3D electrical resistivity inversion using prior spatial shape constraints

To minimize the number of solutions in 3D resistivity inversion, an inherent problem in inversion, the amount of data considered have to be large and prior constraints need to be applied. Geological and geophysical data regarding the extent of a geological anomaly are important prior information. We propose the use of shape constraints in 3D electrical resistivity inversion, Three weighted orthogonal vectors （a normal and two tangent vectors） were used to control the resistivity differences at the boundaries of the anomaly. The spatial shape of the anomaly and the constraints on the boundaries of the anomaly are thus established. We incorporated the spatial shape constraints in the objective function of the 3D resistivity inversion and constructed the 3D resistivity inversion equation with spatial shape constraints. Subsequently, we used numerical modeling based on prior spatial shape data to constrain the direction vectors and weights of the 3D resistivity inversion. We established a reasonable range between the direction vectors and weights, and verified the feasibility and effectiveness of using spatial shape prior constraints in reducing excessive structures and the number of solutions. We applied the prior spatially shape-constrained inversion method to locate the aquifer at the Guangzhou subway. The spatial shape constraints were taken from ground penetrating radar data. The inversion results for the location and shape of the aquifer agree well with drilling data, and the number of inversion solutions is significantly reduced.

Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.

Max-margin non-negative matrix factorization with flexible spatial constraints based on factor analysis

Non-negative matrix factorization （NMF） is a popular feature encoding method for image understanding due to its non-negative properties in representation, but the learnt basis images are not always local due to the lack of explicit constraints in its objective. Various algebraic or geometric local constraints are hence proposed to shape the behaviour of the original NMF. Such constraints are usually rigid in the sense that they have to be specified beforehand instead of learning from the data. In this paper, we propose a flexible spatial constraint method for NMF learning based on factor analysis. Particularly, to learn the local spatial structure of the images, we apply a series of transformations such as orthogonal rotation and thresholding to the factor loading matrix obtained through factor analysis. Then we map the transformed loading matrix into a Laplacian matrix and incorporate this into a max-margin non-negative matrix factorization framework as a penalty term, aiming to learn a representation space which is non-negative, discriminative and localstructure-preserving. We verify the feasibility and effectiveness of the proposed method on several real world datasets with encouraging results.

Global video object segmentation with spatial constraint module

We present a lightweight and efficient semisupervised video object segmentation network based on the space-time memory framework.To some extent,our method solves the two difficulties encountered in traditional video object segmentation:one is that the single frame calculation time is too long,and the other is that the current frame’s segmentation should use more information from past frames.The algorithm uses a global context(GC)module to achieve highperformance,real-time segmentation.The GC module can effectively integrate multi-frame image information without increased memory and can process each frame in real time.Moreover,the prediction mask of the previous frame is helpful for the segmentation of the current frame,so we input it into a spatial constraint module(SCM),which constrains the areas of segments in the current frame.The SCM effectively alleviates mismatching of similar targets yet consumes few additional resources.We added a refinement module to the decoder to improve boundary segmentation.Our model achieves state-of-the-art results on various datasets,scoring 80.1%on YouTube-VOS 2018 and a J&F score of 78.0%on DAVIS 2017,while taking 0.05 s per frame on the DAVIS 2016 validation dataset.

Spatial geometric constraints histogram descriptors based on curvature mesh graph for 3D pollen particles recognition

This paper presents one novel spatial geometric constraints histogram descriptors （SGCHD） based on curvature mesh graph for automatic three-dimensional （3D） pollen particles recognition. In order to reduce high dimensionality and noise disturbance arising from the abnormal record approach under microscopy, the separated surface curvature voxels are ex- tracted as primitive features to represent the original 3D pollen particles, which can also greatly reduce the computation time for later feature extraction process. Due to the good invariance to pollen rotation and scaling transformation, the spatial geometric constraints vectors are calculated to describe the spatial position correlations of the curvature voxels on the 3D curvature mesh graph. For exact similarity evaluation purpose, the bidirectional histogram algorithm is applied to the spatial geometric constraints vectors to obtain the statistical histogram descriptors with fixed dimensionality, which is invariant to the number and the starting position of the curvature voxels. Our experimental results compared with the traditional methods validate the argument that the presented descriptors are invariant to different pollen particles geometric transformations （such as posing change and spatial rotation）, and high recognition precision and speed can be obtained simultaneously.

Flight parameter calculation method of multi-projectiles using temporal and spatial information constraint

The dynamic parameters of multiple projectiles that are fired using multi-barrel weapons in highfrequency continuous firing modes are important indicators to measure the performance of these weapons.The characteristics of multiple projectiles are high randomness and large numbers launched in a short period of time,making it very difficult to obtain the real dispersion parameters of the projectiles due to the occlusion or coincidence of multiple projectiles.Using six intersecting-screen testing system,in this paper,we propose an association recognition and matching algorithm of multiple projectiles using a temporal and spatial information constraint mechanism.We extract the output signal from each detection screen and then use the wavelet transform to process the output signal.We present a method to identify and extract the time values on which the projectiles pass through the detection screens using the wavelet transform modulus maximum theory.We then use the correlation of the output signals of three parallel detection screens to establish a correlation coefficient recognition constraint function for the multiple projectiles.Based on the premise of linear projectile motion,we establish a temporal and spatial constraint matching model using the projectile’s position coordinates in each detection screen and the projectile’s time constraints within the multiple intersecting-screen geometry.We then determine the time values of the multiple projectiles in each detection screen using an iterative search cycle registration,and finally obtain the flight parameters for the multiple projectiles in the presence of uncertainty.The proposed method and algorithm were verified experimentally and can solve the problem of uncertainty in projectiles flight parameter under different multiple projectile firing states.

Over-Constraints and a Unified Mobility Method for General Spatial Mechanisms Part 2:Application of the Principle

The pre-research on mobility analysis presented a unified-mobility formula and a methodology based on reciprocal screw theory by HUANG, which focused on classical and modem parallel mechanisms. However its range of application needs to further extend to general multi-loop spatial mechanism. This kind of mechanism is not only more complex in structure but also with strong motion coupling among loops, making the mobility analysis even more complicated, and the relevant research has long been ignored. It is focused on how to apply the new principle for general spatial mechanism to those various multi-loop spatial mechanisms, and some new meaningful knowledge is further found. Several typical examples of the genera/multi-loop spatial mechanisms with motion couple even strong motion couple are considered. These spatial mechanisms include different closing way： over-constraint appearing in rigid closure, in movable closure, and in dynamic closure as well; these examples also include two different new methods to solve this kind of issue： the way to recognize over-constraints by analyzing relative movement between two connected links and by constructing a virtual loop to recognize over-constraints. In addition, over-constraint determination tabulation is brought to analyze the motion couple. The researches above are all based upon the screw theory. All these multi-loop spatial mechanisms with different kinds of structures can completely be solved by following the directions and examples, and the new mobility theory based on the screw theory is also proved to be valid. This study not only enriches and develops the theory and makes the theory more universal, but also has a special meaning for innovation in mechanical engineering.

地理链接数据的空间拓扑完整性验证

为能准确且快捷地验证地理链接数据多重实体空间拓扑关系的完整性,提出一种基于RCC8模型的饱和推理方法,用于检验多重空间拓扑关系是否具有冲突.该方法应用推理规则,将关系对进行两两组合推理,逐步推导出潜在空间关系并对推理结果进行检验,不断重复以上过程,直到确保推理过程在所有关系对均被推导后终止.在此基础上,封装一个基于RCC8模型的饱和推理验证组件,以方便使用者在无需重复编写代码的情况下,通过直接调用组件验证多重空间拓扑关系.利用该方法和组件对SLIPO项目的链接数据集的部分数据进行测试,成功识别出GeoSHACL组件无法检测到的多个空间拓扑关系冲突实体.

空间几何约束下的特高压变电站巡检机器人下坡节能控速方法

现有巡检机器人控速方法在实际使用过程中,缺乏对机器人本身位置变化的考虑,导致能耗高、速度偏差大,为此设计一种基于空间几何约束的特高压变电站巡检机器人下坡节能控速方法。在空间几何约束条件下,提取特征点进行匹配,基于拉格朗日方程建立机器人工作点轨迹与运行速度之间的驱动关系模型,根据机器人最大功率约束条件进行电机节能参数匹配,完成下坡速度控制方法设计。实验结果表明,该方法在不同工况下对特高压变电站巡检机器人的速度控制精度和节能效果都有一定提升。

生态环境分区管控与国土空间规划关系研究

生态环境分区管控和国土空间规划均属建立区域空间分区体系的举措,目标是实现国土空间分区分类管控,但在内容上各有侧重,目前在实践过程中存在衔接内容和衔接技术不清晰等问题,亟须厘清二者之间的关系。通过梳理生态环境分区管控与国土空间规划在管理要求、技术逻辑、主要成果等方面的异同,分析总结地方在生态环境分区管控、国土空间规划编制过程中的衔接实践。结果表明:生态环境分区管控和国土空间规划在国家推进生态文明建设战略中的基本理念相同,共同维护发展保护格局,推动高质量发展;但各有侧重,生态环境分区管控的管控目标是环境质量,国土空间规划的管控目标是用途管制,二者不能相互替代。生态环境分区管控衔接国土空间规划生态保护红线和用途管制成果,可实现生态保护红线成果和管控要求完全一致,国土空间规划衔接生态环境分区管控的生态环境现状问题分析结论、环境质量改善目标、生态环境准入清单等成果,可促进国土空间规划在优化产业布局、基础设施布局、矿产资源开发布局时更多考虑生态环境约束,在政府招商引资阶段,二者协同发力,共同保障项目选址科学、布局合理。

FRAMEWORKS FOR GENERALIZATION CONSTRAINTS AND OPERATIONS BASED ON OBJECT-ORIENTED DATA STRUCTURE IN DATABASE GENERALIZATION

The constraints and the operations play an important role in database generalization.They guide and govern database generalization.The constraints are translation of the required conditions that should take into account not only the objects and relationships among objects but also spatial data schema (classification and aggregation hierarchy) associated with the final existing database.The operations perform the actions of generalization in support of data reduction in the database.The constraints in database generalization are still lack of research.There is still the lack of frameworks to express the constraints and the operations on the basis of object_oriented data structure in database generalization.This paper focuses on the frameworks for generalization operations and constraints on the basis of object_oriented data structure in database generalization.The constraints as the attributes of the object and the operations as the methods of the object can be encapsulated in classes.They have the inheritance and polymorphism property.So the framework of the constraints and the operations which are based on object_oriented data structure can be easily understood and implemented.The constraint and the operations based on object_oriented database are proposed based on object_oriented database.The frameworks for generalization operations,constraints and relations among objects based on object_oriented data structure in database generalization are designed.The categorical database generalization is concentrated on in this paper.

考虑结构空间作用的RC框架梁轴向约束刚度研究

为真实反映结构对框架梁的空间约束作用,提出了轴向约束刚度指标以量化结构空间约束,并建立可模拟框架结构空间约束作用的数值模型。对比足尺框架结构试验数据表明,按规范计算的框架梁抗弯承载力与试验值相对误差为42%~75%,考虑结构轴向约束作用后相对误差缩小至25%以内,说明该模型可较好地模拟框架结构轴向约束作用,验证了该数值模型的合理性和可靠性。在有限元软件SAP2000中建立等效弹性数值模型,通过单参数分析得到对RC框架梁轴向约束刚度有显著影响的关键变量。在常见工程的取值范围内对关键变量进行充分的排列组合,开展规模化数值分析并总结结构空间约束的作用机理与RC框架梁极限状态下轴向约束刚度分布规律,得出了极限状态下RC框架梁轴向约束刚度的计算方法。

考虑偏好的空间文本对象多目标最短路径查询

为了解决路网中考虑偏好的空间文本对象多目标最短路径查询问题,设计了包含属性的IR树索引结构;然后利用类别约束,排序约束构建限定的有向无环图.提出了支持属性的局部贪婪算法SALG_SPG,以对最短路径查询进行处理;为进一步提高查询处理效率,提出了支持属性的全局优化算法SAGO_SPG,该算法利用阈值和缓存机制减少了大量无效、重复的计算;最后,通过与现有的FEBF算法的对比实验,分析并验证了所提算法的高效性.

结构空间约束对钢筋混凝土梁受弯性能的影响

为探究结构空间约束对框架结构屈服机制的影响,借助多尺度数值方法,建立了具有不同边界条件的钢筋混凝土(reinforced concrete,RC)梁模型.定量分析了端部约束及添加现浇楼板对RC框架梁刚度和受弯承载力,即试件所能承受的最大弯矩的影响,揭示了端部约束及现浇楼板对RC梁弯曲机制的影响机理.此外,对各国规范计算的受弯承载力进行对比分析.结果表明,结构空间约束会影响RC框架梁的破坏形态.固支梁的刚度和受弯承载力显著高于简支梁,固支梁的受弯承载力和刚度最高可达简支梁的3.06倍和4.10倍.添加现浇楼板可显著提高梁的受弯承载力与刚度.各国规范可准确地计算简支梁的受弯承载力.然而,计算的固支梁及楼盖梁的受弯承载力极其保守,剪跨比为5.0的固支加板梁的受弯承载力模拟值分别是中国、美国和加拿大规范值的6.25倍、6.76倍和6.06倍.

自然灾害监测卫星协同任务规划研究

当前对地观测卫星具有快速、动态、准确等特点,是自然灾害高精度监测的必要手段。然而当前对地观测卫星数量众多,且卫星的主要任务和分辨率也存在较大差异,如何对卫星任务进行合理的调配是自然灾害应急监测的关键。文章在自然灾害监测需求分析的基础上,提出了一种基于时空约束和任务优先级的自然灾害卫星观测规划方法。通过建立卫星任务规划模型,结合贪婪算法和遗传算法分别进行优化,最后使用优化模型进行模拟仿真实验来验证模型的可靠性。结果表明,贪婪算法和遗传算法分别适合于中小区域和大型区域的自然灾害对地观测任务规划。

抽象性位移事件及其汉语编码的认知阐释

作为认知主体的人不仅有能力识解出抽象性位移事件,而且有能力将其编码为特定的语言结构并用于交际。作为一种特殊的位移事件,抽象性位移事件的形成是有认知理据的,这一认知理据就是抽象实体的可动化机制。该机制有其自身的认知特性,其使用会受到一定的条件限制。编码抽象性位移事件的语言表达式可以叫作抽象性空间位移关系构式。汉语抽象性空间位移关系构式的构成既要受到整体性限制条件的制约,又要受到局部性限制条件的制约。

受空间约束时曲线钢箱梁步履式多点顶推策略

针对曲线钢箱梁多点步履式顶推同步控制难度高、往往受到各类空间约束限制的难题,为提高顶推施工的精确性与可靠性,应充分降低曲线顶推施工过程中的多点异向和异速顶推工况次数,根据尽量使得顶推过程中曲线箱梁各点顶推方向与速度相同这一基本原则,提出了受空间约束时曲线钢箱梁以平移和纠偏为主,旋转与调整为辅的顶推策略和方法,建立了各基本工法对应的顶推数学模型,并将其成功应用于兰州市某非对称曲线斜拉桥的钢箱梁顶推施工。研究结果表明:随曲线钢箱梁顶推行进,理论计算出的梁体尾部偏差值逐渐变大、梁体所需旋转角度逐渐变小,故曲线钢箱梁顶推初期宜多次采用旋转工法减小曲线夹角,后期宜多次采用纠偏工法减小轴线偏差;调整工法可有效减少其余工法的实施次数,其计算流程独立于其他工法,只与当前曲线钢箱梁到达的临时墩所在平面位置有关;曲线钢箱梁即将穿越桥塔等空间障碍物时,梁体与障碍物碰撞风险最大,而随顶推进程的继续,梁体与障碍物碰撞风险会逐步降低;该曲线钢箱梁顶推策略与方法思路明确、可操作性高,可大幅降低对多点步履式顶推系统的要求,提高顶推施工可靠性,适用于市政桥梁的曲线钢箱梁步履式顶推施工。

一种面向精细化地理分区的空间约束聚类方法

在空间分区的相关研究中,虽然已有经典聚类算法k均值聚类(k-means)结合空间约束的成果,但其对于连续平铺面状地理要素的空间聚类适用性不高。因此,本文开展对k-means算法进行空间约束的探讨。通过改进SKATER算法的空间约束方式,构建一种包含自然扩张与次优扩张过程的空间约束的k-means算法;并在两个公共数据集上与已有研究方法进行比较评价。结果表明:本文方法尤其适用于处理连续平铺面状地理要素的分区;通过轮廓系数、DB指数及总残差平方和三个评价指标知,本文方法优于已有的SKATER、AZP及SC k-means方法。研究成果不仅能够为地理信息系统中的空间数据处理提供新的工具,也为聚类算法的研究提供了新的视角。

抚仙湖流域典型农田土壤质量状况及烟草种植障碍因素

以云南抚仙湖北岸澄江市约1130 hm^(2)农田土壤为研究对象,通过调查分析土壤物理、化学性质,评价了研究区土壤质量状况,并进一步利用空间分析、相关分析与主成分分析对研究区烟草种植的主要土壤障碍因子进行了分析。结果表明:研究区土壤整体偏黏(平均黏粒含量496.7 g/kg)、偏碱(pH均值7.45)、有机质含量较高(均值28.55 g/kg)、大中微量营养元素有效态含量也整体偏高(水解性氮均值119.10 mg/kg、有效磷均值68.85 mg/kg、速效钾均值208.44 mg/kg、有效锰均值28.14 mg/kg),但各土壤性质在空间上变异较大。土壤基础地力、人为施肥管理、质地、酸碱性、有效锰是影响该地区土壤肥力的主要障碍因素,这些因素可通过有机质、速效钾、黏粒、pH、有效锰等指标进行评价,并指导烟草种植的土壤管理。烟草种植过程中应根据土壤性质、烟草养分需求,结合土壤养分空间变异采取相应的土壤改良措施。