基于大数据的智慧林业系统设计

With the development of 5G, big data, cloud computing, IOT, mobile Internet and other information technologies of new generation, the design of forestry information system establishes a new mode of forestry development integrating three-dimensional perception, collaborative management and internal and external services by means of perception, IOT and intelligence. Intelligent forestry system is a comprehensive information management system integrating forest management, intelligent forestry business management, green maintenance management and emergency command and dispatching management. Based on the specific project practice, this paper puts forward the overall framework design scheme and management platform design scheme of intelligent forest- ry.     

高职院校计算机理实一体化实训室建设的探索

The integration of computer theory and practice in higher vocational colleges is the necessary condition to realize the train- ing of professional talents and improve the comprehensive quality of skilled talents. It is also the problem that needs to be solved first in the teaching of computer major in higher vocational colleges. This paper firstly introduces the definition and connotation of the integration of computer theory and practice, discusses on its construction objectives and basic concepts, then analyzes the con- struction value of the integration of computer theory and practice, including the contents of employment, professional teaching, cur- riculum supporting and qualification examination, finally discusses on the construction scheme of the training room of the integra- tion of computer theory and practice, and gives the objective evaluation of the construction results, hoping to effectively improve the level of the integration of computer theory and practice, and achieve the sustainable development of teaching.     

大数据时代大学生个人隐私保护问题研究

伴随着互联网+的风生水起,信息量暴增的大数据时代应运而来,"网络原住民"大学生不可避免、理所当然地处于大数据洪流之中,但也为其个人隐私保护带来了极大挑战。文章针对大数据带来的安全隐私问题,指出大学生个人隐私泄露的可能原因,提出可以采取的个人隐私保护措施,给出大数据时代隐私保护几种技术,期望能给相关人士提供有效参考。     

Polynomial filtering for nonlinear stochastic systems with state‐ and disturbance‐dependent noises

This article is concerned with the polynomial filtering problem for a class of nonlinear stochastic systems governed by the Itô differential equation. The system under investigation involves polynomial nonlinearities, unknown‐but‐bounded disturbances, and state‐ and disturbance‐dependent noises ((x,d)‐dependent noises for short). By expanding the polynomial nonlinear functions in Taylor series around the state estimate, a new polynomial filter design method is developed with hope to reduce the conservatism of the existing results. In virtue of stochastic analysis and inequality technique, sufficient conditions in terms of parameter‐dependent linear matrix inequalities (PDLMIs) are derived to guarantee that the estimation error system is input‐to‐state stable in probability. Moreover, the desired polynomial matrix can be obtained by solving the PDLMIs via the sum‐of‐squares approach. The effectiveness and applicability of the proposed method are illustrated by two numerical examples with one concerning the permanent magnet synchronous motor.     

Smart work packaging-enabled constraint-free path re-planning for tower crane in prefabricated products assembly process

Lack of constraint-free crane path planning is one of the critical concerns in the dynamic on-site assembly process of prefabrication housing production (PHP). For decades, researchers and practitioners have endeavored to improve both the efficiency and safety of crane path planning from either static environment or re-planning the path when colliding with constraints or periodically updating the path in the dynamic environment. However, there is a lack of approach related to the in-depth exploration of the nature of dynamic constraints so as to assist the crane operators in making adaptive path re-planning decisions by categorizing and prioritizing constraints. To address this issue, this study develops the smart work packaging (SWP)-enabled constraints optimization service. This service embraces the core characteristics of SWP, including adaptivity, sociability, and autonomy to achieve autonomous initial path planning, networked constraints classification, and adaptive decisions on path re-planning. This service is simulated and verified in the BIM environment, and it is found that SWP-enabled constraints optimization service can generate the constraint-free path when it is necessary.     

一种基于深度森林的恶意代码分类方法

针对当前恶意代码静态分析方法精度不足的问题，将恶意代码映射为无压缩的灰度图像，然后根据图像变换方法将图像变换为恒定大小的图像，使用方向梯度直方图提取图像的特征，最后提出一种基于深度森林的恶意代码分类方法.实验中选择不同家族的多个恶意代码样本进行分类，验证了该方法的有效性，并且实验结果优于近期提出的SPAM-GIST方法.     

新时代背景下电力精准扶贫模式研究及建议

发挥电力行业优势特点,开展电力精准扶贫,对打赢脱贫攻坚战具有十分重要的作用,并能够助推脱贫攻坚与乡村振兴战略有效衔接.本文从电力扶贫在脱贫攻坚的重要作用出发,以“三聚焦”“三优先”“三模式”“三保障”为指引,详尽梳理并总结了电力精准扶贫主要模式和经验.在此基础上,深刻剖析了当前电力扶贫面临的困难及问题,提出电力精准扶贫的策略,以期为下一步开展电力精准扶贫提供参考与借鉴.     

南海北部陆坡天然气水合物成藏特征研究进展分析

南海北部陆坡区域构造地质控制着气源、流体疏导体系、富集空间及储层物性特征,因此,东沙海域、神狐海域、西沙海槽和琼东南盆地的水合物成藏条件及控制因素具有明显差异性。东沙海域深部气体可沿断层、裂缝、不整合面、砂岩疏导层和气烟囱等通道向上运移,并形成天然气水合物,具有渗漏型水合物产出特征;神狐海域水合物成藏与规模巨大的泥底辟活动相关,并与布莱克海台天然气水合物产出特征具有相似性;琼东南盆地中央坳陷带内为天然气水合物发育的重点区,底辟、泥火山或麻坑构造与天然气水合物发育密切相关。     

Analysis and assessment of a nanoparticle seeded small scale absorption refrigeration system driven by a low‐grade waste heat source

The thermoeconomic behaviour of a nanoparticle seeded single effect LiBr‐H₂O absorption refrigeration system (ARS) is investigated for a small scale application. In the proposed method, alumina nanoparticles with volume concentrations of 3%, 5%, and 7% are dispersed into an aqua lithium bromide solution. The multiobjective heat transfer search algorithm is employed to examine the design trade‐off between the coefficient of performance (COP) and total annualized cost (TAC). To analyze the overall performance of the system, the influence of five design parameters, namely the temperatures of the generator, absorber, evaporator, condenser and heat exchanger pipe diameter, are studied. It is found that with an increase in the COP, the TAC of the system is initially raised marginally, and after that, raised rigorously with further increment. The comparative results indicate that the COP and TAC of the nanofluid based ARS system are increased by about 7% and decreased by about 3.2%, respectively, corresponding to the Pareto points of the base ARS system. A lower break‐even point of about 2.6 years is achieved for the ARS system containing nanoparticles compared to the base ARS system. Overall, the ARS system containing 5% nanoparticles is the best solution from a thermodynamic and economic point of view.     

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP_max) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP_max values as compared with PV–battery and WT–battery systems.