全球-地方联结与产业集群的技术学习--以河南许昌发制品产业为例

以产业区理论、管制理论和全球生产网络理论为基础,以学习创新为核心,构建了一个融生产体系与社会生产体制、制度与协调机制、地方生产网络、全球生产网络“四位一体”的学习型产业区分析框架;运用该框架,以河南许昌发制品产业集群为案例,研究了全球-地方网络联结的方式、动态及其对技术学习的影响。研究发现,通过全球与地方生产网络的建构和有机联结,传统产业集群的技术学习是可以从“低端道路”迈向“高端道路”的,发展学习型产业区应作为我国经济发展与技术创新的一项重大战略和政策。     

Simulation of torsional shear test results with neuro-fuzzy control system

In the first part of this study, a series of stress-controlled hollow cylinder cyclic torsional triaxial shear tests were conducted on loose to medium dense saturated samples of clean Toyoura sand to investigate its liquefaction behavior. A uniform cyclic sinusoidal loading at a 0.1 Hz frequency was applied to air-pluviated samples where confining pressure and relative density was varied. Cyclic shear stress–strain changes, the number of cycles to reach liquefaction and pore pressure variations were recorded. Results indicate that the liquefaction resistances of uniform sands are significantly affected by the method of sample preparation and initial conditions.     

The use of digital technologies for landslide disaster risk research and disaster risk management: progress and prospects

Landslide is a serious natural disaster next only to earthquake and flood, which will cause a great threat to people’s lives and property safety. The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective , difficult to quantify, and no pertinence. As a new research method for landslide susceptibility assessment, machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models. Taking Western Henan for example, the study selected 16 landslide influencing factors such as topography, geological environment, hydrological conditions, and human activities, and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination (RFE) method. Five machine learning methods [Support Vector Machines (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Linear Discriminant Analysis (LDA)] were used to construct the spatial distribution model of landslide susceptibility. The models were evaluated by the receiver operating characteristic curve and statistical index. After analysis and comparison, the XGBoost model (AUC 0.8759) performed the best and was suitable for dealing with regression problems. The model had a high adaptability to landslide data. According to the landslide susceptibility map of the five models, the overall distribution can be observed. The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest, the Xiaoshan Mountain range in the west, and the Yellow River Basin in the north. These areas have large terrain fluctuations, complicated geological structural environments and frequent human engineering activities. The extremely high and highly prone areas were 12043.3 km² and 3087.45 km², accounting for 47.61% and 12.20% of the total area of the study area, respectively. Our study reflects the distribution of landslide susceptibility in western Henan Province, which provides a scientific basis for regional disaster warning, prediction, and resource protection. The study has important practical significance for subsequent landslide disaster management.     

Learning about learning: lessons from public engagement and deliberation on urban river restoration

This paper provides a new discussion of how people learn through deliberative processes, drawing upon empirical analysis of a novel public engagement process for urban river restoration. Such critical evaluation is rare and yet will be crucial to both theoretical development and learning about engagement practice, not least in a policy area subject to strong regulatory drivers for public participation. The analysis supports two important learning mechanisms – the use of 'gatekeepers' of knowledge, interests and values, and the privileging of narrative. It provides new evidence of instrumental and communicative learning about shared priorities and criteria for effective river restoration that evolved through the deliberative process and directly informed the restoration scheme. It is important to question whether and how such site or context-specific learning might inform other restoration schemes. Finally, the paper questions the often ignored issue of expert learning, not least the issue of the link between individual and organizational learning.     

Elements of viral cartography

ABSTRACT

Making and sharing maps is easier than ever, and social media platforms make it possible for maps to rapidly attain widespread visibility and engagement. Such maps can be considered examples of viral cartography – maps that reach rapid popularity via social media dissemination. In this research we propose a framework for evaluating the design and social dissemination characteristics of viral maps. We apply this framework in two case studies using maps that reached wide audiences on Twitter. We then analyze collections of maps derived from and inspired by viral maps using image analysis and machine learning to characterize their design elements. Based on our initial work to conceptualize and analyze virality in cartography, we propose a set of new research challenges to better understand viral mapmaking and leverage its social affordances.     

粤港澳闪电定位系统对高建筑物雷电的探测

为了评估不同聚类算法对雷暴系统的识别效果,进一步提高雷电临近预报能力,本文采用地闪定位数据和雷达反射率数据,利用基于密度的空间聚类(Density-Based Spatial Clustering of Application with Noise,DBSCAN)、快速搜索和查找密度峰聚类(Clustering by Fast Search and Find of Density Peaks,CFSFDP)以及改进的快速搜索和查找密度峰聚类(Extended Clustering by Fast Search and Find of Density Peaks,E_CFSFDP)三种聚类算法,对2018年9月21日19∶15—20∶57(北京时)发生在(114°—117°E、27°—30°N)区域的一次雷暴过程进行了聚类识别计算,探讨了三类聚类算法在雷暴系统识别中的差异。结果表明：(1) DBSCAN算法在地闪数据分布清晰且不同数据簇之间有显著距离间隔时,分类识别的准确率较高;当各个闪电数据簇的簇间距离或密度相差很大时,分类识别的准确率较低;(2) 地闪数据“无密度峰值”分布时CFSFDP算法会分裂出错误类,每个闪电数据簇仅具备唯一的密度峰值点是CFSFDP算法识别准确的前提条件;(3) E_CFSFDP算法解决了CFSFDP算法的“无密度峰值”问题,受地闪数据分布影响较小,因此基于E_CFSFDP算法的雷暴系统识别准确率明显高于DBSCAN和CFSFDP算法。

     

It’s Time To Learn About Learning: Where Should the Environmental and Natural Resource Governance Field Go Next?

This Commentary reflects on the state of the scholarship on learning for environmental and natural resource policy and governance. How have we been learning about learning? We highlight theoretical and empirical advancements related to learning, as well as areas of divergence between learning theories and frameworks, and underdeveloped knowledge around processes and outcomes. To address these limitations and improve progress in both theory and practice, we offer recommendations for learning scholarship by focusing on how to collectively engage in ‘learning about learning’.     

Time and Practice: Learning to Become a Geographer

Abstract

Illustrated Dictionary of Place Names: United States and Canada. By Kelsie B. Harder. New York: Van Nostrand, 1976. Pp. xiv + 631, $18.95.

Middle America: Its Lands and Peoples. 2nd ed. By Robert C. West and John P. Augelli. Englewood Cliffs, N.J.: Prentice-Hall, 1976. Pp. xvii + 494, $14.95.

Contemporary Africa: Geography and Change. Edited by C. Gregory Knight and James L. Newman. Englewood Cliffs, N.J.: Prentice-Hall, 1976. Pp. xiv + 546, $14.95.

Atlas of Mexico. By Stanley A. Arbingast et al. 2nd ed. Austin, Tex.: Bureau of Business Research, University of Texas, 1975. Pp. ix + 165, $15.00.

Readings in Social Geography. Edited by Emrys Jones. London: Oxford University Press, 1975. Pp. 328, $18.50 and $6.95.

California: Patterns on the Land. 5th ed. By Robert Durrenberger and Robert Johnson. A California Council for Geographic Education Publication. Palo Alto, Calif.: Mayfield Publishing, 1976. Pp. viii + 134, $6.95.

Studying China in Elementary and Secondary Schools, Studying India in Elementary and Secondary Schools, and Studying Japan in Elementary and Secondary Schools. By Leonard S. Ken-worthy. World Affairs Guides. New York: Teachers College Press, 1975. Pp. 68, iii + 67, and iii + 65, $2.75 each.

World Regional Geography: A Question of Place. By Paul Ward English and James Andrew Miller. Harper &; Row Series in Geography. New York: Harper &; Row, 1977. Pp. xiii + 591, $15.95.

Census Data: Geographic Significance and Classroom Utility. Edited by Borden D. Dent. Tualatin, Oreg.: Geographic and Area Study Publications, 1976. Pp. ix + 277.

The Middle East: A Geographical Study. By Peter Beaumont, Gerald H. Blake, and Malcolm J. Wagstaff. London: John Wiley &; Sons, 1976. Pp. xvii + 572, $25.50 and $14.95.

Man's Economic Environment. By Edgar C. Conklingand Maurice Yeates. New York: McGraw-Hill Book Co., 1976. Pp. xi + 308, $11.95.

Applied Climatology: An Introduction. 2nd ed. By John F. Griffiths. New York/London: Oxford University Press, 1976. Pp. xiii + 136, $9.00.

Man and the Environment: Regional Perspectives. Edited by J. H. Holmes. Hawthorn, Victoria: Longman Australia Pty Limited, 1976. Pp. vi + 261, $7.95.

Introduction to Cultural Geography. 5th ed. By Henry M. Kendall, Robert M. Glendinning, Clifford H. MacFadden, and Craig H. MacFadden. New York: Harcourt Brace Jovanovich, 1976. Pp. xx + 449, $12.95.

Interpretation of Aerial Photographs. 3rd ed. By Thomas Eugene Avery. Minneapolis, Minn.: Burgess Publishing Company, 1977. Pp. xi + 392, $14.95.

Geography of the U.S.S.R. 3rd ed. By Paul Lydolph. New York: John Wiley &; Sons, 1977. Pp. xi + 495, $18.95.     

基于机器学习的重庆长江航道雾图像特征识别研究

基于重庆市境内长江航道雷达站拍摄的雾天气过程影像资料,利用K最近邻、支持向量机、BP神经网络、随机森林等机器学习算法,对无雾和5类有雾天气个例进行图像识别训练,构建雾图像识别模型,并检验了识别准确率。结果表明：机器学习能够有效识别雾图像,随机森林算法的识别效果优于其余3种算法。对于能见度超过1500 m的无雾天气,模型的识别准确率为100%,对于能见度在1000—1500 m范围内的轻雾、能见度低于50 m的强浓雾,模型的识别准确率在90%以上,对于能见度在50—1000 m范围内的雾、大雾和浓雾,识别准确率超过70%。     

成矿预测:从二维到三维

随着矿产资源勘探方法以及计算机科学技术的不断发展,成矿预测的理论和方法已从定性发展至定量,从二维拓展到三维。近十年来,随着深部矿产资源勘探工作的推进,三维成矿预测研究得到了迅猛发展,相关理论与方法也已逐步走向成熟。本文总结了国内外二维成矿预测研究的现状,同时对近十年来国内外学者在三维地质建模技术、三维成矿预测方法等方面的主要成果和进展做了系统总结和分析。目前,国内外多个地区已相继开展了三维成矿预测工作,并成功圈定多个深部找矿靶区,相关成果为深部找矿勘探工作提供了新的方法和方向。在此基础上,本文对未来三维成矿预测的发展趋势进行展望,相较于传统的二维成矿预测,三维成矿预测往往受限于三维预测信息的缺乏。如何更好的挖掘二维数据在深度方向的指示能力,将二维数据推演至三维环境,利用数值模拟、机器学习等方法开展数据挖掘、充分发挥已有数据的内蕴信息将在未来推动三维成矿预测理论的深入发展,提高三维成矿预测的理论方法及应用实践水平。