Application of multivariate statistics and 3D visualization analysis in tacit knowledge diffusion map

Tacit knowledge is an important factor for enterprises and institutions to enhance their knowledge innovation and value-added capabilities, and it is also a basic link to enhance organizational learning capabilities. With the development of technology, the dissemination of tacit knowledge has increasingly shown complex and dynamic trends. In order to make the tacit knowledge in the enterprise better circulate and generate greater economic value, therefore, this paper proposes a study on the diffusion map of tacit knowledge based on multivariate statistics and 3D visualization analysis. First of all, this paper analyzes the internal relationship between organizational learning and organizational tacit knowledge integration and organizational tacit knowledge innovation, and combines multiple statistical methods to propose an organizational tacit knowledge integration method based on tacit knowledge management. Secondly, we combine 3D visualization and generative confrontation network methods to analyze the data of tacit knowledge dissemination, and visualize the distribution of knowledge dissemination in three dimensions. In the simulation experiment test, this paper reveals that the spreading efficiency of tacit knowledge in the network is affected by related factors. Through this model, we hope to explore the behavioral laws of different types of nodes in the network and propose effective countermeasures to improve the efficiency of knowledge dissemination.     

A DEMATEL analysis of smart city determinants

Substantial population growth, increasing urbanization, overloaded infrastructure, more energy consumption, environmental impacts, and investment in technological developments are major challenges in city management and development. Municipalities seek to improve their citizens’ wellbeing and quality of life, but the need to find a balance between these complex factors makes decision-making processes more difficult. Experts must analyze the determinants of smart cities, which are urban centers intended to be socially involved, habitable, and economically and environmentally sustainable, and that rely strongly on technology and innovation. Based on multiple-criteria decision analysis (MCDA) principles, this study combines cognitive mapping techniques and the decision-making trial and evaluation laboratory (DEMATEL) method to develop a multicriteria model that can help managers analyze smart city determinants in a collaborative manner. The research included identifying these determinants and their respective cause-and-effect relationships using an expert panel’s experience and knowledge related to the subject under analysis. The results were validated by both the panel and the city councilor responsible for mobility and municipal projects within Évora City Council, Portugal, which has implemented smart city strategies. The latter specialist verified that the proposed evaluation system can be used as a tool to facilitate smart city collaborative decision-making processes. The study’s main advantages and limitations are also analyzed and discussed.     

A Lane-Level Road Marking Map Using a Monocular Camera

The essential requirement for precise localization of a self-driving car is a lane-level map which includes road markings (RMs). Obviously, we can build the lane-level map by running a mobile mapping system (MMS) which is equipped with a high-end 3D LiDAR and a number of high-cost sensors. This approach, however, is highly expensive and ineffective since a single high-end MMS must visit every place for mapping. In this paper, a lane-level RM mapping system using a monocular camera is developed. The developed system can be considered as an alternative to expensive high-end MMS. The developed RM map includes the information of road lanes (RLs) and symbolic road markings (SRMs). First, to build a lane-level RM map, the RMs are segmented at pixel level through the deep learning network. The network is named RMNet. The segmented RMs are then gathered to build a lane-level RM map. Second, the lane-level map is improved through loop-closure detection and graph optimization. To train the RMNet and build a lane-level RM map, a new dataset named SeRM set is developed. The set is a large dataset for lane-level RM mapping and it includes a total of 25157 pixel-wise annotated images and 21000 position labeled images. Finally, the proposed lane-level map building method is applied to SeRM set and its validity is demonstrated through experimentation.      

Green hydrogen production potential for Turkey with solar energy

The current study develops a hydrogen map concept where renewable energy sources are considered for green hydrogen production and specifically investigates the solar energy-based hydrogen production potential in Turkey. For all cities in the country, the available onshore and offshore potentials for solar energy are considered for green hydrogen production. The vacant areas are calculated after deducting the occupied areas based on the available governmental data. Abundant solar energy as a key renewable energy source is exploited by photovoltaic cells. To obtain the hydrogen generation potential, monocrystalline and polycrystalline type solar cells are considered, and the generated renewable electricity is directed to electrolysers. For this purpose, alkaline, proton exchange membrane (PEM), and solid oxide electrolysers (SOEs) are considered to obtain the green hydrogen. The total hydrogen production potential for Turkey is estimated to be between 415.48 and 427.22 Million tons (Mt) depending on the type of electrolyser. The results show that Erzurum, Konya, Sivas, and Van are found to be the highest hydrogen production potentials. The main idea is to prepare hydrogen map in detail for each city in Turkey, based on the solar energy potential. This, in turn, can be considered in the context of the current policies of the local communities and policy-makers to supply the required energy of each country.     

浅议地理信息系统与空间数据库建设

该文阐述了在地理信息系统建设过程中,地图数据库、空间数据库的作用与差别。针对我国现阶段地理信息系统建设的现状,分析了现阶段同时建立与维护空间数据库与地图数据库的必要性。指出了随着空间数据库技术的发展,空间数据库最终将取代地图数据库,同时提供多比例尺地图服务及各种时空尺度的地理信息服务。     

退火态TC4合金的热变形行为

采用Gleeble-3 5 0 0热模拟机系统研究退火态TC4(Ti 6Al 4V)合金在75 0～95 0℃,应变速率0 0 0 1～1s- 1 条件下的热变形行为。TC4合金的热变形激活能约为482kJ/mol,热变形方程为ε′=2 95×10 1 9[sinh(α·σp) ] 2 4 9exp(-4 82 0 0 0 /RT)。不同真应变下的热加工图相似,随变形温度升高及应变速率降低,能量消耗效率η逐渐升高。在变形温度90 0℃左右、应变速率为0 0 0 1s- 1 时,能量消耗效率η达到峰值,约为5 8%。     

全数字化地形图测量数据检测精度分析

针对数字化产品具有数据量大、用途多、技术方法多样等特点,根据用户对全数字化地形图的内容和精度要求较高的情况,提出在全数字地形测量中应加强质量控制、采取分阶段参照监理程序,对成果数据进行监控检核度分析,以保证最终成果质量能满足精度要求的技术方案。     

矿山矿图数字化技术

介绍了几种常用的纸质矿图数字化的方法,认为用扫描数字化法是当前矿图数字化的最好方法,并详细论述了该方法的实施要点.     

三级瓦斯地质图与瓦斯治理

在多年瓦斯地质研究的实践基础上，研究矿区、矿井、采掘工作面瓦斯地质图的作用和编制方法，运用板块构造和区域地质演化理论，做到区域控制矿区，矿区控制矿井，矿井控制采区和采煤工作面.结合大量的瓦斯地质资料和瓦斯测试参数，搞清瓦斯地质规律、赋存规律和涌出规律、瓦斯突出危险性的分区分带特征，编制三级彩色瓦斯地质图.认为瓦斯地质图是指导煤矿瓦斯治理的最重要的基础和技术，使瓦斯地质规律一目了然，指导瓦斯灾害预测、防治和瓦斯资源开发利用，有的放矢综合治理瓦斯.