Using Web resources to construct multilingual medical thesaurus for cross-language medical information retrieval

Due to the language barrier, non-English users are unable to retrieve the most updated medical information from the U.S. authoritative medical websites, such as PubMed and MedlinePlus. However, currently, there is no any cross-language medical information retrieval (CLMIR) system that can help Chinese-speaking consumers cross the language barrier in finding useful English medical information. A few CLMIR systems utilize MeSH (Medical Subject Headings) to help overcome the language barrier. Unfortunately, the traditional Chinese version of MeSH is currently unavailable.In this paper, we employ a semi-automatic term translation method to construct a Chinese–English MeSH by exploiting abundant multilingual Web resources, including Web anchor texts and search–result pages. Through this method, we have developed a Chinese–English Mesh Compilation System to assist knowledge engineers in compiling a Chinese–English medical thesaurus with more than 19,000 entries. Furthermore, this thesaurus has been used to develop a prototypical system for cross-language medical information retrieval, MMODE, which can help consumers retrieve top-quality English medical information using Chinese terms.     

平差法预计矿区导线网精度

分析了矿区导线网精度预计经典方法存在的问题 ,推导出严密平差法精度预计的数学模型 ,并编制机算程序。     

阳泉矿区高产高效矿井建设现状及发展趋势

近年来,阳泉煤业集团公司在高产高效矿井建设方面取得了一定成绩,但与国内外先进水平相比仍有较大差距。介绍了国内外和集团公司高产高效矿井建设的现状,指出了制约集团公司高产高效矿井建设的因素及发展趋势。     

中铝河南分公司矿山在土地复垦中的有益探索

分析了铝土矿露天开采和土地、环境之间的利害关系，并对矿山公司“土地复垦”工艺技术进行了阐述，介绍了中铝河南分公司矿山公司方面的具体作法和成功经验。     

Mining process models with non-free-choice constructs

Process mining aims at extracting information from event logs to capture the business process as it is being executed. Process mining is particularly useful in situations where events are recorded but there is no system enforcing people to work in a particular way. Consider for example a hospital where the diagnosis and treatment activities are recorded in the hospital information system, but where health-care professionals determine the “careflow.” Many process mining approaches have been proposed in recent years. However, in spite of many researchers’ persistent efforts, there are still several challenging problems to be solved. In this paper, we focus on mining non-free-choice constructs, i.e., situations where there is a mixture of choice and synchronization. Although most real-life processes exhibit non-free-choice behavior, existing algorithms are unable to adequately deal with such constructs. Using a Petri-net-based representation, we will show that there are two kinds of causal dependencies between tasks, i.e., explicit and implicit ones. We propose an algorithm that is able to deal with both kinds of dependencies. The algorithm has been implemented in the ProM framework and experimental results shows that the algorithm indeed significantly improves existing process mining techniques.     

A Simple Constraint-Based Algorithm for Efficiently Mining Observational Databases for Causal Relationships

This paper presents a simple, efficient computer-based method for discovering causal relationships from databases that contain observational data. Observational data is passively observed, as contrasted with experimental data. Most of the databases available for data mining are observational. There is great potential for mining such databases to discover causal relationships. We illustrate how observational data can constrain the causal relationships among measured variables, sometimes to the point that we can conclude that one variable is causing another variable. The presentation here is based on a constraint-based approach to causal discovery. A primary purpose of this paper is to present the constraint-based causal discovery method in the simplest possible fashion in order to (1) readily convey the basic ideas that underlie more complex constraint-based causal discovery techniques, and (2) permit interested readers to rapidly program and apply the method to their own databases, as a start toward using more elaborate causal discovery algorithms.     

我国钨业“四矿”问题及其对策思考

简要回顾了我国钨矿业悠久的历史、资源的优势、技术的进步和卓越的贡献 ;20世纪80年代中期以后 ,逐步陷入困境 ,举步维艰的主要表现 ;以及在解决“四矿”(矿业、矿山、矿工、矿城)问题中的艰苦经历。指出应在“四矿”问题讨论中做更多、更深的对策思考 ,并对钨业的“四矿”问题加以重点研究。     

复杂开采条件矿体三强回采作业技术应用

本文针对金翅岭金矿矿体开采条件极其复杂的情况，在采矿方法试验中，率先在岩金矿山采用了三强作业技术，既保证了安全回采，又取是了较好的技术经济指标。     

露天矿场有规则安全小平台开采方法

文中提出了在高阶段不分层开采的露天矿场采用“有规则安全小平台开采方法”。开采坡度能够得到控制，有效地控制了采石场经常发生的塌方事故，能提高产量，降低生产成本，安全性好，且技术简单，易于推广。     

A Search for Hidden Relationships: Data Mining with Genetic Algorithms

This paper presents an algorithm that permits the search for dependencies among sets of data (univariate or multivariate time-series, or cross-sectional observations). The procedure is modeled after genetic theories and Darwinian concepts, such as natural selection and survival of the fittest. It permits the discovery of equations of the data-generating process in symbolic form. The genetic algorithm that is described here uses parts of equations as building blocks to breed ever better formulas. Apart from furnishing a deeper understanding of the dynamics of a process, the method also permits global predictions and forecasts. The algorithm is successfully tested with artificial and with economic time-series and also with cross-sectional data on the performance and salaries of NBA players during the 94–95 season.