TimeDif leaky modes phase matching normal incidence

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Pb-S-O vapor system re-evaluated using genetic algorithms

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JOURNAL OF PHASE EQUILIBRIA AND DIFFUSION 2004年第5期25卷 421-426页

作者： Chakraborti, N Jha, PK Indian Inst Technol Dept Met & Mat Engn Kharagpur 721302 W Bengal India

The efficacy of biologically inspired genetic algorithms for optimization is now well established. This article discusses the scope of using such an algorithm as an equation solver and presents detailed calculations on the Pb-S-O vapor system containing a total of 20 species as a paradigm case. This further increases the scope of applications of this evolutionary methodology in the domain of phase equilibria research, and this methodology is expected to be more advantageous than many other conventional techniques.

关键词： algorithm optimization Traditional technology Vapors phase equilibria Genetic algorithm (GA)

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The collection of theater music data and genre recognition under the internet of things and deep belief network

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JOURNAL OF SUPERCOMPUTING 2022年第7期78卷 9307-9325页

作者： Xiang, Hua Hunan Normal Univ Coll Mus Changsha Hunan Peoples R China

In order to improve the efficiency and accuracy of collecting theater music data and recognizing genres, and solve the problem that a single feature in traditional algorithms cannot efficiently classify music genres, the technology of collecting data based on the Internet of Things (IoT) and Deep Belief Network (DBN) is firstly proposed for application of collecting music data and recognizing genres. The study firstly introduces the scheme of collecting music data based on the Internet of Things (IoT) and the theoretical basis of the recognition and classification of music genres by DBN. Second, the study focuses on the construction and improvement of the music genre recognition algorithm under DBN. In other words, the algorithm is optimized by adding Dropout and momentum to the network, and the optimal network model after training is implemented. And finally, the effectiveness of the algorithm is confirmed by experiment and research. The experimental results show that the efficiency of the optimized algorithm of identifying the music genres in the music library reaches 75.8%, which is far better than the traditional classic algorithms in the past. It is concluded that the technology of music data collection and genre recognition based on IoT and DBN has strong advantages, which will greatly contribute to reducing the workload of manual collection and identification of classification features, and improve efficiency. Meanwhile, the optimized algorithm model can also be extended to other fields.

关键词： Internet of Things Deep belief network Collection of music data Genre recognition algorithm optimization Classification features

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