2020 Vol.38

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Journal of Applied Sciences    2020, 38 (1): 0-0.   Abstract （400）      PDF（pc） （49KB）（91）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Blockchain for Edge AI Computing: A Survey FANG Junjie, LEI Kai Journal of Applied Sciences    2020, 38 (1): 1-21.   DOI: 10.3969/j.issn.0255-8297.2020.01.001 Abstract （2104）      PDF（pc） （2418KB）（1958）       Knowledge map    Save Blockchain builds a distributed point-to-point system, which is widely used in the fields of financial economy, Internet of Things (IoT), big data, cloud computing and edge computing. Meanwhile, edge artificial intelligence (AI) computing refers to the emergence of swarm intelligence AI computing model for edge network application scenarios. Although featuring in the characteristics of high dynamic, ultra-low delay, resource limitation, data calculation decoupling in application scenarios of edge networks such as intelligent car, blockchain faces further challenges including cross-domain trust, privacy protection, intrusion monitoring and fine-grained incentives. Focusing on the trend of transforming the algorithm and application of AI from cloud centers to the edges of networks, this paper discusses the application of blockchain in the emerging edge AI computing research. We first introduce the infrastructure of blockchain and summarize related researches and application directions. Then, beginning with the concept and rise of edge AI computing, the application requirements of blockchain in edge AI computing are analyzed and discussed in detail, including relevant research review, application trend and future research direction. Additionally, we summarize the advantages of applicating blockchain in edge AI computing and the deficiencies need to be addressed in the future. Reference | Related Articles | Metrics | Comments（0）

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Blockchain in Internet of Things: Application and Challenges HE Zhengyuan, DUAN Tiantian, ZHANG Ying, ZHANG Hanwen, SUN Yi Journal of Applied Sciences    2020, 38 (1): 22-33.   DOI: 10.3969/j.issn.0255-8297.2020.01.002 Abstract （1325）      PDF（pc） （3656KB）（638）       Knowledge map    Save Since the Internet of Things (IoT) technology has developed rapidly and been widely used in various fields, issues such as identity verification, data privacy, network security, that need to be considered by IoT will become more important in the distributed environment. And these problems can be effectively solved by introducing blockchain technology into IoT. In this paper, we briefly describe the basic concepts of blockchain and application scenarios of blockchain in the IoT, and review some current relevant research works, among which the works on underlying technologies of blockchain IoT and the problems and challenges faced in the blockchain IoT are emphasized. The work of this paper will provide reference value for the future researches of blockchain IoT. Reference | Related Articles | Metrics | Comments（0）

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A Practical Byzantine Fault Tolerance Consensus Algorithm Based on Tree Topological Network BAO Zhenshan, WANG Kaixuan, ZHANG Wenbo Journal of Applied Sciences    2020, 38 (1): 34-50.   DOI: 10.3969/j.issn.0255-8297.2020.01.003 Abstract （988）      PDF（pc） （10189KB）（533）       Knowledge map    Save The practical Byzantine fault tolerance (PBFT) algorithm suffers its performance bottleneck in wide-area networks with a large number of nodes. In order to improve the scalability of the algorithm, we propose to divide the whole network consensus into several subnetwork consensus based on tree topology network. At the same time, a reputation model is introduced to reduce the influence of fault nodes in the consensus process and improve the security, fault tolerance and reliability of the system. Experimental results show that the performance of the proposed algorithm is significantly improved comparing with the original one, showing good scalability and applicability to large-scale permissioned blockchain system. Reference | Related Articles | Metrics | Comments（0）

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A Scalable Consensus Protocol Based on Equity Representation LI Zhongcheng, HUANG Jianhua, TANG Ruicong, HU Qingchun, XIA Xu Journal of Applied Sciences    2020, 38 (1): 51-64.   DOI: 10.3969/j.issn.0255-8297.2020.01.004 Abstract （995）      PDF（pc） （5760KB）（715）       Knowledge map    Save The difficulty in achieving dynamic balance of decentralization, security and scalability of blockchain systems lies in the design of efficient consensus mechanisms. In order to solve the bottleneck problem of security and performance faced by the consensus mechanisms in the existing blockchain systems, this paper proposes a delegate-based scalable consensus protocol (DSCP) based on equity representatives. First, DSCP uses the partition parallel consensus method to build a high-performance and scalable blockchain and generate a consensus block that is recognized by the entire network through a proxy mechanism. Then, in order to improve the network partition speed and the consensus performance during the partition, this paper proposes a fast partitioning mechanism based on VRF algorithm, and designs a voting-based partitioning high-performance consensus algorithm voting-based consensus protocol (VCP). At last, this paper also proposes a new incentive and deposit mechanism to enhance the security of the DSCP protocol. Experimental analysis shows that DSCP has a good performance advantage compared with the existing blockchain consensus protocols. Reference | Related Articles | Metrics | Comments（0）

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System of River Chief-Oriented Water Quality Information Certification Based on Blockchain ZOU Xiuqing, LUO Decun, LIN Ping, SHEN Shiping, XIE Zhenping, WANG Yujue, DING Yong Journal of Applied Sciences    2020, 38 (1): 65-80.   DOI: 10.3969/j.issn.0255-8297.2020.01.005 Abstract （919）      PDF（pc） （11814KB）（393）       Knowledge map    Save In this paper, the blockchain technology is applied to the water quality information management field of the river chief-oriented system, for solving the problems of data management centralization, non-openness, and opaque faced by traditional technologies. The river chief-oriented water quality information system is built with the enterprise-level open-source framework Hyperledger Fabric. It uploads the core water quality information to the blockchain and provides relevant information certification storage function for users. It could restore illegally tampered water information by verification, thus ensuring the security and reliability of system data. Experimental results show that the average throughput of water quality information uploading and query on the chain reaches more than 200 tps, up to 500 tps, which meets the expected requirements of system performance. Reference | Related Articles | Metrics | Comments（0）

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Credible Depository Chain System of Card Games YUAN Chenjuan, SUN Guozi, LI Huakang, WANG Jitao Journal of Applied Sciences    2020, 38 (1): 81-92.   DOI: 10.3969/j.issn.0255-8297.2020.01.006 Abstract （860）      PDF（pc） （2799KB）（321）       Knowledge map    Save At present, the trust problem of chess and card games on the market has not been solved with effective methods, and phenomena of cheating such as plug-ins are endless. Therefore, based on the characteristics of decentralization and tamper resistance of the current blockchain, we propose a card game anti-cheat method. This method uses the API to access the player's card information and applies the Huffman Merkle Hash tree (HuffMHT) algorithm to compress card information which is then encrypted by various encryption algorithms. At last, a smart contract is written to anchor the encrypted information on the blockchain. In the proposal, everyone has the access to compare the licensing information on the blockchain with the final complete card information to find out if they are cheating. Experimental results show that the proposed method is capable of solving the trust problem of card games effectively and enables a safe card game environment. Reference | Related Articles | Metrics | Comments（0）

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A Byzantine Fault Tolerance Raft Algorithm Combines with BLS Signature WANG Rihong, ZHANG Lifeng, ZHOU Hang, XU Quanqing Journal of Applied Sciences    2020, 38 (1): 93-104.   DOI: 10.3969/j.issn.0255-8297.2020.01.007 Abstract （733）      PDF（pc） （3098KB）（739）       Knowledge map    Save Aiming at the problem of Byzantine fault tolerance (BFT) in the Raft algorithm, a Raft Byzantine fault tolerance (RBFT) algorithm combined with BLS signature is proposed. First, it uses BLS signatures to implement threshold signatures, converts the voting process into a threshold signature process, and combines this process with the Raft algorithm's AppendEntries message and RequestVote message to minimize the impact of the fault-tolerant process on consensus efficiency. Second, it introduces a safe status through the incremental Hash value to ensure the log's tamper-resistibility. Then it provides dynamical monitoring on the leader node so as to avoid the possible negative feedback of Byzantine leader and ensure the liveness of the algorithm. Finally, local multi-node simulation experiments show that the RBFT algorithm could improve the throughput and scalability, and reduce the latency of transactions effectively. Reference | Related Articles | Metrics | Comments（0）

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Trustworthy Storage Technology about Electronic Warehouse Receipts Based on Blockchain WANG Wenqi, PAN Heng, PAN Lei, GUAN Yunyun Journal of Applied Sciences    2020, 38 (1): 105-118.   DOI: 10.3969/j.issn.0255-8297.2020.01.008 Abstract （1067）      PDF（pc） （9394KB）（666）       Knowledge map    Save Warehouse receipt is an important voucher in the supply-chain logistics circulation. The basic requirement is that the electronic warehouse receipts and its warehouse process information are credible and non-modifiable, but the traditional database technology cannot solve these issues. In this paper, based on blockchain technology, the overall framework for storing electronic warehouse and related IoT information is proposed, and a consensus algorithm-based credit degree is designed. Based on the source code of bitcoin, an underlying blockchain storage system is re-designed to store various information and to be suitable for trading operations. The trading algorithm that can trade warehouse and store storage information is redesigned. Finally, experimental results show the system has good effectiveness and practicability. Reference | Related Articles | Metrics | Comments（0）

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Blockchain Node Storage Optimization Scheme JIANG Yunchao, HE Xiaowei, CUI Yiju Journal of Applied Sciences    2020, 38 (1): 119-126.   DOI: 10.3969/j.issn.0255-8297.2020.01.009 Abstract （942）      PDF（pc） （3463KB）（807）       Knowledge map    Save With the development of blockchain technology, the blocks in blockchain are keeping increasing, the new blockchain nodes are facing the problems of increasingly large storage and increasingly long time in block synchronization. In order to solve the problems, this paper proposes a blockchain node storage optimization scheme, which firstly calculates the number of blocks in each sharding by analyzing the probability of blockchain malicious nodes, then obtains the number of blockchain nodes and the probability of the block with the largest number being attacked by malicious node within the sharding, and at last, calculates the number of copies that need to be stored in each sharding. Experimental analysis shows that the optimization scheme reduces 50% blocks storage and 22% synchronization time in blockchain nodes, therefore, it can not only reduce the node storage in blockchain, but also improve the efficiency of new nodes joining the blockchain. Reference | Related Articles | Metrics | Comments（0）

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A Patient-Controlled Security Access Mechanism for Electronic Health Records PAN Heng, PAN Lei, YAO Zhongyuan, SI Xueming Journal of Applied Sciences    2020, 38 (1): 127-138.   DOI: 10.3969/j.issn.0255-8297.2020.01.010 Abstract （906）      PDF（pc） （4745KB）（486）       Knowledge map    Save In the existing cloud environment, the special requirements of patients to make full control of his/her electronic health record can hardly be fulfilled. In order to solve this problem, a secure access scheme HyperEHR based on Hyperledger fabric and interplanetary file system (IPFS) is proposed. In the proposal, the medical record requester first needs to obtain the consent of his/her organization, and the patient have the final right to make the decision of accessing permission. To ensure the security of cross-organization medical data access, information like medical record generation, update and access is stored in collaborative blockchain. Moreover, specific medical record information and access control policies generated by hospitals and clinics are encrypted and stored in the cloud interplanetary file system. System implementation and analysis show that the scheme has good scalability, interoperability and security. HyperEHR can not only help patient to make control of his/her medical data accessing, but also prevent the privacy disclosure of electronic health record effectively. Reference | Related Articles | Metrics | Comments（0）

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Location Information Protection Model for IoT Nodes Based on Blockchain SHE Wei, CHEN Jiansen, GU Zhihao, TIAN Zhao, XU Li, LIU Wei Journal of Applied Sciences    2020, 38 (1): 139-151.   DOI: 10.3969/j.issn.0255-8297.2020.01.011 Abstract （904）      PDF（pc） （4656KB）（274）       Knowledge map    Save The Internet of Things (IoT) is changing people's consuming behavior and business processes. Aiming at the information privacy and security of IoT devices, this paper proposes a location information protection model for IoT devices based on blockchain technology. Firstly, this model records device identification with the help of blockchain technology to ensure that the information of IoT devices cannot be tampered. Then the distributed Hash table (DHT) network is implemented based on white list technology and the device location information is XOR processed to hide the network topology of the IoT. Finally, the sensitive attributes of the data are generalized according to k-anonymous algorithm to provide users with regional information statistics services. The experimental results show that the model can effectively hide device location information, provide customized regional statistics service and protect user information security. Reference | Related Articles | Metrics | Comments（0）

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Intelligent Eco Networking (IEN): Knowledge-Driven and Value-Oriented Future Internet Infrastructure LEI Kai, HUANG Shuokang, FANG Junjie, HUANG Jiyue, XIE Yingying, PENG Bo Journal of Applied Sciences    2020, 38 (1): 152-172.   DOI: 10.3969/j.issn.0255-8297.2020.01.012 Abstract （1854）      PDF（pc） （17166KB）（260）       Knowledge map    Save As the trend of knowledgelization of content, evaluation of knowledge, networking of value, ecologicalization of network and intellectualization of ecology is becoming increasingly prominent in the future Internet. In this paper, we propose the con-cept of intelligent eco networking (IEN) for the future Internet, countering with the deficiencies of the current IP networks, including rigid architecture, weak content awareness, poor multi-architecture/multi-network integration, low scheduling flexibility, lacking endogenous security and trust maintenance mechanism, single quality of service (QoS) mode and outdated evaluation indicators and methods. IEN adopts software and hardware integrated technology roadmap based on virtualization and configurable devices, improves information-centric networking (ICN) architecture, integrates distributed artificial intelligence (AI) analysis decision and blockchain consensus computing technology, considers network resource cost/profit indicators regarding storage, computing and bandwidth resources, aims at building a hierarchical, intelligent and semantic network architecture. IEN is backward compatible with IP protocol; forward evolves towards naming and IP integrated, heterogeneous computing addressing and multi-modal network protocol for cross-domain, edge-critical scenario, overlays content, identity authentication and multi-party trusted incentive mechanism; optimizes network resources allocation model and evaluation system. Through content semantic detection and identity credibility authentication, IEN insists on both security and openness. IEN aims to form a network infrastructure with high expansion, dynamic adaptation, and multi-objective optimization. It explores a new generation of industrialization, economics, and ecological Internet, and establishes an intelligent network of openness, sharing and synergy. Reference | Related Articles | Metrics | Comments（0）

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Identity Authentication Protocol of Micro-grid Power Based on Consortium Blockchain ZHANG Lihua, HU Fangzhou, HUANG Yang, WAN Yuanhua, LI Jingjing Journal of Applied Sciences    2020, 38 (1): 173-183.   DOI: 10.3969/j.issn.0255-8297.2020.01.013 Abstract （987）      PDF（pc） （3712KB）（292）       Knowledge map    Save At present, the key problems existing in micro-grid power transaction include the insecurity of identity authentication protocol, the centralization of transaction, and the lack of data traceability and consensus among nodes. Blockchain has the advantages of distributed storage, decentralization and non-tampering of data. To this sense, this paper proposes an authentication protocol of micro-grid power transaction based on consortium Blockchain, which applies blockchain to micro-grid identity authentication to solve the above problems. First, the new node authentication solution is obtained by using zero knowledge proof. Second, its ID is written in the Merkle tree and broadcast in the consortium blockchain, thus, getting rid of the existing problems mentioned above in microgrid power transaction, and ensuring the immutability, security, and traceability of data. Finally, by taking the advantages of Ripple consensus protocol (RCP) in security and efficiency, the proposed protocol can effectively solve the consensus problem between nodes. In comparison with other schemes, the proposed scheme has a lower computational overhead and faster consensus rate. Scheme analysis on security and function shows that this scheme can not only guarantee the security of micro-grid identity authentication, but also ensure the optimal performance of nodes. Reference | Related Articles | Metrics | Comments（0）

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Book Infringement Record Depositing Platform Based on Blockchain ZHANG Yifei, CAO Shaozhong, QI Deli, WANG Liang, YANG Yanhong Journal of Applied Sciences    2020, 38 (1): 184-196.   DOI: 10.3969/j.issn.0255-8297.2020.01.014 Abstract （784）      PDF（pc） （4901KB）（204）       Knowledge map    Save Aiming at the dilemma that more and more frequent audio reading books failing to validate the infringement of books in a timely and effective manner, this paper proposes a scheme for using the blockchain technology to automatically deposit certificates of copyright infringement records. Firstly, the audio information crawled from the network, then, the results are stored in the private blockchain structure after checking and comparing with the content of the book. Secondly, based on the proof of work (PoW) consensus, the platform designs and implements a feasible consensus algorithm. Finally, the security of block data is verified by combining the cryptographic summary information authentication as well as digital signature verification mechanism. System testing results show the efficiency and reliability of the platform, providing it a valid and feasible book infringement record deposit scheme. Reference | Related Articles | Metrics | Comments（0）

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Journal of Applied Sciences    2020, 38 (2): 0-0.   Abstract （4）      PDF（pc） （106KB）（48）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Journal of Applied Sciences    2020, 38 (2): 0-0.   Abstract （8）      PDF（pc） （45KB）（22）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Journal of Applied Sciences    2020, 38 (2): 0-0.   Abstract （464）      PDF（pc） （297KB）（138）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Progress in Research of Brillouin Optical Time Domain Analysis for Dynamic Strain Sensing ZHU Tao, ZHENG Hua, ZHANG Jingdong Journal of Applied Sciences    2020, 38 (2): 197-214.   DOI: 10.3969/j.issn.0255-8297.2020.02.001 Abstract （981）      PDF（pc） （29946KB）（291）       Knowledge map    Save Brillouin optical time domain analysis (BOTDA) has wide application prospects in health monitoring of large infrastructure and condition monitoring of aircraft, since it is capable of sensing distributed strain over long distance with high spatial resolution and accuracy. However, the sensing speed of conventional BOTDA is fairly slow and hardly realize dynamic strain measurement due to its frequency sweeping process. Aim at this problem, this paper reviews the research progress of BOTDA for dynamic strain sensing in recent years, including slope-assisted BOTDA (SA-BOTDA), fast BOTDA (F-BOTDA), sweep free BOTDA (SF-BOTDA) and dynamic BOTDA based on chirped pump/probe. The advantages and disadvantages of these technologies are discussed, and the development prospects of BOTDA for dynamic sensing are estimated as well. Reference | Related Articles | Metrics | Comments（0）

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Distributed Optical Fiber Sensing Technology and Its Application in Coal Mine Safety Production LI Shinian, ZHANG Xuping, SONG Hong, CHEN Jian, ZHANG Yixin, LU Jinbo, ZHAO Xiaojing Journal of Applied Sciences    2020, 38 (2): 215-225.   DOI: 10.3969/j.issn.0255-8297.2020.02.002 Abstract （964）      PDF（pc） （8840KB）（374）       Knowledge map    Save Coal is the main source of energy in China, and coal mine geological monitoring is an important guarantee for the safe production of coal mines. Distributed optical fber sensing technology has the advantages of sensing continuity, high precision, antielectromagnetic interference and corrosion resistance, and has been applied in coal-mine geological monitoring in recent years. First, this paper introduces the principle of Brillouin optical time-domain reflectometry (BOTDR) technology and its applications in the coal-mine geological monitoring. Second, a practical application of BOTDR to monitor the deformation of coal-mine goaf is demonstrated. It shows that the distributed optical fber measurement could sufciently meet the requirements of coal-mine geological monitoring and has a good application prospect. Reference | Related Articles | Metrics | Comments（0）

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Research Progress of Fiber Micro Cavity Fabry-Perot Interference Sensors ZHAO Chunliu, LI Jiali, XU Ben, GONG Huaping, WANG Dongning Journal of Applied Sciences    2020, 38 (2): 226-259.   DOI: 10.3969/j.issn.0255-8297.2020.02.003 Abstract （1012）      PDF（pc） （68687KB）（308）       Knowledge map    Save Fiber microcavity sensors have gained widespread attention in the feld of optical fber sensing due to their inherent safety, small size, low cost, and resistance to electromagnetic interference. Fiber microcavity Fabry-Perot interference sensors features with multiple measurable parameters and the capability of simultaneous measurement of multiple parameters. This article reviews the research progress of the fber microcavity Fabry-Perot interference sensors in various sensing scenarios, such as temperature, pressure, liquid refractive index, hydrogen concentration, organic volatiles concentration and so on, and introduces the manufacturing method, sensing principle and experimental results of the sensors in detail. Reference | Related Articles | Metrics | Comments（0）

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Research on Temperature Sensors Based on Microstructured Fiber GENG Youfu, LI Xuejin Journal of Applied Sciences    2020, 38 (2): 260-278.   DOI: 10.3969/j.issn.0255-8297.2020.02.004 Abstract （1857）      PDF（pc） （33192KB）（267）       Knowledge map    Save A variety of microstructured fber temperature sensors, including intermodalinterference types of Mach-Zehnder, Michelson and F-P interferometers and fluorescence type based on demodulation method, have been studied comprehensively and profoundly.The corresponding theories, sensor systems and functional devices are constructed. Among these works, a novel multi-parameter fluorescence fber temperature sensor with a new signal processing method based on the strong correlation between excitation light and fluorescence was proposed. And based on a small segment of liquid-flled microstructured fber, an all-fber Mach-Zehnder temperature fber sensor with ultrahigh sensitivity of -1.83 nm/℃ was developed. In addition, a Michelson-type high temperature fber sensor with a tiny probe size of only 1.03 mm was achieved by utilizing a high-order mode in all-solid photonic bandgap fber. Moreover, a grape-type microstructured fber F-P interferometer sensor for high temperature measurement was proposed and demonstrated. The high temperature sensor performs a sensitivity of 17.7 pm/℃ at 1 570 nm and a high measurable temperature of up to 1 000 ℃. Reference | Related Articles | Metrics | Comments（0）

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Progress in High Resolution Demodulation Techniquesfor Wavelength-Encoded Optical Fiber Sensor CHEN Jiageng, LIU Qingwen, ZHAO Shuangxiang, He Zuyuan Journal of Applied Sciences    2020, 38 (2): 279-295.   DOI: 10.3969/j.issn.0255-8297.2020.02.005 Abstract （728）      PDF（pc） （25789KB）（113）       Knowledge map    Save This paper introduces the latest progress in the demodulation techniques of high resolution wavelength-coded optical fber sensor, which are applicable to high performance optical fber strain sensor and sensor array with sub-nano strain resolution. This paper frst reviews and discusses the classical FBG strain sensing technique and introduces the optimized sensing elements in high resolution optical fber strain sensing systems; then presents the authors' recent works on demodulation methods for high resolution optical fber sensors, including a feed-forward frequency-swept laser linewidth compression technique and a closed-loop cyclic interrogation technique in detail. Finally, we introduces an implementation of the high resolution optical fber sensors in the observation of crustal deformation, providing an example for other related research and application scenarios. Reference | Related Articles | Metrics | Comments（0）

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New Type of Microstructure-Fiber Distributed Acoustic Sensing Technology and Its Applications LIU Deming, HE Tao, XU Zhijie, SUN Qizhen Journal of Applied Sciences    2020, 38 (2): 296-309.   DOI: 10.3969/j.issn.0255-8297.2020.02.006 Abstract （1068）      PDF（pc） （29394KB）（536）       Knowledge map    Save A new distributed microstructure optical fber (DMOF) and a distributed acoustic sensing technology based on the DMOF are introduced in this paper. The DMOF is a new type of longitudinal microstructure fber formed by continuously preparing microstructure scattering unit in the core of ordinary communication optical fber through precise lithography technology. The microstructure-fber distributed acoustic sensor (MFDAS) based on this new type of DMOF has superior performance such as high sensitivity,large monitoring scale and wide frequency response. The key technologies and research progress of the MF-DAS are introduced in this paper, including that the signal-to-noise ratio of the MF-DAS sensing signal is increased by enhancing the microstructure light scattering, the near-far-end signal difference of the MF-DAS is reduced by the microstructure fber link equalization, and the response broadband of detectable distributed sound-wave is improved signifcantly by the microstructure optical time domain reflection (M-OTDR) and the time slot multiplexing of microstructure optical time domain reflection. The new MF-DAS features with large-scale, high-sensitivity and broad response bandwidth in the acquisition of sound wave information, and shows a very broad application prospect in the injury detection of critical infrastructure and the security monitoring of external intrusion. Reference | Related Articles | Metrics | Comments（0）

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Few-Mode Fiber Long-Period Gratings—From Mode Conversion to High Sensitivity Fiber-Optic Sensing ZHAO Yunhe, LIU Yunqi Journal of Applied Sciences    2020, 38 (2): 310-338.   DOI: 10.3969/j.issn.0255-8297.2020.02.007 Abstract （761）      PDF（pc） （69539KB）（208）       Knowledge map    Save Few-mode fber (FMF) long-period grating (LPG) with advantages of good wavelength selectivity, low insertion loss, flexible structure, high integration and compatibility with optical fber systems,is an effective means to realize mode conversion and vortex mode regulation in the FMF, which have great potential for applications in the optical fber communications and fber-optic sensing. This paper presents the research progress of FMF-LPG in mode conversion and optical fber sensing. Firstly, the mode coupling principle and fabrication methods of FMF-LPG are introduced. Then, the mode converters based on FMF-LPG including standard LPG and helical LPG are investigated. Finally, the working principle and implementation method of fber-optic sensors based on FMF-LPG are demonstrated. Reference | Related Articles | Metrics | Comments（0）

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Journal of Applied Sciences    2020, 38 (3): 0-0.   Abstract （10）      PDF（pc） （48KB）（16）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Journal of Applied Sciences    2020, 38 (3): 0-0.   Abstract （343）      PDF（pc） （425KB）（74）       Knowledge map    Save Related Articles | Metrics | Comments（0）

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Analysis for Psychological Scale Big Data Based on Improved Ising Model YAO Rujing, YANG Lei, YANG Tao, HU Yingxin, TIAN Qiang, WU Ou Journal of Applied Sciences    2020, 38 (3): 339-352.   DOI: 10.3969/j.issn.0255-8297.2020.03.001 Abstract （717）      PDF（pc） （10581KB）（138）       Knowledge map    Save In recent years, the quantitative measurement of individual psychology has attracted more and more attention of administrators and researchers. It has become a new trend to use Ising model for analyzing the psychological scale data. In this paper, aiming at the shortcomings of the existing Ising model, we propose a multi-class Ising model and an ordinal Ising model. By applying them to analyze a large-scale psychological scales data set, we verify the performance of the two improved Ising models, construct complex networks of psychological scales for different groups of people, and conduct the comparisons of various indicators. Some meaningful conclusions have been drawn from the constructed psychological networks, and how machine learning and big data can be better involved in the analysis of psychological scale big data is discussed as well. Reference | Related Articles | Metrics | Comments（0）

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Topic-Specific Assessment Approach for Social Network Influence Evaluation JIANG Qinyin, ZHANG Xi Journal of Applied Sciences    2020, 38 (3): 353-366.   DOI: 10.3969/j.issn.0255-8297.2020.03.002 Abstract （587）      PDF（pc） （5804KB）（229）       Knowledge map    Save Previous studies on user influence modeling in social networks mostly depend on user friendship network structures and retweeting behaviors. It lacks of the consideration of contents and topics of the tweets, which may also play important roles. In addition, taking the interaction among topics into account would facilitate a more accurate user influence modeling. In this paper, we propose a semi-supervised topic extraction method, which brings in a set of seed words during initialization and assigns these seed words higher weights than other words, to improve the effectiveness of topic extraction. To better model the user influence, we involve the interactions among topics, and combine the similarity of topics together with the similarity of users. Experimental results on real-world datasets demonstrate the effectiveness of our proposed methods. Reference | Related Articles | Metrics | Comments（0）

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Lightweight Phytoplankton Detection Network Based on Knowledge Distillation ZHANG Tongtong, DONG Junyu, ZHAO Haoran, LI Qiong, SUN Xin Journal of Applied Sciences    2020, 38 (3): 367-376.   DOI: 10.3969/j.issn.0255-8297.2020.03.003 Abstract （585）      PDF（pc） （8938KB）（203）       Knowledge map    Save Object detection framework based on convolution neural network usually uses a very deep convolution neural network to extract object features before detection. However, its huge network structure leads to the reduction of detection speed, thus, the model can hardly achieve real-time object detection and be put into embedded devices. Address to the problem, this paper applies a knowledge distillation method to feature extraction network of object detection network to improve the performance of shallow feature extraction network. In this way, the model can ensure the same performance with a big reduction on computational load and model scale. Experimental results show that the detection accuracy of feature extraction networks employing distilled shallow network is 11.7% higher than that of networks without teacher’s guidance. Moreover, we build a phytoplankton dataset in this paper, which can not only be used for the evaluation of the performance of object detection algorithms, but also will be helpful to the development of phytoplankton microscopic vision technology. Reference | Related Articles | Metrics | Comments（0）

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Improved Faster R-CNN Algorithm and Its Application on Vehicle Detection WEI Ziyang, ZHAO Zhihong, ZHAO Jingjiao Journal of Applied Sciences    2020, 38 (3): 377-387.   DOI: 10.3969/j.issn.0255-8297.2020.03.004 Abstract （860）      PDF（pc） （18464KB）（312）       Knowledge map    Save In order to obtain an initial candidate frame that conforms to the morphological characteristics of vehicles more accurately, a vehicle detection algorithm based on the improved Faster R-CNN model is proposed. First, the coordinate values of target frames are extracted to get width and height values of labeled boxes, and then K-means algorithm is used to cluster the width and height values of all boxes. Second, by resetting the anchor box size and the anchor box ratio of region proposal network (RPN) according to the coordinates of the cluster center point, the three sizes and three ratios of the Faster R-CNN can be improved. Finally, vehicle data of four types including cars, SUVs, buses and trucks are selected to train both the unimproved and the improved Faster R-CNN models. At the same time, the performance of the two models in vehicle detection and vehicle identification tasks are compared. Experimental results show that the improved Faster R-CNN model can achieve 84.69% detection accuracy, which is 3.12% higher than the original model. The algorithm effectively improves the missed detection and false detection problems, and shows high robustness in bad weather and complex background. Reference | Related Articles | Metrics | Comments（0）

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Research and Application of Improved CRNN Model in Classification of Alarm Texts WANG Mengxuan, ZHANG Sheng, WANG Yue, LEI Ting, DU Wen Journal of Applied Sciences    2020, 38 (3): 388-400.   DOI: 10.3969/j.issn.0255-8297.2020.03.005 Abstract （925）      PDF（pc） （10162KB）（135）       Knowledge map    Save Aiming at classifying the police text descriptions of city’s public security for police stations, this paper builds a text classification of police descriptions based on the existing text classification methods used in other industries. By demonstrating the applicable occasions of common classification networks and their advantages and disadvantages, and combining with the text characteristics of the police case description data, a network structure based on Improved convolutional reccurrent neural network (CRNN) is proposed. The proposed structure provides an optimization key feature extraction process to make up the insufficiency of the existing model in the extraction of short-text feature. Through the comparison test between the proposed model and the existing common classification model, the proposed model not only shows an improved classification accuracy, 2%～3% higher than the existing model, but also provides effective guarantee on the relevance of local features of the data. The model can achieve accurate type classification of police descriptions, thus improving the automation efficiency of the police station. Reference | Related Articles | Metrics | Comments（0）

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Monitoring Microstructural Variations of Plant Tissues by Mueller Matrix Imaging LIU Gang, ZHANG Yali, ZHAO Jingjing, WANG Chunhua Journal of Applied Sciences    2020, 38 (3): 401-409.   DOI: 10.3969/j.issn.0255-8297.2020.03.006 Abstract （539）      PDF（pc） （21657KB）（52）       Knowledge map    Save Mueller matrix imaging, which contents the full polarization information of samples under test, has become an important way to investigate the inner micro-structure of the sample. Based on dual rotating waveplates, a Mueller matrix polarization microscopy imaging system is designed to measure the Mueller matrix images of an anisotropic plant tissue, combining with a novel data processing algorithm. The Mueller matrix imaging and polar decomposition parameters are analyzed, and the changes of plant tissues are monitored by observing the imaging of decomposition parameters. It shows that Mueller matrix imaging are more sensitive to the micro-structure of plant samples, comparing with the traditional intensity images. Reference | Related Articles | Metrics | Comments（0）

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Research on Intelligent Sensing of Radio Signals in Cognitive Networks HUANG Tangsen, LI Xiaowu, CAO Qingjiao Journal of Applied Sciences    2020, 38 (3): 410-418.   DOI: 10.3969/j.issn.0255-8297.2020.03.007 Abstract （509）      PDF（pc） （6690KB）（222）       Knowledge map    Save In the case of noise fluctuation, the performance of the radio signal detection needs to be improved. In this paper, a method for cognitive users to automatically adjust the detection threshold according to the changes of the radio environment is proposed. The fusion center applies coordinate search algorithm to provide the optimal control parameters to cognitive users. Cognitive users set the detection threshold according to the optimal parameters and autonomously learn the optimal threshold for a specific radio environment. In addition, by taking a full consideration of the distinctions and sensing contributions of cognitive users, a new weight calculation method to reflect the distinctions is designed. Simulation results show that the spectrum sensing method has excellent robustness to noise fluctuation. It performs a much higher detection probability than the traditional sensing methods as signal-to-noise ratio (SNR) is below -15 dB. Reference | Related Articles | Metrics | Comments（0）

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Random Interpolation Method for Data Hiding in Encrypted Images SUN Ronghai, SHI Linfu, YU Chunqiang, LAO Huan, TANG Zhenjun Journal of Applied Sciences    2020, 38 (3): 419-430.   DOI: 10.3969/j.issn.0255-8297.2020.03.008 Abstract （660）      PDF（pc） （23976KB）（130）       Knowledge map    Save When traditional data interpolation methods are applied to data hiding in encrypted images, they will reduce security of the data hiding system. To address this problem, we exploit random weight strategy to design a random interpolation method for encrypted images. The proposed method firstly generates the initial interpolated image, which is twice the size of the encrypted image. For the pixels in the odd rows and the odd columns of the interpolated image, the proposed method fills them with the corresponding pixels of the encrypted image. For the rest pixels of the interpolated image, the proposed method generates random values by pseudo-random function and calculates the interpolated results in terms of their detailed locations. Experimental results show that the histograms of interpolated encrypted images calculated by our random interpolation are approximately uniformly distributed. Comparison results demonstrate that our random interpolation outperforms three popular existing interpolation methods. Reference | Related Articles | Metrics | Comments（0）

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Optimization Design of Polar Codes Based on MI Heterogeneity in MLC NAND Flash Channel ZHANG Siqi, KONG Lingjun, ZHANG Shunwai, ZHANG Nan Journal of Applied Sciences    2020, 38 (3): 431-440.   DOI: 10.3969/j.issn.0255-8297.2020.03.009 Abstract （646）      PDF（pc） （7545KB）（191）       Knowledge map    Save In order to further improve the durability and reliability of multi-level-cell (MLC) flash memory, a polar code optimization method based on mutual information (MI) heterogeneity in the MLC flash channel is proposed. By exploiting the differences of log-likelihood ratio (LLR) distribution between MLC flash channels and AWGN (additive white Gaussian noise) channels, and employing MI re-fitting for obeying Gaussian distribution in AWGN channels, the method obtains its equivalent variance of AWGN channels. Thereafter, the polar code optimization design in the high-density storage system is performed according to the obtained new variance. This paper also analyzes the effects of other different polar code construction methods on the error correction of multi-level memory cells, and compares them with the proposed construction method. Simulation results show that the optimization method is better than the traditional construction methods in AWGN channels. It improves bit error rate (BER) by more than 2 orders of magnitudes compared with Monte-Carlo method when program-and-erase (P/E) cycles is 21 000, and it can increase the lifetime of MLC flash memory up to 6 800 P/E cycles at the BER of 2×10-5. Reference | Related Articles | Metrics | Comments（0）

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Robust Coverless Data Hiding Based on Texture Classification and Synthesis SI Guangwen, QIN Chuan, YAO Heng, HAN Yanfang, ZHANG Zhichao Journal of Applied Sciences    2020, 38 (3): 441-454.   DOI: 10.3969/j.issn.0255-8297.2020.03.010 Abstract （524）      PDF（pc） （49960KB）（371）       Knowledge map    Save Aiming at the problem that the embedding rate and robustness of coverless information hiding cannot be well balanced, a robust coverless information hiding scheme based on texture feature classification and synthesis is proposed. In this scheme, texture image features are extracted with spatial pyramid algorithm, and classification models are obtained by supervised classification training. A mapping dictionary is constructed according to the classification of image blocks and different location information. The sender chooses image blocks based on secret information and combines all image blocks into one image according to public key, then generates complex lines through reversible deformation. The texture image can be restored to image blocks by using the key, and the classification model is used to identify the classification of image blocks and determine the location information. Finally, secret information is extracted based on the mapping dictionary. Experimental results show that the proposed scheme has strong robustness against JPEG compression, Gaussian noise, salt and pepper noise and other typical attacks, and the embedding capacity can be further improved with the increase of image category number. Reference | Related Articles | Metrics | Comments（0）

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TOA Estimation Based on Narrowband Interference Mitigation Technique JING Yanliang, LUO Xuetao, WANG Xue, NIE Hong Journal of Applied Sciences    2020, 38 (3): 455-465.   DOI: 10.3969/j.issn.0255-8297.2020.03.011 Abstract （451）      PDF（pc） （8495KB）（185）       Knowledge map    Save Focused on the low accuracy of time of arrive (TOA) estimation in traditional energy detection methods with the presence of narrowband interference, a square filtering technique combining square-law device and band-pass filter is used to eliminate the influence of narrowband interference on TOA estimation in this paper. Then the TOA estimation algorithm is applied to get output estimation results with the IEEE 802.15.4 CM3 channels and CM4 channels. Theoretical analysis and simulation results show that the proposed ED method using square filtering technique has higher TOA estimation accuracy than the traditional ED method in the presence of strong NBI. In the line-of-sight (LOS) environment, the TOA estimation accuracy can be improved from 2.8 ns to 0.5 ns after applying the square filtering scheme, and in non-line-of-sight (NLOS) environment, it can be improved from 6 ns to 1 ns. Reference | Related Articles | Metrics | Comments（0）

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Urban Spatial Form Analysis of GBA Based on “LJ1-01” Nighttime Light Remote Sensing Images ZHANG Yuxin, LI Xi, SONG Yang, LI Changhui Journal of Applied Sciences    2020, 38 (3): 466-477.   DOI: 10.3969/j.issn.0255-8297.2020.03.012 Abstract （21425）      PDF（pc） （15211KB）（2551）       Knowledge map    Save In this paper, “LJ1-01” nighttime light (NTL) images are used to extract urban built-up areas of Guangdong-Hong Kong-Macao greater bay area (GBA) by employing simple threshold method and vegetation adjusted NTL urban index (VANUI). Comparing the two methods, VANUI is capable of reducing the over-saturations in LJ1-01 images, thus reducing misclassifications caused by “blooming”. The landscape indices of the urban builtup areas in GBA are calculated and analyzed. It is found that there are different patterns in distribution of built-up areas in different cities. As the cores of the development of GBA, Guangzhou, Shenzhen and Hong Kong have expanding urban areas. The urban built-up areas, like Dongguan, Foshan, Macao, Zhongshan and Zhuhai, are highly compact and integrated in spatial distribution. And the urban built-up areas of less developed cities, including Zhaoqing, Jiangmen and Huizhou, are small and separated. This study proves that the LJ1-01 nighttime light images can effectively reveal the urban spatial form of GBA, providing a basis for urban planning policy of GBA. Reference | Related Articles | Metrics | Comments（0）

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Collaborative Filtering Recommendation Model Based on Hybrid Neural Network MA Xin, WU Yun, LU Zeguang Journal of Applied Sciences    2020, 38 (3): 478-487.   DOI: 10.3969/j.issn.0255-8297.2020.03.013 Abstract （791）      PDF（pc） （7718KB）（280）       Knowledge map    Save In the recommendation system, data sparsity is one of the important factors that seriously affect the accuracy of recommendation results. Aiming at the data sparsity, this paper proposes a hybrid neural network collaborative filtering score prediction model convolutional-denosing auto-encoder (CDAE) to perform prediction scoring for solving the problem of data sparsity. The CDAE model combines a convolutional neural network (CNN) and a denoising auto-encoder (DAE) neural network. Firstly, the vectorized user review data is trained by the CNN to obtain a user feature vector matrix. Secondly, the user feature vector matrix is used as the initial weight of the DAE neural network, and the user-item prediction score is obtained by training the auto-encoder neural network in combination with user rating data. Accordingly, user-based collaborative filtering recommendations can be made. In the paper, the proposed convolutional-denosing auto-encoder collaborative filtering (CDAECF) model is experimentally verified by comparing with the experimental data set of movielens-1M. Experiment results prove that the CDAECF model can effectively combine implicit and explicit feedback data, and performs a higher recommendation accuracy rate. Reference | Related Articles | Metrics | Comments（0）

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