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20 June 2019, Volume 1 Issue 2

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Regular Papers

Parallel agriculture:intelligent technology toward smart agriculture

Mengzhen KANG,Xiujuan WANG,Jing HUA,Haoyu WANG,Fei-Yue WANG

2019, 1(2):  107-117.  doi:10.11959/j.issn.2096-6652.201904

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Agricultural production is featured by strong uncertainty,diversity and complexity.Production benefit is related to natural conditions,national policies and market environment.Internet brings new challenges and chances to the management in agriculture.Generally speaking,smart agriculture refers to smart control on full production chain including management and service,using ICT techniques,in order to achieve high quality,high efficiency,security and controllability.Based on a brief introduction on the techniques related to these three aspects,the parallel agriculture as the methodology for decision support in smart agriculture was proposed,with artificial system for description intelligence,computational experiments for prediction intelligence,and parallel execution for prescription intelligence.Moreover,the link to agricultural enterprise resource planning (ERP) system,manufacturing execution system (MES) and process control system (PCS) was discussed.As China was developing large-scale agricultural production,methodology for managing scaled agriculture production was provided.

Parallel offshore oil/gas field:ACP-based front end engineering design and evaluation

Li WEI, Hong WANG, Min HUANG, Qun WEI, Qinghai MIAO

2019, 1(2):  118-124.  doi:10.11959/j.issn.2096-6652.201923

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Front end engineering design (FEED) and its related evaluation plays an important role in the life cycle of offshore oil/gas field development.A digitalized way of FEED based on ACP architecture was provided by the proposed parallel offshore oil/gas field system.Firstly,based on several developed oil/gas fields located in South China Sea,a virtual oil/gas field using building information modeling (BIM) was constructed.Secondly,the case-based reasoning (CBR) to evaluate the FEED based on both BIM and successful cases was introduced.The methods of real-virtual interactions were also enhanced by the introduction of CBR into ACP architecture.The parallel platform has been used to visually design and evaluate oil/gas field FEED,which improves the efficiency and accuracy of users.

Research and application of cloud service system for cold chain

Shichao CHEN,Bin TIAN,Yisheng LV,Bin HU,Shuangshuang HAN

2019, 1(2):  125-132.  doi:10.11959/j.issn.2096-6652.201919

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For the current challenges of lacking cold chain logistics information,traceability and other issues,the end-to-end cold chain cloud service system was designed in this paper,based on Internet of Things (IoT) technology and micro-service system architecture.Full cycle for cold chain logistics and data monitoring in different business scenarios could be realized by this system.It can solve the problem of information isolated island and data sharing in the existing cold chain monitoring system,and meet the actual demand of the constant chain of pharmaceutical cold chain monitoring.The designed cold chain cloud service system includes intelligent monitoring terminal,cloud service management platform and cold chain manager App.This system can be applied to logistics of medicine,fresh,fruit,flowers,etc.In this paper,the application of the system in the pharmaceutical industry was described in detail,especially in the three business scenarios of storage,transportation and sales of pharmaceutical cold chain.The proposed system is stable and has been applied in commercial operation.Besides,its advantages have been approved by many users in the pharmaceutical industry.

Integral back-stepping algorithm for designing the quadrotor aircraft controller

Yan GUO,Meiping WU,Kanghua TANG,Xueying WANG

2019, 1(2):  133-139.  doi:10.11959/j.issn.2096-6652.201924

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In view of the problem that the back-stepping algorithm control model is complex and physically difficult to realize,a method of integral back-stepping algorithm for the under-actuated quadrotor aircraft was proposed in this paper.The back-stepping technique based on the Lyapunov stability theory was used to realize the effective tracking control of position and attitude,and ensure the stability of the quadrotor aircraft controller.In order to simplify the controller model,it is proposed to add the integral term in the process of the back-stepping attitude controller design according to the characteristics of the aircraft model,and set the appropriate integral term constant to reduce the burden of the controller and to enhance the practicability of the control algorithm.The controller can realize the stabilization of each attitude,the fixed point,the trajectory track of the position and yaw without error.

Research on control algorithm of a four axis air vehicle-inverted pendulum system

Fanguo KONG,Zhaoxing LI,Jiancun ZHANG,Gang XIONG,R.Nyberg Timo

2019, 1(2):  140-144.  doi:10.11959/j.issn.2096-6652.201916

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Controlling the balance of a movable rod or a wine cup filled with water on a four axis air vehicle is a hard job.A system called four axis air vehicle-inverted pendulum balance control system is needed.With this special kind of balance control system and the idea of a simplified model to replace the complex system for analysis,the performance of a linear four axis vehicle-inverted pendulum on X-Z plane was studied,its dynamic and physical formula was also discussed.The simplified model equipped with the control algorithm of sliding mode control was designed and simulated on the computer with the help of MATLAB.The result shows that the control algorithm works well on the four axis air vehicle-inverted pendulum balance control system and the system has a good performance.

Method of functional brain network modeling with group similarity constraint for mild cognitive impairment classification

Weikai LI,Xin GAO,Tongjian JI,Zhengxia WANG

2019, 1(2):  145-153.  doi:10.11959/j.issn.2096-6652.201922

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Functional brain network provides an effective biomarker for understanding brain activation patterns,the development of neurodegenerative diseases,and the structure of brain signaling.How to use priori information to build accurate brain network is particularly important in subsequent applications.A functional brain network construction model based on group similarity constraints was proposed.By introducing a tensor low rank constraint and using the nuclear norm of the tensor,a brain network group with a low rank prior in the group was solved.The group similarity constraints to shrink the solution space of the brain network was used,thus constructing a better functional brain network effectively.For evaluating the performance of the proposed method,the constructed brain network was adopted for the discriminative task of mild cognitive impairment.The experimental results show that the proposed functional brain network modeling method based on group similarity constraints can construct more discriminative brain network.In addition,based on the brain network constructed by the proposed method,the significant connections consistent with previous studies are obtained,and the effectiveness of the proposed method is further verified.

Research of independent and controllable information system based on natural immune system and trusted computing

Wei LIU,Linlin CI,Liping LIU

2019, 1(2):  154-162.  doi:10.11959/j.issn.2096-6652.201920

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The competition in the field of information is a kind of system competition.Aiming at the problem that a single defense method cannot cope with the comprehensive attack,an independent and controllable information system based on natural immune system and trusted computing was constructed.The system includes trusted network basic function subsystem,user behavior measurement subsystem,software behavior measurement subsystem and fault-tolerant subsystem.The advantage of this way of adding security mechanisms to basic functionality is the extension of the chain of trust,integration of trusted network access control model and role-based access control model and trusted access of trusted terminal throughout life cycle can be achieved.

Research and application on combustion optimization of coal-fired boiler in thermal power plant based on artificial intelligence technology

Peifeng NIU,Yunpeng MA,Xinxin ZHANG,Xiaobin HU

2019, 1(2):  163-170.  doi:10.11959/j.issn.2096-6652.201925

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In order to reduce the NO_xemission concentration and coal consumption of coal-fired boilers in thermal power plants,the sample increment quantum neural network and an improved quantum bee colony algorithm were proposed.The quantum sample incremental feed-forward neural network can dynamically establish a comprehensive model of Nitrogen and Oxygen emission concentration and boiler coal consumption of coal-fired boiler,and can realize rolling optimization of the model.Based on the established comprehensive model,the optimization of the primary and secondary air volume and coal and the opening degree of each secondary air valve were realized by using the improved quantum bee colony algorithm.Based on the above two methods,a set of intelligent combustion optimization software for coal-fired boiler was developed and applied to the 330 MW boiler of a thermal power plant.The test results show that the Nitrogen and Oxygen emission concentration and the coal consumption of the boiler have been reduced in varying degrees.It is shown that the modeling method and the optimization algorithm are effective.

Study on path planning of unmanned surface vessel based on data-driven genetic algorithm

Junfeng XIN,Yongbo ZHANG,Jiageng BO,Bowen ZHAO,Shiyuan FAN

2019, 1(2):  171-180.  doi:10.11959/j.issn.2096-6652.201926

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The genetic algorithm (GA) is an effective method for the path planning system of unmanned surface vessel (USV),but it is easy to fall into local optimal precocity and converges slowly.For this,without increasing the complexity of the algorithm,a data-driven linear changing parameters genetic algorithm (LCPGA) was proposed,which can adjust adaptively control parameters in the shortest time.Compared with the traditional genetic algorithm,the LCPGA increases the diversity of the population,avoids falling into local optimum more effectively,and improves the accuracy,robustness and convergence speed of path planning.Then simulation experiments and field tests verify the more excellent performance of the LCPGA.This algorithm can be helpful in path planning for unmanned surface vessel.

Parallel machine:a framework for the control and management for intelligent machines

Tianxiang BAI,Zhen SHEN,Yating LIU,Xisong DONG

2019, 1(2):  181-191.  doi:10.11959/j.issn.2096-6652.201915

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The concept of parallel machine framework as a solution to the challenges of the complexity of intelligent machines was proposed in this paper.The ACP theory was incorporated into intelligent machine field,and a virtual-real interactive pattern was formed in the control and management of machine.The parallel machine concept is composed of the real machine and corresponding software-defined virtual ones,and through which the functionality including describing,predicting and prescription can be achieved.Finally,relevant technologies and potential applications of parallel machine were discussed.

Parallel nuclear power:intelligent technology for smart nuclear power

Jiachen HOU,Xisong DONG,Gang XIONG,Jun ZHANG,Ke TAN

2019, 1(2):  192-201.  doi:10.11959/j.issn.2096-6652.201912

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A framework to incorporate nuclear plants using the ACP based parallel system theory was proposed.This research framework has established a convenient and safe platform for nuclear power plants to experiment,learn and work in complex environments,namely parallel nuclear power system.Proceeding from the basic concept of parallel nuclear power,the basic framework of parallel nuclear power system was proposed,and the elementary functions and implementation methods of description,prediction and guidance module were also introduced.The key technologies were also further discussed.At last,this paper looks forward to the nuclear power system application in emergency,and the future development direction of parallel nuclear power system was proposed.

Decentralized autonomous organizations:the state of the art,analysis framework and future trends

Wenwen DING,Shuai WANG,Juanjuan LI,Yong YUAN,Liwei OUYANG,Fei-Yue WANG

2019, 1(2):  202-213.  doi:10.11959/j.issn.2096-6652.201917

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The decentralized autonomy is not a new concept,the self-organization phenomenon in natural ecosystems,the cyber movement organizations on the Internet,and the distributed artificial intelligence,etc.,can all be regarded as its early manifestations.In recent years,the rapid development of block chain technology has spawned the emergence of the so-called decentralized autonomous organization (DAO),which is a new organization form that the management and operational rules are typically encoded on block chain in the form of smart contracts,and can autonomously operate without centralized control or third-party intervention.Therefore,DAO is expected to become a new and effective organization to deal with uncertain,diverse and complex environments.Defining the conception and features is the first priority.Furthermore,the five layer structural model of DAO analyzing frame to analyze typical Aragon model was proposed and the current issues as well as the research direction in future were discussed,hoping to provide significant guidance and reference for following researchers.