移动学习与数据挖掘技术的关联及应用研究

随着网络技术与通信技术的迅速发展,移动学习呈现出强大的发展势头。本文提出利用数据挖掘技术对移动学习网站客观数据进行分析研究,对移动学习及数据挖掘技术研究者具有一定的启发意义和参考价值。     

Evolutionary governance in mining: Boom and bust in peripheral communities in Sweden

This study investigates the consequences of dramatic price fluctuations on the global iron ore market between boom and bust for the Swedish communities Kiruna and Pajala, located above the polar circle, in the years 2006-2018. It focuses on the impact of the Swedish state’s reorientation towards neoliberal policies that have entailed reduced state involvement in peripheral communities still dependant on heavy industry. This reorientation was manifested in the Mineral Strategy presented by the liberal-conservative government in 2013, in which the state was prescribed a role as facilitator of investment of foreign and private capital in the Swedish mining sector, but not as an active owner or developer of mining enterprises. The neoliberalisation of Swedish mining has established a fundamental conflict of interests between communities whose economic, social and cultural wellbeing depends on long-term state commitment, and the state whose main interests are aimed at global capital flows rather than the maintenance of industrial production in peripheral regions. This conflict remained latent as long as global mineral prices were high, but as boom turned to bust around 2012, it was activated in a way that highlighted asymmetric relations of power and economic development between the sparsely populated and resource-rich northern parts of the country and the densely populated south.     

Evaluating accessibility impacts of the proposed America 2050 high-speed rail corridor for the Appalachian Region

Transportation improvements are often considered to be precursors of economic growth. This paper examines industry-specific ‘attractiveness’ due to changes in the transportation network for 23 counties in the Appalachian Region. The network improvements result from new highway construction and the proposed America 2050 High-Speed Rail (HSR) plan for the Piedmont Atlantic Megaregion. The impacted counties that are proximate to five HSR stations (Birmingham, Atlanta, Greenville, Charlotte, and Greensboro) are studied for potential accessibility changes between the years 2002 to 2035. The impacts are examined with respect to six key industry sectors found around the proposed HSR stations: manufacturing; retail; construction; mining, quarrying, oil and gas extraction; health-care services; and all other remaining industries combined. The analysis shows that, for transportation improvements with highways only (and no HSR), a decrease in accessibility for all the impacted counties occurs for the six industry sectors examined in the future year of 2035. The HSR speed of 150 miles per hour is found to be adequate enough to cause positive changes in potential accessibility of the directly impacted counties containing the Birmingham and Greenville HSR stations. With combined transportation network improvements from both highway construction and the new 150 mph HSR line, counties around the Atlanta and Greensboro HSR stations would see accessibility increases in 2035 compared to 2002 with respect to five industry sectors: manufacturing; retail; construction; health-care services; and all other remaining industries combined. However, accessibility changes with respect to mining, quarrying, oil and gas extraction would be positive specifically only for the indirectly impacted counties around the Atlanta HSR station and the county containing the Greenville HSR station. This clearly shows differences in the spatial distribution of attractiveness for different industry sectors across the impacted counties along the HSR corridor. Thus, this exploratory analysis could serve as an aid to proactive public policy decision-making for large-scale transportation network improvements, such as the HSR, in understanding and improving economic activities for different industry mixes across other regions of the United States.     

中、美矿产资源产业的经济贡献率研究

本文运用采矿业的产值占GDP的比重来考察矿产资源产业的经济贡献率,通过核算表明,当前美国的矿业经济贡献率维持在3.53%的较低水平。中国矿产资源的贡献率在12%左右,预估2015-2020,中美矿产资源产业的经济贡献率分别为10%和3%左右。通过对中美矿产资源产业的贡献率比较发现,中国矿产资源的贡献率中煤炭行业对GDP贡献率占较大的部分。而美国油气产业对GDP的贡献率所占绝大部分的比例,未来中国的矿产资源产业的结构必须优化升级。     

技术源头降成本的具体实践

文章介绍了淮南矿业集团张集矿从思想观念、方案设计、方法确立、作业过程、技术创新、提高工效等方面降低成本的经验,并强调了考核在降低成本方面的重要性。     

American boomers and the flotation of shares in the city of London in the late nineteenth century

During the late nineteenth century there was a wave of promotions of American companies on the London Stock Exchange, which have been described as ‘free-standing’. The British company promoter, H. Osborne O'Hagan, is often regarded as the first mover in these promotions, a view based on his autobiography. This article suggests that, in fact, the American lawyer promoters, Samuel and Isaac Untermyer, were the first movers in these company promotions. This article looks at a number of free-standing companies where everyday managerial control was retained by the original managers, and in particular, the case of the Untermyer brothers who competed with O'Hagan.     

LUCC of large opencast mines in loess area during ecological restoration： a case study of Pingshuo Mine

1. Introduction Studies on land eco-recovery and ecology re- construction emerged in1960s in the world, but it didn't begin until 1980s in China. Actually, the stud- ies on land recovery and ecological reconstruction began in China in 1990s. Many large progresses have been made in the study on the theory of eco- logical recovery of disused land in recent 10 years [1-3]. According to the characters of terrene and min- eral resources, the research areas of ecological re- covery consist of: (1) …     

基于数据挖掘技术的国际铁路工程估价分析

国际铁路工程估价是国际铁路工程管理领域正确进行投标报价及决策的重要依据。针对国际铁路工程估价相关数据特征分析,提出将数据挖掘(Data Mining)技术应用于国际铁路工程估价过程的基本运作模式和工作程序,并建立了相应的估价流程模式图,为国际铁路工程估价方法提供一个新的思路。     

Literature-related discovery (LRD): Methodology

Literature-related discovery (LRD) is linking two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge. LRD has two components: Literature-based discovery (LBD) generates potential discovery through literature analysis alone, whereas literature-assisted discovery (LAD) generates potential discovery through a combination of literature analysis and interactions among selected literature authors. In turn, there are two types of LBD and LAD: open discovery systems (ODS), where one starts with a problem and arrives at a solution, and closed discovery systems (CDS), where one starts with a problem and a solution, then determines the mechanism(s) that links them.The generic methodology for identifying potential discovery candidates through ODS LRD, focusing mainly on its ODS LBD component, is described in this paper. A comprehensive flow chart showing the details of our systematic potential discovery generation process, including the evolution of the flow chart steps through each of the studies performed, is presented. Also shown is a vetting procedure that insures potential discoveries claimed are potential discoveries realized. The semantic filters that replace the numerical filters of other ODS LBD approaches are overviewed. The rationale for addressing the five topics studied (Raynaud's Phenomenon (RP), Cataracts, Parkinson's Disease (PD), Multiple Sclerosis (MS), and Water Purification (WP)) is summarized.     

Empirical Analyses of Extreme Value Models for the South African Mining Index

While the classical normality assumption is simple to implement, it is well known to underestimate the leptokurtic behaviour demonstrated in most financial data. After examining properties of the Johannesburg Stock Exchange Mining Index returns, we propose two extreme value models to fit its negative tail with a higher degree of accuracy. The generalised extreme value distribution (GEVD) is fitted using the block maxima approach, while the generalised Pareto distribution (GPD) is fitted using the peaks‐over‐threshold method. Numerical assessment of value‐at‐risk (VaR) estimates indicates that both GEVD and GPD increasingly outperform the normal distribution as we move further into the lower tail. In addition, GEVD produces lower estimates relative to that of the historical VaR, and GPD provides slightly more conservative estimates for adequate capitalisation.