Research on Circular Area Search algorithm of multi-robot service based on SOA cloud platform

Considering autonomous mobile robots with a variety of specific functions as a kind of service, when there are many types and quantities of services and the density of regional services is large, proposing an algorithm of Circular Area Search (CAS) because of the problem of multi-robot service scheduling in various areas. Firstly, Django is used as the web framework to build the Service-Oriented Architecture (SOA) multi-robot service cloud platform, which is the basic platform for multi-service combination. Then, the service type, the latitude and longitude and the scoring parameters of the service are selected as the service search metrics to design the CAS algorithm that based on the existing service information registered in MySQL and the Gaode Map for screening optimal service, and then providing the service applicant with the best service. Finally, the service applicant applies for the self-driving tour service as an example to perform performance simulation test on the proposed CAS algorithm. The results show that the CAS algorithm of the multi-robot service cloud platform proposed in this paper is practical compared to the global search. And compared with the Greedy Algorithm experiment, the service search time is reduced about 58% compared with the Greedy Algorithm, which verifies the efficiency of CAS algorithm.     

Mixing numerical and categorical data in a Self-Organizing Map by means of frequency neurons

Even though Self-Organizing Maps (SOMs) constitute a powerful and essential tool for pattern recognition and data mining, the common SOM algorithm is not apt for processing categorical data, which is present in many real datasets. It is for this reason that the categorical values are commonly converted into a binary code, a solution that unfortunately distorts the network training and the posterior analysis. The present work proposes a SOM architecture that directly processes the categorical values, without the need of any previous transformation. This architecture is also capable of properly mixing numerical and categorical data, in such a manner that all the features adopt the same weight. The proposed implementation is scalable and the corresponding learning algorithm is described in detail. Finally, we demonstrate the effectiveness of the presented algorithm by applying it to several well-known datasets.     

SRS: Spatial-tagged radio-mapping system combining LiDAR and mobile-phone data for indoor location-based services

One of the most challenging issues in radio received signal strength (RSS)-based localization systems is the generation and distribution of a radio map with a coordinate system linked with spatial information in a large indoor space. This study proposes a novel spatial-tagged radio-mapping system (SRS) that effectively combines the heterogeneous properties of LiDAR and mobile phones to simultaneously perform both spatial and radio mappings. The SRS consists of synchronization, localization, and map building processes, and enables real-time spatial and radio mapping. In the synchronization process, the distance range, motion data, and radio signals obtained through the LiDAR and mobile phone are collected in nodal units according to the sensing time. In the localization process, a feature variance filter is used to control the number of features generated from LiDAR and estimate the positions at which the nodes are generated in real time according to the motion data and radio signals. In map building, the estimated positions of the nodes are used to extract spatial and radio maps by using a unified location coordinate system. To ensure mobility, the SRS is manufactured in the form of a backpack supporting LiDAR and a mobile phone; the usefulness of the system is experimentally verified. The experiments are performed in a large indoor shopping mall with a complex structure. The experimental results demonstrated that a common coordinate system could be used to build spatial and radio maps with high accuracy and efficiency in real time. In addition, the field applicability of the SRS to location-based services is experimentally verified by applying the constructed radio map to well-known fingerprinting algorithms using the heterogeneous mobile phones.     

自组织特征映射网络在水质分类中的应用

应用自组织特征映射网络对阜新新邱露天煤矿排土场附近于家沟地下水污染区的水质分类问题进行了研究,通过调用MATLAB中相关函数,在不同的训练步数下,对研究区17个采样点进行了不同精度的分类,确定出了污染范围。研究结果表明,于家沟地区的大部分地下水已受到严重污染,不可再饮用。分类结果与综合指数法、模糊综合评价、灰色关联分析等方法的分析结果基本一致,说明自组织特征映射网络应用于解决水质分类问题是可行的。     

基于GIS技术的矿产资源管理信息系统

矿产资源是国民经济可持续发展的重要保证,开发一个功能强大的矿产资源管理信息系统对于管理、规划、开发矿产资源是十分重要的。阿拉善矿产资源信息管理系统采用集成二次开发方式,选择开发平台（Visual Basic 6.0）和OCX设计思路。开发组件应用SuperMap系列软件。本系统实现了档案管理,矿产资源信息的查询检索、开采区的影响预测等功能。结合原有采矿权、探矿权系统进行矿产资源管理。     

浅谈勘测定界图成图及用色

根据勘测定界图不同用途的需要，在制作成图及用色方面存在着不同的要求，为使勘测定界图在经济建设中发挥更大的作用，结合实际工作情况，对勘测定界图的成图及用色进行了初步探讨。     

从《万寿盛典图》解析清代北京城街道活动空间

以康熙《万寿盛典图》为对象,结合乾隆《京城全图》对所绘街道场景进行转译,解析清代北京城街道活动空间,发掘中国古代街道空间的内涵特征。结果表明:康熙《万寿盛典图》所描绘的清代北京城街道场景具有极强的写实性;其次,街道活动空间包含围合式、开放式、沿街式的形态类型,空间相对独立,实质性质与"广场"相似,串联分布,在街道上具有连贯性;最后指出,由于街道上的公共活动使得街道形态由线性空间发展为树状空间,形成富有变化的场所。     

基于WebGIS的海事监测系统设计与实现

为了解决国内外海事局将无人机引入海洋执法却无法实现数据快速共享的问题,本文设计并实现了基于WebGIS的海事监测系统。该系统基于B/S架构进行设计,以OpenLayers作为WebGIS显示层开发框架,搭载MySQL数据库储存空间数据与各类信息数据,将无人机传输的包括位置信息和视频信息与地理信息系统做关联,使得数据的展示更加具象化;同时实现无人机飞行任务智能操作、无人机数据的实时接入、数据库查询进行视频回放与轨迹回放处理关联等功能。达到海事应用实时化、高效化、全面化。     

由疏散地图到城市建设的平台 ——论“逃生地图”的可能性

所谓“疏散地形时间地图”（一般叫逃生地图）是指从绘制详细的疏散地图到致力于震后重建方法论的一系列举措。这一系列举措不仅保护了众多今后可能会没落的地域文化。而且还从地震中吸取教训,在进行建设和规划以人命优先为主旨的城市的前提下尝试着对地域进行改变。本文主要介绍了“逃生地图”概要、地方研讨会的地图效果以及逃生地图在汽车导航服务方面的应用等。     

城市环境气候信息在德国城市规划中的应用及其启示

随着公众关于气候变化与全球变暖的意识逐渐增强,适应气候变化创造宜居的城市环境是当前城市规划师的首要课题.德国早在1970年代就已开始探索相关城市气候应用研究与实践,并开发了城市环境气候图这一城市气候信息的应用平台.目前德国在该领域处于世界领先地位.本文立足于城市规划和城市气候领域,选取德国城市环境气候信息在城市规划应用中的典型案例作为研究重点,针对德国城市环境气候图的构建和应用展开了详细探讨,并总结了此类气候环境评估方法在应用中存在的优缺点,为我国快速城镇化发展中气候信息评估的应用提供了可借鉴的参照范例.