基于原始套接字的局域网数据包监听系统

设计并实现了一个局域网数据包监听系统,能够将本局域网内所有的数据包截获并分析,对局域网内的数据传输进行实时监控,提高网络的安全性。从系统功能介绍、实现原理、软件设计等几个方面阐述了该系统的实现。     

Partitioning road networks using density peak graphs: Efficiency vs. accuracy

Road traffic networks are rapidly growing in size with increasing complexities. To simplify their analysis in order to maintain smooth traffic, a large urban road network can be considered as a set of small sub-networks, which exhibit distinctive traffic flow patterns. In this paper, we propose a robust framework for spatial partitioning of large urban road networks based on traffic measures. For a given urban road network, we aim to identify the different sub-networks or partitions that exhibit homogeneous traffic patterns internally, but heterogeneous patterns to others externally. To this end, we develop a two-stage algorithm (referred as FaDSPa) within our framework. It first transforms the large road graph into a well-structured and condensed density peak graph (DPG) via density based clustering and link aggregation using traffic density and adjacency connectivity, respectively. Thereafter we apply our spectral theory based graph cut (referred as α-Cut) to partition the DPG and obtain the different sub-networks. Thus the framework applies the locally distributed computations of density based clustering to improve efficiency and the centralized global computations of spectral clustering to improve accuracy. We perform extensive experiments on real as well as synthetic datasets, and compare its performance with that of an existing road network partitioning method. Our results show that the proposed method outperforms the existing normalized cut based method for small road networks and provides impressive results for much larger networks, where other methods may face serious problems of time and space complexities.     

Scale independent surface characterisation: Geography meets precision surface metrology

The recently published standard ISO 25178-2 distinguishes between field parameters and feature parameters for surface texture characterisation, whereby the main difference between these two types is due to the fact that the parameters belonging to the first group are deduced from all points of a scale-limited surface, while the parameters belonging to the second group are deduced from only a subset of predefined topological surface features. As specified in ISO 25178-2, two prerequisites are indispensable for the determination of the feature parameters, viz., an adequate data structure for surface characterisation and a suitable formal method for surface generalisation, i.e. for the successive elimination of the less important surface features. Within ISO 25178-2 change trees are proposed for describing the surface topography, while Wolf pruning is suggested for surface simplification (cf. also ISO 16610-85). Apart from the techniques specified in ISO 25178-2 and ISO 16610-85, the present paper describes a second geometrical–topological approach for the characterisation and generalisation of surfaces that has its origin within the geosciences and is based on weighted surface networks and w-contractions. In addition, it is revealed how the two approaches, both of which have their foundations in graph theory, are interrelated to each other and how, from a historical point of view, the GIScience approach forms the basis of the one applied within surface metrology. Finally, some applications within precision engineering are described.     

Multi-scale qualitative location: A direction-based model

Qualitative locations describe the locations of spatial objects by relating them to a reference frame with qualitative relations. Existing models concerned with regional partitions are mainly topology-based and do not consider the effects of scale changes on locations. This study develops a direction-based multi-scale qualitative location (DMQL) model to fill this gap. First, a cell partition is defined by extending the borders of the minimum bounding rectangles of the regions in a regional partition. Relating spatial objects to all regions by a set of directions is equal to representing the objects as a set of cells in a cell partition. Second, due to the multiple cell representations of spatial objects and the changes in direction relations across scales, some approaches are presented to derive the direction changes between regions in different frames, between spatial objects and regions, and between spatial objects at different scales. Third, the location and relation consistencies of qualitative locations are evaluated based on the cell representations of spatial objects at multiple scales through a case study. The results indicate that the DMQL model can locate objects more precisely than the topology-based models.     

融合环境特征与改进YOLOv4的安全帽佩戴检测

目的 在施工现场，安全帽是最为常见和实用的个人防护用具，能够有效防止和减轻意外带来的头部伤害。但在施工现场的安全帽佩戴检测任务中，经常出现难以检测到小目标，或因为复杂多变的环境因素导致检测准确率降低等情况。针对这些问题，提出一种融合环境特征与改进YOLOv4（you only look once version 4）的安全帽佩戴检测方法。方法 为补充卷积池化等过程中丢失的特征，在保证YOLOv4得到的3种不同大小的输出特征图与原图经过特征提取得到的特征图感受野一致的情况下，将两者相加，融合高低层特征，捕捉更多细节信息；对融合后的特征图采用3×3卷积操作，以减小特征图融合后的混叠效应，保证特征稳定性；为适应施工现场的各种环境，利用多种数据增强方式进行环境模拟，并采用对抗训练方法增强模型的泛化能力和鲁棒性。结果 提出的改进YOLOv4方法在开源安全帽佩戴检测数据集（safety helmet wearing dataset，SHWD）上进行测试，平均精度均值（mean average precision，mAP）达到91.55%，较当前流行的几种目标检测算法性能有所提升，其中相比于YOLOv4，mAP提高了5.2%。此外，改进YOLOv4方法在融合环境特征进行数据增强后，mAP提高了4.27%，在各种真实环境条件下进行测试时都有较稳定的表现。结论 提出的融合环境特征与改进YOLOv4的安全帽佩戴检测方法，以改进模型和数据增强的方式提升模型准确率、泛化能力和鲁棒性，为安全帽佩戴检测提供了有效保障。     

Synthesis of Hydroxypropyl Methacrylate/Polysaccharide Graft Copolymers as Matrices for Controlled Release Tablets

ABSTRACT

Hydrophilic matrices are an interesting option when developing drug delivery systems. With this aim, hydroxypropyl methacrylate was grafted onto hydroxypropyl starch and hydroxypropyl cellulose substrates by following the Ce(IV) redox initiation method. Different amounts of ethyleneglycol dimethacrylate, 7 and 34 mol%, as the crosslinking monomer, were also added. The drying of grafted products was carried out by lyophilization, obtaining white powders. Reaction yields (percent grafting, grafting efficiency, etc.) and some physical characteristics of the powders (particle size, moisture uptake, density, morphology, etc.) were determined. These parameters indicate how useful these products may be as potential matrices for direct compressed tablets. In this light, the powder flowability and the binding properties of each copolymer were determined. The graft copolymers can be considered of great interest as direct compression excipients. Due to their different chemical structure and composition, they showed differences in viscoelastic properties that revealed an interesting range of possibilities for use in drug delivery formulations. Tablets formulated with conventional excipients were also tested. Dissolution tests of various tablets were carried out. In 12 hr, 60–80% of the model drugs was released.     

Influence of Avicel PH-301 on the Compressibility of α-Methyldopa and Phenobarbitone in Direct Compression

The aim of this work was to investigate the compressibilitybehavior of α-methyldopa and phenobarbitone using a Korsch EK0 instrumentedeccentric tablet machine, with force-time and force-displacement curves constructedand applied to calculate different compressional values to study the compressionalbehavior. The results of this work revealed a difference in compressibilitybehavior between the two drugs during the compressional process. α-Methyldopagave an abnormal compressional curve with high friction in the pre- and postcompressionalphases. A residual force could be seen on the lower punch. Furthermore, cappingand sticking were observed visually during tablet pressing, indicating poorcompressibility behavior. In the case of phenobarbitone, no friction was observedin the precompressional phase, but there was higher friction in the postcompressionalphase, especially in the ejection phase. The compressibility of the drugswas improved by the addition of Avicel PH-301 and magnesium stearate.     

基于pu-learning的同行评议文本情感分析

最近几年逐渐出现了对同行评议文本情感分析的研究，包括通过同行评议文本预测审稿人的推荐状态的任务。现有模型融入了论文本身或摘要信息，采用神经网络学习论文或摘要的高层表示，结合同行评议文本预测审稿人的推荐状态，这使得模型变得非常复杂的同时结果却没有实质性的提高。为此，提出了OSA机制来提高情感分析模型中对观点句的关注度。具体来说，采用pu-learning从同行评议文本的前N个句子中学习观点句的特征，使每一个句子都得到一个观点句权重，将其应用于情感分析模型的倒数第二层，由此得到最终的预测结果。在ICLR2017—2018数据集上使用不同的情感分析模型对OSA进行了评估，实验结果验证了OSA的高效性，并在两个数据集上取得了优异的性能。     

Dimension reduction in principal component analysis for trees

The statistical analysis of tree structured data is a new topic in statistics with wide application areas. Some Principal Component Analysis (PCA) ideas have been previously developed for binary tree spaces. These ideas are extended to the more general space of rooted and ordered trees. Concepts such as tree-line and forward principal component tree-line are redefined for this more general space, and the optimal algorithm that finds them is generalized.An analog of the classical dimension reduction technique in PCA for tree spaces is developed. To do this, backward principal components, the components that carry the least amount of information on tree data set, are defined. An optimal algorithm to find them is presented. Furthermore, the relationship of these to the forward principal components is investigated, and a path-independence property between the forward and backward techniques is proven.These methods are applied to a brain artery data set of 98 subjects. Using these techniques, the effects of aging to the brain artery structure of males and females is investigated. A second data set of the organization structure of a large US company is also analyzed and the structural differences across different types of departments within the company are explored.