Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

The relationship between centrality and land use patterns: Empirical evidence from five Chinese metropolises

The relationship between location and land use patterns is one of the classic theoretical issues in urban studies. Classic models based on the monocentricity hypothesis have limitations in the interpretation of modern urban structure. China has experienced institutional transformation in recent decades, and the interaction of national government policy, market forces and the natural environment has influenced urban planning in Chinese metropolises, resulting in urban structures with special characteristics. This paper examines the distribution of location and land use intensity, and tested the Alonso model by the relationship between them in five Chinese metropolises using Point of Interest data, space syntax methodology, the grid weighted statistical method and the Geographically Weighted Regression (GWR) model. Universal patterns about the scaling relation between intensity of land use types and the centrality of location are revealed. The elasticity of land use types to location, from high to low sensitivity, is commercial, residential then industrial land in most of the five metropolises studied. The sensitivity sequence of land use studied suggests that the hypothetical model based on the classical Alonso model can explain the spatial structure of modern metropolises in China to some extent, especially for the commercial land. But the order of sensitivity of residential land and industrial land to location does not conform to the model. The spatial heterogeneity in land use intensity and centrality were explored and the factors embedded were discussed. It can be found that the relation between centrality and land use intensity conforms to power law. In most of the metropolises studied, when the scaling relation between land use intensity and centrality is super linear, the sequence of the frequency value from high to low are commercial, residential and industrial land; when the scaling relation is sublinear, the sequence of the frequency value is industrial, residential and commercial land.     

Distortion visualization techniques for 3D coherent sets: A case study of 3D building property units

In the fields of 3D cadastre and 3D property management system, numerous building property objects are adjacent as primary property units assemble into a 3D coherent set. During visualization process of the coherent set, occlusion, obscure, mazy spatial relationships and relative location relationships among the units of the coherent set cause difficulty in observing and understanding the set and its units. Common 3D objects viewing method, such as rotation and navigation obtaining desired visualization effects through adjusting the view angle and position of the camera's field of view, provides weak interactive experience and orientation control for the coherent set because of the neighbour relationships of the 3D objects inside the set. In this paper, a novel method is proposed to solve the prior problems with two basic distortion methods based on “focus + context” theory. The coherent set is first discretized into individual objects and changed them locations according to linear or orthogonal function, while keeping their relative location and dual topological relationships. To maintain both global context awareness (topology and locations) of 3D coherent set and highlight effect of the focus 3D building property object, three evaluation indexes are adopted to assess the corresponding distortion results. A case study based on the real clustered 3D property in Shenzhen was conducted to evaluate the performance of distortion functions, the result shows that the method proposed in this article can not only expand the visual area of focused object and create a clear line of sight (LOS) to the focal object previously obscured, but also maintain verticality and proximity in some degree to facilitate understand the spatial occupation and distribution of whole coherent objects.     

ICT application in the informal sector: The case of the Kariokor market MSE cluster in Nairobi

Conclusion A successful informal sector of sustainable ICT clusters requires that the ICT provided are the ones in demand by the entrepreneurs and that they should be located strategically, in order to generate optimal utilisation and avoid the loss of man-hours by the informal sector having to search for the services. There should also be a strategy aiming at investment in human capital, which will trigger active absorption of skills and technology. This calls for a collaboration or partnership between government and other development partners, especially those who can facilitate training in business development and management skills, as well as the use of ICT. A special focus of this ICT strategy should be to demystify and promote diffusion of ICT as a general-purpose technology to the informal sector. It is believed that the use of new technologies can be crucial to meeting the Millennium Development Goals (MDGs) in a timely and effective fashion. In response to this noble call the study concludes that there is a need to prevent further marginalization of the informal sector by availing ICT services which are mixed appropriately and also properly located. This will help them access markets and other business information which can enable, or make their economic activities, more vibrant and facilitate availability of information about new opportunities. The study concludes that for one to understand the application of ICT and their locational dynamics in informal sector clusters there is a need to comprehend and acknowledge the drivers and pressures leading to the adoption of new technology such as ICT in the informal sector.     

Degrees of destitution: a typology of homelessness in developing countries

There is an ongoing attempt to develop a globally acceptable definition of homelessness. Whether such a definition is broad and inclusive of squatters, and those living in particularly poor quality housing, or narrowly focused on street homelessness, it is likely to include a large population. Therefore, we are left with a need to develop criteria for identifying, allocating and prioritising appropriate support. Drawing on a study of homelessness in nine developing countries, this paper presents a new categorisation or typology of homelessness, based on choice and opportunity. It highlights the way in which homeless people, living in identical shelter situations, and for ostensibly similar reasons, might require different responses to support them out of homelessness. This paper does not seek to debate the definition of homelessness but to stimulate discussion on finding a way to identify and prioritise the needs of those included within any given definition.     

A graph-based semi-supervised approach to classification learning in digital geographies

As the distinction between online and physical spaces rapidly degrades, social media have now become an integral component of how many people's everyday experiences are mediated. As such, increasing interest has emerged in exploring how the content shared through those online platforms comes to contribute to the collaborative creation of places in physical space at the urban scale. Exploring digital geographies of social media data using methods such as qualitative coding (i.e., content labelling) is a flexible but complex task, commonly limited to small samples due to its impracticality over large datasets. In this paper, we propose a new tool for studies in digital geographies, bridging qualitative and quantitative approaches, able to learn a set of arbitrary labels (qualitative codes) on a small, manually-created sample and apply the same labels on a larger set. We introduce a semi-supervised, deep neural network approach to classify geo-located social media posts based on their textual and image content, as well as geographical and temporal aspects. Our innovative approach is rooted in our understanding of social media posts as augmentations of the time-space configurations that places are, and it comprises a stacked multi-modal autoencoder neural network to create joint representations of text and images, and a spatio-temporal graph convolution neural network for semi-supervised classification. The results presented in this paper show that our approach performs the classification of social media content with higher accuracy than traditional machine learning models as well as two state-of-art deep learning frameworks.     

Comparative study on economic contribution rate of education of China and foreign countries based on soft computing method

Economic contribution rate of education (ECRE) is the key factor of education economics. This article selected China, South Korea, United States and other countries for a total of 15 samples, and put the data of the same period under the framework of soft computing, to simulate the production chain of “education–potential human capital–actual human capital–economic growth”. The basic idea is: Firstly, 15 countries are softly categorized according to the level of science and technology (S&T) progress. Secondly, potential human capital and actual human capital establish the internal correlation (fuzzy mapping) in the same classification, and we conceptualize actual human capital as one production factor, joined with the other two production factors, fixed asset and land, to set up the fuzzy mapping to economic growth., and then calculate economic contribution rate of education of China and foreign by two fuzzy mapping of them. Thirdly, this paper analyzes the present state and differences in the development of education between China and foreign according to different ECRE, and offers proposals for promoting the education in China.     

基于网络文本的山地景观游客行为与形象感知研究——以重庆市长嘉汇弹子石老街为例

剖析网络评价文本能为景观规划设计提供科学的依据支撑,弥补因快速城镇化建设发展而导致的公众参与不足,对于景观设计而言是非常重要的。以重庆市弹子石老街为例,基于网络文本内容分析法,利用rostcm6、excel及python等分析和数据抓取软件,采集大众点评的相关评论数据,以山地景观设计视角结合相关数据分析软件进行定性定量分析并制作可视化分析图,最终从多维度分析游客评论得出结果及改进建议,总结针对重庆弹子石老街及山地景观设计的6条设计策略:(1)交通可达的组织方式;(2)垂直上下的衔接转换;(3)对景远眺的外向空间;(4)本土文化的特色彰显;(5)城市事件的策划安排;(6)游览夜景的慢行系统,期望对今后的类似山地景观空间规划设计提供一定参考和借鉴价值。