Recent trends of machine learning applied to multi-source data of medicinal plants

In traditional medicine and ethnomedicine,medicinal plants have long been recognized as the basis for materials in therapeutic applications worldwide.In particular,the remarkable curative effect of traditional Chinese medicine during corona virus disease 2019(COVID-19)pandemic has attracted extensive attention globally.Medicinal plants have,therefore,become increasingly popular among the public.However,with increasing demand for and profit with medicinal plants,commercial fraudulent events such as adulteration or counterfeits sometimes occur,which poses a serious threat to the clinical outcomes and interests of consumers.With rapid advances in artificial intelligence,machine learning can be used to mine information on various medicinal plants to establish an ideal resource database.We herein present a review that mainly introduces common machine learning algorithms and discusses their application in multi-source data analysis of medicinal plants.The combination of machine learning algorithms and multi-source data analysis facilitates a comprehensive analysis and aids in the effective evaluation of the quality of medicinal plants.The findings of this review provide new possibilities for promoting the development and utilization of medicinal plants.

Research on Data Fusion of Adaptive Weighted Multi-Source Sensor

Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single sensor.The data of water quality in the environment comes from different sensors,thus the data must be fused.In our research,self-adaptive weighted data fusion method is used to respectively integrate the data from the PH value,temperature,oxygen dissolved and NH3 concentration of water quality environment.Based on the fusion,the Grubbs method is used to detect the abnormal data so as to provide data support for estimation,prediction and early warning of the water quality.

Image Processing on Geological Data in Vector Format and Multi-Source Spatial Data Fusion

The geological data are constructed in vector format in geographical information system (GIS) while other data such as remote sensing images, geographical data and geochemical data are saved in raster ones. This paper converts the vector data into 8 bit images according to their importance to mineralization each by programming. We can communicate the geological meaning with the raster images by this method. The paper also fuses geographical data and geochemical data with the programmed strata data. The result shows that image fusion can express different intensities effectively and visualize the structure characters in 2 dimensions. Furthermore, it also can produce optimized information from multi-source data and express them more directly.

Threat Modeling and Application Research Based on Multi-Source Attack and Defense Knowledge

Cyber Threat Intelligence(CTI)is a valuable resource for cybersecurity defense,but it also poses challenges due to its multi-source and heterogeneous nature.Security personnel may be unable to use CTI effectively to understand the condition and trend of a cyberattack and respond promptly.To address these challenges,we propose a novel approach that consists of three steps.First,we construct the attack and defense analysis of the cybersecurity ontology(ADACO)model by integrating multiple cybersecurity databases.Second,we develop the threat evolution prediction algorithm(TEPA),which can automatically detect threats at device nodes,correlate and map multisource threat information,and dynamically infer the threat evolution process.TEPA leverages knowledge graphs to represent comprehensive threat scenarios and achieves better performance in simulated experiments by combining structural and textual features of entities.Third,we design the intelligent defense decision algorithm(IDDA),which can provide intelligent recommendations for security personnel regarding the most suitable defense techniques.IDDA outperforms the baseline methods in the comparative experiment.

Unequal-interval data fusion algorithm for inertial/gravity matching integrated navigation system

Inertial/gravity matching integrated navigation system can effectively improve the longendurance navigation ability of underwater vehicles.Through the analysis of the matching process,the problem of unequal-interval in matching trajectory is addressed by an unequal-interval data fusion algorithm which is based on the unequal-interval characteristics analysis of the matching trajectory.Compared with previously available methods,the proposed algorithm improves the location precision.In conclusion,simulations of the integrated navigation system demonstrated the effectiveness and superiority of the proposed algorithm.

基于地球物理数据融合的大兴安岭中段东缘地壳结构研究

位于中亚造山带东段的兴安地块和松辽锡林浩特地块被晚古生代贺根山-黑河缝合带分开。随后,大兴安岭与松辽盆地被中新生代嫩江-八里罕断裂分开。在大兴安岭中段,这两构造带的位置及板块拼合时间尚不明确。为研究大兴安岭中段东缘重要构造断裂、构造单元及结晶基底属性特征,在扎兰屯-阿荣旗地区采集处理一条长60 km的重力、磁法和大地电磁数据,重新处理了1:20万扎兰屯幅、阿荣旗幅区域布格重力异常数据。通过多种地球物理数据融合,解译了7条重要断裂,其中庞家街断裂和红星断裂是控制贺根山-黑河缝合带的深大断裂。北西向阿伦河断裂为深大断裂,至少切割到中地壳。发现了两个中地壳低阻带,其中C2异常解释为贺根山-黑河缝合带。通过1:25万阿荣旗幅地质填图资料,证实了地球物理数据融合的推断结果,为大兴安岭中段东缘构造带演化研究提供了重要支撑。

重磁测量在海岛礁及其邻域中的应用与展望

重磁测量在海岛礁及其邻域的应用与研究中不可或缺。由于海岛礁及邻域重磁场空间分布的梯度和幅度变化较大,又受地理环境与技术的限制,获取该区域高分辨率、高精度的重磁测量信息较为困难,导致测量成果质量不高且产品单一,亟需科技创新来扭转此局面。本文系统分析了海岛礁及其邻域地理环境、重磁特征和相关测量技术方法的发展现状,针对存在的问题,深入探讨了该领域的新技术、新方法及应用研究,并对未来发展方向作出展望:(1)加强重磁测量技术方法的研究,构建高水平的立体观测系统;(2)深化多源数据融合处理技术方法研究,丰富测量成果的输出方式;(3)充分利用海岛礁作为定点的中长期观测平台的天然优势,开展地球物理场的融合研究,拓展其应用与研究领域。

Carbon Emission Evaluation in Jinan Western New District based on Multi-source Data Fusion

Carbon emissions caused by human activities are closely related to the process of urbanization,and urban land utilization,function vitality and traffic systems are three important factors that may influence the emission levels.For clarifying the space structure of a low-carbon eco-city,and combining the concept of"Combining Assessment with Construction"to track and contrast the construction of the low-carbon eco-city,this research selects quantifiable low-carbon eco-city spatial characteristics as indicators,and evaluates and analyzes the potential carbon emissions.Taking the Jinan Western New District as an example,diversity of construction land,travel carbon emission potential,and density and accessibility of adjacent road networks in the overall urban planning were measured.After the completion of the new urban area,the evaluation mainly reflected certain factors,such as the mixed degree of urban functions,the density of urban functions,the walking distance to bus stops and the density and number of bus stops.Dividing the levels and adding equal weights after index normalization,the carbon emission potential is evaluated at the two levels of the overall and fragmented areas.The results show that:(1)The low-carbon emission potential areas in the planning scheme basically reached the planned goals.(2)There is inconsistency between districts and indicators in the planning scheme.The diversity of construction land and the accessibility of the adjacent road network are relatively small;however,there is a large difference between the travel carbon emission potential and the road network accessibility.(3)Carbon emission potential after completion did not reach the planned expectation,and the low-carbon emission potential plots were concentrated in the Changqing Old City Area and Central Area of Dangjia Town Area.(4)The carbon emission indicators varied greatly in different areas,and there were serious imbalances in the density of public transportation lines and the mixed degree of urban functions.

Relationship between the Extent of Igneous Rocks and Deep Structures as Determined by Gravitational and Magnetic Data in the South China Sea

The distribution of oil and gas resources in the South China Sea and adjacent areas is closely related to the structural pattern that helped to define the controlling effect of deep processes on oil-bearing basins.Igneous rocks can record important information from deep processes.Deep structures such as faults,basin uplift and depression,Cenozoic basement and magnetic basement are all the results of energy exchange within the earth.The study of the relationship between igneous rocks and deep structures is of great significance for the study of the South China Sea.By using the minimum curvature potential field separation technique and the correlation analysis technique of gravitational and magnetic anomalies,the fusion of gravitational and magnetic data reflecting igneous rocks can be obtained,through which the igneous rocks with high susceptibility/high density or high susceptibility/low density can be identified.In this study area,igneous rocks do not develop in the Yinggehai basin,Qiongdongnan basin,Zengmu basin and Brunei-Sabah basin whilst igneous rocks with high susceptibility/high density or high susceptibility/low density are widely-developed in other basins.In undeveloped igneous areas,faults are also undeveloped the Cenozoic thickness is greater,the magnetic basement depth is greater and the Cenozoic thickness is highly positively correlated with the magnetic basement depth.In igneously developed regions,the distribution pattern of the Qiongtai block is mainly controlled by primary faults,while the distribution of the Zhongxisha block,Xunta block and Yongshu-Taiping block is mainly controlled by secondary faults,the Cenozoic thickness having a low correlation with the depth of the magnetic basement.

A heuristic cabin-type component alignment method based on multi-source data fusion

In cabin-type component alignment, digital measurement technology is usually adopted to provide guidance for assembly. Depending on the system of measurement, the alignment process can be divided into measurement-assisted assembly(MAA) and force-driven assembly. In MAA,relative pose between components is directly measured to guide assembly, while in force-driven assembly, only contact state can be recognized according to measured six-dimensional force and torque(6 D F/T) and the process is completed based on preset assembly strategy. Aiming to improve the efficiency of force-driven cabin-type component alignment, this paper proposed a heuristic alignment method based on multi-source data fusion. In this method, measured 6 D F/T, pose data and geometric information of components are fused to calculate the relative pose between components and guide the movement of pose adjustment platform. Among these data types, pose data and measured 6 D F/T are combined as data set. To collect the data sets needed for data fusion, dynamic gravity compensation method and hybrid motion control method are designed. Then the relative pose calculation method is elaborated, which transforms collected data sets into discrete geometric elements and calculates the relative poses based on the geometric information of components.Finally, experiments are conducted in simulation environment and the results show that the proposed alignment method is feasible and effective.

Application Research on Two-Layer Threat Prediction Model Based on Event Graph

Advanced Persistent Threat(APT)is now the most common network assault.However,the existing threat analysis models cannot simultaneously predict the macro-development trend and micro-propagation path of APT attacks.They cannot provide rapid and accurate early warning and decision responses to the present system state because they are inadequate at deducing the risk evolution rules of network threats.To address the above problems,firstly,this paper constructs the multi-source threat element analysis ontology(MTEAO)by integrating multi-source network security knowledge bases.Subsequently,based on MTEAO,we propose a two-layer threat prediction model(TL-TPM)that combines the knowledge graph and the event graph.The macro-layer of TL-TPM is based on the knowledge graph to derive the propagation path of threats among devices and to correlate threat elements for threat warning and decision-making;The micro-layer ingeniously maps the attack graph onto the event graph and derives the evolution path of attack techniques based on the event graph to improve the explainability of the evolution of threat events.The experiment’s results demonstrate that TL-TPM can completely depict the threat development trend,and the early warning results are more precise and scientific,offering knowledge and guidance for active defense.

Design and Realization of Block Level Augmented Reality Three-Dimensional Map

In response to the construction needs of “Real 3D China”, the system structure, functional framework, application direction and product form of block level augmented reality three-dimensional map is designed. Those provide references and ideas for the later large-scale production of augmented reality three-dimensional map. The augmented reality three-dimensional map is produced based on skyline software. Including the map browsing, measurement and analysis and so on, the basic function of three-dimensional map is realized. The special functional module including housing management, pipeline management and so on is developed combining the need of residential quarters development, that expands the application fields of augmented reality three-dimensional map. Those lay the groundwork for the application of augmented reality three-dimensional map. .

卫星测高与船载重力测量数据融合的点质量拟合法

以拟合方差最小为准则,通过点质量法拟合船载重力测量数据,得到点质量大小、埋深等参数。回避点质量法数值求解的不稳定性问题,借鉴移去-恢复技术的思路,利用该参数计算船载重力测量点上的重力异常,并将其在测线上的重力异常中扣除,计算出船载重力残差值。以点质量大小、埋深等参数计算卫星测高重力格网点上重力异常,同样得到测高重力残差值。采用加权最小曲率格网化方法,将船载重力残差值与测高重力残差值格网化,进而恢复由点质量大小、埋深等参数计算格网点处的重力异常,实现卫星测高与船载重力测量数据融合。经国际船载重力测量数据检核,融合后的模型较国际船载重力测量数据的平均偏差在1~2mGal(1Gal=1×10^(-2) m/s^2),标准差约为4mGal。本文的研究方法可为陆地、海岸带区域的多种重力数据的融合、航空重力及卫星重力的向下延拓等问题提供参考。

海空重力测量及应用技术研究进展与展望(四):数值模型构建与综合应用技术

分析总结了海空重力测量数据向上和向下延拓技术的研究现状及发展方向,简要论述了海空重力测量多源数据融合处理技术的研究动态及发展前景,分析讨论了海空重力测量数据应用于地球外部重力场赋值和大地水准面精化技术的研究进展及发展思路,为海空重力测量数值建模与数据综合应用技术的未来发展提供参考。

基于双干涉仪的自由落体绝对重力测量

为了避免用光学干涉法测量自由落体绝对重力过程中落体旋转对测量结果准确度的影响,提出了基于双干涉仪的绝对重力测量方法。介绍了落体旋转影响绝对重力测量结果的机理,提出了对同时测量的两组干涉仪数据进行融合处理的方法。根据预先设定的重力值,双干涉仪中落体上、下反射棱镜光心与质心垂直方向的初始高度差,以及随机生成的每次测量对应的角速度序列和振动引起的上、下干涉仪重力测量偏差序列,进行了仿真计算。结果表明:光心-质心的距离为2.5mm的双干涉仪通过数据融合处理得到的重力测量结果的偏差约为0.5μGal,标准偏差约为0.3μGal,与现有调校落体光心-质心的方法得到的结果相当。选择合适的上、下棱镜光心-质心距离可以更好地消减落体旋转对测量结果的影响,将其分别设计为±3mm时,用双干涉法数据融合得到的重力值偏差小于1μGal,满足相关领域对精密重力测量的需求。

融合多源重力数据的Tikhonov正则化配置法

针对最小二乘配置法在融合处理多源重力数据过程中可能出现的病态性问题,特别引入Tikhonov正则化方法,对配置法计算模型进行正则化改造,建立了相应的正则化配置模型。使用EGM2008位模型模拟产生航空重力和海面船测重力数据进行了融合处理仿真实验,实际验证了正则化处理方法的有效性。

渤海湾多源重力数据的自适应融合处理

在最小二乘逐步配置基础上,提出多源重力数据自适应融合处理方法,构建基于传统逐步配置的自适应融合以及基于递推配置的自适应融合两种融合模式。分别利用两种融合模式对渤海湾陆海交界区域的航空重力数据、卫星测高反演重力数据以及陆地重力数据进行融合处理,其中基于递推配置的自适应融合模式取得了较优的融合效果。通过两个区域船测重力数据的外部检核表明,融合数据的精度分别达到3.7×10-5m/s2和2.1×10-5m/s2。

观测噪声对频域输入输出法数据融合的影响

以融合大地水准面高和重力异常数据精化局部大地水准面或重力异常为例,利用模拟数据分析了不同大小的观测噪声和非稳态误差对数据融合结果的影响。模拟结果表明:双输入单输出法融合处理不同大小的观测噪声和非稳态误差数据均能获得较满意的结果。

重力数据融合与重力垂直梯度异常反演

重力垂直梯度异常反应了重力异常的空间变化率,在地球物理勘探等多学科中得到越来越多的应用。利用南海局部区域实测重力异常数据和Sandwell测高重力异常数据,将搜索范围、距离和精度多种因素融合考虑并对Shepard算法进行改进,给出了南海局部区域(19°N^20.5°N,114°E^115.5°E)分辨率1'×1'的重力异常并反演了对应分辨率的重力垂直梯度异常。结果表明,基于Shepard改进算法的高精度船测重力和测高重力的有机融合,增强了单一测高重力数据反演重力垂直梯度异常的细节纹理,提高了反演重力垂直梯度异常的分辨率和精度。

北秦岭华阳川地区重磁三维反演及岩浆岩特征研究

华山岩体、老牛山杂岩体等中酸性花岗岩体和华阳川韧性剪切带在北秦岭华阳川地区的成矿过程中起着重要的作用,既是构造演化的记录,又是构造—岩浆—成矿的重要指示。本文在系统研究华阳川地区地面和航空重力、磁测数据以及地面电法剖面等多种地球物理资料的基础上,完成物性统计分析、航空和地面数据融合处理,通过先验信息约束的重磁2.5D交互式反演和三维反演计算,构建了华阳川地区区域三维地质—地球物理模型,为区域地质背景和深部地质构造的研究提供地球物理依据;推断解释了华山岩体、老牛山岩体和华阳川韧性剪切带的三维形态和空间分布,探讨了华阳川韧性剪切带、老牛山岩体和华山岩体的深部接触关系,对大岩体外围接触带的铀、钼等矿床的深部找矿具有一定指导意义。