Possibility of new mining project extracting in conditions of crisis

Directory of Open Access Journals (Sweden)

Stanislav Szabo

2009-03-01

Full Text Available This paper gives some information about investment in mining company, it specifies project of Strieborná Vein. The project usesinstruments of financial management and it gives a lot of information about cost, taxes, return of investment, incomes and loan. Thatinformation is very important for application of project in Strieborná Vein and they support decision of investors. Strieborná Veinis an example of investment in period of crisis. Gold, silver, copper and iron extracting needs great investment but commodities are toointeresting to invest to them.

Mining and information: defining the need

Energy Technology Data Exchange (ETDEWEB)

Gray, J.; Peck, J. [AQUILA Mining Systems Ltd., Calgary, AB (Canada)

1996-07-01

Some of the current technologies at surface mining operations are discussed. The information system and communication system requirements needed to integrate these components are considered. A plan of a new mine that uses operating information, optimization through planning, monitoring, and locating systems, data processing and analysis, and integration of monitored data and information via the Total Mining System (TMS) is described. The TMS will allow integration of a network of stand-alone modules. There is an immediate requirement for setting standards in surface mining operations to prevent duplication of effort. 12 refs., 2 figs.

Social big data mining

CERN Document Server

Ishikawa, Hiroshi

2015-01-01

Social Media. Big Data and Social Data. Hypotheses in the Era of Big Data. Social Big Data Applications. Basic Concepts in Data Mining. Association Rule Mining. Clustering. Classification. Prediction. Web Structure Mining. Web Content Mining. Web Access Log Mining, Information Extraction and Deep Web Mining. Media Mining. Scalability and Outlier Detection.

TSC mobile mining and extraction technology

Energy Technology Data Exchange (ETDEWEB)

Lavender, W.J. [TSC Company Ltd., Calgary, AB (Canada)

2001-11-01

This Power-Point presentation described an innovative mining and extraction technology developed by Calgary-based TSC Company Ltd. that has provided a major breakthrough in bitumen production from mineable oil sands. The presentation described the process and key mechanical components as demonstrated on oil sands leases. It also described the step change in cost structure and profitability. Oil sands mining provide a hugh resource base with no exploration costs and no decline in production. Despite these advantages, oil sands mining faces the challenge of high capital and operating costs and materials handling. Other challenges include the variability of the ore and environmental impacts. This paper described the fundamentals of the new technology called the Tar Sand Combine (TSC), a continuous mining machine, crusher, cyclone, tailings filter and stacker all in one mobile module. Several viewgraphs were included with the presentation to depict the recovery process as successfully demonstrated at a pilot project. Patent is pending on the process and components. The advantages of the TSC are reduced materials handling, and no tailings ponds are generated since tailings remain where they are mined. The final product is clean bitumen. The specifications of a commercial TSC are: 2000 ton/stream hour mining produce 25,000 bpsd bitumen at 12 per cent ore grade; mined ore bitumen recovery is greater than 95 per cent and the availability factor is 85 per cent. It was concluded that the TSC can maximize oil sands reserves, while providing significant cost savings and environmental benefits. 2 tabs., 24 figs.

A Two-Step Resume Information Extraction Algorithm

Directory of Open Access Journals (Sweden)

Jie Chen

2018-01-01

Full Text Available With the rapid growth of Internet-based recruiting, there are a great number of personal resumes among recruiting systems. To gain more attention from the recruiters, most resumes are written in diverse formats, including varying font size, font colour, and table cells. However, the diversity of format is harmful to data mining, such as resume information extraction, automatic job matching, and candidates ranking. Supervised methods and rule-based methods have been proposed to extract facts from resumes, but they strongly rely on hierarchical structure information and large amounts of labelled data, which are hard to collect in reality. In this paper, we propose a two-step resume information extraction approach. In the first step, raw text of resume is identified as different resume blocks. To achieve the goal, we design a novel feature, Writing Style, to model sentence syntax information. Besides word index and punctuation index, word lexical attribute and prediction results of classifiers are included in Writing Style. In the second step, multiple classifiers are employed to identify different attributes of fact information in resumes. Experimental results on a real-world dataset show that the algorithm is feasible and effective.

Gold-Mining

DEFF Research Database (Denmark)

Raaballe, J.; Grundy, B.D.

2002-01-01

  Based on standard option pricing arguments and assumptions (including no convenience yield and sustainable property rights), we will not observe operating gold mines. We find that asymmetric information on the reserves in the gold mine is a necessary and sufficient condition for the existence...... of operating gold mines. Asymmetric information on the reserves in the mine implies that, at a high enough price of gold, the manager of high type finds the extraction value of the company to be higher than the current market value of the non-operating gold mine. Due to this under valuation the maxim of market...

Feature extraction for classification in the data mining process

NARCIS (Netherlands)

Pechenizkiy, M.; Puuronen, S.; Tsymbal, A.

2003-01-01

Dimensionality reduction is a very important step in the data mining process. In this paper, we consider feature extraction for classification tasks as a technique to overcome problems occurring because of "the curse of dimensionality". Three different eigenvector-based feature extraction approaches

An Application for Data Preprocessing and Models Extractions in Web Usage Mining

Directory of Open Access Journals (Sweden)

Claudia Elena DINUCA

2011-11-01

Full Text Available Web servers worldwide generate a vast amount of information on web users’ browsing activities. Several researchers have studied these so-called clickstream or web access log data to better understand and characterize web users. The goal of this application is to analyze user behaviour by mining enriched web access log data. With the continued growth and proliferation of e-commerce, Web services, and Web-based information systems, the volumes of click stream and user data collected by Web-based organizations in their daily operations has reached astronomical proportions. This information can be exploited in various ways, such as enhancing the effectiveness of websites or developing directed web marketing campaigns. The discovered patterns are usually represented as collections of pages, objects, or re-sources that are frequently accessed by groups of users with common needs or interests. In this paper we will focus on displaying the way how it was implemented the application for data preprocessing and extracting different data models from web logs data, finding association as a data mining technique to extract potentially useful knowledge from web usage data. We find different data models navigation patterns by analysing the log files of the web-site. I implemented the application in Java using NetBeans IDE. For exemplification, I used the log files data from a commercial web site www.nice-layouts.com.

Towards A Model Of Knowledge Extraction Of Text Mining For Palliative Care Patients In Panama.

Directory of Open Access Journals (Sweden)

Denis Cedeno Moreno

2015-08-01

Full Text Available Solutions using information technology is an innovative way to manage the information hospice patients in hospitals in Panama. The application of techniques of text mining for the domain of medicine especially information from electronic health records of patients in palliative care is one of the most recent and promising research areas for the analysis of textual data. Text mining is based on new knowledge extraction from unstructured natural language data. We may also create ontologies to describe the terminology and knowledge in a given domain. In an ontology conceptualization of a domain that may be general or specific formalized. Knowledge can be used for decision making by health specialists or can help in research topics for improving the health system.

The role of conflict minerals, artisanal mining, and informal trading networks in African intrastate and regional conflicts

Science.gov (United States)

Chirico, Peter G.; Malpeli, Katherine C.

2014-01-01

The relationship between natural resources and armed conflict gained public and political attention in the 1990s, when it became evident that the mining and trading of diamonds were connected with brutal rebellions in several African nations. Easily extracted resources such as alluvial diamonds and gold have been and continue to be exploited by rebel groups to fund their activities. Artisanal and small-scale miners operating under a quasi-legal status often mine these mineral deposits. While many African countries have legalized artisanal mining and established flow chains through which production is intended to travel, informal trading networks frequently emerge in which miners seek to evade taxes and fees by selling to unauthorized buyers. These networks have the potential to become international in scope, with actors operating in multiple countries. The lack of government control over the artisanal mining sector and the prominence of informal trade networks can have severe social, political, and economic consequences. In the past, mineral extraction fuelled violent civil wars in Sierra Leone, Liberia, and Angola, and it continues to do so today in several other countries. The significant influence of the informal network that surrounds artisanal mining is therefore an important security concern that can extend across borders and have far-reaching impacts.

Genetic process mining

NARCIS (Netherlands)

Aalst, van der W.M.P.; Alves De Medeiros, A.K.; Weijters, A.J.M.M.; Ciardo, G.; Darondeau, P.

2005-01-01

The topic of process mining has attracted the attention of both researchers and tool vendors in the Business Process Management (BPM) space. The goal of process mining is to discover process models from event logs, i.e., events logged by some information system are used to extract information about

Selectivity assessment of an arsenic sequential extraction procedure for evaluating mobility in mine wastes

International Nuclear Information System (INIS)

Drahota, Petr; Grösslová, Zuzana; Kindlová, Helena

2014-01-01

Highlights: • Extraction efficiency and selectivity of phosphate and oxalate were tested. • Pure As-bearing mineral phases and mine wastes were used. • The reagents were found to be specific and selective for most major forms of As. • An optimized sequential extraction scheme for mine wastes has been developed. • It has been tested over a model mineral mixtures and natural mine waste materials. - Abstract: An optimized sequential extraction (SE) scheme for mine waste materials has been developed and tested for As partitioning over a range of pure As-bearing mineral phases, their model mixtures, and natural mine waste materials. This optimized SE procedure employs five extraction steps: (1) nitrogen-purged deionized water, 10 h; (2) 0.01 M NH 4 H 2 PO 4 , 16 h; (3) 0.2 M NH 4 -oxalate in the dark, pH3, 2 h; (4) 0.2 M NH 4 -oxalate, pH3/80 °C, 4 h; (5) KClO 3 /HCl/HNO 3 digestion. Selectivity and specificity tests on natural mine wastes and major pure As-bearing mineral phases showed that these As fractions appear to be primarily associated with: (1) readily soluble; (2) adsorbed; (3) amorphous and poorly-crystalline arsenates, oxides and hydroxosulfates of Fe; (4) well-crystalline arsenates, oxides, and hydroxosulfates of Fe; as well as (5) sulfides and arsenides. The specificity and selectivity of extractants, and the reproducibility of the optimized SE procedure were further verified by artificial model mineral mixtures and different natural mine waste materials. Partitioning data for extraction steps 3, 4, and 5 showed good agreement with those calculated in the model mineral mixtures (<15% difference), as well as that expected in different natural mine waste materials. The sum of the As recovered in the different extractant pools was not significantly different (89–112%) than the results for acid digestion. This suggests that the optimized SE scheme can reliably be employed for As partitioning in mine waste materials

The mine where extracting coal is a bonus

Energy Technology Data Exchange (ETDEWEB)

NONE

1993-07-01

Bowmans Harbour opencast mine is probably unique. Here Clay Colliery is mining an area that was derelict and contaminated land, which became a landfill site. When standards for landfill were raised the Black Country Development Corporation decided to redeposit the waste in a new repository on the same site, using higher standards. New cells for waste are being constructed. In creating these new cells coal is being extracted and sold. Four excavators are involved in this project.

Mine robotics for the extraction of minerals at great depths

Energy Technology Data Exchange (ETDEWEB)

Chaikovskii, Eh G; Poller, B V; Konyukh, V L

1983-09-01

An article is discussed which was written by A.A. Bovin, N.V. Kurleni and E.I. Shemyakin on Problems in mining mineral deposits at great depth, printed in issue No. 2 of this journal in 1983. First the authors define the problems, then discuss the construction of automatic systems for the control of underground extraction and haulage and end with the basic problems and organizational measures connected with the development and construction of mining robots. They also deal with systems of control and radio communications for underground winning and hauling operations. The article represents a complex study of the need for full automation of mining and the gradual introduction of robots to replace men in hazardous work places. The authors suggest equipment for the automatic extraction and hauling of minerals based on the use of microcomputers underground and computers located on the surface, videosensors and pressure transducers. The authors state that in order to solve the problems of automation and remote control of mining operations it is necessary to involve more specialists in robotics and remote control at the mining scientific research institutes and to increase the number of graduates in this field. 28 references.

A COMPARATIVE ANALYSIS OF WEB INFORMATION EXTRACTION TECHNIQUES DEEP LEARNING vs. NAÏVE BAYES vs. BACK PROPAGATION NEURAL NETWORKS IN WEB DOCUMENT EXTRACTION

Directory of Open Access Journals (Sweden)

J. Sharmila

2016-01-01

Full Text Available Web mining related exploration is getting the chance to be more essential these days in view of the reason that a lot of information is overseen through the web. Web utilization is expanding in an uncontrolled way. A particular framework is required for controlling such extensive measure of information in the web space. Web mining is ordered into three noteworthy divisions: Web content mining, web usage mining and web structure mining. Tak-Lam Wong has proposed a web content mining methodology in the exploration with the aid of Bayesian Networks (BN. In their methodology, they were learning on separating the web data and characteristic revelation in view of the Bayesian approach. Roused from their investigation, we mean to propose a web content mining methodology, in view of a Deep Learning Algorithm. The Deep Learning Algorithm gives the interest over BN on the basis that BN is not considered in any learning architecture planning like to propose system. The main objective of this investigation is web document extraction utilizing different grouping algorithm and investigation. This work extricates the data from the web URL. This work shows three classification algorithms, Deep Learning Algorithm, Bayesian Algorithm and BPNN Algorithm. Deep Learning is a capable arrangement of strategies for learning in neural system which is connected like computer vision, speech recognition, and natural language processing and biometrics framework. Deep Learning is one of the simple classification technique and which is utilized for subset of extensive field furthermore Deep Learning has less time for classification. Naive Bayes classifiers are a group of basic probabilistic classifiers in view of applying Bayes hypothesis with concrete independence assumptions between the features. At that point the BPNN algorithm is utilized for classification. Initially training and testing dataset contains more URL. We extract the content presently from the dataset. The

Information Retrieval and Text Mining Technologies for Chemistry.

Science.gov (United States)

Krallinger, Martin; Rabal, Obdulia; Lourenço, Anália; Oyarzabal, Julen; Valencia, Alfonso

2017-06-28

Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.

Information extraction from multi-institutional radiology reports.

Science.gov (United States)

Hassanpour, Saeed; Langlotz, Curtis P

2016-01-01

The radiology report is the most important source of clinical imaging information. It documents critical information about the patient's health and the radiologist's interpretation of medical findings. It also communicates information to the referring physicians and records that information for future clinical and research use. Although efforts to structure some radiology report information through predefined templates are beginning to bear fruit, a large portion of radiology report information is entered in free text. The free text format is a major obstacle for rapid extraction and subsequent use of information by clinicians, researchers, and healthcare information systems. This difficulty is due to the ambiguity and subtlety of natural language, complexity of described images, and variations among different radiologists and healthcare organizations. As a result, radiology reports are used only once by the clinician who ordered the study and rarely are used again for research and data mining. In this work, machine learning techniques and a large multi-institutional radiology report repository are used to extract the semantics of the radiology report and overcome the barriers to the re-use of radiology report information in clinical research and other healthcare applications. We describe a machine learning system to annotate radiology reports and extract report contents according to an information model. This information model covers the majority of clinically significant contents in radiology reports and is applicable to a wide variety of radiology study types. Our automated approach uses discriminative sequence classifiers for named-entity recognition to extract and organize clinically significant terms and phrases consistent with the information model. We evaluated our information extraction system on 150 radiology reports from three major healthcare organizations and compared its results to a commonly used non-machine learning information extraction method. We

Planning maximum extraction of a safety pillar in the Most surface mine

Energy Technology Data Exchange (ETDEWEB)

Helis, P; Hess, L; Kubiznak, K [SHR - Banske Projekty, Teplice (Czechoslovakia)

1990-11-01

Discusses planned coal surface mining in the Most mine in the area of the Hnevin safety pillar with coal reserves amounting to about 7.5 Mt. The following aspects are evaluated: coal reserves and their distribution in the pillar, coal seam thickness and dip angles, water conditions, water influx rates, mechanical properties of the overburden and strata situated in the seam floor, slope stability and hazards of landslides, effects of water influx on landslide hazards, types of bucket wheel excavators used for overburden removal and mining, types of belt conveyors used for mine haulage, stackers, position of mining equipment in the mine. A scheme developed by Banske Projekty Teplice for partial extraction of the safety pillar would result in extraction of 4.5 Mt coal. About 1.7 Mt coal would be left in a safety coal layer about 10.0 m thick situated in the floor in zones with landslide hazards. KU 300 bucket wheel excavators, belt conveyors 1,200 mm wide and ZP 2,500 stackers would be used. 4 refs.

A Mining Algorithm for Extracting Decision Process Data Models

Directory of Open Access Journals (Sweden)

Cristina-Claudia DOLEAN

2011-01-01

Full Text Available The paper introduces an algorithm that mines logs of user interaction with simulation software. It outputs a model that explicitly shows the data perspective of the decision process, namely the Decision Data Model (DDM. In the first part of the paper we focus on how the DDM is extracted by our mining algorithm. We introduce it as pseudo-code and, then, provide explanations and examples of how it actually works. In the second part of the paper, we use a series of small case studies to prove the robustness of the mining algorithm and how it deals with the most common patterns we found in real logs.

WEB STRUCTURE MINING USING PAGERANK, IMPROVED PAGERANK – AN OVERVIEW

Directory of Open Access Journals (Sweden)

V. Lakshmi Praba

2011-03-01

Full Text Available Web Mining is the extraction of interesting and potentially useful patterns and information from Web. It includes Web documents, hyperlinks between documents, and usage logs of web sites. The significant task for web mining can be listed out as Information Retrieval, Information Selection / Extraction, Generalization and Analysis. Web information retrieval tools consider only the text on pages and ignore information in the links. The goal of Web structure mining is to explore structural summary about web. Web structure mining focusing on link information is an important aspect of web data. This paper presents an overview of the PageRank, Improved Page Rank and its working functionality in web structure mining.

A Process Mining Based Service Composition Approach for Mobile Information Systems

Directory of Open Access Journals (Sweden)

Chengxi Huang

2017-01-01

Full Text Available Due to the growing trend in applying big data and cloud computing technologies in information systems, it is becoming an important issue to handle the connection between large scale of data and the associated business processes in the Internet of Everything (IoE environment. Service composition as a widely used phase in system development has some limits when the complexity of relationship among data increases. Considering the expanding scale and the variety of devices in mobile information systems, a process mining based service composition approach is proposed in this paper in order to improve the adaptiveness and efficiency of compositions. Firstly, a preprocessing is conducted to extract existing service execution information from server-side logs. Then process mining algorithms are applied to discover the overall event sequence with preprocessed data. After that, a scene-based service composition is applied to aggregate scene information and relocate services of the system. Finally, a case study that applied the work in mobile medical application proves that the approach is practical and valuable in improving service composition adaptiveness and efficiency.

Comparison of three-stage sequential extraction and toxicity characteristic leaching tests to evaluate metal mobility in mining wastes

International Nuclear Information System (INIS)

Margui, E.; Salvado, V.; Queralt, I.; Hidalgo, M.

2004-01-01

Abandoned mining sites contain residues from ore processing operations that are characterised by high concentrations of heavy metals. The form in which a metal exists strongly influences its mobility and, thus, the effects on the environment. Operational methods of speciation analysis, such as the use of sequential extraction procedures, are commonly applied. In this work, the modified three-stage sequential extraction procedure proposed by the BCR (now the Standards, Measurements and Testing Programme) was applied for the fractionation of Ni, Zn, Pb and Cd in mining wastes from old Pb-Zn mining areas located in the Val d'Aran (NE Spain) and Cartagena (SE Spain). Analyses of the extracts were performed by inductively coupled plasma atomic emission spectrometry and electrothermal atomic absorption spectrometry. The procedure was evaluated by using a certified reference material, BCR-701. The results of the partitioning study indicate that more easily mobilised forms (acid exchangeable) were predominant for Cd and Zn, particularly in the sample from Cartagena. In contrast, the largest amount of lead was associated with the iron and manganese oxide fractions. On the other hand, the applicability of lixiviation tests commonly used to evaluate the leaching of toxic species from landfill disposal (US-EPA Toxicity Characteristic Leaching Procedure and DIN 38414-S4) to mining wastes was also investigated and the obtained results compared with the information on metal mobility derivable from the application of the three-stage sequential extraction procedure

Text mining of web-based medical content

CERN Document Server

Neustein, Amy

2014-01-01

Text Mining of Web-Based Medical Content examines web mining for extracting useful information that can be used for treating and monitoring the healthcare of patients. This work provides methodological approaches to designing mapping tools that exploit data found in social media postings. Specific linguistic features of medical postings are analyzed vis-a-vis available data extraction tools for culling useful information.

DiMeX: A Text Mining System for Mutation-Disease Association Extraction.

Science.gov (United States)

Mahmood, A S M Ashique; Wu, Tsung-Jung; Mazumder, Raja; Vijay-Shanker, K

2016-01-01

The number of published articles describing associations between mutations and diseases is increasing at a fast pace. There is a pressing need to gather such mutation-disease associations into public knowledge bases, but manual curation slows down the growth of such databases. We have addressed this problem by developing a text-mining system (DiMeX) to extract mutation to disease associations from publication abstracts. DiMeX consists of a series of natural language processing modules that preprocess input text and apply syntactic and semantic patterns to extract mutation-disease associations. DiMeX achieves high precision and recall with F-scores of 0.88, 0.91 and 0.89 when evaluated on three different datasets for mutation-disease associations. DiMeX includes a separate component that extracts mutation mentions in text and associates them with genes. This component has been also evaluated on different datasets and shown to achieve state-of-the-art performance. The results indicate that our system outperforms the existing mutation-disease association tools, addressing the low precision problems suffered by most approaches. DiMeX was applied on a large set of abstracts from Medline to extract mutation-disease associations, as well as other relevant information including patient/cohort size and population data. The results are stored in a database that can be queried and downloaded at http://biotm.cis.udel.edu/dimex/. We conclude that this high-throughput text-mining approach has the potential to significantly assist researchers and curators to enrich mutation databases.

Using Open Web APIs in Teaching Web Mining

Science.gov (United States)

Chen, Hsinchun; Li, Xin; Chau, M.; Ho, Yi-Jen; Tseng, Chunju

2009-01-01

With the advent of the World Wide Web, many business applications that utilize data mining and text mining techniques to extract useful business information on the Web have evolved from Web searching to Web mining. It is important for students to acquire knowledge and hands-on experience in Web mining during their education in information systems…

An unsupervised text mining method for relation extraction from biomedical literature.

Directory of Open Access Journals (Sweden)

Changqin Quan

Full Text Available The wealth of interaction information provided in biomedical articles motivated the implementation of text mining approaches to automatically extract biomedical relations. This paper presents an unsupervised method based on pattern clustering and sentence parsing to deal with biomedical relation extraction. Pattern clustering algorithm is based on Polynomial Kernel method, which identifies interaction words from unlabeled data; these interaction words are then used in relation extraction between entity pairs. Dependency parsing and phrase structure parsing are combined for relation extraction. Based on the semi-supervised KNN algorithm, we extend the proposed unsupervised approach to a semi-supervised approach by combining pattern clustering, dependency parsing and phrase structure parsing rules. We evaluated the approaches on two different tasks: (1 Protein-protein interactions extraction, and (2 Gene-suicide association extraction. The evaluation of task (1 on the benchmark dataset (AImed corpus showed that our proposed unsupervised approach outperformed three supervised methods. The three supervised methods are rule based, SVM based, and Kernel based separately. The proposed semi-supervised approach is superior to the existing semi-supervised methods. The evaluation on gene-suicide association extraction on a smaller dataset from Genetic Association Database and a larger dataset from publicly available PubMed showed that the proposed unsupervised and semi-supervised methods achieved much higher F-scores than co-occurrence based method.

Data mining in Cloud Computing

Directory of Open Access Journals (Sweden)

Ruxandra-Ştefania PETRE

2012-10-01

Full Text Available This paper describes how data mining is used in cloud computing. Data Mining is used for extracting potentially useful information from raw data. The integration of data mining techniques into normal day-to-day activities has become common place. Every day people are confronted with targeted advertising, and data mining techniques help businesses to become more efficient by reducing costs.Data mining techniques and applications are very much needed in the cloud computing paradigm. The implementation of data mining techniques through Cloud computing will allow the users to retrieve meaningful information from virtually integrated data warehouse that reduces the costs of infrastructure and storage.

WEB STRUCTURE MINING

Directory of Open Access Journals (Sweden)

CLAUDIA ELENA DINUCĂ

2011-01-01

Full Text Available The World Wide Web became one of the most valuable resources for information retrievals and knowledge discoveries due to the permanent increasing of the amount of data available online. Taking into consideration the web dimension, the users get easily lost in the web’s rich hyper structure. Application of data mining methods is the right solution for knowledge discovery on the Web. The knowledge extracted from the Web can be used to raise the performances for Web information retrievals, question answering and Web based data warehousing. In this paper, I provide an introduction of Web mining categories and I focus on one of these categories: the Web structure mining. Web structure mining, one of three categories of web mining for data, is a tool used to identify the relationship between Web pages linked by information or direct link connection. It offers information about how different pages are linked together to form this huge web. Web Structure Mining finds hidden basic structures and uses hyperlinks for more web applications such as web search.

A New Challenge for Information Mining

Directory of Open Access Journals (Sweden)

Roberto Paiano

2017-07-01

Full Text Available In the field of "Data Exploration" many approaches have been developed to solve the problem of management of big data that are also semantically rich. Nowadays, there is a strong need to support the discovery-oriented applications where data discovery is a highly ad hoc interactive process to support the users by assisting the navigation in the data to find interesting objects. In this work starting by a theoretical data exploration system, where we identified the main features that a data exploration system must have to an efficient exploratory experience, we propose a combination of two data exploration techniques faceted navigation and data mining with the aim to improve the discovery information during exploration. This approach is contextualized better in Information Mining. Information mining, in fact, aims at discovering knowledge, i.e. more general patterns within objects or collections of objects.

Partnership in mining

Energy Technology Data Exchange (ETDEWEB)

Haslam, R

1988-04-01

This paper discusses the benefits resulting from mutual cooperation and information exchange between the UK and USA coal industries. The aim of this cooperation is to promote safe and efficient extraction and profitable use of coal. Advanced mining technologies and mechanisation of the coal mines are some of the results of research cooperation between British Coal and the US Bureau of Mines. In addition, Britain has studied and put into good use the management styles, working practices and pay structure, and mining engineering adopted in the USA.

GROUND DEFORMATION EXTRACTION USING VISIBLE IMAGES AND LIDAR DATA IN MINING AREA

Directory of Open Access Journals (Sweden)

W. Hu

2016-06-01

Full Text Available Recognition and extraction of mining ground deformation can help us understand the deformation process and space distribution, and estimate the deformation laws and trends. This study focuses on the application of ground deformation detection and extraction combining with high resolution visible stereo imagery, LiDAR observation point cloud data and historical data. The DEM in large mining area is generated using high-resolution satellite stereo images, and ground deformation is obtained through time series analysis combined with historical DEM data. Ground deformation caused by mining activities are detected and analyzed to explain the link between the regional ground deformation and local deformation. A district of covering 200 km2 around the West Open Pit Mine in Fushun of Liaoning province, a city located in the Northeast China is chosen as the test area for example. Regional and local ground deformation from 2010 to 2015 time series are detected and extracted with DEMs derived from ZY-3 images and LiDAR point DEMs in the case study. Results show that the mean regional deformation is 7.1 m of rising elevation with RMS 9.6 m. Deformation of rising elevation and deformation of declining elevation couple together in local area. The area of higher elevation variation is 16.3 km2 and the mean rising value is 35.8 m with RMS 15.7 m, while the deformation area of lower elevation variation is 6.8 km2 and the mean declining value is 17.6 m with RMS 9.3 m. Moreover, local large deformation and regional slow deformation couple together, the deformation in local mining activities has expanded to the surrounding area, a large ground fracture with declining elevation has been detected and extracted in the south of West Open Pit Mine, the mean declining elevation of which is 23.1 m and covering about 2.3 km2 till 2015. The results in this paper are preliminary currently; we are making efforts to improve more precision results with

Challenges in service mining : record, check, discover

NARCIS (Netherlands)

Aalst, van der W.M.P.; Daniel, F.; Dolog, P.; Li, Q.

2013-01-01

Process mining aims to discover, monitor and improve real processes by extracting knowledge from event logs abundantly available in today’s information systems. Although process mining has been applied in hundreds of organizations and process mining techniques have been embedded in a variety of

Personal continuous route pattern mining

Institute of Scientific and Technical Information of China (English)

Qian YE; Ling CHEN; Gen-cai CHEN

2009-01-01

In the daily life, people often repeat regular routes in certain periods. In this paper, a mining system is developed to find the continuous route patterns of personal past trips. In order to count the diversity of personal moving status, the mining system employs the adaptive GPS data recording and five data filters to guarantee the clean trips data. The mining system uses a client/server architecture to protect personal privacy and to reduce the computational load. The server conducts the main mining procedure but with insufficient information to recover real personal routes. In order to improve the scalability of sequential pattern mining, a novel pattern mining algorithm, continuous route pattern mining (CRPM), is proposed. This algorithm can tolerate the different disturbances in real routes and extract the frequent patterns. Experimental results based on nine persons' trips show that CRPM can extract more than two times longer route patterns than the traditional route pattern mining algorithms.

76 FR 589 - Proposed Extension of Existing Information Collection; Mine Accident, Injury, Illness, Mine...

Science.gov (United States)

2011-01-05

... requires mine operators and independent contractors to immediately notify MSHA in the event of an accident... provides for uniform information gathering across the mining industry. Section 50.30 requires mine... types. These rates are used to analyze trends and to assess the degree of success of the health and...

MBA: a literature mining system for extracting biomedical abbreviations.

Science.gov (United States)

Xu, Yun; Wang, ZhiHao; Lei, YiMing; Zhao, YuZhong; Xue, Yu

2009-01-09

The exploding growth of the biomedical literature presents many challenges for biological researchers. One such challenge is from the use of a great deal of abbreviations. Extracting abbreviations and their definitions accurately is very helpful to biologists and also facilitates biomedical text analysis. Existing approaches fall into four broad categories: rule based, machine learning based, text alignment based and statistically based. State of the art methods either focus exclusively on acronym-type abbreviations, or could not recognize rare abbreviations. We propose a systematic method to extract abbreviations effectively. At first a scoring method is used to classify the abbreviations into acronym-type and non-acronym-type abbreviations, and then their corresponding definitions are identified by two different methods: text alignment algorithm for the former, statistical method for the latter. A literature mining system MBA was constructed to extract both acronym-type and non-acronym-type abbreviations. An abbreviation-tagged literature corpus, called Medstract gold standard corpus, was used to evaluate the system. MBA achieved a recall of 88% at the precision of 91% on the Medstract gold-standard EVALUATION Corpus. We present a new literature mining system MBA for extracting biomedical abbreviations. Our evaluation demonstrates that the MBA system performs better than the others. It can identify the definition of not only acronym-type abbreviations including a little irregular acronym-type abbreviations (e.g., ), but also non-acronym-type abbreviations (e.g., ).

Recurrent process mining with live event data

NARCIS (Netherlands)

Syamsiyah, A.; van Dongen, B.F.; van der Aalst, W.M.P.; Teniente, E.; Weidlich, M.

2018-01-01

In organizations, process mining activities are typically performed in a recurrent fashion, e.g. once a week, an event log is extracted from the information systems and a process mining tool is used to analyze the process’ characteristics. Typically, process mining tools import the data from a

Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining

Directory of Open Access Journals (Sweden)

Yo-Ping Huang

2008-02-01

Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.

Mining Hesitation Information by Vague Association Rules

Science.gov (United States)

Lu, An; Ng, Wilfred

In many online shopping applications, such as Amazon and eBay, traditional Association Rule (AR) mining has limitations as it only deals with the items that are sold but ignores the items that are almost sold (for example, those items that are put into the basket but not checked out). We say that those almost sold items carry hesitation information, since customers are hesitating to buy them. The hesitation information of items is valuable knowledge for the design of good selling strategies. However, there is no conceptual model that is able to capture different statuses of hesitation information. Herein, we apply and extend vague set theory in the context of AR mining. We define the concepts of attractiveness and hesitation of an item, which represent the overall information of a customer's intent on an item. Based on the two concepts, we propose the notion of Vague Association Rules (VARs). We devise an efficient algorithm to mine the VARs. Our experiments show that our algorithm is efficient and the VARs capture more specific and richer information than do the traditional ARs.

Metal speciation of historic and new copper mine tailings from Repparfjorden, Northern Norway, before and after acid, base and electrodialytic extraction

DEFF Research Database (Denmark)

Pedersen, Kristine B.; Jensen, Pernille Erland; Ottosen, Lisbeth M.

2017-01-01

the new mine tailings. Electrodialysis, based on applying an electric field of low intensity to extract metals from polluted soils/sediments, was designed for acidic and alkaline extraction, and in both cases more Cu was extracted than in the pure acid/base extractions, while maintaining low mobilisation......In Kvalsund, Northern Norway, a permit for submarine mine tailings disposal in Repparfjorden was recently issued for a copper mine with expected operation from 2019. A copper mine was active in the same area in the 1970s and also deposited mine tailings in the fjord. Investigations of the metal...... tailings. Substantial desorption (>40%) for both historic and new mine tailings occurred at pH values below 3 and above 12. These results combined with metal speciation, showing that the binding of Cu in the sediment changes around pH values 3 and 10, indicate potential for extraction of more Cu from...

The viability of business data mining in the sports environment ...

African Journals Online (AJOL)

Data mining can be viewed as the process of extracting previously unknown information from large databases and utilising this information to make crucial business decisions (Simoudis, 1996: 26). This paper considers the viability of using data mining tools and techniques in sports, particularly with regard to mining the ...

Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER)system.

Science.gov (United States)

Pandey, Abhishek; Kreimeyer, Kory; Foster, Matthew; Botsis, Taxiarchis; Dang, Oanh; Ly, Thomas; Wang, Wei; Forshee, Richard

2018-01-01

Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

A STUDY OF TEXT MINING METHODS, APPLICATIONS,AND TECHNIQUES

OpenAIRE

R. Rajamani*1 & S. Saranya2

2017-01-01

Data mining is used to extract useful information from the large amount of data. It is used to implement and solve different types of research problems. The research related areas in data mining are text mining, web mining, image mining, sequential pattern mining, spatial mining, medical mining, multimedia mining, structure mining and graph mining. Text mining also referred to text of data mining, it is also called knowledge discovery in text (KDT) or knowledge of intelligent text analysis. T...

Information extraction system

Science.gov (United States)

Lemmond, Tracy D; Hanley, William G; Guensche, Joseph Wendell; Perry, Nathan C; Nitao, John J; Kidwell, Paul Brandon; Boakye, Kofi Agyeman; Glaser, Ron E; Prenger, Ryan James

2014-05-13

An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

A malware detection scheme based on mining format information.

Science.gov (United States)

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.

Proactive mining system in potosi silver mines : new information from re-evaluation of historical materials regarding the fifth viceroy toledo’s various policies on environment

OpenAIRE

Miyoshi, Emako; Anezaki, Shoji

2016-01-01

In this paper, the proactive mining system introduced by the fifth viceroy, Francisco de Toledo (1569–1581) to the Potosi Silver Mine is clarified on the facts found in the historical documents. Main policies in Toledo’s mining business are followings, the application of mercury-amalgamation to extract silver from ores, the construction of the hydraulic-powered system for silver-ore crashing with cascading uses, the recycle system included the extraction of silver from waste ores and collecti...

Extracting software static defect models using data mining

Directory of Open Access Journals (Sweden)

Ahmed H. Yousef

2015-03-01

Full Text Available Large software projects are subject to quality risks of having defective modules that will cause failures during the software execution. Several software repositories contain source code of large projects that are composed of many modules. These software repositories include data for the software metrics of these modules and the defective state of each module. In this paper, a data mining approach is used to show the attributes that predict the defective state of software modules. Software solution architecture is proposed to convert the extracted knowledge into data mining models that can be integrated with the current software project metrics and bugs data in order to enhance the prediction. The results show better prediction capabilities when all the algorithms are combined using weighted votes. When only one individual algorithm is used, Naïve Bayes algorithm has the best results, then the Neural Network and the Decision Trees algorithms.

Impact of historical mining assessed in soils by kinetic extraction and lead isotopic ratios

International Nuclear Information System (INIS)

Camizuli, E.; Monna, F.; Bermond, A.; Manouchehri, N.; Besançon, S.; Losno, R.; Oort, F. van; Labanowski, J.; Perreira, A.; Chateau, C.; Alibert, P.

2014-01-01

The aim of this study is to estimate the long-term behaviour of trace metals, in two soils differently impacted by past mining. Topsoils from two 1 km 2 zones in the forested Morvan massif (France) were sampled to assess the spatial distribution of Cd, Cu, Pb and Zn. The first zone had been contaminated by historical mining. As expected, it exhibits higher trace-metal levels and greater spatial heterogeneity than the second non-contaminated zone, supposed to represent the local background. One soil profile from each zone was investigated in detail to estimate metal behaviour, and hence, bioavailability. Kinetic extractions were performed using EDTA on three samples: the A horizon from both soil profiles and the B horizon from the contaminated soil. For all three samples, kinetic extractions can be modelled by two first-order reactions. Similar kinetic behaviour was observed for all metals, but more metal was extracted from the contaminated A horizon than from the B horizon. More surprising is the general predominance of the residual fraction over the “labile” and “less labile” pools. Past anthropogenic inputs may have percolated over time through the soil profiles because of acidic pH conditions. Stable organo-metallic complexes may also have been formed over time, reducing metal availability. These processes are not mutually exclusive. After kinetic extraction, the lead isotopic compositions of the samples exhibited different signatures, related to contamination history and intrinsic soil parameters. However, no variation in lead signature was observed during the extraction experiment, demonstrating that the “labile” and “less labile” lead pools do not differ in terms of origin. Even if trace metals resulting from past mining and metallurgy persist in soils long after these activities have ceased, kinetic extractions suggest that metals, at least for these particular forest soils, do not represent a threat for biota. - Highlights: • Trace

Impact of historical mining assessed in soils by kinetic extraction and lead isotopic ratios

Energy Technology Data Exchange (ETDEWEB)

Camizuli, E., E-mail: estelle.camizuli@u-bourgogne.fr [UMR 6298, ArTeHiS, Université de Bourgogne — CNRS — Culture, 6 bd Gabriel, Bat. Gabriel, 21000 Dijon (France); Monna, F. [UMR 6298, ArTeHiS, Université de Bourgogne — CNRS — Culture, 6 bd Gabriel, Bat. Gabriel, 21000 Dijon (France); Bermond, A.; Manouchehri, N.; Besançon, S. [Institut des sciences et industries du vivant et de l' environnement (AgroParisTech), Laboratoire de Chimie Analytique, 16, rue Claude Bernard, 75231 Paris Cedex 05 (France); Losno, R. [UMR 7583, LISA, Universités Paris 7-Paris 12 — CNRS, 61 av. du Gal de Gaulle, 94010 Créteil Cedex (France); Oort, F. van [UR 251, Pessac, Institut National de la Recherche Agronomique, Centre de Versailles-Grignon, RD 10, 78026 Versailles Cedex (France); Labanowski, J. [UMR 7285, IC2MP, Université de Poitiers — CNRS, 4, rue Michel Brunet, 86022 Poitiers (France); Perreira, A. [UMR 6298, ArTeHiS, Université de Bourgogne — CNRS — Culture, 6 bd Gabriel, Bat. Gabriel, 21000 Dijon (France); Chateau, C. [UFR SVTE, Université de Bourgogne, 6 bd Gabriel, Bat. Gabriel, 21000 Dijon (France); Alibert, P. [UMR 6282, Biogeosciences, Université de Bourgogne — CNRS, 6 bd Gabriel, Bat. Gabriel, 21000 Dijon (France)

2014-02-01

The aim of this study is to estimate the long-term behaviour of trace metals, in two soils differently impacted by past mining. Topsoils from two 1 km{sup 2} zones in the forested Morvan massif (France) were sampled to assess the spatial distribution of Cd, Cu, Pb and Zn. The first zone had been contaminated by historical mining. As expected, it exhibits higher trace-metal levels and greater spatial heterogeneity than the second non-contaminated zone, supposed to represent the local background. One soil profile from each zone was investigated in detail to estimate metal behaviour, and hence, bioavailability. Kinetic extractions were performed using EDTA on three samples: the A horizon from both soil profiles and the B horizon from the contaminated soil. For all three samples, kinetic extractions can be modelled by two first-order reactions. Similar kinetic behaviour was observed for all metals, but more metal was extracted from the contaminated A horizon than from the B horizon. More surprising is the general predominance of the residual fraction over the “labile” and “less labile” pools. Past anthropogenic inputs may have percolated over time through the soil profiles because of acidic pH conditions. Stable organo-metallic complexes may also have been formed over time, reducing metal availability. These processes are not mutually exclusive. After kinetic extraction, the lead isotopic compositions of the samples exhibited different signatures, related to contamination history and intrinsic soil parameters. However, no variation in lead signature was observed during the extraction experiment, demonstrating that the “labile” and “less labile” lead pools do not differ in terms of origin. Even if trace metals resulting from past mining and metallurgy persist in soils long after these activities have ceased, kinetic extractions suggest that metals, at least for these particular forest soils, do not represent a threat for biota. - Highlights: • Trace

A Financial Data Mining Model for Extracting Customer Behavior

Directory of Open Access Journals (Sweden)

Mark K.Y. Mak

2011-08-01

Full Text Available Facing the problem of variation and chaotic behavior of customers, the lack of sufficient information is a challenge to many business organizations. Human analysts lacking an understanding of the hidden patterns in business data, thus, can miss corporate business opportunities. In order to embrace all business opportunities, enhance the competitiveness, discovery of hidden knowledge, unexpected patterns and useful rules from large databases have provided a feasible solution for several decades. While there is a wide range of financial analysis products existing in the financial market, how to customize the investment portfolio for the customer is still a challenge to many financial institutions. This paper aims at developing an intelligent Financial Data Mining Model (FDMM for extracting customer behavior in the financial industry, so as to increase the availability of decision support data and hence increase customer satisfaction. The proposed financial model first clusters the customers into several sectors, and then finds the correlation among these sectors. It is noted that better customer segmentation can increase the ability to identify targeted customers, therefore extracting useful rules for specific clusters can provide an insight into customers' buying behavior and marketing implications. To validate the feasibility of the proposed model, a simple dataset is collected from a financial company in Hong Kong. The simulation experiments show that the proposed method not only can improve the workflow of a financial company, but also deepen understanding of investment behavior. Thus, a corporation is able to customize the most suitable products and services for customers on the basis of the rules extracted.

Selective extraction of metals from products of mine acidic water treatment

International Nuclear Information System (INIS)

Andreeva, N.N.; Romanchuk, S.A.; Voronin, N.N.; Demidov, V.D.; Pasynkova, T.A.; Manuilova, O.A.; Ivanova, N.V.

1989-01-01

A study was made on possibility of processing of foam products prepared during flotation purification of mine acidic waters for the purpose of selective extraction of non-ferrous (Co, Ni) and rare earth elements (REE) and their separation from the basic macrocomponent of waters-iron. Optimal conditions of selective metal extraction from foam flotation products are the following: T=333 K, pH=3.0-3.5, ratio of solid and liquid phase - 1:4-1:7, duration of sulfuric acid leaching - 30 min. Rare earth extraction under such conditions equals 87.6-93.0%. The degree of valuable component concentration equals ∼ 10. Rare earths are separated from iron by extraction methods

Symposium 'geology, mining and extractive processing of uranium, with special reference to Europe'

International Nuclear Information System (INIS)

Pietsch, H.B.

1977-01-01

This review of the symposium 'Geology, mining and extractive processing of uranium' gives a survey from the point of view of ore processing rather than exploration. A reason for the uranium consumption assumed is given, and uranium deposits and availability, methods of exploration, and interesting facts on uranium extraction from ores are gone into. (HK) [de

Data mining

CERN Document Server

Gorunescu, Florin

2011-01-01

The knowledge discovery process is as old as Homo sapiens. Until some time ago, this process was solely based on the 'natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since 'knowledge is power'. The goal of this book is to provide, in a friendly way

Environmental Impacts and Health Aspects in the Mining Industry. A Comparative Study of the Mining and Extraction of Uranium, Copper and Gold

International Nuclear Information System (INIS)

Nilsson, Jenny-Ann; Randhem, Johan

2008-01-01

This thesis work has analysed environmental impacts and health aspects in the mining industry of copper, uranium and gold with the aim of determining the relative performance, in a given set of parameters, of the uranium mining industry. A selection of fifteen active mining operations in Australia, Canada, Namibia, South Africa, and the United States of America constitute the subject of this study. The project includes detailed background information about mineral extraction methods, the investigated minerals and the mining operations together with descriptions of the general main health hazards and environmental impacts connected to mining. The mineral operations are investigated in a cradle to gate analysis for the year of activity of 2007 using the economic value of the product at the gate as functional unit. Primary data has been collected from environmental reports, company web pages, national databases and through personal contact with company representatives. The subsequent analysis examines the collected data from a resource consumption, human health and ecological consequences point of view. Using the Life Cycle Impact Assessment methodology of characterisation, primary data of environmental loads have been converted to a synoptic set of environmental impacts. For radiation and tailings issues, a more general approach is used to address the problem. Based on the collected data and the investigated parameters, the results indicate a presumptive relative disadvantageous result for the uranium mining industry in terms of health aspects but an apparent favourable relative result in terms of environmental impacts. Given the prerequisites of this study, it is not feasible to draw any unambiguous conclusions. Inabilities to do this are mainly related to inadequate data availability from mine sites (especially in areas concerning tailings management), and difficulties concerned with the relative valuation of specific performance parameters, in particular radiation

Environmental Impacts and Health Aspects in the Mining Industry. A Comparative Study of the Mining and Extraction of Uranium, Copper and Gold

Energy Technology Data Exchange (ETDEWEB)

Nilsson, Jenny-Ann; Randhem, Johan

2008-07-01

This thesis work has analysed environmental impacts and health aspects in the mining industry of copper, uranium and gold with the aim of determining the relative performance, in a given set of parameters, of the uranium mining industry. A selection of fifteen active mining operations in Australia, Canada, Namibia, South Africa, and the United States of America constitute the subject of this study. The project includes detailed background information about mineral extraction methods, the investigated minerals and the mining operations together with descriptions of the general main health hazards and environmental impacts connected to mining. The mineral operations are investigated in a cradle to gate analysis for the year of activity of 2007 using the economic value of the product at the gate as functional unit. Primary data has been collected from environmental reports, company web pages, national databases and through personal contact with company representatives. The subsequent analysis examines the collected data from a resource consumption, human health and ecological consequences point of view. Using the Life Cycle Impact Assessment methodology of characterisation, primary data of environmental loads have been converted to a synoptic set of environmental impacts. For radiation and tailings issues, a more general approach is used to address the problem. Based on the collected data and the investigated parameters, the results indicate a presumptive relative disadvantageous result for the uranium mining industry in terms of health aspects but an apparent favourable relative result in terms of environmental impacts. Given the prerequisites of this study, it is not feasible to draw any unambiguous conclusions. Inabilities to do this are mainly related to inadequate data availability from mine sites (especially in areas concerning tailings management), and difficulties concerned with the relative valuation of specific performance parameters, in particular radiation

Innovative Extraction Method for a Coal Seam with a Thick Rock-Parting for Supporting Coal Mine Sustainability

Directory of Open Access Journals (Sweden)

Meng Li

2017-10-01

Full Text Available As thick rock partings delay the efficient mining of coal seams and constrain the sustainable development of coal mines, an innovative extraction method for a coal seam with thick rock parting was proposed. The coal seams were divided into different sub-zones according to the thickness of rock parting and then the sub-zones were mined by separately using three mining schemes involving full-seam mining, combined mining using backfill and caving (CMBC, and reducing height mining. Afterwards, the study introduced the basic mechanism and key devices for the CMBC and analysed the working state of the backfill support in detail. Moreover, the method for calculating the length of the backfill zone was proposed to design the length of backfill zone and the influences of four factors (including bulking coefficient of rock parting on the length of the backfill zone were also explored. By taking the No. 22203 panel, Buertai mine, Inner Mongolia, China as an example, the mined coal resource by using the CMBC extraction method will increase by 1.83 × 106 tons and the recovery ratio will rise from 56.2% to 92.4% compared with mining of the 2-2 upper coal seam alone. Moreover, by applying CMBC, a series of environmental and ecological problems caused by rock parting is reduced, which can improve the environment in mined areas. The research can provide technological guidance for mining panels of a coal seam with a thick rock parting and the disposal thereof under similar conditions.

77 FR 58170 - Proposed Renewal of Existing Information Collection; Fire Protection (Underground Coal Mines)

Science.gov (United States)

2012-09-19

... Renewal of Existing Information Collection; Fire Protection (Underground Coal Mines) AGENCY: Mine Safety... INFORMATION: I. Background Fire protection standards for underground coal mines are based on section 311(a) of the Federal Mine Safety and Health Act of 1977 (Mine Act). 30 CFR 75.1100 requires that each coal mine...

Applications of Geomatics in Surface Mining

Science.gov (United States)

Blachowski, Jan; Górniak-Zimroz, Justyna; Milczarek, Wojciech; Pactwa, Katarzyna

2017-12-01

In terms of method of extracting mineral from deposit, mining can be classified into: surface, underground, and borehole mining. Surface mining is a form of mining, in which the soil and the rock covering the mineral deposits are removed. Types of surface mining include mainly strip and open-cast methods, as well as quarrying. Tasks associated with surface mining of minerals include: resource estimation and deposit documentation, mine planning and deposit access, mine plant development, extraction of minerals from deposits, mineral and waste processing, reclamation and reclamation of former mining grounds. At each stage of mining, geodata describing changes occurring in space during the entire life cycle of surface mining project should be taken into consideration, i.e. collected, analysed, processed, examined, distributed. These data result from direct (e.g. geodetic) and indirect (i.e. remote or relative) measurements and observations including airborne and satellite methods, geotechnical, geological and hydrogeological data, and data from other types of sensors, e.g. located on mining equipment and infrastructure, mine plans and maps. Management of such vast sources and sets of geodata, as well as information resulting from processing, integrated analysis and examining such data can be facilitated with geomatic solutions. Geomatics is a discipline of gathering, processing, interpreting, storing and delivering spatially referenced information. Thus, geomatics integrates methods and technologies used for collecting, management, processing, visualizing and distributing spatial data. In other words, its meaning covers practically every method and tool from spatial data acquisition to distribution. In this work examples of application of geomatic solutions in surface mining on representative case studies in various stages of mine operation have been presented. These applications include: prospecting and documenting mineral deposits, assessment of land accessibility

Process mining can be applied to software too!

NARCIS (Netherlands)

Rubin, V.A.; Mitsyuk, A.A.; Lomazova, I.A.; Aalst, van der W.M.P.

2014-01-01

Modern information systems produce tremendous amounts of event data. The area of process mining deals with extracting knowledge from this data. Real-life processes can be effectively discovered, analyzed and optimized with the help of mature process mining techniques. There is a variety of process

USING WEB MINING IN E-COMMERCE APPLICATIONS

Directory of Open Access Journals (Sweden)

Claudia Elena Dinucă

2011-09-01

Full Text Available Nowadays, the web is an important part of our daily life. The web is now the best medium of doing business. Large companies rethink their business strategy using the web to improve business. Business carried on the Web offers the opportunity to potential customers or partners where their products and specific business can be found. Business presence through a company web site has several advantages as it breaks the barrier of time and space compared with the existence of a physical office. To differentiate through the Internet economy, winning companies have realized that e-commerce transactions is more than just buying / selling, appropriate strategies are key to improve competitive power. One effective technique used for this purpose is data mining. Data mining is the process of extracting interesting knowledge from data. Web mining is the use of data mining techniques to extract information from web data. This article presents the three components of web mining: web usage mining, web structure mining and web content mining.

Improving the extraction-and-loading process in the open mining operations

Directory of Open Access Journals (Sweden)

Cheban A. Yu.

2017-09-01

Full Text Available Using the explosions is the main way to prepare solid rocks for the excavation, and that results in the formation of a rock mass of uneven granulometric composition, which makes it impossible to use a conveyor quarry transport without the preliminary large crushing of the rock mass obtained during the explosion. A way to achieve the greatest technical and economic effect is the full conveyorization of quarry transport, what, in this case, ensures the sequenced-flow of transport operations, automation of management and high labor productivity. The extraction-and-loading machines are the determining factor in the performance of mining and transport machines in the technological flow of the quarry. When extracting a blasted rock mass with single-bucket excavators or loaders working in combination with bottom-hole conveyors, one uses self-propelled crushing and reloading units of various designs to grind large individual parts to fractions of conditioning size. The presence of a crushing and reloading unit in the pit-face along with the excavator requires an additional space for its placement, complicates the maneuvering of the equipment in the pit-face, and increases the number of personnel and the cost of maintaining the extraction-and-reloading operations. The article proposes an improved method for carrying out the extraction-and-loading process, as well as the design of extraction-and-grinding unit based on a quarry hydraulic excavator. The design of the proposed unit makes it possible to convert the cyclic process of scooping the rock mass into the continuous process of its loading on the bottom-hole conveyor. Using the extraction-and-grinding unit allows one to combine the processes of excavation, preliminary crushing and loading of the rock mass, which ensures an increase in the efficiency of mining operations.

Multimedia Information Extraction

CERN Document Server

Maybury, Mark T

2012-01-01

The advent of increasingly large consumer collections of audio (e.g., iTunes), imagery (e.g., Flickr), and video (e.g., YouTube) is driving a need not only for multimedia retrieval but also information extraction from and across media. Furthermore, industrial and government collections fuel requirements for stock media access, media preservation, broadcast news retrieval, identity management, and video surveillance.  While significant advances have been made in language processing for information extraction from unstructured multilingual text and extraction of objects from imagery and vid

Economic statistics for the mining and metallurgical industries: 1990. Statistique economique des industries extractives et metallurgiques annee 1990

Energy Technology Data Exchange (ETDEWEB)

Rzonzef, L.

1991-01-01

Provides economic statistics for the Belgian mining and metallurgical industries in 1990. The review is divided into 4 parts: the extractive industries (including an analysis of the coal market and mines, quarries and associated industries); coke and briquette making; metallurgy (i.e. blast furnaces, steel making, rolling mills and manpower and materials consumption in the steel industry); and the extraction of sand from the Belgian continental shelf. 17 tabs.

Geographical Information System Model for Potential Mines Data Management Presentation in Kabupaten Gorontalo

Science.gov (United States)

Roviana, D.; Tajuddin, A.; Edi, S.

2017-03-01

Mining potential in Indonesian is very abundant, ranging from Sabang to Marauke. Kabupaten Gorontalo is one of many places in Indonesia that have different types of minerals and natural resources that can be found in every district. The abundant of mining potential must be balanced with good management and ease of getting information by investors. The current issue is, (1) ways of presenting data/information about potential mines area is still manually (the maps that already capture from satellite image, then printed and attached to information board in the office) it caused the difficulties of getting information; (2) the high cost of maps printing; (3) the difficulties of regency leader (bupati) to obtain information for strategic decision making about mining potential. The goal of this research is to build a model of Geographical Information System that could provide data management of potential mines, so that the investors could easily get information according to their needs. To achieve that goal Research and Development method is used. The result of this research, is a model of Geographical Information System that implemented in an application to presenting data management of mines.

Benchmarking infrastructure for mutation text mining.

Science.gov (United States)

Klein, Artjom; Riazanov, Alexandre; Hindle, Matthew M; Baker, Christopher Jo

2014-02-25

Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption.

Benchmarking infrastructure for mutation text mining

Science.gov (United States)

2014-01-01

Background Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. Results We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. Conclusion We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption. PMID:24568600

Modeling of information on the impact of mining exploitation on bridge objects in BIM

Science.gov (United States)

Bętkowski, Piotr

2018-04-01

The article discusses the advantages of BIM (Building Information Modeling) technology in the management of bridge infrastructure on mining areas. The article shows the problems with information flow in the case of bridge objects located on mining areas and the advantages of proper information management, e.g. the possibility of automatic monitoring of structures, improvement of safety, optimization of maintenance activities, cost reduction of damage removal and preventive actions, improvement of atmosphere for mining exploitation, improvement of the relationship between the manager of the bridge and the mine. Traditional model of managing bridge objects on mining areas has many disadvantages, which are discussed in this article. These disadvantages include among others: duplication of information about the object, lack of correlation in investments due to lack of information flow between bridge manager and mine, limited assessment possibilities of damage propagation on technical condition and construction resistance to mining influences.

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

Science.gov (United States)

Renganathan, Vinaitheerthan

2017-07-01

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

Text mining in livestock animal science: introducing the potential of text mining to animal sciences.

Science.gov (United States)

Sahadevan, S; Hofmann-Apitius, M; Schellander, K; Tesfaye, D; Fluck, J; Friedrich, C M

2012-10-01

In biological research, establishing the prior art by searching and collecting information already present in the domain has equal importance as the experiments done. To obtain a complete overview about the relevant knowledge, researchers mainly rely on 2 major information sources: i) various biological databases and ii) scientific publications in the field. The major difference between the 2 information sources is that information from databases is available, typically well structured and condensed. The information content in scientific literature is vastly unstructured; that is, dispersed among the many different sections of scientific text. The traditional method of information extraction from scientific literature occurs by generating a list of relevant publications in the field of interest and manually scanning these texts for relevant information, which is very time consuming. It is more than likely that in using this "classical" approach the researcher misses some relevant information mentioned in the literature or has to go through biological databases to extract further information. Text mining and named entity recognition methods have already been used in human genomics and related fields as a solution to this problem. These methods can process and extract information from large volumes of scientific text. Text mining is defined as the automatic extraction of previously unknown and potentially useful information from text. Named entity recognition (NER) is defined as the method of identifying named entities (names of real world objects; for example, gene/protein names, drugs, enzymes) in text. In animal sciences, text mining and related methods have been briefly used in murine genomics and associated fields, leaving behind other fields of animal sciences, such as livestock genomics. The aim of this work was to develop an information retrieval platform in the livestock domain focusing on livestock publications and the recognition of relevant data from

Challenges in Managing Information Extraction

Science.gov (United States)

Shen, Warren H.

2009-01-01

This dissertation studies information extraction (IE), the problem of extracting structured information from unstructured data. Example IE tasks include extracting person names from news articles, product information from e-commerce Web pages, street addresses from emails, and names of emerging music bands from blogs. IE is all increasingly…

WEKA-G: Parallel data mining on computational grids

Directory of Open Access Journals (Sweden)

PIMENTA, A.

2009-12-01

Full Text Available Data mining is a technology that can extract useful information from large amounts of data. However, mining a database often requires a high computational power. To resolve this problem, this paper presents a tool (Weka-G, which runs in parallel algorithms used in the mining process data. As the environment for doing so, we use a computational grid by adding several features within a WAN.

Mining residential water and electricity demand data in Southern California to inform demand management strategies

Science.gov (United States)

Cominola, A.; Spang, E. S.; Giuliani, M.; Castelletti, A.; Loge, F. J.; Lund, J. R.

2016-12-01

Demand side management strategies are key to meet future water and energy demands in urban contexts, promote water and energy efficiency in the residential sector, provide customized services and communications to consumers, and reduce utilities' costs. Smart metering technologies allow gathering high temporal and spatial resolution water and energy consumption data and support the development of data-driven models of consumers' behavior. Modelling and predicting resource consumption behavior is essential to inform demand management. Yet, analyzing big, smart metered, databases requires proper data mining and modelling techniques, in order to extract useful information supporting decision makers to spot end uses towards which water and energy efficiency or conservation efforts should be prioritized. In this study, we consider the following research questions: (i) how is it possible to extract representative consumers' personalities out of big smart metered water and energy data? (ii) are residential water and energy consumption profiles interconnected? (iii) Can we design customized water and energy demand management strategies based on the knowledge of water- energy demand profiles and other user-specific psychographic information? To address the above research questions, we contribute a data-driven approach to identify and model routines in water and energy consumers' behavior. We propose a novel customer segmentation procedure based on data-mining techniques. Our procedure consists of three steps: (i) extraction of typical water-energy consumption profiles for each household, (ii) profiles clustering based on their similarity, and (iii) evaluation of the influence of candidate explanatory variables on the identified clusters. The approach is tested onto a dataset of smart metered water and energy consumption data from over 1000 households in South California. Our methodology allows identifying heterogeneous groups of consumers from the studied sample, as well as

Educational Data Mining Application for Estimating Students Performance in Weka Environment

Science.gov (United States)

Gowri, G. Shiyamala; Thulasiram, Ramasamy; Amit Baburao, Mahindra

2017-11-01

Educational data mining (EDM) is a multi-disciplinary research area that examines artificial intelligence, statistical modeling and data mining with the data generated from an educational institution. EDM utilizes computational ways to deal with explicate educational information keeping in mind the end goal to examine educational inquiries. To make a country stand unique among the other nations of the world, the education system has to undergo a major transition by redesigning its framework. The concealed patterns and data from various information repositories can be extracted by adopting the techniques of data mining. In order to summarize the performance of students with their credentials, we scrutinize the exploitation of data mining in the field of academics. Apriori algorithmic procedure is extensively applied to the database of students for a wider classification based on various categorizes. K-means procedure is applied to the same set of databases in order to accumulate them into a specific category. Apriori algorithm deals with mining the rules in order to extract patterns that are similar along with their associations in relation to various set of records. The records can be extracted from academic information repositories. The parameters used in this study gives more importance to psychological traits than academic features. The undesirable student conduct can be clearly witnessed if we make use of information mining frameworks. Thus, the algorithms efficiently prove to profile the students in any educational environment. The ultimate objective of the study is to suspect if a student is prone to violence or not.

Semantics-based information extraction for detecting economic events

NARCIS (Netherlands)

A.C. Hogenboom (Alexander); F. Frasincar (Flavius); K. Schouten (Kim); O. van der Meer

2013-01-01

textabstractAs today's financial markets are sensitive to breaking news on economic events, accurate and timely automatic identification of events in news items is crucial. Unstructured news items originating from many heterogeneous sources have to be mined in order to extract knowledge useful for

When process mining meets bioinformatics

NARCIS (Netherlands)

Jagadeesh Chandra Bose, R.P.; Aalst, van der W.M.P.; Nurcan, S.

2011-01-01

Process mining techniques can be used to extract non-trivial process related knowledge and thus generate interesting insights from event logs. Similarly, bioinformatics aims at increasing the understanding of biological processes through the analysis of information associated with biological

Informing child welfare policy and practice: using knowledge discovery and data mining technology via a dynamic Web site.

Science.gov (United States)

Duncan, Dean F; Kum, Hye-Chung; Weigensberg, Elizabeth Caplick; Flair, Kimberly A; Stewart, C Joy

2008-11-01

Proper management and implementation of an effective child welfare agency requires the constant use of information about the experiences and outcomes of children involved in the system, emphasizing the need for comprehensive, timely, and accurate data. In the past 20 years, there have been many advances in technology that can maximize the potential of administrative data to promote better evaluation and management in the field of child welfare. Specifically, this article discusses the use of knowledge discovery and data mining (KDD), which makes it possible to create longitudinal data files from administrative data sources, extract valuable knowledge, and make the information available via a user-friendly public Web site. This article demonstrates a successful project in North Carolina where knowledge discovery and data mining technology was used to develop a comprehensive set of child welfare outcomes available through a public Web site to facilitate information sharing of child welfare data to improve policy and practice.

Modeling stress–strain state of rock mass under mining of complex-shape extraction pillar

Science.gov (United States)

Fryanov, VN; Pavlova, LD

2018-03-01

Based on the results of numerical modeling of stresses and strains in rock mass, geomechanical parameters of development workings adjacent to coal face operation area are provided for multi-entry preparation and extraction of flat seams with production faces of variable length. The negative effects on the geomechanical situation during the transition from the longwall to shortwall mining in a fully mechanized extraction face are found.

Effect of coal mine dust and clay extracts on the biological activity of the quartz surface

Energy Technology Data Exchange (ETDEWEB)

Stone, V.; Jones, R.; Rollo, K.; Duffin, R.; Donaldson, K.; Brown, D.M. [Napier University, Edinburgh (United Kingdom). School of Life Science

2004-04-01

Modification of the quartz surface by aluminum salts and metallic iron have been shown to reduce the biological activity of quartz. This study aimed to investigate the ability of water soluble extracts of coal mine dust (CMD), low aluminum clays (hectorite and montmorillonite) and high aluminum clays (attapulgite and kaolin) to inhibit the reactivity of the quartz surface. DQ12 induced significant haemolysis of sheep erythrocytes in vitro and inflammation in vivo as indicated by increases in the total cell numbers, neutrophil cell numbers, MIP-2 protein and albumin content of bronchoalveolar lavage (BAL) fluid. Treatment of DQ12 with CMD extract prevented both haemolysis and inflammation. Extracts of the high aluminum clays (kaolin and attapulgite) prevented inhibition of DQ12 induced haemolysis, and the kaolin extract inhibited quartz driven inflammation. DQ12 induced haemolysis by coal mine dust and kaolin extract could be prevented by pre-treatment of the extracts with a cation chellator. Extracts of the low aluminum clays (montmorillonite and hectorite) did not prevent DQ12 induced haemolysis, although the hectorite extract did prevent inflammation. These results suggest that CMD, and clays both low and rich in aluminum, all contain soluble components (possibly cations) capable of masking the reactivity of the quartz surface.

Introduction to the JASIST Special Topic Issue on Web Retrieval and Mining: A Machine Learning Perspective.

Science.gov (United States)

Chen, Hsinchun

2003-01-01

Discusses information retrieval techniques used on the World Wide Web. Topics include machine learning in information extraction; relevance feedback; information filtering and recommendation; text classification and text clustering; Web mining, based on data mining techniques; hyperlink structure; and Web size. (LRW)

Uranium mining and metallurgy library information service under the network environment

International Nuclear Information System (INIS)

Tang Lilei

2012-01-01

This paper analyzes the effect of the network environment on the uranium mining and metallurgy of the information service. Introduces some measures such as strengthening professional characteristic literature resources construction, changing the service mode, building up information navigation, deepening service, meet the individual needs of users, raising librarian's quality, promoting the co-construction and sharing of library information resources, and puts forward the development idea of uranium mining and metallurgy library information service under the network environment. (author)

Mining biomarker information in biomedical literature

Directory of Open Access Journals (Sweden)

Younesi Erfan

2012-12-01

Full Text Available Abstract Background For selection and evaluation of potential biomarkers, inclusion of already published information is of utmost importance. In spite of significant advancements in text- and data-mining techniques, the vast knowledge space of biomarkers in biomedical text has remained unexplored. Existing named entity recognition approaches are not sufficiently selective for the retrieval of biomarker information from the literature. The purpose of this study was to identify textual features that enhance the effectiveness of biomarker information retrieval for different indication areas and diverse end user perspectives. Methods A biomarker terminology was created and further organized into six concept classes. Performance of this terminology was optimized towards balanced selectivity and specificity. The information retrieval performance using the biomarker terminology was evaluated based on various combinations of the terminology's six classes. Further validation of these results was performed on two independent corpora representing two different neurodegenerative diseases. Results The current state of the biomarker terminology contains 119 entity classes supported by 1890 different synonyms. The result of information retrieval shows improved retrieval rate of informative abstracts, which is achieved by including clinical management terms and evidence of gene/protein alterations (e.g. gene/protein expression status or certain polymorphisms in combination with disease and gene name recognition. When additional filtering through other classes (e.g. diagnostic or prognostic methods is applied, the typical high number of unspecific search results is significantly reduced. The evaluation results suggest that this approach enables the automated identification of biomarker information in the literature. A demo version of the search engine SCAIView, including the biomarker retrieval, is made available to the public through http

Mining biological networks from full-text articles.

Science.gov (United States)

Czarnecki, Jan; Shepherd, Adrian J

2014-01-01

The study of biological networks is playing an increasingly important role in the life sciences. Many different kinds of biological system can be modelled as networks; perhaps the most important examples are protein-protein interaction (PPI) networks, metabolic pathways, gene regulatory networks, and signalling networks. Although much useful information is easily accessible in publicly databases, a lot of extra relevant data lies scattered in numerous published papers. Hence there is a pressing need for automated text-mining methods capable of extracting such information from full-text articles. Here we present practical guidelines for constructing a text-mining pipeline from existing code and software components capable of extracting PPI networks from full-text articles. This approach can be adapted to tackle other types of biological network.

Integrated system of production information processing for surface mines

Energy Technology Data Exchange (ETDEWEB)

Li, K.; Wang, S.; Zeng, Z.; Wei, J.; Ren, Z. [China University of Mining and Technology, Xuzhou (China). Dept of Mining Engineering

2000-09-01

Based on the concept of geological statistic, mathematical program, condition simulation, system engineering, and the features and duties of each main department in surface mine production, an integrated system for surface mine production information was studied systematically and developed by using the technology of data warehousing, CAD, object-oriented and system integration, which leads to the systematizing and automating of the information management, data processing, optimization computing and plotting. In this paper, its overall object, system design, structure and functions and some key techniques were described. 2 refs., 3 figs.

CONAN : Text Mining in the Biomedical Domain

NARCIS (Netherlands)

Malik, R.

2006-01-01

This thesis is about Text Mining. Extracting important information from literature. In the last years, the number of biomedical articles and journals is growing exponentially. Scientists might not find the information they want because of the large number of publications. Therefore a system was

Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio

Directory of Open Access Journals (Sweden)

Khashayar Kotobi

2015-03-01

Full Text Available We propose the data mining-informed cognitive radio, which uses non-traditional data sources and data-mining techniques for decision making and improving the performance of a wireless network. To date, the application of information other than wireless channel data in cognitive radios has not been significantly studied. We use a novel dataset (Twitter traffic as an indicator of network load in a wireless channel. Using this dataset, we present and test a series of predictive algorithms that show an improvement in wireless channel utilization over traditional collision-detection algorithms. Our results demonstrate the viability of using these novel datasets to inform and create more efficient cognitive radio networks.

The study on privacy preserving data mining for information security

Science.gov (United States)

Li, Xiaohui

2012-04-01

Privacy preserving data mining have a rapid development in a short year. But it still faces many challenges in the future. Firstly, the level of privacy has different definitions in different filed. Therefore, the measure of privacy preserving data mining technology protecting private information is not the same. So, it's an urgent issue to present a unified privacy definition and measure. Secondly, the most of research in privacy preserving data mining is presently confined to the theory study.

Text mining for adverse drug events: the promise, challenges, and state of the art.

Science.gov (United States)

Harpaz, Rave; Callahan, Alison; Tamang, Suzanne; Low, Yen; Odgers, David; Finlayson, Sam; Jung, Kenneth; LePendu, Paea; Shah, Nigam H

2014-10-01

Text mining is the computational process of extracting meaningful information from large amounts of unstructured text. It is emerging as a tool to leverage underutilized data sources that can improve pharmacovigilance, including the objective of adverse drug event (ADE) detection and assessment. This article provides an overview of recent advances in pharmacovigilance driven by the application of text mining, and discusses several data sources-such as biomedical literature, clinical narratives, product labeling, social media, and Web search logs-that are amenable to text mining for pharmacovigilance. Given the state of the art, it appears text mining can be applied to extract useful ADE-related information from multiple textual sources. Nonetheless, further research is required to address remaining technical challenges associated with the text mining methodologies, and to conclusively determine the relative contribution of each textual source to improving pharmacovigilance.

Process mining applied to the test process of wafer steppers in ASML

NARCIS (Netherlands)

Rozinat, A.; Jong, de I.S.M.; Günther, C.W.; Aalst, van der W.M.P.

2009-01-01

Process mining techniques attempt to extract nontrivial and useful information from event logs. For example, there are many process mining techniques to automatically discover a process model describing the causal dependencies between activities. Several successful case studies have been reported in

Data Mining and Statistics for Decision Making

CERN Document Server

Tufféry, Stéphane

2011-01-01

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized lin

A summary of fish and wildlife information needs to surface mine coal in the United States. Part 1. Fish and wildlife information needs in the federal surface mining permanent regulations. Final report

Energy Technology Data Exchange (ETDEWEB)

1980-01-01

This is part 1 of three part series to assist government agencies and private citizens in determining fish and wildlife information needs for new coal mining operations pursuant to the Surface Mining Control and Reclamation Act of 1977. Part 2 will document status of individual state surface mining regulations as of January 1980 in those states having significant strippable reserves and/or active strip mining operations. It will also provide documentation of fish and wildlife information needs identified in the state regulations of compliance to PL 95-87. Part 3 will be a discussion of the information needed to develop the Fish and Wildlife Plan identified in the Permanent Regulations. The objective of this three part series is to include consideration of fish and wildlife resources in the surface mining process.

Accounting and Financial Data Analysis Data Mining Tools

Directory of Open Access Journals (Sweden)

Diana Elena Codreanu

2011-05-01

Full Text Available Computerized accounting systems in recent years have seen an increase in complexity due to thecompetitive economic environment but with the help of data analysis solutions such as OLAP and DataMining can be a multidimensional data analysis, can detect the fraud and can discover knowledge hidden indata, ensuring such information is useful for decision making within the organization. In the literature thereare many definitions for data mining but all boils down to same idea: the process takes place to extract newinformation from large data collections, information without the aid of data mining tools would be verydifficult to obtain. Information obtained by data mining process has the advantage that only respond to thequestion of what happens but at the same time argue and show why certain things are happening. In this paperwe wish to present advanced techniques for analysis and exploitation of data stored in a multidimensionaldatabase.

Data Mining in Education : A Review on the Knowledge Discovery Perspective

OpenAIRE

Pratiyush Guleria; Manu Sood

2014-01-01

Knowledge Discovery in Databases is the process of finding knowledge in massive amount of data where data mining is the core of this process. Data minin g can be used to mine understandable meaningful patterns from large databases and these patterns ma y then be converted into knowledge.Data mining is t he process of extracting the information and patterns derived by the KDD process which helps in crucial decision-making.Data mining works with data warehou se and...

A Remote Sensing Approach to Environmental Monitoring in a Reclaimed Mine Area

OpenAIRE

Rajchandar Padmanaban; Avit K. Bhowmik; Pedro Cabral

2017-01-01

Padmanaban, R., Bhowmik, A. K., & Cabral, P. (2017). A Remote Sensing Approach to Environmental Monitoring in a Reclaimed Mine Area. ISPRS International Journal of Geo-Information, 6(12), 1-14. [401]. DOI: 10.3390/ijgi6120401 Mining for resources extraction may lead to geological and associated environmental changes due to ground movements, collision with mining cavities, and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may en...

Multiple-Feature Extracting Modules Based Leak Mining System Design

Directory of Open Access Journals (Sweden)

Ying-Chiang Cho

2013-01-01

mining system that is equipped with SQL injection vulnerability detection, by means of an algorithm developed for the web crawler. In addition, we analyze portal sites of the governments of various countries or regions in order to investigate the information leaking status of each site. Subsequently, we analyze the database structure and content of each site, using the data collected. Thus, we make use of practical verification in order to focus on information security and privacy through black-box testing.

Addressing Information Proliferation: Applications of Information Extraction and Text Mining

Science.gov (United States)

Li, Jingjing

2013-01-01

The advent of the Internet and the ever-increasing capacity of storage media have made it easy to store, deliver, and share enormous volumes of data, leading to a proliferation of information on the Web, in online libraries, on news wires, and almost everywhere in our daily lives. Since our ability to process and absorb this information remains…

Applied data mining for business and industry

CERN Document Server

Giudici, Paolo

2009-01-01

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.Features detailed case studies based on applied projects within industry.Incorporates discussion of data mining software, with case studies a...

Model architecture of intelligent data mining oriented urban transportation information

Science.gov (United States)

Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

2007-06-01

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

Uranium in situ leach mining in the United States. Information circular

International Nuclear Information System (INIS)

Larson, W.C.

1978-01-01

This report discusses uranium in situ leach mining in the United States; the purpose of which is to acquaint the reader with an overview of this emerging mining technology. This report is not a technical discussion of the subject matter, but rather should be used as a reference source for information on in situ leaching. An in situ leaching bibliography is included as well as engineering data tables for almost all of the active pilot-scale and commercial uranium in situ leaching operators. These tables represent a first attempt at consolidating operational data in one source, on a regional scale. Additional information is given which discusses the current Bureau of Mines uranium in situ leaching research program. Also included is a listing of various State and Federal permitting agencies, and a summary of the current uranium in situ leaching operators. Finally, a glossary of terms has been added, listing some of the more common terms used in uranium in situ leach mining

Summary of fish and wildlife information needs to surface mine coal in the United States. Part 3. A handbook for meeting fish and wildlife information needs to surface mine coal: OSM Region IV. Final report

Energy Technology Data Exchange (ETDEWEB)

Hinkle, C.R.; Ambrose, R.E.; Wenzel, C.R.

1981-02-01

The report contains information to assist in protecting, enhancing, and reducing impacts to fish and wildlife resources during surface mining of coal. It gives information on the premining, mining, reclamation and compliance phases of surface mining. Methods and sources to obtain information to satisfy state and Federal regulations are presented. This volume is specifically for the states of Nebraska, Iowa, Kansas, Missouri, Oklahoma, Arkansas, Texas and Louisiana.

Environmental stewardship for gold mining in tropical regions

Directory of Open Access Journals (Sweden)

A Isahak

2013-10-01

Full Text Available Mining has gained strong popularity in recent years due to the increase in global demand for metals and other industrial raw material derived from the ground. However, information and good governance regarding activities related to mining is still very much lacking especially in underdeveloped and developing countries in the tropics. In Malaysia, the importance of environmental stewardship in mining is a new phenomenon. The new National Mineral Policy 2 calls for compliance with existing standards and guidelines, stresses on progressive and post mining rehabilitation as well as promotes the gathering and dissemination of information, best mining practices, public disclosure and corporate social responsibility. Our preliminary studies however have shown that its implementation may have been hampered by inadequate legal and administrative structures, lack of freedom of information, physical inaccessibility, lack of information and public participation. In this presentation, the above issues and measures to reduce the impact of mining, particularly that of gold on the environment with a special focus on Malaysia is discussed. These measures include alternative gold extraction methods, appropriate tailing dam construction and management, health risk assessment and risk management, compliance with the Cyanide Code and liberalization of access to information, facilitation of access to justice, the strengthening of legal and administrative structures as well as corporate accountability to the public as part of corporate social responsibility.

Data mining in healthcare: decision making and precision

Directory of Open Access Journals (Sweden)

Ionuţ ŢĂRANU

2016-05-01

Full Text Available The trend of application of data mining in healthcare today is increased because the health sector is rich with information and data mining has become a necessity. Healthcare organizations generate and collect large volumes of information to a daily basis. Use of information technology enables automation of data mining and knowledge that help bring some interesting patterns which means eliminating manual tasks and easy data extraction directly from electronic records, electronic transfer system that will secure medical records, save lives and reduce the cost of medical services as well as enabling early detection of infectious diseases on the basis of advanced data collection. Data mining can enable healthcare organizations to anticipate trends in the patient's medical condition and behaviour proved by analysis of prospects different and by making connections between seemingly unrelated information. The raw data from healthcare organizations are voluminous and heterogeneous. It needs to be collected and stored in organized form and their integration allows the formation unite medical information system. Data mining in health offers unlimited possibilities for analyzing different data models less visible or hidden to common analysis techniques. These patterns can be used by healthcare practitioners to make forecasts, put diagnoses, and set treatments for patients in healthcare organizations.

Text Mining of Supreme Administrative Court Jurisdictions

OpenAIRE

Feinerer, Ingo; Hornik, Kurt

2007-01-01

Within the last decade text mining, i.e., extracting sensitive information from text corpora, has become a major factor in business intelligence. The automated textual analysis of law corpora is highly valuable because of its impact on a company's legal options and the raw amount of available jurisdiction. The study of supreme court jurisdiction and international law corpora is equally important due to its effects on business sectors. In this paper we use text mining methods to investigate Au...

Nuclear expert web mining system: monitoring and analysis of nuclear acceptance by information retrieval and opinion extraction on the Internet

Energy Technology Data Exchange (ETDEWEB)

Reis, Thiago; Barroso, Antonio C.O.; Imakuma, Kengo, E-mail: thiagoreis@usp.b, E-mail: barroso@ipen.b, E-mail: kimakuma@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

This paper presents a research initiative that aims to collect nuclear related information and to analyze opinionated texts by mining the hypertextual data environment and social networks web sites on the Internet. Different from previous approaches that employed traditional statistical techniques, it is being proposed a novel Web Mining approach, built using the concept of Expert Systems, for massive and autonomous data collection and analysis. The initial step has been accomplished, resulting in a framework design that is able to gradually encompass a set of evolving techniques, methods, and theories in such a way that this work will build a platform upon which new researches can be performed more easily by just substituting modules or plugging in new ones. Upon completion it is expected that this research will contribute to the understanding of the population views on nuclear technology and its acceptance. (author)

Nuclear expert web mining system: monitoring and analysis of nuclear acceptance by information retrieval and opinion extraction on the Internet

International Nuclear Information System (INIS)

Reis, Thiago; Barroso, Antonio C.O.; Imakuma, Kengo

2011-01-01

This paper presents a research initiative that aims to collect nuclear related information and to analyze opinionated texts by mining the hypertextual data environment and social networks web sites on the Internet. Different from previous approaches that employed traditional statistical techniques, it is being proposed a novel Web Mining approach, built using the concept of Expert Systems, for massive and autonomous data collection and analysis. The initial step has been accomplished, resulting in a framework design that is able to gradually encompass a set of evolving techniques, methods, and theories in such a way that this work will build a platform upon which new researches can be performed more easily by just substituting modules or plugging in new ones. Upon completion it is expected that this research will contribute to the understanding of the population views on nuclear technology and its acceptance. (author)

Summary of fish and wildlife information needs to surface mine coal in the United States. Part 3. A handbook for meeting fish and wildlife information needs to surface mine coal: OSM Region II. Final report

Energy Technology Data Exchange (ETDEWEB)

Hinkle, C.R.; Ambrose, R.E.; Wenzel, C.R.

1981-02-01

The report contains information to assist in protecting, enhancing, and reducing impacts to fish and wildlife resources during surface mining of coal. It gives information on the premining, mining, reclamation and compliance phases of surface mining. Methods and sources to obtain information to satisfy state and Federal regulations are presented. This volume is specifically for the states of Kentucky, Tennessee, North Carolina, South Carolina, Georgia, Alabama, Mississippi and Florida.

Uranium mining

International Nuclear Information System (INIS)

2008-01-01

Full text: The economic and environmental sustainability of uranium mining has been analysed by Monash University researcher Dr Gavin Mudd in a paper that challenges the perception that uranium mining is an 'infinite quality source' that provides solutions to the world's demand for energy. Dr Mudd says information on the uranium industry touted by politicians and mining companies is not necessarily inaccurate, but it does not tell the whole story, being often just an average snapshot of the costs of uranium mining today without reflecting the escalating costs associated with the process in years to come. 'From a sustainability perspective, it is critical to evaluate accurately the true lifecycle costs of all forms of electricity production, especially with respect to greenhouse emissions, ' he says. 'For nuclear power, a significant proportion of greenhouse emissions are derived from the fuel supply, including uranium mining, milling, enrichment and fuel manufacture.' Dr Mudd found that financial and environmental costs escalate dramatically as the uranium ore is used. The deeper the mining process required to extract the ore, the higher the cost for mining companies, the greater the impact on the environment and the more resources needed to obtain the product. I t is clear that there is a strong sensitivity of energy and water consumption and greenhouse emissions to ore grade, and that ore grades are likely to continue to decline gradually in the medium to long term. These issues are critical to the current debate over nuclear power and greenhouse emissions, especially with respect to ascribing sustainability to such activities as uranium mining and milling. For example, mining at Roxby Downs is responsible for the emission of over one million tonnes of greenhouse gases per year and this could increase to four million tonnes if the mine is expanded.'

DEXTER: Disease-Expression Relation Extraction from Text.

Science.gov (United States)

Gupta, Samir; Dingerdissen, Hayley; Ross, Karen E; Hu, Yu; Wu, Cathy H; Mazumder, Raja; Vijay-Shanker, K

2018-01-01

Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression-disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our text-mined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential expression information for 2024 genes in lung

A COMPARATIVE ANALYSIS OF WEB INFORMATION EXTRACTION TECHNIQUES DEEP LEARNING vs. NAÏVE BAYES vs. BACK PROPAGATION NEURAL NETWORKS IN WEB DOCUMENT EXTRACTION

OpenAIRE

J. Sharmila; A. Subramani

2016-01-01

Web mining related exploration is getting the chance to be more essential these days in view of the reason that a lot of information is overseen through the web. Web utilization is expanding in an uncontrolled way. A particular framework is required for controlling such extensive measure of information in the web space. Web mining is ordered into three noteworthy divisions: Web content mining, web usage mining and web structure mining. Tak-Lam Wong has proposed a web content mining methodolog...

Knowledge discovery: Extracting usable information from large amounts of data

International Nuclear Information System (INIS)

Whiteson, R.

1998-01-01

The threat of nuclear weapons proliferation is a problem of world wide concern. Safeguards are the key to nuclear nonproliferation and data is the key to safeguards. The safeguards community has access to a huge and steadily growing volume of data. The advantages of this data rich environment are obvious, there is a great deal of information which can be utilized. The challenge is to effectively apply proven and developing technologies to find and extract usable information from that data. That information must then be assessed and evaluated to produce the knowledge needed for crucial decision making. Efficient and effective analysis of safeguards data will depend on utilizing technologies to interpret the large, heterogeneous data sets that are available from diverse sources. With an order-of-magnitude increase in the amount of data from a wide variety of technical, textual, and historical sources there is a vital need to apply advanced computer technologies to support all-source analysis. There are techniques of data warehousing, data mining, and data analysis that can provide analysts with tools that will expedite their extracting useable information from the huge amounts of data to which they have access. Computerized tools can aid analysts by integrating heterogeneous data, evaluating diverse data streams, automating retrieval of database information, prioritizing inputs, reconciling conflicting data, doing preliminary interpretations, discovering patterns or trends in data, and automating some of the simpler prescreening tasks that are time consuming and tedious. Thus knowledge discovery technologies can provide a foundation of support for the analyst. Rather than spending time sifting through often irrelevant information, analysts could use their specialized skills in a focused, productive fashion. This would allow them to make their analytical judgments with more confidence and spend more of their time doing what they do best

Relational XES: Data management for process mining

NARCIS (Netherlands)

Dongen, van B.F.; Shabani, S.; Grabis, J.; Sandkuhl, K.

2015-01-01

Information systems log data during the execution of business processes in so called "event logs". Process mining aims to improve business processes by extracting knowledge from event logs. Currently, the de-facto standard for storing and managing event data, XES, is tailored towards sequential

Relational XES : data management for process mining

NARCIS (Netherlands)

Dongen, van B.F.; Shabani, S.

2015-01-01

Information systems log data during the execution of business processes in so called "event logs". Process mining aims to improve business processes by extracting knowledge from event logs. Currently, the de-facto standard for storing and managing event data, XES, is tailored towards sequential

Data mining and business analytics with R

CERN Document Server

Ledolter, Johannes

2013-01-01

Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining

Summary of fish and wildlife information needs to surface mine coal in the United States. Part 3. A handbook for meeting fish and wildlife information needs to surface mine coal: OSM Region I. Final report

Energy Technology Data Exchange (ETDEWEB)

Hinkle, C.R.; Ambrose, R.E.; Wenzel, C.R.

1981-02-01

The report contains information to assist in protecting, enhancing, and reducing impacts to fish and wildlife resources during surface mining of coal. It gives information on the premining, mining, reclamation and compliance phases of surface mining. Methods and sources to obtain information to satisfy state and Federal regulations are presented. This volume is specifically for the states of Maine, Vermont, New Hampshire, Massachusetts, Connecticut, New York, Rhode Island, Pennsylvania, New Jersey, Delaware, Maryland, West Virginia and Virginia.

77 FR 38323 - Proposed Extension of Existing Information Collection; Respirable Coal Mine Dust Sampling

Science.gov (United States)

2012-06-27

... Information Collection; Respirable Coal Mine Dust Sampling AGENCY: Mine Safety and Health Administration... Sampling'' to more accurately reflect the type of information that is collected. Chronic exposure to... dust levels since 1970 and, consequently, the prevalence rate of black lung among coal miners, severe...

Mine railway equipments management information system

Energy Technology Data Exchange (ETDEWEB)

Zhang, X.; Han, K.; Duan, T.; Liu, Z.; Lu, H. [China University of Mining and Technology, Xuzhou (China)

2007-06-15

Based on client/server and browser/server models, the management information system described realized the entire life-cycle management of mine railway equipment which included universal equipment and special equipment in the locomotive depot, track maintenance division, electrical depot and car depot. The system has other online functions such as transmitting reports, graphics management, statistics, searches, graphics wizard and web propaganda. It was applied in Pingdingshan Coal Co. Ltd.'s Railway Transport Department. 5 refs., 4 figs.

KneeTex: an ontology-driven system for information extraction from MRI reports.

Science.gov (United States)

Spasić, Irena; Zhao, Bo; Jones, Christopher B; Button, Kate

2015-01-01

In the realm of knee pathology, magnetic resonance imaging (MRI) has the advantage of visualising all structures within the knee joint, which makes it a valuable tool for increasing diagnostic accuracy and planning surgical treatments. Therefore, clinical narratives found in MRI reports convey valuable diagnostic information. A range of studies have proven the feasibility of natural language processing for information extraction from clinical narratives. However, no study focused specifically on MRI reports in relation to knee pathology, possibly due to the complexity of knee anatomy and a wide range of conditions that may be associated with different anatomical entities. In this paper we describe KneeTex, an information extraction system that operates in this domain. As an ontology-driven information extraction system, KneeTex makes active use of an ontology to strongly guide and constrain text analysis. We used automatic term recognition to facilitate the development of a domain-specific ontology with sufficient detail and coverage for text mining applications. In combination with the ontology, high regularity of the sublanguage used in knee MRI reports allowed us to model its processing by a set of sophisticated lexico-semantic rules with minimal syntactic analysis. The main processing steps involve named entity recognition combined with coordination, enumeration, ambiguity and co-reference resolution, followed by text segmentation. Ontology-based semantic typing is then used to drive the template filling process. We adopted an existing ontology, TRAK (Taxonomy for RehAbilitation of Knee conditions), for use within KneeTex. The original TRAK ontology expanded from 1,292 concepts, 1,720 synonyms and 518 relationship instances to 1,621 concepts, 2,550 synonyms and 560 relationship instances. This provided KneeTex with a very fine-grained lexico-semantic knowledge base, which is highly attuned to the given sublanguage. Information extraction results were evaluated

Summary of fish and wildlife information needs to surface mine coal in the United States. Part 3. A handbook for meeting fish and wildlife information needs to surface mine coal: OSM Region V. Final report

Energy Technology Data Exchange (ETDEWEB)

Hinkle, C.R.; Ambrose, R.E.; Wenzel, C.R.

1981-02-01

This report contains information to assist in protecting, enhancing, and reducing impacts to fish and wildlife resources during surface mining of coal. It gives information on the premining, mining, reclamation and compliance phases of surface mining. This volume is specifically for the states of Washington, Idaho, Montana, North Dakota, South Dakota, Wyoming, Oregon, California, Nevada, Utah, Colorado, Arizona and New Mexico.

A summary of fish and wildlife information needs to surface mine coal in the United States. Part 3. A handbook for meeting fish and wildlife information needs to surface mine coal: OSM Region III. Final report

Energy Technology Data Exchange (ETDEWEB)

Hinkle, C.R.; Ambrose, R.E.; Wenzel, C.R.

1981-02-01

The report contains information to assist in protecting, enhancing, and reducing impacts to fish and wildlife resources during surface mining of coal. It gives information on the premining, mining, reclamation and compliance phases of surface mining. Methods and sources to obtain information to satisfy state and Federal regulations are presented. Considerable emphasis is placed on postmining assistance. This volume is specifically for the states of Minnesota, Wisconsin, Michigan, Illinois, Indiana and Ohio.

INFRASTRUCTURE FOR INTEGRATED DATA ENVIRONMENTS AND ANALYSIS (IIDEA) FOR MINING AND PROCESSING SYSTEMS

Energy Technology Data Exchange (ETDEWEB)

Dessureault, Sean

2007-06-29

Almost all the high-production businesses face a problem of having terabytes of data but very little information is extracted from them. Efforts are being made continuously to bring the raw data into a usable format so that the meaningful information can be inferred. Once the knowledge discovery is done, proper action can be taken accordingly. The data mining and process modeling approach are used in many business sectors to better understand the process interactions within production chains by analyzing huge data repositories. A decade of intense investment in information technology by mining companies as resulted in vast quantities of underutilized data. Other industries have undergone fundamental changes through the innovative application of IT and business intelligence. This project was to undertake the investigation of the tools and techniques that would bring such data mining and requisite business processes to the mining industry. Phase I of this project was to establish the research infrastructure for Phase II and to pilot the tools and techniques through the development of an Energy Consumption Model (ECM) to predict the energy consumption in the material handling processes based on the key input variables like distance, elevation, tons hauled etc. Data mining techniques that can extract meaningful information from a raw data is available. The model developed as part of this research is an example of how energy consumption can be estimated from fundamental data.

A REVIEW ON PREDICTIVE ANALYTICS IN DATA MINING

OpenAIRE

Arumugam.S

2016-01-01

The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is mainly used to make predictions about future events which are unknown. Predictive analytics which uses various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for analyzing the current data and to make predictions about futu...

Ergonomic, psychosocial factors and risks at work in informal mining

Directory of Open Access Journals (Sweden)

Milena Nunes Alves de Sousa

2015-09-01

Full Text Available The goal of this study was to identify ergonomic and psychosocial factors, and risks at informal work in the mining sector of the State of Paraíba, Brazil, from miners' perspective. A cross-sectional and descriptive study was conducted with 371 informal mining workers. They responded two questionnaires for assessing work performed in three dimensions: ergonomic factors; psychosocial factors; and occupational risks. The scores of the items of each dimension were added so that, the higher the score, the lower workers' satisfaction related to the area investigated. The results indicated that noise was common in the working environment (66%. Most workers (54.7% pointed out that the work was too hard and that it required attention and reasoning (85.7%. The workers emphasized the lack of training for working in mining (59.3% and few of them regarded the maintenance of the workplace as a component to prevent lumbago (32.3%. Risk of accidents was pointed out as the factor that needed increased attention in daily work (56.6%. All occupational risks were mentioned, including physical and chemical risks. There was significant correlation between age and occupational risks, indicating that the greater the age, the greater the perception of harmful agents (ρ = -0.23; p < 0.01. In the end, it was observed that, to a greater or lesser degree, all workers perceived ergonomic and psychosocial factors, and risks in informal mining. Length of service and age were the features that interfered significantly with the understanding of those factors and occupational risks.

KID - an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information of enzymes

Directory of Open Access Journals (Sweden)

Schomburg Dietmar

2010-07-01

Full Text Available Abstract Background The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger projects aiming at the analysis, modelling and simulation of biological networks as well as large scale comparison of cellular properties. It is therefore essential that biological knowledge is easily accessible. However, most information is contained in the written literature in an unstructured way, so that methods for the systematic extraction of knowledge directly from the primary literature have to be deployed. Description Here we present a text mining algorithm for the extraction of kinetic information such as KM, Ki, kcat etc. as well as associated information such as enzyme names, EC numbers, ligands, organisms, localisations, pH and temperatures. Using this rule- and dictionary-based approach, it was possible to extract 514,394 kinetic parameters of 13 categories (KM, Ki, kcat, kcat/KM, Vmax, IC50, S0.5, Kd, Ka, t1/2, pI, nH, specific activity, Vmax/KM from about 17 million PubMed abstracts and combine them with other data in the abstract. A manual verification of approx. 1,000 randomly chosen results yielded a recall between 51% and 84% and a precision ranging from 55% to 96%, depending of the category searched. The results were stored in a database and are available as "KID the KInetic Database" via the internet. Conclusions The presented algorithm delivers a considerable amount of information and therefore may aid to accelerate the research and the automated analysis required for today's systems biology approaches. The database obtained by analysing PubMed abstracts may be a valuable help in the field of chemical and biological kinetics. It is completely based upon text mining and therefore complements manually curated databases. The database is available at http://kid.tu-bs.de. The source code of the algorithm is provided under the GNU General Public

Optimizing Transport in Surface Mines, Taking into Account the Quality of Extracted Raw Ore

Directory of Open Access Journals (Sweden)

Marian Šofranko

2012-12-01

Full Text Available This articles concerns problemacy of appropriate separation of transporting mechanisms for mining minerals from individulalteritories. In the following sections of the article a model solution is presented with the use of newly created program for optimizationof transport, taking into account the required quality of extracted raw ore. This process is being done through computing analysisand programming language Borland C++ Builder

Text Mining for Protein Docking.

Directory of Open Access Journals (Sweden)

Varsha D Badal

2015-12-01

Full Text Available The rapidly growing amount of publicly available information from biomedical research is readily accessible on the Internet, providing a powerful resource for predictive biomolecular modeling. The accumulated data on experimentally determined structures transformed structure prediction of proteins and protein complexes. Instead of exploring the enormous search space, predictive tools can simply proceed to the solution based on similarity to the existing, previously determined structures. A similar major paradigm shift is emerging due to the rapidly expanding amount of information, other than experimentally determined structures, which still can be used as constraints in biomolecular structure prediction. Automated text mining has been widely used in recreating protein interaction networks, as well as in detecting small ligand binding sites on protein structures. Combining and expanding these two well-developed areas of research, we applied the text mining to structural modeling of protein-protein complexes (protein docking. Protein docking can be significantly improved when constraints on the docking mode are available. We developed a procedure that retrieves published abstracts on a specific protein-protein interaction and extracts information relevant to docking. The procedure was assessed on protein complexes from Dockground (http://dockground.compbio.ku.edu. The results show that correct information on binding residues can be extracted for about half of the complexes. The amount of irrelevant information was reduced by conceptual analysis of a subset of the retrieved abstracts, based on the bag-of-words (features approach. Support Vector Machine models were trained and validated on the subset. The remaining abstracts were filtered by the best-performing models, which decreased the irrelevant information for ~ 25% complexes in the dataset. The extracted constraints were incorporated in the docking protocol and tested on the Dockground unbound

Methods for Estimating Water Withdrawals for Mining in the United States, 2005

Science.gov (United States)

Lovelace, John K.

2009-01-01

The mining water-use category includes groundwater and surface water that is withdrawn and used for nonfuels and fuels mining. Nonfuels mining includes the extraction of ores, stone, sand, and gravel. Fuels mining includes the extraction of coal, petroleum, and natural gas. Water is used for mineral extraction, quarrying, milling, and other operations directly associated with mining activities. For petroleum and natural gas extraction, water often is injected for secondary oil or gas recovery. Estimates of water withdrawals for mining are needed for water planning and management. This report documents methods used to estimate withdrawals of fresh and saline groundwater and surface water for mining during 2005 for each county and county equivalent in the United States, Puerto Rico, and the U.S. Virgin Islands. Fresh and saline groundwater and surface-water withdrawals during 2005 for nonfuels- and coal-mining operations in each county or county equivalent in the United States, Puerto Rico, and the U.S. Virgin Islands were estimated. Fresh and saline groundwater withdrawals for oil and gas operations in counties of six states also were estimated. Water withdrawals for nonfuels and coal mining were estimated by using mine-production data and water-use coefficients. Production data for nonfuels mining included the mine location and weight (in metric tons) of crude ore, rock, or mineral produced at each mine in the United States, Puerto Rico, and the U.S. Virgin Islands during 2004. Production data for coal mining included the weight, in metric tons, of coal produced in each county or county equivalent during 2004. Water-use coefficients for mined commodities were compiled from various sources including published reports and written communications from U.S. Geological Survey National Water-use Information Program (NWUIP) personnel in several states. Water withdrawals for oil and gas extraction were estimated for six States including California, Colorado, Louisiana, New

Scholarly Information Extraction Is Going to Make a Quantum Leap with PubMed Central (PMC).

Science.gov (United States)

Matthies, Franz; Hahn, Udo

2017-01-01

With the increasing availability of complete full texts (journal articles), rather than their surrogates (titles, abstracts), as resources for text analytics, entirely new opportunities arise for information extraction and text mining from scholarly publications. Yet, we gathered evidence that a range of problems are encountered for full-text processing when biomedical text analytics simply reuse existing NLP pipelines which were developed on the basis of abstracts (rather than full texts). We conducted experiments with four different relation extraction engines all of which were top performers in previous BioNLP Event Extraction Challenges. We found that abstract-trained engines loose up to 6.6% F-score points when run on full-text data. Hence, the reuse of existing abstract-based NLP software in a full-text scenario is considered harmful because of heavy performance losses. Given the current lack of annotated full-text resources to train on, our study quantifies the price paid for this short cut.

Imitating manual curation of text-mined facts in biomedicine.

Directory of Open Access Journals (Sweden)

Raul Rodriguez-Esteban

2006-09-01

Full Text Available Text-mining algorithms make mistakes in extracting facts from natural-language texts. In biomedical applications, which rely on use of text-mined data, it is critical to assess the quality (the probability that the message is correctly extracted of individual facts--to resolve data conflicts and inconsistencies. Using a large set of almost 100,000 manually produced evaluations (most facts were independently reviewed more than once, producing independent evaluations, we implemented and tested a collection of algorithms that mimic human evaluation of facts provided by an automated information-extraction system. The performance of our best automated classifiers closely approached that of our human evaluators (ROC score close to 0.95. Our hypothesis is that, were we to use a larger number of human experts to evaluate any given sentence, we could implement an artificial-intelligence curator that would perform the classification job at least as accurately as an average individual human evaluator. We illustrated our analysis by visualizing the predicted accuracy of the text-mined relations involving the term cocaine.

Greenhouse gas emission from Australian coal mining

International Nuclear Information System (INIS)

Williams, D.

1998-01-01

Since 1997, when the Australian Coal Association (ACA) signed a letter of Intent in respect of the governments Greenhouse Challenge Program, it has encouraged its member companies to participate. Earlier this year, the ACA commissioned an independent scoping study on greenhouse gas emissions in the black coal mining industry This was to provide background information, including identification of information gaps and R and D needs, to guide the formulation of a strategy for the mitigation of greenhouse gas emissions associated with the mining, processing and handling of black coals in Australia. A first step in the process of reducing emission levels is an appreciation of the source, quantity and type of emissions om nine sites. It is shown that greenhouse gas emissions on mine sites come from five sources: energy consumption during mining activities, the coal seam gas liberated due to the extraction process i.e. fugitive emissions, oxidation of carbonaceous wastes, land use, and embodied energy. Also listed are indications of the degree of uncertainty associated with each of the estimates

Accumulation of some metals by legumes and their extractability from acid mine spoils

International Nuclear Information System (INIS)

Taylor, R.W.; Ibeabuchi, I.O.; Sistani, K.R.; Shuford, J.W.

1992-01-01

A greenhouse study was conducted to investigate the growth (dry matter yield) of selected legume cover crops; phytoaccumulation of metals such as Zn, Mn, Pb, Cu, Ni, and Al; the extractability of heavy metals from three different Alabama acid mine spoils. The spoils were amended based on soil test recommended levels of N, P, K, Ca and Mg prior to plant growth. Metals were extracted by three extractants (Mehlich 1, DTPA, and 0.1 M HCl) and values correlated with their accumulation by the selected legumes. Among the cover crops, kobe lespedeza Lespedeza striata (Thung.) Hook and Arn, sericea lespedeza Lespedeza cuneata (Dum.) G. Don, and red clover (Trifolium pratense L.) did not survive the stressful conditions of the spoils. However, cowpea (Vigna unguiculata L.) followed by 'Bragg' soybean Glycine max (L.) Merr. generally produced the highest dry matter yield while accumulating the largest quantity of metals, except Al, from spoils. The extractability of most metals from the spoils was generally in the order of: 0.1 MHCl > DTPA. Mehlich 1 did not extract Pb and 0.1 M HCl did not extract Ni, whereas DTPA extracted all the metals in a small amount relative to HCl and Mehlich 1. All the extractants were quite effective in removing plant-available Zn from the spoils. In general, the extractants' ability to predict plant-available metals depended on the crop species, spoil type, and extractant used. 28 refs., 4 tabs

Mining compressing sequential problems

NARCIS (Netherlands)

Hoang, T.L.; Mörchen, F.; Fradkin, D.; Calders, T.G.K.

2012-01-01

Compression based pattern mining has been successfully applied to many data mining tasks. We propose an approach based on the minimum description length principle to extract sequential patterns that compress a database of sequences well. We show that mining compressing patterns is NP-Hard and

Analysis of gas migration patterns in fractured coal rocks under actual mining conditions

Directory of Open Access Journals (Sweden)

Gao Mingzhong

2017-01-01

Full Text Available Fracture fields in coal rocks are the main channels for gas seepage, migration, and extraction. The development, evolution, and spatial distribution of fractures in coal rocks directly affect the permeability of the coal rock as well as gas migration and flow. In this work, the Ji-15-14120 mining face at the No. 8 Coal Mine of Pingdingshan Tian’an Coal Mining Co. Ltd., Pingdingshan, China, was selected as the test site to develop a full-parameter fracture observation instrument and a dynamic fracture observation technique. The acquired video information of fractures in the walls of the boreholes was vectorized and converted to planarly expanded images on a computer-aided design platform. Based on the relative spatial distances between the openings of the boreholes, simultaneous planar images of isolated fractures in the walls of the boreholes along the mining direction were obtained from the boreholes located at various distances from the mining face. Using this information, a 3-D fracture network under mining conditions was established. The gas migration pattern was calculated using a COMSOL computation platform. The results showed that between 10 hours and 1 day the fracture network controlled the gas-flow, rather than the coal seam itself. After one day, the migration of gas was completely controlled by the fractures. The presence of fractures in the overlying rock enables the gas in coal seam to migrate more easily to the surrounding rocks or extraction tunnels situated relatively far away from the coal rock. These conclusions provide an important theoretical basis for gas extraction.

78 FR 45566 - Agency Information Collection Activities; Submission for OMB Review; Comment Request; Coal Mine...

Science.gov (United States)

2013-07-29

... for OMB Review; Comment Request; Coal Mine Dust Sampling Devices ACTION: Notice. SUMMARY: The... information collection request (ICR) titled, ``Coal Mine Dust Sampling Devices,'' to the Office of Management...) determine the concentration of respirable dust in coal mines. CPDMs must be designed and constructed for...

77 FR 26046 - Proposed Extension of Existing Information Collection; Ground Control for Surface Coal Mines and...

Science.gov (United States)

2012-05-02

... Extension of Existing Information Collection; Ground Control for Surface Coal Mines and Surface Work Areas of Underground Coal Mines AGENCY: Mine Safety and Health Administration, Labor. ACTION: Request for... inspections and investigations in coal or other mines shall be made each year for the purposes of, among other...

Concept and Establishment of the Mine Information System within the CROMAC GIP Project

Directory of Open Access Journals (Sweden)

Zvonko Biljecki

2006-12-01

Full Text Available In order to solve mine problems in the Republic of Croatia, a unique project CROMAC GIP (Croatian Mine Action Centre Geoinformation Project has been initiated significantly increasing the functional quality of the existing Mine Information System (MIS. Since mine problems are closely related to space, geodata are a crucial part of MIS intended for monitoring and planning of demining. Since the moment the Croatian Mine Action Centre was funded till today, the process of demining has progressed. The implementation of a topographic database in accordance with the CROTIS data model and the usage of orthophoto data produced according to the official product specifications can be pointed out in that progress. Usage of such geodata requires a sophisticated information system that enables a simultaneous usage of geodata and other data connected with solving mine problems. In order to reach all goals in demining and to use all advantages of geodata, it was indispensable to upgrade the existing Mine Information System by merging geodata and HCR data and to collect new data according to the standardized procedures, but controlling at the same time the quality and automated procedures of uploading into the system. Apart from being constructed in accordance with the Standard Operative Procedures (SOP, the modernised MIS is also based on generally accepted standards in the field of geoinformation and it is implemented on advanced technology. The core of the system is the Oracle database, and GeoMedia is a WebMap Professional tool on the basis of which the distribution and the work with spatial data is possible on intranet/Internet. In order to achieve full efficiency of the system, it is necessary to provide high quality and updated geodata. In this respect, photogrammetric data are the most efficient solution.

A method for extracting design rationale knowledge based on Text Mining

Directory of Open Access Journals (Sweden)

Liu Jihong

2017-01-01

Full Text Available Capture design rationale (DR knowledge and presenting it to designers by good form, which have great significance for design reuse and design innovation. Since the 1970s design rationality began to develop, many teams have developed their own design rational system. However, the DR acquisition system is not intelligent enough, and it still requires designers to do a lot of operations. In addition, the existing design documents contain a large number of DR knowledge, but it has not been well excavated. Therefore, a method and system are needed to better extract DR knowledge in design documents. We have proposed a DRKH (design rationale knowledge hierarchy model for DR representation. The DRKH model has three layers, respectively as design intent layer, design decision layer and design basis layer. In this paper, we use text mining method to extract DR from design documents and construct DR model. Finally, the welding robot design specification is taken as an example to demonstrate the system interface.

Presentations from the 1992 Coal Mining Impoundment Informational Meeting

Energy Technology Data Exchange (ETDEWEB)

1993-12-31

On May 20 and 21, 1992, the MSHA Coal Mining Impoundment Informational Meeting was held at the National Mine Health and Safety Academy in Beckley, West Virginia. Fifteen presentations were given on key issues involved in the design and construction of dams associated with coal mining. The attendees were told that to improve the consistency among the plan reviewers, engineers from the Denver and Pittsburgh Technical Support Centers meet twice annually to discuss specific technical issues. It was soon discovered that the topics being discussed needed to be shared with anyone involved with coal waste dam design, construction, or inspection. The only way to accomplish that goal was through the issuance of Procedure Instruction Letters. The Letters present a consensus of engineering philosophy that could change over time. They do not present policy or carry the force of law. Currently, thirteen position papers have been disseminated and more will follow as the need arises. The individual paper were not even entered into the database.

Extraction of Eu (III) in monazite from soils containing amang collected from Kampung Gajah ex-mining area

International Nuclear Information System (INIS)

Zaini Hamzah; Nor Monica Ahmad; Ahmad Saat

2011-01-01

Malaysia was once a major tin exporting country. One of the by-products of the tin-mining activities is tin-tailing which known as amang very rich in rare earth elements, especially the lanthanides which are present as a mixture of phosphate minerals, mainly as ilmenite, xenotime and monazite. In this study, Kg Gajah in Kinta Valley occupying the State of Perak was chosen as a study area, since this area used to be the largest mining area in the 60s and 70s. The soil samples were separated using wet separation technique followed by magnetic separation. The monazite was then digested using a mixture of HF/ HNO 3 acids. The digested sample was extracted for its cerium content. The extraction behaviour of cerium in those samples has been investigated as a function of Cyanex 302 concentration in diluents and the time taken to reach the equilibrium. Extractant of bis(2,4,4-trimethylpentyl)-mono-thio phosphinic acid (Cyanex302) in n-heptane was used throughout the analysis. Aqueous phase from extraction was analyzed spectro metrically using Arsenazo (III) while organic phase was subjected to rotavapour followed by analysis by FTIR. The aim of this study is to have the best concentration for Cyanex302 in order to extract as much as possible of Europium and to confirm the transfer of Eu (III) to the Cyanex 302 as an extractant. Result from UV/ VIS shows that 0.7 M is the best concentration of Cyanex 302 for the Eu (III) extraction from samples. Result from FTIR confirmed the structure of Cyanex302 has been replaced by Ce (IV). (author)

Extracting useful information from images

DEFF Research Database (Denmark)

Kucheryavskiy, Sergey

2011-01-01

The paper presents an overview of methods for extracting useful information from digital images. It covers various approaches that utilized different properties of images, like intensity distribution, spatial frequencies content and several others. A few case studies including isotropic and heter......The paper presents an overview of methods for extracting useful information from digital images. It covers various approaches that utilized different properties of images, like intensity distribution, spatial frequencies content and several others. A few case studies including isotropic...

Score Mining Rents in Terms of Investment Attractiveness of Peat Mining

Science.gov (United States)

Alexandrov, Gennady; Yablonev, Alexander

2017-11-01

In this article, as determinants in the system factors underlying the investment attractiveness of the peat industry is considered a rental factor, which predetermines the significant differences and peculiarities of the investment climate in the mining business and, in particular, in the sphere of peat mining. In contrast to modern studies treated the essence and role of rents in the economic mechanism, is proposed for a new approach to solving the problems of its formation. Our approach differs in that it, firstly, adequate rental relations, objectively in extractive industries, secondly, provides consensus in the interests of the owner of peat deposits and entrepreneurs, businesses in these deposits and, thus, thirdly, contributes to the creation of a favourable investment climate in the peat extraction industry. In practical terms, in accordance with the proposed approach, we have proposed specific allocation algorithm of mining rents from the profits of peat extraction enterprises.

Combining complex networks and data mining: Why and how

Science.gov (United States)

Zanin, M.; Papo, D.; Sousa, P. A.; Menasalvas, E.; Nicchi, A.; Kubik, E.; Boccaletti, S.

2016-05-01

The increasing power of computer technology does not dispense with the need to extract meaningful information out of data sets of ever growing size, and indeed typically exacerbates the complexity of this task. To tackle this general problem, two methods have emerged, at chronologically different times, that are now commonly used in the scientific community: data mining and complex network theory. Not only do complex network analysis and data mining share the same general goal, that of extracting information from complex systems to ultimately create a new compact quantifiable representation, but they also often address similar problems too. In the face of that, a surprisingly low number of researchers turn out to resort to both methodologies. One may then be tempted to conclude that these two fields are either largely redundant or totally antithetic. The starting point of this review is that this state of affairs should be put down to contingent rather than conceptual differences, and that these two fields can in fact advantageously be used in a synergistic manner. An overview of both fields is first provided, some fundamental concepts of which are illustrated. A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented. Contexts in which the appropriate integration of complex network metrics can lead to improved classification rates with respect to classical data mining algorithms and, conversely, contexts in which data mining can be used to tackle important issues in complex network theory applications are illustrated. Finally, ways to achieve a tighter integration between complex networks and data mining, and open lines of research are discussed.

Hematite mining in the ancient Americas: Mina Primavera, A 2,000 year old Peruvian mine

Science.gov (United States)

Vaughn, Kevin J.; Grados, Moises Linares; Eerkens, Jelmer W.; Edwards, Matthew J.

2007-12-01

Mina Primavera, a hematite (Fe2O3) mine located in southern Peru, was exploited beginning approximately 2,000 years ago by two Andean civilizations, the Nasca and Wari. Despite the importance of hematite in the material culture of the ancient Americas, few hematite mines have been reported in the New World literature and none have been reported for the Central Andes. An estimated 3,710 tonnes of hematite were extracted from the mine for over 1,400 years at an average rate of 2.65 tonnes per year, suggesting regular and extensive mining prior to Spanish conquest. The hematite was likely used as a pigment for painting pottery, and the mine demonstrates that iron ores were extracted extensively at an early date in the Americas.

Mining for solutions, extracting discord: corporate social responsibility and canadian mining companies in Latin America

OpenAIRE

Stevens, Julie Ann

2009-01-01

While the mining industry generates many benefits to society, the industry has in some cases had a detrimental impact on affected communities. This paradox, manifested in the unequal distribution of costs and benefits amongst stakeholders, has prompted widespread scrutiny of the mining industry. Critique of the industry has questioned whether mining provides an economically, environmentally and socially sustainable model of development. Mining companies are increasingly adopting Corporate Soc...

Application of text mining for customer evaluations in commercial banking

Science.gov (United States)

Tan, Jing; Du, Xiaojiang; Hao, Pengpeng; Wang, Yanbo J.

2015-07-01

Nowadays customer attrition is increasingly serious in commercial banks. To combat this problem roundly, mining customer evaluation texts is as important as mining customer structured data. In order to extract hidden information from customer evaluations, Textual Feature Selection, Classification and Association Rule Mining are necessary techniques. This paper presents all three techniques by using Chinese Word Segmentation, C5.0 and Apriori, and a set of experiments were run based on a collection of real textual data that includes 823 customer evaluations taken from a Chinese commercial bank. Results, consequent solutions, some advice for the commercial bank are given in this paper.

Mining for Social Media: Usage Patterns of Small Businesses

OpenAIRE

Balan, Shilpa; Rege, Janhavi

2017-01-01

Background: Information can now be rapidly exchanged due to social media. Due to its openness, Twitter has generated massive amounts of data. In this paper, we apply data mining and analytics to extract the usage patterns of social media by small businesses. Objectives: The aim of this paper is to describe with an example how data mining can be applied to social media. This paper further examines the impact of social media on small businesses. The Twitter posts related to small businesses are...

Application of the method of optimum increase of Carboniferous gass exploitation for the determination of its extractable amount from the space of attenuated plant of the Paskov Mine

Directory of Open Access Journals (Sweden)

Dragon Vladimír

2003-09-01

Full Text Available A way of optimum extraction increase of Carboniferous gas which can be applied in any mine of the Ostrava-Karviná Mining District (OKMD during the current period of the restructuralisation and mining attenuation.

Point Cloud Classification of Tesserae from Terrestrial Laser Data Combined with Dense Image Matching for Archaeological Information Extraction

Science.gov (United States)

Poux, F.; Neuville, R.; Billen, R.

2017-08-01

Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.

Appraisal of Hydrologic Information Needed in Anticipation of Lignite Mining in Lauderdale County, Tennessee

Science.gov (United States)

Parks, William Scott

1981-01-01

Lignite in western Tennessee occurs as lenses or beds at various stratigraphic horizons in the Coastal Plain sediments of Late Cretaceous and Tertiary age. The occurrence of this lignite has been known for many decades, but not until the energy crisis was it considered an important energy resource. In recent years, several energy companies have conducted extensive exploration programs in western Tennessee, and tremendous reserves of lignite have been found. From available information, Lauderdale County was selected as one of the counties where strip-mining of lignite will most likely occur. Lignite in this county occurs in the Jackson and Cockfield Formations, undivided, of Tertiary age. The hydrology of the county is known only from regional studies and the collection of some site-specific data. Therefore, in anticipation of the future mining of lignite, a plan is needed for obtaining hydrologic and geologic information to adequately define the hydrologic system before mining begins and to monitor the effects of strip-mining once it is begun. For this planning effort, available hydrologic, geologic, land use, and associated data were located and compiled; a summary description of the surface and shallow subsurface hydrologic system was prepared: the need for additional baseline hydrologic information was outlined; and plans to monitor the effects of strip-mining were proposed. This planning approach, although limited to a county area, has transferability to other Coastal Plain areas under consideration for strip-mining of lignite.

SURVEY ON CRIME ANALYSIS AND PREDICTION USING DATA MINING TECHNIQUES

Directory of Open Access Journals (Sweden)

H Benjamin Fredrick David

2017-04-01

Full Text Available Data Mining is the procedure which includes evaluating and examining large pre-existing databases in order to generate new information which may be essential to the organization. The extraction of new information is predicted using the existing datasets. Many approaches for analysis and prediction in data mining had been performed. But, many few efforts has made in the criminology field. Many few have taken efforts for comparing the information all these approaches produce. The police stations and other similar criminal justice agencies hold many large databases of information which can be used to predict or analyze the criminal movements and criminal activity involvement in the society. The criminals can also be predicted based on the crime data. The main aim of this work is to perform a survey on the supervised learning and unsupervised learning techniques that has been applied towards criminal identification. This paper presents the survey on the Crime analysis and crime prediction using several Data Mining techniques.

A summary of fish and wildlife information needs to surface mine coal in the United States. Part 2. The status of state surface mining regulations as of January 1980 and the fish and wildlife information needs. Final report

Energy Technology Data Exchange (ETDEWEB)

1980-01-01

This is part 2 of a three part series to assist government agencies and private citizens in determining fish and wildlife information needs for new coal mining operations pursuant to the Surface Mining Control and Reclamation Act of 1977. This portion documents the status of individual state surface mining regulations as of January 1980 in those states having significant strippable reserves and/or active strip mining operations. It also provides documentation of fish and wildlife information needs identified in the state regulations of compliance to PL 95-87.

Using association rule mining to identify risk factors for early childhood caries.

Science.gov (United States)

Ivančević, Vladimir; Tušek, Ivan; Tušek, Jasmina; Knežević, Marko; Elheshk, Salaheddin; Luković, Ivan

2015-11-01

Early childhood caries (ECC) is a potentially severe disease affecting children all over the world. The available findings are mostly based on a logistic regression model, but data mining, in particular association rule mining, could be used to extract more information from the same data set. ECC data was collected in a cross-sectional analytical study of the 10% sample of preschool children in the South Bačka area (Vojvodina, Serbia). Association rules were extracted from the data by association rule mining. Risk factors were extracted from the highly ranked association rules. Discovered dominant risk factors include male gender, frequent breastfeeding (with other risk factors), high birth order, language, and low body weight at birth. Low health awareness of parents was significantly associated to ECC only in male children. The discovered risk factors are mostly confirmed by the literature, which corroborates the value of the methods. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The design and implementation of web mining in web sites security

Science.gov (United States)

Li, Jian; Zhang, Guo-Yin; Gu, Guo-Chang; Li, Jian-Li

2003-06-01

The backdoor or information leak of Web servers can be detected by using Web Mining techniques on some abnormal Web log and Web application log data. The security of Web servers can be enhanced and the damage of illegal access can be avoided. Firstly, the system for discovering the patterns of information leakages in CGI scripts from Web log data was proposed. Secondly, those patterns for system administrators to modify their codes and enhance their Web site security were provided. The following aspects were described: one is to combine web application log with web log to extract more information, so web data mining could be used to mine web log for discovering the information that firewall and Information Detection System cannot find. Another approach is to propose an operation module of web site to enhance Web site security. In cluster server session, Density-Based Clustering technique is used to reduce resource cost and obtain better efficiency.

Gold mineralogy and extraction

International Nuclear Information System (INIS)

Cashion, J.D.; Brown, L.J.

1998-01-01

Several examples are examined in which Moessbauer spectroscopic analysis of gold mineral samples, treated concentrates and extracted species has provided information not obtainable by competing techniques. Descriptions are given of current work on bacterial oxidation of pyritic ores and on the adsorbed species from gold extracted from cyanide and chloride solutions onto activated carbon and polyurethane foams. The potential benefits for the gold mining industry from Moessbauer studies and some limitations on the use of the technique are also discussed

Gold mineralogy and extraction

Energy Technology Data Exchange (ETDEWEB)

Cashion, J.D.; Brown, L.J. [Monash University, Physics Department (Australia)

1998-12-15

Several examples are examined in which Moessbauer spectroscopic analysis of gold mineral samples, treated concentrates and extracted species has provided information not obtainable by competing techniques. Descriptions are given of current work on bacterial oxidation of pyritic ores and on the adsorbed species from gold extracted from cyanide and chloride solutions onto activated carbon and polyurethane foams. The potential benefits for the gold mining industry from Moessbauer studies and some limitations on the use of the technique are also discussed.

Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

Science.gov (United States)

Khoshahval, S.; Farnaghi, M.; Taleai, M.

2017-09-01

Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

Extraction of Information of Audio-Visual Contents

Directory of Open Access Journals (Sweden)

Carlos Aguilar

2011-10-01

Full Text Available In this article we show how it is possible to use Channel Theory (Barwise and Seligman, 1997 for modeling the process of information extraction realized by audiences of audio-visual contents. To do this, we rely on the concepts pro- posed by Channel Theory and, especially, its treatment of representational systems. We then show how the information that an agent is capable of extracting from the content depends on the number of channels he is able to establish between the content and the set of classifications he is able to discriminate. The agent can endeavor the extraction of information through these channels from the totality of content; however, we discuss the advantages of extracting from its constituents in order to obtain a greater number of informational items that represent it. After showing how the extraction process is endeavored for each channel, we propose a method of representation of all the informative values an agent can obtain from a content using a matrix constituted by the channels the agent is able to establish on the content (source classifications, and the ones he can understand as individual (destination classifications. We finally show how this representation allows reflecting the evolution of the informative items through the evolution of audio-visual content.

Empirical advances with text mining of electronic health records.

Science.gov (United States)

Delespierre, T; Denormandie, P; Bar-Hen, A; Josseran, L

2017-08-22

Korian is a private group specializing in medical accommodations for elderly and dependent people. A professional data warehouse (DWH) established in 2010 hosts all of the residents' data. Inside this information system (IS), clinical narratives (CNs) were used only by medical staff as a residents' care linking tool. The objective of this study was to show that, through qualitative and quantitative textual analysis of a relatively small physiotherapy and well-defined CN sample, it was possible to build a physiotherapy corpus and, through this process, generate a new body of knowledge by adding relevant information to describe the residents' care and lives. Meaningful words were extracted through Standard Query Language (SQL) with the LIKE function and wildcards to perform pattern matching, followed by text mining and a word cloud using R® packages. Another step involved principal components and multiple correspondence analyses, plus clustering on the same residents' sample as well as on other health data using a health model measuring the residents' care level needs. By combining these techniques, physiotherapy treatments could be characterized by a list of constructed keywords, and the residents' health characteristics were built. Feeding defects or health outlier groups could be detected, physiotherapy residents' data and their health data were matched, and differences in health situations showed qualitative and quantitative differences in physiotherapy narratives. This textual experiment using a textual process in two stages showed that text mining and data mining techniques provide convenient tools to improve residents' health and quality of care by adding new, simple, useable data to the electronic health record (EHR). When used with a normalized physiotherapy problem list, text mining through information extraction (IE), named entity recognition (NER) and data mining (DM) can provide a real advantage to describe health care, adding new medical material and

Development and application of a Chinese webpage suicide information mining system (sims).

Science.gov (United States)

Chen, Penglai; Chai, Jing; Zhang, Lu; Wang, Debin

2014-11-01

This study aims at designing and piloting a convenient Chinese webpage suicide information mining system (SIMS) to help search and filter required data from the internet and discover potential features and trends of suicide. SIMS utilizes Microsoft Visual Studio2008, SQL2008 and C# as development tools. It collects webpage data via popular search engines; cleans the data using trained models plus minimum manual help; translates the cleaned texts into quantitative data through models and supervised fuzzy recognition; analyzes and visualizes related variables by self-programmed algorithms. The SIMS developed comprises such functions as suicide news and blogs collection, data filtering, cleaning, extraction and translation, data analysis and presentation. SIMS-mediated mining of one-year webpage revealed that: peak months and hours of web-reported suicide events were June-July and 10-11 am respectively, and the lowest months and hours, September-October and 1-7 am; suicide reports came mostly from Soho, Tecent, Sina etc.; male suicide victims over counted female victims in most sub-regions but southwest China; homes, public places and rented houses were the top three places to commit suicide; poisoning, cutting vein and jumping from building were the most commonly used methods to commit suicide; love disputes, family disputes and mental diseases were the leading causes. SIMS provides a preliminary and supplementary means for monitoring and understanding suicide. It proposes useful aspects as well as tools for analyzing the features and trends of suicide using data derived from Chinese webpages. Yet given the intrinsic "dual nature" of internet-based suicide information and the tremendous difficulties experienced by ourselves and other researchers, there is still a long way to go for us to expand, refine and evaluate the system.

BioCreative Workshops for DOE Genome Sciences: Text Mining for Metagenomics

Energy Technology Data Exchange (ETDEWEB)

Wu, Cathy H. [Univ. of Delaware, Newark, DE (United States). Center for Bioinformatics and Computational Biology; Hirschman, Lynette [The MITRE Corporation, Bedford, MA (United States)

2016-10-29

The objective of this project was to host BioCreative workshops to define and develop text mining tasks to meet the needs of the Genome Sciences community, focusing on metadata information extraction in metagenomics. Following the successful introduction of metagenomics at the BioCreative IV workshop, members of the metagenomics community and BioCreative communities continued discussion to identify candidate topics for a BioCreative metagenomics track for BioCreative V. Of particular interest was the capture of environmental and isolation source information from text. The outcome was to form a “community of interest” around work on the interactive EXTRACT system, which supported interactive tagging of environmental and species data. This experiment is included in the BioCreative V virtual issue of Database. In addition, there was broad participation by members of the metagenomics community in the panels held at BioCreative V, leading to valuable exchanges between the text mining developers and members of the metagenomics research community. These exchanges are reflected in a number of the overview and perspective pieces also being captured in the BioCreative V virtual issue. Overall, this conversation has exposed the metagenomics researchers to the possibilities of text mining, and educated the text mining developers to the specific needs of the metagenomics community.

Rehabilitation materials from surface- coal mines in western U.S.A. III. Relations between elements in mine soil and uptake by plants.

Science.gov (United States)

Severson, R.C.; Gough, L.P.

1984-01-01

Plant uptake of Cd, Co, Cu, Fe, Mn, Ni, Pb and Zn from mine soils was assessed using alfalfa Medicago sativa, sainfoin Onobrychis viciaefolia, smooth brome Bromus inermis, crested wheatgrass Agropyron cristatum, slender wheatgrass A. trachycaulum and intermediate wheatgrass A. intermedium; mine soil (cover-soil and spoil material) samples were collected from rehabilitated areas of 11 western US surface-coal mines in North Dakota, Montana, Wyoming and Colorado. Correlations between metals in plants and DTPA-extractable metals from mine soils were generally not statistically significant and showed no consistent patterns for a single metal or for a single plant species. Metal uptake by plants, relative to amounts in DTPA extracts of mine soil, was positively related to mine soil organic matter content or negatively related to mine soil pH. DTPA-extractable metal levels were significantly correlated with mine soil pH and organic-matter content.-from Authors

Data mining, mining data : energy consumption modelling

Energy Technology Data Exchange (ETDEWEB)

Dessureault, S. [Arizona Univ., Tucson, AZ (United States)

2007-09-15

Most modern mining operations are accumulating large amounts of data on production and business processes. Data, however, provides value only if it can be translated into information that appropriate users can utilize. This paper emphasized that a new technological focus should emerge, notably how to concentrate data into information; analyze information sufficiently to become knowledge; and, act on that knowledge. Researchers at the Mining Information Systems and Operations Management (MISOM) laboratory at the University of Arizona have created a method to transform data into action. The data-to-action approach was exercised in the development of an energy consumption model (ECM), in partnership with a major US-based copper mining company, 2 software companies, and the MISOM laboratory. The approach begins by integrating several key data sources using data warehousing techniques, and increasing the existing level of integration and data cleaning. An online analytical processing (OLAP) cube was also created to investigate the data and identify a subset of several million records. Data mining algorithms were applied using the information that was isolated by the OLAP cube. The data mining results showed that traditional cost drivers of energy consumption are poor predictors. A comparison was made between traditional methods of predicting energy consumption and the prediction formed using data mining. Traditionally, in the mines for which data were available, monthly averages of tons and distance are used to predict diesel fuel consumption. However, this article showed that new information technology can be used to incorporate many more variables into the budgeting process, resulting in more accurate predictions. The ECM helped mine planners improve the prediction of energy use through more data integration, measure development, and workflow analysis. 5 refs., 11 figs.

Data Processing and Text Mining Technologies on Electronic Medical Records: A Review

Directory of Open Access Journals (Sweden)

Wencheng Sun

2018-01-01

Full Text Available Currently, medical institutes generally use EMR to record patient’s condition, including diagnostic information, procedures performed, and treatment results. EMR has been recognized as a valuable resource for large-scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy, and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation, and data reduction. For semistructured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (named-entity recognition and RE (relation extraction. This paper focuses on the process of EMR processing and emphatically analyzes the key techniques. In addition, we make an in-depth study on the applications developed based on text mining together with the open challenges and research issues for future work.

36 CFR 6.7 - Mining wastes.

Science.gov (United States)

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Mining wastes. 6.7 Section 6... DISPOSAL SITES IN UNITS OF THE NATIONAL PARK SYSTEM § 6.7 Mining wastes. (a) Solid waste from mining includes but is not limited to mining overburden, mining byproducts, solid waste from the extraction...

A New Framework for Textual Information Mining over Parse Trees. CRESST Report 805

Science.gov (United States)

Mousavi, Hamid; Kerr, Deirdre; Iseli, Markus R.

2011-01-01

Textual information mining is a challenging problem that has resulted in the creation of many different rule-based linguistic query languages. However, these languages generally are not optimized for the purpose of text mining. In other words, they usually consider queries as individuals and only return raw results for each query. Moreover they…

A sequential approach to control gas for the extraction of multi-gassy coal seams from traditional gas well drainage to mining-induced stress relief

International Nuclear Information System (INIS)

Kong, Shengli; Cheng, Yuanping; Ren, Ting; Liu, Hongyong

2014-01-01

Highlights: • The gas reservoirs characteristics are measured and analyzed. • A sequential approach to control gas of multi-gassy coal seams is proposed. • The design of gas drainage wells has been improved. • The utilization ways of different concentrations of gas production are shown. - Abstract: As coal resources become exhausted in shallow mines, mining operations will inevitably progress from shallow depth to deep and gassy seams due to increased demands for more coal products. However, during the extraction process of deeper and gassier coal seams, new challenges to current gas control methods have emerged, these include the conflict between the coal mine safety and the economic benefits, the difficulties in reservoirs improvement, as well as the imbalance between pre-gas drainage, roadway development and coal mining. To solve these problems, a sequential approach is introduced in this paper. Three fundamental principles are proposed: the mining-induced stress relief effect of the first-mined coalbed should be sufficient to improve the permeability of the others; the coal resource of the first-mined seams must be abundant to guarantee the economic benefits; the arrangement of the vertical wells must fit the underground mining panel. Tunlan coal mine is taken as a typical example to demonstrate the effectiveness of this approach. The approach of integrating surface coalbed methane (CBM) exploitation with underground gas control technologies brings three major benefits: the improvement of underground coal mining safety, the implementation of CBM extraction, and the reduction of greenhouse gas emissions. This practice could be used as a valuable example for other coal mines having similar geological conditions

Scenario Customization for Information Extraction

National Research Council Canada - National Science Library

Yangarber, Roman

2001-01-01

Information Extraction (IE) is an emerging NLP technology, whose function is to process unstructured, natural language text, to locate specific pieces of information, or facts, in the text, and to use these facts to fill a database...

77 FR 25205 - Proposed Extension of Existing Information Collection; Roof Control Plans for Underground Coal Mines

Science.gov (United States)

2012-04-27

... collections of information in accordance with the Paperwork Reduction Act of 1995. This program helps to assure that requested data can be provided in the desired format, reporting burden (time and financial... Information Collection; Roof Control Plans for Underground Coal Mines AGENCY: Mine Safety and Health...

Can we replace curation with information extraction software?

Science.gov (United States)

Karp, Peter D

2016-01-01

Can we use programs for automated or semi-automated information extraction from scientific texts as practical alternatives to professional curation? I show that error rates of current information extraction programs are too high to replace professional curation today. Furthermore, current IEP programs extract single narrow slivers of information, such as individual protein interactions; they cannot extract the large breadth of information extracted by professional curators for databases such as EcoCyc. They also cannot arbitrate among conflicting statements in the literature as curators can. Therefore, funding agencies should not hobble the curation efforts of existing databases on the assumption that a problem that has stymied Artificial Intelligence researchers for more than 60 years will be solved tomorrow. Semi-automated extraction techniques appear to have significantly more potential based on a review of recent tools that enhance curator productivity. But a full cost-benefit analysis for these tools is lacking. Without such analysis it is possible to expend significant effort developing information-extraction tools that automate small parts of the overall curation workflow without achieving a significant decrease in curation costs.Database URL. © The Author(s) 2016. Published by Oxford University Press.

Transductive Pattern Learning for Information Extraction

National Research Council Canada - National Science Library

McLernon, Brian; Kushmerick, Nicholas

2006-01-01

.... We present TPLEX, a semi-supervised learning algorithm for information extraction that can acquire extraction patterns from a small amount of labelled text in conjunction with a large amount of unlabelled text...

Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities.

Science.gov (United States)

Abraham, Paul E; Giannone, Richard J; Xiong, Weili; Hettich, Robert L

2014-06-17

Contemporary microbial ecology studies usually employ one or more "omics" approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other "meta-omic" approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool. Copyright © 2014 John Wiley & Sons, Inc.

Microarray data and gene expression statistics for Saccharomyces cerevisiae exposed to simulated asbestos mine drainage

Directory of Open Access Journals (Sweden)

Heather E. Driscoll

2017-08-01

Full Text Available Here we describe microarray expression data (raw and normalized, experimental metadata, and gene-level data with expression statistics from Saccharomyces cerevisiae exposed to simulated asbestos mine drainage from the Vermont Asbestos Group (VAG Mine on Belvidere Mountain in northern Vermont, USA. For nearly 100 years (between the late 1890s and 1993, chrysotile asbestos fibers were extracted from serpentinized ultramafic rock at the VAG Mine for use in construction and manufacturing industries. Studies have shown that water courses and streambeds nearby have become contaminated with asbestos mine tailings runoff, including elevated levels of magnesium, nickel, chromium, and arsenic, elevated pH, and chrysotile asbestos-laden mine tailings, due to leaching and gradual erosion of massive piles of mine waste covering approximately 9 km2. We exposed yeast to simulated VAG Mine tailings leachate to help gain insight on how eukaryotic cells exposed to VAG Mine drainage may respond in the mine environment. Affymetrix GeneChip® Yeast Genome 2.0 Arrays were utilized to assess gene expression after 24-h exposure to simulated VAG Mine tailings runoff. The chemistry of mine-tailings leachate, mine-tailings leachate plus yeast extract peptone dextrose media, and control yeast extract peptone dextrose media is also reported. To our knowledge this is the first dataset to assess global gene expression patterns in a eukaryotic model system simulating asbestos mine tailings runoff exposure. Raw and normalized gene expression data are accessible through the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO Database Series GSE89875 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89875.

PKDE4J: Entity and relation extraction for public knowledge discovery.

Science.gov (United States)

Song, Min; Kim, Won Chul; Lee, Dahee; Heo, Go Eun; Kang, Keun Young

2015-10-01

Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means of information search, knowledge discovery, and hypothesis generation. Most previous studies have primarily focused on the design and performance improvement of either named entity recognition or relation extraction. In this paper, we present PKDE4J, a comprehensive text-mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Starting with the Stanford CoreNLP, we developed the system to cope with multiple types of entities and relations. The system also has fairly good performance in terms of accuracy as well as the ability to configure text-processing components. We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction. Copyright © 2015 Elsevier Inc. All rights reserved.

Automated data mining: an innovative and efficient web-based approach to maintaining resident case logs.

Science.gov (United States)

Bhattacharya, Pratik; Van Stavern, Renee; Madhavan, Ramesh

2010-12-01

Use of resident case logs has been considered by the Residency Review Committee for Neurology of the Accreditation Council for Graduate Medical Education (ACGME). This study explores the effectiveness of a data-mining program for creating resident logs and compares the results to a manual data-entry system. Other potential applications of data mining to enhancing resident education are also explored. Patient notes dictated by residents were extracted from the Hospital Information System and analyzed using an unstructured mining program. History, examination and ICD codes were obtained and compared to the existing manual log. The automated data History, examination, and ICD codes were gathered for a 30-day period and compared to manual case logs. The automated method extracted all resident dictations with the dates of encounter and transcription. The automated data-miner processed information from all 19 residents, while only 4 residents logged manually. The manual method identified only broad categories of diseases; the major categories were stroke or vascular disorder 53 (27.6%), epilepsy 28 (14.7%), and pain syndromes 26 (13.5%). In the automated method, epilepsy 114 (21.1%), cerebral atherosclerosis 114 (21.1%), and headache 105 (19.4%) were the most frequent primary diagnoses, and headache 89 (16.5%), seizures 94 (17.4%), and low back pain 47 (9%) were the most common chief complaints. More detailed patient information such as tobacco use 227 (42%), alcohol use 205 (38%), and drug use 38 (7%) were extracted by the data-mining method. Manual case logs are time-consuming, provide limited information, and may be unpopular with residents. Data mining is a time-effective tool that may aid in the assessment of resident experience or the ACGME core competencies or in resident clinical research. More study of this method in larger numbers of residency programs is needed.

Using Local Grammar for Entity Extraction from Clinical Reports

Directory of Open Access Journals (Sweden)

Aicha Ghoulam

2015-06-01

Full Text Available Information Extraction (IE is a natural language processing (NLP task whose aim is to analyze texts written in natural language to extract structured and useful information such as named entities and semantic relations linking these entities. Information extraction is an important task for many applications such as bio-medical literature mining, customer care, community websites, and personal information management. The increasing information available in patient clinical reports is difficult to access. As it is often in an unstructured text form, doctors need tools to enable them access to this information and the ability to search it. Hence, a system for extracting this information in a structured form can benefits healthcare professionals. The work presented in this paper uses a local grammar approach to extract medical named entities from French patient clinical reports. Experimental results show that the proposed approach achieved an F-Measure of 90. 06%.

Utilizing a Value of Information Framework to Improve Ore Collection and Classification Procedures

National Research Council Canada - National Science Library

Phillips, Julia A

2006-01-01

.... We use a value of information framework (VOI) to consider the economic feasibility of a mine purchasing additional information on extracted ore type to reduce the uncertainty of extracted ore grade quality...

Sentiment topic mining based on comment tags

Science.gov (United States)

Zhang, Daohai; Liu, Xue; Li, Juan; Fan, Mingyue

2018-03-01

With the development of e-commerce, various comments based on tags are generated, how to extract valuable information from these comment tags has become an important content of business management decisions. This study takes HUAWEI mobile phone tags as an example using the sentiment analysis and topic LDA mining method. The first step is data preprocessing and classification of comment tag topic mining. And then make the sentiment classification for comment tags. Finally, mine the comments again and analyze the emotional theme distribution under different sentiment classification. The results show that HUAWEI mobile phone has a good user experience in terms of fluency, cost performance, appearance, etc. Meanwhile, it should pay more attention to independent research and development, product design and development. In addition, battery and speed performance should be enhanced.

Safety Psychology Applicating on Coal Mine Safety Management Based on Information System

Science.gov (United States)

Hou, Baoyue; Chen, Fei

In recent years, with the increase of intensity of coal mining, a great number of major accidents happen frequently, the reason mostly due to human factors, but human's unsafely behavior are affected by insecurity mental control. In order to reduce accidents, and to improve safety management, with the help of application security psychology, we analyse the cause of insecurity psychological factors from human perception, from personality development, from motivation incentive, from reward and punishment mechanism, and from security aspects of mental training , and put forward countermeasures to promote coal mine safety production,and to provide information for coal mining to improve the level of safety management.

Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

Science.gov (United States)

Elayavilli, Ravikumar Komandur; Liu, Hongfang

2016-01-01

Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological

SparkText: Biomedical Text Mining on Big Data Framework.

Science.gov (United States)

Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Information Extraction and Interpretation Analysis of Mineral Potential Targets Based on ETM+ Data and GIS technology: A Case Study of Copper and Gold Mineralization in Burma

International Nuclear Information System (INIS)

Wenhui, Du; Yongqing, Chen; Nana, Guo; Yinglong, Hao; Pengfei, Zhao; Gongwen, Wang

2014-01-01

Mineralization-alteration and structure information extraction plays important roles in mineral resource prospecting and assessment using remote sensing data and the Geographical Information System (GIS) technology. Choosing copper and gold mines in Burma as example, the authors adopt band ratio, threshold segmentation and principal component analysis (PCA) to extract the hydroxyl alteration information using ETM+ remote sensing images. Digital elevation model (DEM) (30m spatial resolution) and ETM+ data was used to extract linear and circular faults that are associated with copper and gold mineralization. Combining geological data and the above information, the weights of evidence method and the C-A fractal model was used to integrate and identify the ore-forming favourable zones in this area. Research results show that the high grade potential targets are located with the known copper and gold deposits, and the integrated information can be used to the next exploration for the mineral resource decision-making

Web Mining

Science.gov (United States)

Fürnkranz, Johannes

The World-Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to Web data and documents. This chapter provides a brief overview of web mining techniques and research areas, most notably hypertext classification, wrapper induction, recommender systems and web usage mining.

Text mining by Tsallis entropy

Science.gov (United States)

Jamaati, Maryam; Mehri, Ali

2018-01-01

Long-range correlations between the elements of natural languages enable them to convey very complex information. Complex structure of human language, as a manifestation of natural languages, motivates us to apply nonextensive statistical mechanics in text mining. Tsallis entropy appropriately ranks the terms' relevance to document subject, taking advantage of their spatial correlation length. We apply this statistical concept as a new powerful word ranking metric in order to extract keywords of a single document. We carry out an experimental evaluation, which shows capability of the presented method in keyword extraction. We find that, Tsallis entropy has reliable word ranking performance, at the same level of the best previous ranking methods.

Information Extraction From Chemical Patents

Directory of Open Access Journals (Sweden)

Sandra Bergmann

2012-01-01

Full Text Available The development of new chemicals or pharmaceuticals is preceded by an indepth analysis of published patents in this field. This information retrieval is a costly and time inefficient step when done by a human reader, yet it is mandatory for potential success of an investment. The goal of the research project UIMA-HPC is to automate and hence speed-up the process of knowledge mining about patents. Multi-threaded analysis engines, developed according to UIMA (Unstructured Information Management Architecture standards, process texts and images in thousands of documents in parallel. UNICORE (UNiform Interface to COmputing Resources workflow control structures make it possible to dynamically allocate resources for every given task to gain best cpu-time/realtime ratios in an HPC environment.

Multiple-feature extracting modules based leak mining system design.

Science.gov (United States)

Cho, Ying-Chiang; Pan, Jen-Yi

2013-01-01

Over the years, human dependence on the Internet has increased dramatically. A large amount of information is placed on the Internet and retrieved from it daily, which makes web security in terms of online information a major concern. In recent years, the most problematic issues in web security have been e-mail address leakage and SQL injection attacks. There are many possible causes of information leakage, such as inadequate precautions during the programming process, which lead to the leakage of e-mail addresses entered online or insufficient protection of database information, a loophole that enables malicious users to steal online content. In this paper, we implement a crawler mining system that is equipped with SQL injection vulnerability detection, by means of an algorithm developed for the web crawler. In addition, we analyze portal sites of the governments of various countries or regions in order to investigate the information leaking status of each site. Subsequently, we analyze the database structure and content of each site, using the data collected. Thus, we make use of practical verification in order to focus on information security and privacy through black-box testing.

Heavy metal concentration in forage grasses and extractability from some acid mine spoils

Energy Technology Data Exchange (ETDEWEB)

Taylor, R.W.; Ibeabuchi, I.O.; Sistani, K.R.; Shuford, J.W. (Alabama A and M University, Normal (United States). Department of Plant and Soil Science)

1993-06-01

Laboratory and greenhouse studies were conducted on several forage grasses, bermudagrass ([ital Cynodon dactylon]), creeping red fescue ([ital Festuca rubra]), Kentucky 31-tall fescue ([ital Festuca arundinacea]), oat ([ital Avena sativa]), orchardgrass ([ital Dactylis glomerata]), perennial ryegrass ([ital Lolium perenne]), sorghum ([ital Sorghum bicolor]), triticale (X. [ital triticosecale Wittmack]), and winter wheat ([ital Triticum aestivum]) grown on three Alabama acid mine spoils to study heavy metal accumulation, dry matter yield and spoil metal extractability by three chemical extractants (Mehlich 1, DTPA, and 0.1 M HCl). Heavy metals removed by these extractants were correlated with their accumulation by several forage grasses. Among the forages tested, creeping red fescue did not survive the stressful conditions of any of the spoils, while orchard grass and Kentucky 31-tall fescue did not grow in Mulberry spoil. Sorghum followed by bermudagrass generally produced the highest dry matter yield. However, the high yielding bermudagrass was most effective in accumulating high tissue levels of Mn and Zn from all spoils (compared to the other grasses) but did not remove Ni. On the average, higher levels of metals were extracted from spoils in the order of 0.1 M HCl[gt] Mehlich 1[gt] DTPA. However, DTPA extracted all the metals from spoils while Mehlich 1 did not extract Pb and 0.1 M HCl did not extract detectable levels of Ni. All of the extractants were quite effective in determining plant available Zn from the spoils. For the other metals, the effective determination of plant availability depended on the crop, the extractant, and the metal in concert. 20 refs., 6 tabs.

Mining multi-dimensional data for decision support

Energy Technology Data Exchange (ETDEWEB)

Donato, J.M.; Schryver, J.C.; Hinkel, G.C.; Schmoyer, R.L. Jr. [Oak Ridge National Lab., TN (United States); Grady, N.W.; Leuze, M.R. [Oak Ridge National Lab., TN (United States)]|[Joint Inst. for Computational Science, Knoxville, TN (United States)

1998-06-01

While it is widely recognized that data can be a valuable resource for any organization, extracting information contained within the data is often a difficult problem. Attempts to obtain information from data may be limited by legacy data storage formats, lack of expert knowledge about the data, difficulty in viewing the data, or the volume of data needing to be processed. The rapidly developing field of Data Mining or Knowledge Data Discovery is a blending of Artificial Intelligence, Statistics, and Human-Computer Interaction. Sophisticated data navigation tools to obtain the information needed for decision support do not yet exist. Each data mining task requires a custom solution that depends upon the character and quantity of the data. This paper presents a two-stage approach for handling the prediction of personal bankruptcy using credit card account data, combining decision tree and artificial neural network technologies. Topics to be discussed include the pre-processing of data, including data cleansing, the filtering of data for pertinent records, and the reduction of data for attributes contributing to the prediction of bankruptcy, and the two steps in the mining process itself.

Utilization of Integrated Geophysical Techniques to Delineate the Extraction of Mining Bench of Ornamental Rocks (Marble

Directory of Open Access Journals (Sweden)

Julián Martínez

2017-12-01

Full Text Available Low yields in ornamental rock mining remain one of the most important problems in this industry. This fact is usually associated with the presence of anisotropies in the rock, which makes it difficult to extract the blocks. An optimised planning of the exploitation, together with an improved geological understanding of the deposit, could increase these yields. In this work, marble mining in Macael (Spain was studied to test the capacity of non-destructive geophysical prospecting methods (GPR and ERI as tools to characterize the geology of the deposit. It is well-known that the ERI method provides a greater penetration depth. By using this technique, it is possible to distinguish the boundaries between the marble and the underlying micaschists, the morphology of the unit to be exploited, and even fracture zones to be identified. Therefore, this technique could be used in the early stages of research, to estimate the reserves of the deposit. The GPR methodology, with a lower penetration depth, is able to offer more detailed information. Specifically, it detects lateral and vertical changes of the facies inside the marble unit, as well as the anisotropies of the rock (fractures or holes. This technique would be suitable for use in a second stage of research. On the one hand, it is very useful for characterization of the texture and fabric of the rock, which allows us to determine in advance its properties, and therefore, the quality for ornamental use. On the other hand, the localization of anisotropy using the GPR technique will make it possible to improve the planning of the rock exploitation in order to increase yields. Both integrated geophysical techniques are effective for assessing the quality of ornamental rock and thus can serve as useful tools in mine planning to improve yields and costs.

Data mining in radiology

International Nuclear Information System (INIS)

Kharat, Amit T; Singh, Amarjit; Kulkarni, Vilas M; Shah, Digish

2014-01-01

Data mining facilitates the study of radiology data in various dimensions. It converts large patient image and text datasets into useful information that helps in improving patient care and provides informative reports. Data mining technology analyzes data within the Radiology Information System and Hospital Information System using specialized software which assesses relationships and agreement in available information. By using similar data analysis tools, radiologists can make informed decisions and predict the future outcome of a particular imaging finding. Data, information and knowledge are the components of data mining. Classes, Clusters, Associations, Sequential patterns, Classification, Prediction and Decision tree are the various types of data mining. Data mining has the potential to make delivery of health care affordable and ensure that the best imaging practices are followed. It is a tool for academic research. Data mining is considered to be ethically neutral, however concerns regarding privacy and legality exists which need to be addressed to ensure success of data mining

Availability analysis of selected mining machinery

Directory of Open Access Journals (Sweden)

Brodny Jarosław

2017-06-01

Full Text Available Underground extraction of coal is characterized by high variability of mining and geological conditions in which it is conducted. Despite ever more effective methods and tools, used to identify the factors influencing this process, mining machinery, used in mining underground, work in difficult and not always foreseeable conditions, which means that these machines should be very universal and reliable. Additionally, a big competition, occurring on the coal market, causes that it is necessary to take action in order to reduce the cost of its production, e.g. by increasing the efficiency of utilization machines. To meet this objective it should be pro-ceed with analysis presented in this paper. The analysis concerns to availability of utilization selected mining machinery, conducted using the model of OEE, which is a tool for quantitative estimate strategy TPM. In this article we considered the machines being part of the mechanized longwall complex and the basis of analysis was the data recording by the industrial automation system. Using this data set we evaluated the availability of studied machines and the structure of registered breaks in their work. The results should be an important source of information for maintenance staff and management of mining plants, needed to improve the economic efficiency of underground mining.

Mining engineer requirements in a German coal mine

Energy Technology Data Exchange (ETDEWEB)

Rauhut, F J

1985-10-01

Basic developments in German coal mines, new definitions of working areas of mining engineers, and groups of requirements in education are discussed. These groups include: requirements of hard-coal mining at great depth and in extended collieries; application of process technology and information systems in semi-automated mines; thinking in processes and systems; organizational changes; future requirements of mining engineers; responsibility of the mining engineer for employees and society.

The Effect of Mining Activity on the Occurrence of Mining Tremors in the Safety Shaft Pillar of the Kladno-Mayrau Coal Mine

Czech Academy of Sciences Publication Activity Database

Živor, Roman; Buben, Jiří

16(118) (2000), s. 203-214 ISSN 1211-1910 R&D Projects: GA ČR GA105/96/1065 Institutional research plan: CEZ:AV0Z3046908 Keywords : tremor s * drifting * extraction Subject RIV: DH - Mining, incl. Coal Mining

Optical Aperture Synthesis Object's Information Extracting Based on Wavelet Denoising

International Nuclear Information System (INIS)

Fan, W J; Lu, Y

2006-01-01

Wavelet denoising is studied to improve OAS(optical aperture synthesis) object's Fourier information extracting. Translation invariance wavelet denoising based on Donoho wavelet soft threshold denoising is researched to remove Pseudo-Gibbs in wavelet soft threshold image. OAS object's information extracting based on translation invariance wavelet denoising is studied. The study shows that wavelet threshold denoising can improve the precision and the repetition of object's information extracting from interferogram, and the translation invariance wavelet denoising information extracting is better than soft threshold wavelet denoising information extracting

DEVELOPMENT OF AUTOMATIC EXTRACTION METHOD FOR ROAD UPDATE INFORMATION BASED ON PUBLIC WORK ORDER OUTLOOK

Science.gov (United States)

Sekimoto, Yoshihide; Nakajo, Satoru; Minami, Yoshitaka; Yamaguchi, Syohei; Yamada, Harutoshi; Fuse, Takashi

Recently, disclosure of statistic data, representing financial effects or burden for public work, through each web site of national or local government, enables us to discuss macroscopic financial trends. However, it is still difficult to grasp a basic property nationwide how each spot was changed by public work. In this research, our research purpose is to collect road update information reasonably which various road managers provide, in order to realize efficient updating of various maps such as car navigation maps. In particular, we develop the system extracting public work concerned and registering summary including position information to database automatically from public work order outlook, released by each local government, combinating some web mining technologies. Finally, we collect and register several tens of thousands from web site all over Japan, and confirm the feasibility of our method.

SPATIO-TEMPORAL PATTERN MINING ON TRAJECTORY DATA USING ARM

Directory of Open Access Journals (Sweden)

S. Khoshahval

2017-09-01

Full Text Available Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user’s visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users’ behaviour in a system and can be utilized in various location-based applications.

Natural radioactivity in mining and hydrocarbon extraction industry. Vol. 1

Energy Technology Data Exchange (ETDEWEB)

Testa, C; Desideri, D; Meli, M A; Roselli, C [General Chemistry Institute, Urbino University, 61029 Urbino, (Italy)

1996-03-01

Water and soil natural radioactivity is a well known phenomenon which can produced by variable concentrations of uranium and thorium series radionuclides. Generally, the relevant radiological hazard is not important; however, some radiation protection problems can occur in particular industrial processes involving the treatment of large quantities of materials. In this case a high concentration of radioactive substance (NORM: nationally occurring radioactive materials) can be found at special points of the plant, in the manufacture by-products and in the waters. Sometimes the national radioactivity concentration can be so high to raise radiation protection problems which can be assimilated in a sense to the ones faced in the presence, handling, and disposal of non-sealed radioactive sources. In this paper the following mining and hydrocarbon extraction plants were particularly taken into account: (a) industries using zircon sands to produce refractory and ceramic materials; (b) phosphorites manufacture to prepare phosphoric acids, plasters and fertilizers (c) hydrocarbon extraction and treatment processes where formations of low specific activity (L.S.A.) scales and sludges are produced. The relevant results and the possible radiation protection risks for the professional exposed staff will be reported. A special emphasis will be given to some african phosphorites (boucraa, togo, morocco), and L.S.A. scales (tunisia, congo, Egypt). 4 figs., 5 tabs.

Natural radioactivity in mining and hydrocarbon extraction industry. Vol. 1

International Nuclear Information System (INIS)

Testa, C.; Desideri, D.; Meli, M.A.; Roselli, C.

1996-01-01

Water and soil natural radioactivity is a well known phenomenon which can produced by variable concentrations of uranium and thorium series radionuclides. Generally, the relevant radiological hazard is not important; however, some radiation protection problems can occur in particular industrial processes involving the treatment of large quantities of materials. In this case a high concentration of radioactive substance (NORM: nationally occurring radioactive materials) can be found at special points of the plant, in the manufacture by-products and in the waters. Sometimes the national radioactivity concentration can be so high to raise radiation protection problems which can be assimilated in a sense to the ones faced in the presence, handling, and disposal of non-sealed radioactive sources. In this paper the following mining and hydrocarbon extraction plants were particularly taken into account: a) industries using zircon sands to produce refractory and ceramic materials; b) phosphorites manufacture to prepare phosphoric acids, plasters and fertilizers c) hydrocarbon extraction and treatment processes where formations of low specific activity (L.S.A.) scales and sludges are produced. The relevant results and the possible radiation protection risks for the professional exposed staff will be reported. A special emphasis will be given to some african phosphorites (boucraa, togo, morocco), and L.S.A. scales (tunisia, congo, Egypt). 4 figs., 5 tabs

Text mining for traditional Chinese medical knowledge discovery: a survey.

Science.gov (United States)

Zhou, Xuezhong; Peng, Yonghong; Liu, Baoyan

2010-08-01

Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions. Copyright 2010 Elsevier Inc. All rights reserved.

Open Pit Mining & The Cost of Water Potential Opportunities Towards Sustainable Mining

OpenAIRE

Sébastien J.R. Fortin

2015-01-01

Mining operations require vast quantities of water to run ore processing facilities and thus have a responsibility to manage this critical resource. Operations are often located in areas of limited water supply, which may create a competitive climate for water consumption. Make-up water for mineral processing can represent a significant portion of production cost for mining companies. While necessary for mining, water in open pits is problematic for extraction activities and leads to increase...

Improving diagnostic accuracy using agent-based distributed data mining system.

Science.gov (United States)

Sridhar, S

2013-09-01

The use of data mining techniques to improve the diagnostic system accuracy is investigated in this paper. The data mining algorithms aim to discover patterns and extract useful knowledge from facts recorded in databases. Generally, the expert systems are constructed for automating diagnostic procedures. The learning component uses the data mining algorithms to extract the expert system rules from the database automatically. Learning algorithms can assist the clinicians in extracting knowledge automatically. As the number and variety of data sources is dramatically increasing, another way to acquire knowledge from databases is to apply various data mining algorithms that extract knowledge from data. As data sets are inherently distributed, the distributed system uses agents to transport the trained classifiers and uses meta learning to combine the knowledge. Commonsense reasoning is also used in association with distributed data mining to obtain better results. Combining human expert knowledge and data mining knowledge improves the performance of the diagnostic system. This work suggests a framework of combining the human knowledge and knowledge gained by better data mining algorithms on a renal and gallstone data set.

Pharmspresso: a text mining tool for extraction of pharmacogenomic concepts and relationships from full text.

Science.gov (United States)

Garten, Yael; Altman, Russ B

2009-02-05

Pharmacogenomics studies the relationship between genetic variation and the variation in drug response phenotypes. The field is rapidly gaining importance: it promises drugs targeted to particular subpopulations based on genetic background. The pharmacogenomics literature has expanded rapidly, but is dispersed in many journals. It is challenging, therefore, to identify important associations between drugs and molecular entities--particularly genes and gene variants, and thus these critical connections are often lost. Text mining techniques can allow us to convert the free-style text to a computable, searchable format in which pharmacogenomic concepts (such as genes, drugs, polymorphisms, and diseases) are identified, and important links between these concepts are recorded. Availability of full text articles as input into text mining engines is key, as literature abstracts often do not contain sufficient information to identify these pharmacogenomic associations. Thus, building on a tool called Textpresso, we have created the Pharmspresso tool to assist in identifying important pharmacogenomic facts in full text articles. Pharmspresso parses text to find references to human genes, polymorphisms, drugs and diseases and their relationships. It presents these as a series of marked-up text fragments, in which key concepts are visually highlighted. To evaluate Pharmspresso, we used a gold standard of 45 human-curated articles. Pharmspresso identified 78%, 61%, and 74% of target gene, polymorphism, and drug concepts, respectively. Pharmspresso is a text analysis tool that extracts pharmacogenomic concepts from the literature automatically and thus captures our current understanding of gene-drug interactions in a computable form. We have made Pharmspresso available at http://pharmspresso.stanford.edu.

Data Mining – Innovative Method for Obtaining Information in Marketingand Business Management

Directory of Open Access Journals (Sweden)

Mirela-Cristina Voicu

2011-05-01

Full Text Available The existence of massive amounts of data raised the question of using their reorientation to a retrospective to a prospective operation. Data mining offers the promise of an important aid for discovering hidden patterns in data that can be used to predict the behavior of customers, products and processes. Data mining tools must be guided by users who understand the business, the general nature of the data and analytical methods involved. It discovers information within the data that queries and reports can’t effectively reveal. It is vital to collect data and prepare properly, to face reality models. Choosing the most appropriate product data mining is to find a tool with the capabilities required, an interface that matches the skills of users and can be applied in a specific business problem. In this context, the purpose of this paper is to illustrate some of the problems of company activity problems which can be solved by using data mining techniques.

Information Mining from Heterogeneous Data Sources: A Case Study on Drought Predictions

Directory of Open Access Journals (Sweden)

Getachew B. Demisse

2017-07-01

Full Text Available The objective of this study was to develop information mining methodology for drought modeling and predictions using historical records of climate, satellite, environmental, and oceanic data. The classification and regression tree (CART approach was used for extracting drought episodes at different time-lag prediction intervals. Using the CART approach, a number of successful model trees were constructed, which can easily be interpreted and used by decision makers in their drought management decisions. The regression rules produced by CART were found to have correlation coefficients from 0.71–0.95 in rules-alone modeling. The accuracies of the models were found to be higher in the instance and rules model (0.77–0.96 compared to the rules-alone model. From the experimental analysis, it was concluded that different combinations of the nearest neighbor and committee models significantly increase the performances of CART drought models. For more robust results from the developed methodology, it is recommended that future research focus on selecting relevant attributes for slow-onset drought episode identification and prediction.

Text feature extraction based on deep learning: a review.

Science.gov (United States)

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

SparkText: Biomedical Text Mining on Big Data Framework

Science.gov (United States)

He, Karen Y.; Wang, Kai

2016-01-01

Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

SparkText: Biomedical Text Mining on Big Data Framework.

Directory of Open Access Journals (Sweden)

Zhan Ye

Full Text Available Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment.In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM, and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes.This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Knowledge Discovery and Data Mining in Iran's Climatic Researches

Science.gov (United States)

Karimi, Mostafa

2013-04-01

Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for

Personality and Education Mining based Job Advisory System

Directory of Open Access Journals (Sweden)

Rajendra S. Choudhary

2014-09-01

Full Text Available Every job demands an employee with some specific qualities in addition to the basic educational qualification. For example, an introvert person cannot be a good leader despite of a very good academic qualification. Thinking and logical ability is required for a person to be a successful software engineer. So, the aim of this paper is to present a novel approach for advising an ideal job to the job seeker while considering his personality trait and educational qualification both. Very well-known theories of personality like MBTI indicator and OCEAN theory, are used for personality mining. For education mining, score based system is used. The score based system captures the information from attributes like most scoring subject, dream job etc. After personality mining, the resultant values are coalesced with the information extracted from education mining. And finally, the most suited jobs, in terms of personality and educational qualification are recommended to the job seekers. The experiment is conducted on the students who have earned an engineering degree in the field of computer science, information technology and electronics. Nevertheless, the same architecture can easily be extended to other educational degrees also. To the best of the author’s knowledge, this is a first e-job advisory system that recommends the job best suited as per one’s personality using MBTI and OCEAN theory both.

Mining aspects of hard to access oil sands deposits

Energy Technology Data Exchange (ETDEWEB)

Stephenson, G.; Wright, D.; Lukacs, Z. [Norwest Corp., Calgary, AB (Canada)

2006-07-01

While a variety of oil sands mining technologies have been explored since the 1960s, the oil sands industry has generally favoured truck and shovel mining as a proven, low-cost mining solution. However, surface mining economics are affected by the price of bitumen, haul distances, tailings storage and geotechnical constraints. Maintenance, labour and the cost of replacing tires and ground engaging tools also have a significant impact on the economics of surface mining. Large volumes of water are used in surface mining, and remediation of surface mined areas can take hundreds of years. Damage to machinery is common as oil sands are abrasive and adhere to equipment. This presentation examined recent technologies developed to improve the economics of surface mining. Various extraction and tailings technologies were reviewed. Issues concerning the integration of mining and extraction processes were discussed. Various monitoring tools were evaluated. A review of new underground mining options included outlines of: longwall mining; sub-level caving; tunnel boring; and room and pillar extraction techniques. A generalized regional geology was presented. It was concluded that the oil sands surfacing mining industry should concentrate on near-term research needs to improve the performance and economics of proven technologies. Screening studies should also be conducted to determine the focus for the development of underground technologies. refs., tabs., figs.

Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

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André SANTOS

2012-07-01

Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

Applying a text mining framework to the extraction of numerical parameters from scientific literature in the biotechnology domain

Directory of Open Access Journals (Sweden)

Anália LOURENÇO

2013-07-01

Full Text Available Scientific publications are the main vehicle to disseminate information in the field of biotechnology for wastewater treatment. Indeed, the new research paradigms and the application of high-throughput technologies have increased the rate of publication considerably. The problem is that manual curation becomes harder, prone-to-errors and time-consuming, leading to a probable loss of information and inefficient knowledge acquisition. As a result, research outputs are hardly reaching engineers, hampering the calibration of mathematical models used to optimize the stability and performance of biotechnological systems. In this context, we have developed a data curation workflow, based on text mining techniques, to extract numerical parameters from scientific literature, and applied it to the biotechnology domain. A workflow was built to process wastewater-related articles with the main goal of identifying physico-chemical parameters mentioned in the text. This work describes the implementation of the workflow, identifies achievements and current limitations in the overall process, and presents the results obtained for a corpus of 50 full-text documents.

The influence of geomorphology on the role of women at artisanal and small-scale mine sites

Science.gov (United States)

Malpeli, Katherine C.; Chirico, Peter G.

2013-01-01

The geologic and geomorphic expressions of a mineral deposit determine its location, size, and accessibility, characteristics which in turn greatly influence the success of artisans mining the deposit. Despite this critical information, which can be garnered through studying the surficial physical expression of a deposit, the geologic and geomorphic sciences have been largely overlooked in artisanal mining-related research. This study demonstrates that a correlation exists between the roles of female miners at artisanal diamond and gold mining sites in western and central Africa and the physical expression of the deposits. Typically, women perform ore processing and ancillary roles at mine sites. On occasion, however, women participate in the extraction process itself. Women were found to participate in the extraction of ore only when a deposit had a thin overburden layer, thus rendering the mineralized ore more accessible. When deposits required a significant degree of manual labour to access the ore due to thick overburden layers, women were typically relegated to other roles. The identification of this link encourages the establishment of an alternative research avenue in which the physical and social sciences merge to better inform policymakers, so that the most appropriate artisanal mining assistance programs can be developed and implemented.

A Wireless LAN and Voice Information System for Underground Coal Mine

Directory of Open Access Journals (Sweden)

Yu Zhang

2014-06-01

Full Text Available In this paper we constructed a wireless information system, and developed a wireless voice communication subsystem based on Wireless Local Area Networks (WLAN for underground coal mine, which employs Voice over IP (VoIP technology and Session Initiation Protocol (SIP to achieve wireless voice dispatching communications. The master control voice dispatching interface and call terminal software are also developed on the WLAN ground server side to manage and implement the voice dispatching communication. A testing system for voice communication was constructed in tunnels of an underground coal mine, which was used to actually test the wireless voice communication subsystem via a network analysis tool, named Clear Sight Analyzer. In tests, the actual flow charts of registration, call establishment and call removal were analyzed by capturing call signaling of SIP terminals, and the key performance indicators were evaluated in coal mine, including average subjective value of voice quality, packet loss rate, delay jitter, disorder packet transmission and end-to- end delay. Experimental results and analysis demonstrate that the wireless voice communication subsystem developed communicates well in underground coal mine environment, achieving the designed function of voice dispatching communication.

A mine of energy

International Nuclear Information System (INIS)

Fallon, M.

1982-01-01

In July 1978 the then Union Corporation (which is a wholly-owned Subsidiary of the larger Gencor Group) announced its intention to develop Beisa mine in the Orange Free State. They started up a medium sized uranium mine with gold as a by-product. The main idea was for the processing of uranium. The planning of the uranium recovery plant, the actual mining, and the recovery and extraction of uranium are discussed

Assessment of Heavy Metals in Mining Tailing around Boroo and Zuunkharaa Gold Mining Areas of Mongolia

OpenAIRE

Solongo, Enkhzaya; Ohe, Kaoru; Shiomori, Koichiro; Bolormaa, Oyuntsetseg; Ochirkhuyag, Bayanjargal; Watanabe, Makiko

2016-01-01

This study aimed to study the mobility of heavy metals using sequential extraction analysis and assess heavy metals in soil samples of mining tailing around the small-scale gold mining areas at Boroo and Zuunkharaa in Mongolia. The samples were collected from small scale gold mining area existed in Tuv and Selenge province, Mongolia. Physicochemical, chemical and some statistical analyses were made for the mining tailing samples. The pH of the mining tailing samples was determined as 6.10 – 7...

Optimizing the Information Presentation on Mining Potential by using Web Services Technology with Restful Protocol

Science.gov (United States)

Abdillah, T.; Dai, R.; Setiawan, E.

2018-02-01

This study aims to develop the application of Web Services technology with RestFul Protocol to optimize the information presentation on mining potential. This study used User Interface Design approach for the information accuracy and relevance as well as the Web Service for the reliability in presenting the information. The results show that: the information accuracy and relevance regarding mining potential can be seen from the achievement of User Interface implementation in the application that is based on the following rules: The consideration of the appropriate colours and objects, the easiness of using the navigation, and users’ interaction with the applications that employs symbols and languages understood by the users; the information accuracy and relevance related to mining potential can be observed by the information presented by using charts and Tool Tip Text to help the users understand the provided chart/figure; the reliability of the information presentation is evident by the results of Web Services testing in Figure 4.5.6. This study finds out that User Interface Design and Web Services approaches (for the access of different Platform apps) are able to optimize the presentation. The results of this study can be used as a reference for software developers and Provincial Government of Gorontalo.

Mining Heterogeneous Information Networks by Exploring the Power of Links

Science.gov (United States)

Han, Jiawei

Knowledge is power but for interrelated data, knowledge is often hidden in massive links in heterogeneous information networks. We explore the power of links at mining heterogeneous information networks with several interesting tasks, including link-based object distinction, veracity analysis, multidimensional online analytical processing of heterogeneous information networks, and rank-based clustering. Some recent results of our research that explore the crucial information hidden in links will be introduced, including (1) Distinct for object distinction analysis, (2) TruthFinder for veracity analysis, (3) Infonet-OLAP for online analytical processing of information networks, and (4) RankClus for integrated ranking-based clustering. We also discuss some of our on-going studies in this direction.

Text mining of cancer-related information: review of current status and future directions.

Science.gov (United States)

Spasić, Irena; Livsey, Jacqueline; Keane, John A; Nenadić, Goran

2014-09-01

This paper reviews the research literature on text mining (TM) with the aim to find out (1) which cancer domains have been the subject of TM efforts, (2) which knowledge resources can support TM of cancer-related information and (3) to what extent systems that rely on knowledge and computational methods can convert text data into useful clinical information. These questions were used to determine the current state of the art in this particular strand of TM and suggest future directions in TM development to support cancer research. A review of the research on TM of cancer-related information was carried out. A literature search was conducted on the Medline database as well as IEEE Xplore and ACM digital libraries to address the interdisciplinary nature of such research. The search results were supplemented with the literature identified through Google Scholar. A range of studies have proven the feasibility of TM for extracting structured information from clinical narratives such as those found in pathology or radiology reports. In this article, we provide a critical overview of the current state of the art for TM related to cancer. The review highlighted a strong bias towards symbolic methods, e.g. named entity recognition (NER) based on dictionary lookup and information extraction (IE) relying on pattern matching. The F-measure of NER ranges between 80% and 90%, while that of IE for simple tasks is in the high 90s. To further improve the performance, TM approaches need to deal effectively with idiosyncrasies of the clinical sublanguage such as non-standard abbreviations as well as a high degree of spelling and grammatical errors. This requires a shift from rule-based methods to machine learning following the success of similar trends in biological applications of TM. Machine learning approaches require large training datasets, but clinical narratives are not readily available for TM research due to privacy and confidentiality concerns. This issue remains the main

European sites contaminated by residues from the ore extracting and processing industries

International Nuclear Information System (INIS)

Vandenhove, H.

2000-01-01

Activities linked with the ore extraction and processing industries may lead to enhanced levels of naturally occurring radionuclides (NORs) in products, by-products and waste and at the installations and in the surroundings of the facility. In the framework of the EC-DGXI CARE project (Common Approach for REstoration of contaminated sites) nine important categories of industries were identified and discussions were summarized on the industrial processes and the levels of NORs in parent material, waste and by-products. The most contaminating industries are uranium mining and milling, metal mining and smelting and the phosphate industry. Radionuclide levels in products and/or waste products from the oil and gas extraction industry and of the rare earth, zirconium and ceramics industries may be particularly elevated, but waste streams are limited. The impact on the public from coal mining and power production from coal is commonly considered low. No typical values are available for contaminant levels in materials, buildings and surroundings of radium extraction and luminizing plants, nor for thorium extraction and processing plants. An attempt to give an overview of sites in Europe contaminated with NORs, with emphasis on past practices, was only partly successful since information was often limited or unavailable. The most prominent case of environmental contamination due to mining and processing activities (uranium, metal and coal mining) is in eastern Germany. (author)

Cause Information Extraction from Financial Articles Concerning Business Performance

Science.gov (United States)

Sakai, Hiroyuki; Masuyama, Shigeru

We propose a method of extracting cause information from Japanese financial articles concerning business performance. Our method acquires cause informtion, e. g. “_??__??__??__??__??__??__??__??__??__??_ (zidousya no uriage ga koutyou: Sales of cars were good)”. Cause information is useful for investors in selecting companies to invest. Our method extracts cause information as a form of causal expression by using statistical information and initial clue expressions automatically. Our method can extract causal expressions without predetermined patterns or complex rules given by hand, and is expected to be applied to other tasks for acquiring phrases that have a particular meaning not limited to cause information. We compared our method with our previous one originally proposed for extracting phrases concerning traffic accident causes and experimental results showed that our new method outperforms our previous one.

Specialized mining GIS system MineGIS SMZ Jelšava

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Peter Sasvári

2005-12-01

Full Text Available Following, the real needs for new mining information system requested by SMZ Jelšava, the Department of Mineral Deposits and Applied Geology (KLaAG at the Technical University of Košice (TUKE has prepared a specification for the specialized mining geographic information system called MineGIS SMZ Jelšava. The main roles of the new system have been defined as follows of reserves: the administration, analyse and the visualization of all mining geo-data related to the estimation.

Classifying unstructed textual data using the Product Score Model: an alternative text mining algorithm

NARCIS (Netherlands)

He, Qiwei; Veldkamp, Bernard P.; Eggen, T.J.H.M.; Veldkamp, B.P.

2012-01-01

Unstructured textual data such as students’ essays and life narratives can provide helpful information in educational and psychological measurement, but often contain irregularities and ambiguities, which creates difficulties in analysis. Text mining techniques that seek to extract useful

Mining

Directory of Open Access Journals (Sweden)

Khairullah Khan

2014-09-01

Full Text Available Opinion mining is an interesting area of research because of its applications in various fields. Collecting opinions of people about products and about social and political events and problems through the Web is becoming increasingly popular every day. The opinions of users are helpful for the public and for stakeholders when making certain decisions. Opinion mining is a way to retrieve information through search engines, Web blogs and social networks. Because of the huge number of reviews in the form of unstructured text, it is impossible to summarize the information manually. Accordingly, efficient computational methods are needed for mining and summarizing the reviews from corpuses and Web documents. This study presents a systematic literature survey regarding the computational techniques, models and algorithms for mining opinion components from unstructured reviews.

Practical graph mining with R

CERN Document Server

Hendrix, William; Jenkins, John; Padmanabhan, Kanchana; Chakraborty, Arpan

2014-01-01

Practical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or clusters of nodes that share common patterns of attributes and relationships, the extraction of patterns that distinguish one category of graphs from another, and the use of those patterns to predict the category of new graphs. Hands-On Application of Graph Data Mining Each chapter in the book focuses on a graph mining task, such as link analysis, cluster analysis, and classification. Through applications using real data sets, the book demonstrates how computational techniques can help solve real-world problems. The applications covered include network intrusion detection, tumor cell diagnostics, face recognition, predictive toxicology, mining metabolic and protein-protein interaction networks, and community detection in social networks. De...

Development of mechanization of extraction in underground coal mining (part I)

Energy Technology Data Exchange (ETDEWEB)

Strzeminski, J

1984-01-01

The history of underground coal mining and history of mechanizing underground operations of cutting, strata control, mine haulage, hoisting and ventilation are discussed. The following development periods are characterized: until 1769 (date of steam engine invention by J. Watt), from 1769 to 1945 (period of partial mechanization of operations in underground coal mining), from 1945 (period of comprehensive mechanization and automation). A general description of mining in the first development period is given. Evaluation of the second development period concentrates on mechanization in underground coal mining. The following equipment types are described: cutting (pneumatic picks and pneumatic drills, coal saws developed by Eickhoff, coal cutters developed after 1870, cutter loaders patented in 1925-1927, coal plows and coal cutter loaders), mine haulage (mine cars, conveyors developed in the United Kingdom, Germany and Russia, Poland), strata control at working faces (timber props, steel friction props, roof bars), strata control in the goaf (room and pillar mining, stowing, minestone utilization for stowing in Upper Silesia, hydraulic stowing in Upper Silesia). 5 references.

Sample-based XPath Ranking for Web Information Extraction

NARCIS (Netherlands)

Jundt, Oliver; van Keulen, Maurice

Web information extraction typically relies on a wrapper, i.e., program code or a configuration that specifies how to extract some information from web pages at a specific website. Manually creating and maintaining wrappers is a cumbersome and error-prone task. It may even be prohibitive as some

Minimizing the Impact of Mining Activities for Sustainable Mined-Out ...

African Journals Online (AJOL)

Minimizing the Impact of Mining Activities for Sustainable Mined-Out Area ... sensing and Geographical Information System (GIS) in assessing environmental impact of ... Keywords: Solid mineral, Impact assessment, Mined-out area utilization, ...

Ontology-Based Information Extraction for Business Intelligence

Science.gov (United States)

Saggion, Horacio; Funk, Adam; Maynard, Diana; Bontcheva, Kalina

Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution.

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

Science.gov (United States)

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/. © The Author(s) 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

PREVENTION OF ACID MINE DRAINAGE GENERATION FROM OPEN-PIT MINE HIGHWALLS

Science.gov (United States)

Exposed, open pit mine highwalls contribute significantly to the production of acid mine drainage (AMD) thus causing environmental concerns upon closure of an operating mine. Available information on the generation of AMD from open-pit mine highwalls is very limit...

Mine waste management legislation. Gold mining areas in Romania

Science.gov (United States)

Maftei, Raluca-Mihaela; Filipciuc, Constantina; Tudor, Elena

2014-05-01

Agency for Mineral Resources (NAMR) manages, on behalf of the state, the mineral resources. Waste management framework Nowadays, Romania, is trying to align its regulation concerning mining activity to the European legislation taking into consideration waste management and their impact on the environment. Therefore the European Waste Catalog (Commission Decision 2001/118/EC) has been updated and published in the form of HG 856/2002 Waste management inventory and approved wastes list, including dangerous wastes. The HG 349/2005 establishes the legal framework for waste storage activity as well as for the monitoring of the closing and post-closing existing deposits, taking into account the environment protection and the health of the general population. Based on Directive 2000/60/EC the Ministry of Waters Administration, Forests and Environment Protection from Romania issued the GO No 756/1997 (amended by GO 532/2002 and GO 1144/2002),"Regulations for environment pollution assessment" that contains alarm and intervention rates for soil pollution for contaminants such as metals, metalloids (Sb, Ag, As, Be, Bi, B, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Se, Sn, TI, V, Zn) and cyanides. Also GO No 756/1997 was amended and updated by Law No 310/2004 and 112/2006 in witch technical instructions concerning general framework for the use of water sources in the human activities including mining industry, are approved. Chemical compounds contained in industrial waters are fully regulated by H. G. 352/2005 concerning the contents of waste water discharged. Directive 2006/21/EC of the European Parliament and of the Council relating to the management of waste from extractive industries and amending Directive 2004/35/EC is transposed into the national law of the Romanian Government under Decision No 856/2008. The 856/2008 Decision on the management of waste from extractive industries establishes "the legal framework concerning the guidelines, measures and procedures to prevent or reduce as far

GPR Detection of Buried Symmetrically Shaped Mine-like Objects using Selective Independent Component Analysis

DEFF Research Database (Denmark)

Karlsen, Brian; Sørensen, Helge Bjarup Dissing; Larsen, Jan

2003-01-01

from small-scale anti-personal (AP) mines to large-scale anti-tank (AT) mines were designed. Large-scale SF-GPR measurements on this series of mine-like objects buried in soil were performed. The SF-GPR data was acquired using a wideband monostatic bow-tie antenna operating in the frequency range 750......This paper addresses the detection of mine-like objects in stepped-frequency ground penetrating radar (SF-GPR) data as a function of object size, object content, and burial depth. The detection approach is based on a Selective Independent Component Analysis (SICA). SICA provides an automatic...... ranking of components, which enables the suppression of clutter, hence extraction of components carrying mine information. The goal of the investigation is to evaluate various time and frequency domain ICA approaches based on SICA. Performance comparison is based on a series of mine-like objects ranging...

Post-mining in France

International Nuclear Information System (INIS)

2007-01-01

This plentifully illustrated book aims at showing how new equilibria are building up during the transition between mining activity and post-mining, and at stressing on the necessity to keep up the cultural elements, the competencies and knowledge of mining works. The first chapter - mine and men - shows the importance of mineral substances in the objects of the everyday life, illustrates the importance of the mining tradition in France and describes the technical and administrative organisation of the end of the mining activity (works, rehabilitation, regulation, monitoring..). Chapter two - exploitation methods - presents the surface and underground facilities and their impact on the environment (extraction machines, workshops, ore processing plants, decantation ponds..). The third chapter deals with the rehabilitation and monitoring aspects: impact of mining activity stoppage on underground and surface waters, land stability, soils cleansing.. The last chapter summarizes the history of French mining region by region: Nord-Pas-de-Calais, Lorraine-Alsace, Massif central, Bretagne-Normandie, Provence-Alpes-Cote d'Azur and Pyrenees

The Agent of extracting Internet Information with Lead Order

Science.gov (United States)

Mo, Zan; Huang, Chuliang; Liu, Aijun

In order to carry out e-commerce better, advanced technologies to access business information are in need urgently. An agent is described to deal with the problems of extracting internet information that caused by the non-standard and skimble-scamble structure of Chinese websites. The agent designed includes three modules which respond to the process of extracting information separately. A method of HTTP tree and a kind of Lead algorithm is proposed to generate a lead order, with which the required web can be retrieved easily. How to transform the extracted information structuralized with natural language is also discussed.

Mining Matters : Natural Resource Extraction and Local Business Constraints

NARCIS (Netherlands)

de Haas, Ralph; Poelhekke, Steven

2016-01-01

We estimate the impact of local mining activity on the business constraints experienced by 22,150 firms across eight resource-rich countries. We find that with the presence of active mines, the business environment in the immediate vicinity (<20 km) of a firm deteriorates but business constraints of

Study on online community user motif using web usage mining

Science.gov (United States)

Alphy, Meera; Sharma, Ajay

2016-04-01

The Web usage mining is the application of data mining, which is used to extract useful information from the online community. The World Wide Web contains at least 4.73 billion pages according to Indexed Web and it contains at least 228.52 million pages according Dutch Indexed web on 6th august 2015, Thursday. It’s difficult to get needed data from these billions of web pages in World Wide Web. Here is the importance of web usage mining. Personalizing the search engine helps the web user to identify the most used data in an easy way. It reduces the time consumption; automatic site search and automatic restore the useful sites. This study represents the old techniques to latest techniques used in pattern discovery and analysis in web usage mining from 1996 to 2015. Analyzing user motif helps in the improvement of business, e-commerce, personalisation and improvement of websites.

Safety and environmental aspect uranium mining and extraction in Kalan, Kalimantan

International Nuclear Information System (INIS)

Mudiar Masdja; Tampubolon, P.; Sihombing, W.

1996-01-01

Safety in uranium mining and extraction in Kalan, Kalimantan, Batan's activities, has been observed by concerning about personnel safety, monitoring of the work place and radiation surveillance. the personnel safety includes procurements of personnel protective equipment, work clothes, and washing facility. monitoring of the work place covers climate (temperature, humidity) noise frequency, poisonous gases, and tailing management. Radiation surveillance measures Rn gas and radioactive dust . Environmental assessment of Kalan site consist of physical, biological and cultural environments. The physical assessment mayor area such as water and air qualities, morphology and climatology. the biological assessment examines flora, fauna and aquatic biota. The culture assessment collect data of human population and distribution, occupation and income level, education, health and public perception. Guidelines for environmental management and monitoring have been documented and they have in Kalan site. (author). 8 refs; 3 tabs; 3 figs

Text Mining for Information Systems Researchers: An Annotated Topic Modeling Tutorial

DEFF Research Database (Denmark)

Debortoli, Stefan; Müller, Oliver; Junglas, Iris

2016-01-01

, such as manual coding. Yet, the size of text data setsobtained from the Internet makes manual analysis virtually impossible. In this tutorial, we discuss the challengesencountered when applying automated text-mining techniques in information systems research. In particular, weshowcase the use of probabilistic...... researchers,this tutorial provides some guidance for conducting text mining studies on their own and for evaluating the quality ofothers.......t is estimated that more than 80 percent of today’s data is stored in unstructured form (e.g., text, audio, image, video);and much of it is expressed in rich and ambiguous natural language. Traditionally, the analysis of natural languagehas prompted the use of qualitative data analysis approaches...

An investigation on natural radioactivity from mining industry ...

African Journals Online (AJOL)

An investigation on natural radioactivity from mining industry # ... PROMOTING ACCESS TO AFRICAN RESEARCH ... Mining originating industries such as the coal industries, petroleum extraction and processing and natural gas, mining enrichment waste, phosphate, ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

data mining in distributed database

International Nuclear Information System (INIS)

Ghunaim, A.A.A.

2007-01-01

as we march into the age of digital information, the collection and the storage of large quantities of data is increased, and the problem of data overload looms ominously ahead. it is estimated today that the volume of data stored by a company doubles every year but the amount of meaningful information is decreases rapidly. the ability to analyze and understand massive datasets lags far behind the ability to gather and store the data. the unbridled growth of data will inevitably lead to a situation in which it is increasingly difficult to access the desired information; it will always be like looking for a needle in a haystack, and where only the amount of hay will be growing all the time . so, a new generation of computational techniques and tools is required to analyze and understand the rapidly growing volumes of data . and, because the information technology (it) has become a strategic weapon in the modern life, it is needed to use a new decision support tools to be an international powerful competitor.data mining is one of these tools and its methods make it possible to extract decisive knowledge needed by an enterprise and it means that it concerned with inferring models from data , including statistical pattern recognition, applied statistics, machine learning , and neural networks. data mining is a tool for increasing productivity of people trying to build predictive models. data mining techniques have been applied successfully to several real world problem domains; but the application in the nuclear reactors field has only little attention . one of the main reasons, is the difficulty in obtaining the data sets

Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge.

Science.gov (United States)

Cormack, James; Nath, Chinmoy; Milward, David; Raja, Kalpana; Jonnalagadda, Siddhartha R

2015-12-01

This paper describes the use of an agile text mining platform (Linguamatics' Interactive Information Extraction Platform, I2E) to extract document-level cardiac risk factors in patient records as defined in the i2b2/UTHealth 2014 challenge. The approach uses a data-driven rule-based methodology with the addition of a simple supervised classifier. We demonstrate that agile text mining allows for rapid optimization of extraction strategies, while post-processing can leverage annotation guidelines, corpus statistics and logic inferred from the gold standard data. We also show how data imbalance in a training set affects performance. Evaluation of this approach on the test data gave an F-Score of 91.7%, one percent behind the top performing system. Copyright © 2015 Elsevier Inc. All rights reserved.

Arsenic pollution and fractionation in sediments and mine waste samples from different mine sites

International Nuclear Information System (INIS)

Larios, Raquel; Fernández-Martínez, Rodolfo; Álvarez, Rodrigo; Rucandio, Isabel

2012-01-01

A characterization of arsenic pollution and its associations with solid mineral phases in sediments and spoil heap samples from four different abandoned mines in Spain is performed. Three of them were mercury mines located in the same mining district, in the province of Asturias, and the other one, devoted to arsenic mining, is in the province of León. A sequential extraction procedure, especially developed for arsenic, was applied for the study of arsenic partitioning. Very high total arsenic concentrations ranging 300–67,000 mg·kg −1 were found. Arsenic fractionation in each mine is broadly in accordance with the mineralogy of the area and the extent of the mine workings. In almost all the studied samples, arsenic appeared predominantly associated with iron oxyhydroxides, especially in the amorphous form. Sediments from cinnabar roasted piles showed a higher arsenic mobility as a consequence of an intense ore treatment, posing an evident risk of arsenic spread to the surroundings. Samples belonging to waste piles where the mining activity was less intense presented a higher proportion of arsenic associated with structural minerals. Nevertheless, it represents a long-term source of arsenic to the environment. - Highlights: ► Arsenic fractionation in sediments from different mining areas is evaluated. ► A sequential extraction scheme especially designed for arsenic partitioning is applied. ► As associations with mineral pools is in accordance to the mineralogy of each area. ► As distribution and mobility in each area depends on the extent of mining activity. ► As occurs mainly associated with amorphous iron oxyhydroxides in all samples.

Arsenic pollution and fractionation in sediments and mine waste samples from different mine sites

Energy Technology Data Exchange (ETDEWEB)

Larios, Raquel; Fernandez-Martinez, Rodolfo [Unidad de Espectroscopia, Division de Quimica, Departamento de Tecnologia, CIEMAT. Av. Complutense, 40, E-28040 Madrid (Spain); Alvarez, Rodrigo [Dpto. de Explotacion y Prospeccion de Minas, Universidad de Oviedo, ETS de Ingenieros de Minas, C/Independencia, 13, E-33004 Oviedo (Spain); Rucandio, Isabel, E-mail: isabel.rucandio@ciemat.es [Unidad de Espectroscopia, Division de Quimica, Departamento de Tecnologia, CIEMAT. Av. Complutense, 40, E-28040 Madrid (Spain)

2012-08-01

A characterization of arsenic pollution and its associations with solid mineral phases in sediments and spoil heap samples from four different abandoned mines in Spain is performed. Three of them were mercury mines located in the same mining district, in the province of Asturias, and the other one, devoted to arsenic mining, is in the province of Leon. A sequential extraction procedure, especially developed for arsenic, was applied for the study of arsenic partitioning. Very high total arsenic concentrations ranging 300-67,000 mg{center_dot}kg{sup -1} were found. Arsenic fractionation in each mine is broadly in accordance with the mineralogy of the area and the extent of the mine workings. In almost all the studied samples, arsenic appeared predominantly associated with iron oxyhydroxides, especially in the amorphous form. Sediments from cinnabar roasted piles showed a higher arsenic mobility as a consequence of an intense ore treatment, posing an evident risk of arsenic spread to the surroundings. Samples belonging to waste piles where the mining activity was less intense presented a higher proportion of arsenic associated with structural minerals. Nevertheless, it represents a long-term source of arsenic to the environment. - Highlights: Black-Right-Pointing-Pointer Arsenic fractionation in sediments from different mining areas is evaluated. Black-Right-Pointing-Pointer A sequential extraction scheme especially designed for arsenic partitioning is applied. Black-Right-Pointing-Pointer As associations with mineral pools is in accordance to the mineralogy of each area. Black-Right-Pointing-Pointer As distribution and mobility in each area depends on the extent of mining activity. Black-Right-Pointing-Pointer As occurs mainly associated with amorphous iron oxyhydroxides in all samples.

Fine-grained information extraction from German transthoracic echocardiography reports.

Science.gov (United States)

Toepfer, Martin; Corovic, Hamo; Fette, Georg; Klügl, Peter; Störk, Stefan; Puppe, Frank

2015-11-12

Information extraction techniques that get structured representations out of unstructured data make a large amount of clinically relevant information about patients accessible for semantic applications. These methods typically rely on standardized terminologies that guide this process. Many languages and clinical domains, however, lack appropriate resources and tools, as well as evaluations of their applications, especially if detailed conceptualizations of the domain are required. For instance, German transthoracic echocardiography reports have not been targeted sufficiently before, despite of their importance for clinical trials. This work therefore aimed at development and evaluation of an information extraction component with a fine-grained terminology that enables to recognize almost all relevant information stated in German transthoracic echocardiography reports at the University Hospital of Würzburg. A domain expert validated and iteratively refined an automatically inferred base terminology. The terminology was used by an ontology-driven information extraction system that outputs attribute value pairs. The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts. The final system achieved state-of-the-art precision (micro average.996) and recall (micro average.961) on 100 test documents that represent more than 90 % of all reports. In particular, principal aspects as defined in a standardized external terminology were recognized with f 1=.989 (micro average) and f 1=.963 (macro average). As a result of keyword matching and restraint concept extraction, the system obtained high precision also on unstructured or exceptionally short documents, and documents with uncommon layout. The developed terminology and the proposed information extraction system allow to extract fine-grained information from German semi-structured transthoracic echocardiography reports

Sequential extraction of heavy metals in river sediments of an abandoned pyrite mining area: pollution detection and affinity series

International Nuclear Information System (INIS)

Pagnanelli, F.; Moscardini, E.; Giuliano, V.; Toro, L.

2004-01-01

In this paper heavy metal pollution at an abandoned Italian pyrite mine has been investigated by comparing total concentrations and speciation of heavy metals (Fe, Cu, Mn, Zn, Pb and As) in a red mud sample and a river sediment. Acid digestions show that all the investigated heavy metals present larger concentrations in the sediment than in the tailing. A modified Tessier's procedure has been used to discriminate heavy metal bound to organic fraction from those originally present in the mineral sulphide matrix and to detect a possible trend of metal mobilisation from red mud to river sediment. Sequential extractions on bulk and size fractionated samples denote that sediment samples present larger percent concentrations of the investigated heavy metals in the first extractive steps (I-IV) especially in lower dimension size fractionated samples suggesting that heavy metals in the sediment are significantly bound by superficial adsorption mechanisms. - Capsule: A modified Tessier's procedure, discriminating organic and sulphide bound metals, was used to detect pollutant mobilisation from red mud to river sediment in an abandoned pyrite mine

Automatic flow-through dynamic extraction: A fast tool to evaluate char-based remediation of multi-element contaminated mine soils.

Science.gov (United States)

Rosende, María; Beesley, Luke; Moreno-Jimenez, Eduardo; Miró, Manuel

2016-02-01

An automatic in-vitro bioaccessibility test based upon dynamic microcolumn extraction in a programmable flow setup is herein proposed as a screening tool to evaluate bio-char based remediation of mine soils contaminated with trace elements as a compelling alternative to conventional phyto-availability tests. The feasibility of the proposed system was evaluated by extracting the readily bioaccessible pools of As, Pb and Zn in two contaminated mine soils before and after the addition of two biochars (9% (w:w)) of diverse source origin (pine and olive). Bioaccessible fractions under worst-case scenarios were measured using 0.001 mol L(-1) CaCl2 as extractant for mimicking plant uptake, and analysis of the extracts by inductively coupled optical emission spectrometry. The t-test of comparison of means revealed an efficient metal (mostly Pb and Zn) immobilization by the action of olive pruning-based biochar against the bare (control) soil at the 0.05 significance level. In-vitro flow-through bioaccessibility tests are compared for the first time with in-vivo phyto-toxicity assays in a microcosm soil study. By assessing seed germination and shoot elongation of Lolium perenne in contaminated soils with and without biochar amendments the dynamic flow-based bioaccessibility data proved to be in good agreement with the phyto-availability tests. Experimental results indicate that the dynamic extraction method is a viable and economical in-vitro tool in risk assessment explorations to evaluate the feasibility of a given biochar amendment for revegetation and remediation of metal contaminated soils in a mere 10 min against 4 days in case of phyto-toxicity assays. Copyright © 2015 Elsevier B.V. All rights reserved.

Technologies for Decreasing Mining Losses

Science.gov (United States)

Valgma, Ingo; Väizene, Vivika; Kolats, Margit; Saarnak, Martin

2013-12-01

In case of stratified deposits like oil shale deposit in Estonia, mining losses depend on mining technologies. Current research focuses on extraction and separation possibilities of mineral resources. Selective mining, selective crushing and separation tests have been performed, showing possibilities of decreasing mining losses. Rock crushing and screening process simulations were used for optimizing rock fractions. In addition mine backfilling, fine separation, and optimized drilling and blasting have been analyzed. All tested methods show potential and depend on mineral usage. Usage in addition depends on the utilization technology. The questions like stability of the material flow and influences of the quality fluctuations to the final yield are raised.

Mining wastes

International Nuclear Information System (INIS)

Pradel, J.

1981-01-01

In this article mining wastes means wastes obtained during extraction and processing of uranium ores including production of uraniferous concentrates. The hazards for the population are irradiation, ingestion, dust or radon inhalation. The different wastes produced are reviewed. Management of liquid effluents, water treatment, contamined materials, gaseous wastes and tailings are examined. Environmental impact of wastes during and after exploitation is discussed. Monitoring and measurements are made to verify that ICRP recommendations are met. Studies in progress to improve mining waste management are given [fr

Data Stream Mining

Science.gov (United States)

Gaber, Mohamed Medhat; Zaslavsky, Arkady; Krishnaswamy, Shonali

Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).

TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

Directory of Open Access Journals (Sweden)

Chen Hsin-Hsi

2008-10-01

Full Text Available Abstract Background Traditional Chinese Medicine (TCM, a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature. Methods TCM, gene, disease, biological pathway and protein-protein interaction information were collected from public databases. For association discovery, the TCM names, gene names, disease names, TCM ingredients and effects were used to annotate the literature corpus obtained from PubMed. The concept to mine entity associations was based on hypothesis testing and collocation analysis. The annotated corpus was processed with natural language processing tools and rule-based approaches were applied to the sentences for extracting the relations between TCM effecters and effects. Results We developed a database, TCMGeneDIT, to provide association information about TCMs, genes, diseases, TCM effects and TCM ingredients mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information are also available for exploring the regulations of genes associated with TCM curative effects. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in understanding the possible therapeutic mechanisms of TCMs via gene regulations and deducing synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. The database is now available at http://tcm.lifescience.ntu.edu.tw/. Conclusion TCMGeneDIT is a unique database

Mining social networks and security informatics

CERN Document Server

Özyer, Tansel; Rokne, Jon; Khoury, Suheil

2013-01-01

Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for soci

ADA Title I allegations and the Mining, Quarrying, and Oil/Gas Extraction industry.

Science.gov (United States)

Van Wieren, Todd A; Rhoades, Laura; McMahon, Brian T

2017-01-01

The majority of research about employment discrimination in the U.S. Mining, Quarrying, and Oil/Gas (MQOGE) industries has concentrated on gender and race, while little attention has focused on disability. To explore allegations of Americans with Disabilities Act (ADA) Title I discrimination made to the Equal Employment Opportunity Commission (EEOC) by individuals with disabilities against MQOGE employers. Key data available to this study included demographic characteristics of charging parties, size of employers, types of allegations, and case outcomes. Using descriptive analysis, allegation profiles were developed for MQOGE's three main sectors (i.e., Oil/Gas Extraction, Mining except Oil/Gas, and Support Activities). These three profiles where then comparatively analyzed. Lastly, regression analysis explored whether some of the available data could partially predict MQOGE case outcomes. The predominant characteristics of MQOGE allegations were found to be quite similar to the allegation profile of U.S. private-sector industry as a whole, and fairly representative of MQOGE's workforce demographics. Significant differences between MQOGE's three main sector profiles were noted on some important characteristics. Lastly, it was found that MQOGE case outcomes could be partially predicted via some of the available variables. The study's limitations were presented and recommendations were offered for further research.

Undermining the state? Informal mining and trajectories of state formation in Eastern Mindanao, Philippines

NARCIS (Netherlands)

Verbrugge, B.L.P.

2015-01-01

Building on critical perspectives on the state and the informal economy, this article provides an analysis of the "state of the state" on the eastern Mindanao mineral frontier. In the first instance, the author explains that the massive expansion of informal small-scale gold mining, instead of

Prospecção e monitoramento informacional no processo de inteligência competitiva Information scanning and information mining in the process of competitive intelligence

Directory of Open Access Journals (Sweden)

Marta Lígia Pomim Valentim

2004-01-01

Full Text Available A prospecção e o monitoramento informacional são atividades base para a inteligência competitiva, entendida como um processo dinâmico, composto pela gestão da informação e pela gestão do conhecimento. O processo de inteligência competitiva (I. C. nas organizações ocorre a partir de diferentes atividades informacionais, dentre elas estão as ligadas a prospecção e ao monitoramento. O papel destas atividades é essencial, pois alimentam todo o processo com dados, informação e conhecimento, constroem diversas estruturas formais e informais de informação dentro da organização, além do que, as atividades de prospecção e monitoramento geram serviços e produtos informacionais sistematizados, com alto valor agregado.The information scanning and information mining are activities base for the competitive intelligence, understood as a dynamic process, composed by the information management and knowledge management. The process of competitive intelligence (I. C. in the organizations it happens starting from different informational activities, they are the tied up ones information scanning and information mining. The function of these activities is essential, because they feed the whole process with data, information and knowledge, they build several formal structures and you inform inside of information of the organization, in addition, the information scanning and information mining activities generate information services and products systematized, with high value aggregate.

ENVIRONMENTAL MONITORING AT THE NALUNAQ GOLD MINE, SOUTH GREENLAND, 2015

DEFF Research Database (Denmark)

Bach, Lis; Birch Larsen, Morten

the monitoring in 2014, the area has been without any activity. The mining company Angel Mining Gold A/S closed its gold production in November 2013 where after the Nalunaq area was affected by decommissioning and restoration until August 2014. The gold was extracted by chemical extraction with cyanide (carbon......-in-pulp). Due to the use of cyanide to extract gold from the ore, there was strict monitoring with the outflow of cyanide from the mine to the valley during the production period, and monitoring will continue for 5 years after the closure. Also, extensive monitoring is conducted to reveal release of metals...

A Remote Sensing Approach to Environmental Monitoring in a Reclaimed Mine Area

Directory of Open Access Journals (Sweden)

Rajchandar Padmanaban

2017-12-01

Full Text Available Mining for resources extraction may lead to geological and associated environmental changes due to ground movements, collision with mining cavities, and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a reclaimed mine area may experience surface area collapse, i.e., subsidence, and degradation of vegetation productivity. Thus, monitoring short-term landscape dynamics in a reclaimed mine area may provide important information on the long-term geological and environmental impacts of mining activities. We studied landscape dynamics in Kirchheller Heide, Germany, which experienced extensive soil movement due to longwall mining without stowing, using Landsat imageries between 2013 and 2016. A Random Forest image classification technique was applied to analyze land-use and landcover dynamics, and the growth of wetland areas was assessed using a Spectral Mixture Analysis (SMA. We also analyzed the changes in vegetation productivity using a Normalized Difference Vegetation Index (NDVI. We observed a 19.9% growth of wetland area within four years, with 87.2% growth in the coverage of two major waterbodies in the reclaimed mine area. NDVI values indicate that the productivity of 66.5% of vegetation of the Kirchheller Heide was degraded due to changes in ground water tables and surface flooding. Our results inform environmental management and mining reclamation authorities about the subsidence spots and priority mitigation areas from land surface and vegetation degradation in Kirchheller Heide.

Mining of relations between proteins over biomedical scientific literature using a deep-linguistic approach.

Science.gov (United States)

Rinaldi, Fabio; Schneider, Gerold; Kaljurand, Kaarel; Hess, Michael; Andronis, Christos; Konstandi, Ourania; Persidis, Andreas

2007-02-01

The amount of new discoveries (as published in the scientific literature) in the biomedical area is growing at an exponential rate. This growth makes it very difficult to filter the most relevant results, and thus the extraction of the core information becomes very expensive. Therefore, there is a growing interest in text processing approaches that can deliver selected information from scientific publications, which can limit the amount of human intervention normally needed to gather those results. This paper presents and evaluates an approach aimed at automating the process of extracting functional relations (e.g. interactions between genes and proteins) from scientific literature in the biomedical domain. The approach, using a novel dependency-based parser, is based on a complete syntactic analysis of the corpus. We have implemented a state-of-the-art text mining system for biomedical literature, based on a deep-linguistic, full-parsing approach. The results are validated on two different corpora: the manually annotated genomics information access (GENIA) corpus and the automatically annotated arabidopsis thaliana circadian rhythms (ATCR) corpus. We show how a deep-linguistic approach (contrary to common belief) can be used in a real world text mining application, offering high-precision relation extraction, while at the same time retaining a sufficient recall.

Sustainable Remediation of Legacy Mine Drainage: A Case Study of the Flight 93 National Memorial

Science.gov (United States)

Emili, Lisa A.; Pizarchik, Joseph; Mahan, Carolyn G.

2016-03-01

Pollution from mining activities is a global environmental concern, not limited to areas of current resource extraction, but including a broader geographic area of historic (legacy) and abandoned mines. The pollution of surface waters from acid mine drainage is a persistent problem and requires a holistic and sustainable approach to addressing the spatial and temporal complexity of mining-specific problems. In this paper, we focus on the environmental, socio-economic, and legal challenges associated with the concurrent activities to remediate a coal mine site and to develop a national memorial following a catastrophic event. We provide a conceptual construct of a socio-ecological system defined at several spatial, temporal, and organizational scales and a critical synthesis of the technical and social learning processes necessary to achieving sustainable environmental remediation. Our case study is an example of a multi-disciplinary management approach, whereby collaborative interaction of stakeholders, the emergence of functional linkages for information exchange, and mediation led to scientifically informed decision making, creative management solutions, and ultimately environmental policy change.

Monitoring, analyzing and simulating of spatial-temporal changes of landscape pattern over mining area

Science.gov (United States)

Liu, Pei; Han, Ruimei; Wang, Shuangting

2014-11-01

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

Text mining patents for biomedical knowledge.

Science.gov (United States)

Rodriguez-Esteban, Raul; Bundschus, Markus

2016-06-01

Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

Study of the economic valuation of uranium deposits and mine-projects

International Nuclear Information System (INIS)

Alnajim, N.

1980-01-01

A basis is provided for the decisions to be made in connection with the exploration, development mining, processing and marketing of the uranium. Details are given about the kinds and forms of the mines, about the exploration-, extraction- and processing technologies as well as the economicly best extractive processing of uranium. The profitability of uranium mining projects is evaluated according to the economy calculation method. (DG) [de

A preliminary approach to creating an overview of lactoferrin multi-functionality utilizing a text mining method.

Science.gov (United States)

Shimazaki, Kei-ichi; Kushida, Tatsuya

2010-06-01

Lactoferrin is a multi-functional metal-binding glycoprotein that exhibits many biological functions of interest to many researchers from the fields of clinical medicine, dentistry, pharmacology, veterinary medicine, nutrition and milk science. To date, a number of academic reports concerning the biological activities of lactoferrin have been published and are easily accessible through public data repositories. However, as the literature is expanding daily, this presents challenges in understanding the larger picture of lactoferrin function and mechanisms. In order to overcome the "analysis paralysis" associated with lactoferrin information, we attempted to apply a text mining method to the accumulated lactoferrin literature. To this end, we used the information extraction system GENPAC (provided by Nalapro Technologies Inc., Tokyo). This information extraction system uses natural language processing and text mining technology. This system analyzes the sentences and titles from abstracts stored in the PubMed database, and can automatically extract binary relations that consist of interactions between genes/proteins, chemicals and diseases/functions. We expect that such information visualization analysis will be useful in determining novel relationships among a multitude of lactoferrin functions and mechanisms. We have demonstrated the utilization of this method to find pathways of lactoferrin participation in neovascularization, Helicobacter pylori attack on gastric mucosa, atopic dermatitis and lipid metabolism.

Integrating Data Mining Techniques into Telemedicine Systems

Directory of Open Access Journals (Sweden)

Mihaela GHEORGHE

2014-01-01

Full Text Available The medical system is facing a wide range of challenges nowadays due to changes that are taking place in the global healthcare systems. These challenges are represented mostly by economic constraints (spiraling costs, financial issues, but also, by the increased emphasis on accountability and transparency, changes that were made in the education field, the fact that the biomedical research keeps growing in what concerns the complexities of the specific studies etc. Also the new partnerships that were made in medical care systems and the great advances in IT industry suggest that a predominant paradigm shift is occurring. This needs a focus on interaction, collaboration and increased sharing of information and knowledge, all of these may is in turn be leading healthcare organizations to embrace the techniques of data mining in order to create and sustain optimal healthcare outcomes. Data mining is a domain of great importance nowadays as it provides advanced data analysis techniques for extracting the knowledge from the huge volumes of data collected and stored by every system of a daily basis. In the healthcare organizations data mining can provide valuable information for patient's diagnosis and treatment planning, customer relationship management, organization resources management or fraud detection. In this article we focus on describing the importance of data mining techniques and systems for healthcare organizations with a focus on developing and implementing telemedicine solution in order to improve the healthcare services provided to the patients. We provide architecture for integrating data mining techniques into telemedicine systems and also offer an overview on understanding and improving the implemented solution by using Business Process Management methods.

Imprinted magnetic graphene oxide for the mini-solid phase extraction of Eu (III) from coal mine area

Science.gov (United States)

Patra, Santanu; Roy, Ekta; Madhuri, Rashmi; Sharma, Prashant K.

2017-05-01

The present work represents the preparation of imprinted magnetic reduced graphene oxide and applied it for the selective removal of Eu (III) from local coal mines area. A simple solid phase extraction method was used for this purpose. The material shows a very high adsorption as well as removal efficiency towards Eu (III), which suggest that the material have potential to be used in future for their real time applications in removal of Eu (III) from complex matrices.

Early Prediction of Students' Grade Point Averages at Graduation: A Data Mining Approach

Science.gov (United States)

Tekin, Ahmet

2014-01-01

Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…

Design of data warehouse in teaching state based on OLAP and data mining

Science.gov (United States)

Zhou, Lijuan; Wu, Minhua; Li, Shuang

2009-04-01

The data warehouse and the data mining technology is one of information technology research hot topics. At present the data warehouse and the data mining technology in aspects and so on commercial, financial industry as well as enterprise's production, market marketing obtained the widespread application, but is relatively less in educational fields' application. Over the years, the teaching and management have been accumulating large amounts of data in colleges and universities, while the data can not be effectively used, in the light of social needs of the university development and the current status of data management, the establishment of data warehouse in university state, the better use of existing data, and on the basis dealing with a higher level of disposal --data mining are particularly important. In this paper, starting from the decision-making needs design data warehouse structure of university teaching state, and then through the design structure and data extraction, loading, conversion create a data warehouse model, finally make use of association rule mining algorithm for data mining, to get effective results applied in practice. Based on the data analysis and mining, get a lot of valuable information, which can be used to guide teaching management, thereby improving the quality of teaching and promoting teaching devotion in universities and enhancing teaching infrastructure. At the same time it can provide detailed, multi-dimensional information for universities assessment and higher education research.

High utility-itemset mining and privacy-preserving utility mining

Directory of Open Access Journals (Sweden)

Jerry Chun-Wei Lin

2016-03-01

Full Text Available In recent decades, high-utility itemset mining (HUIM has emerging a critical research topic since the quantity and profit factors are both concerned to mine the high-utility itemsets (HUIs. Generally, data mining is commonly used to discover interesting and useful knowledge from massive data. It may, however, lead to privacy threats if private or secure information (e.g., HUIs are published in the public place or misused. In this paper, we focus on the issues of HUIM and privacy-preserving utility mining (PPUM, and present two evolutionary algorithms to respectively mine HUIs and hide the sensitive high-utility itemsets in PPUM. Extensive experiments showed that the two proposed models for the applications of HUIM and PPUM can not only generate the high quality profitable itemsets according to the user-specified minimum utility threshold, but also enable the capability of privacy preserving for private or secure information (e.g., HUIs in real-word applications.

Improvements mineral dressing and extraction processes of gold-silver ores from San Pedro Frio Mining District, Colombia

International Nuclear Information System (INIS)

Yanez Traslavina, J. J.; Vargas Avila, M. A.; Garcia Paez, I. H.; Pedraza Rosas, J. E.

2005-01-01

The San Pedro Frio district mining, Colombia, is a rich region production gold-silver ores. Nowadays, the extraction processes used are amalgamation, percolation cyanidation and precipitation with zinc wood. Due to the ignorance of the ore characteristics, gold and silver treatment processes are inadequate and not efficient. In addition the inappropriate use of mercury and cyanide cause environmental contamination. In this research the ore characterization was carried out obtained fundamental parameters for the technical selection of more efficient gold and silver extraction processes. Experimental work was addressed to the study of both processes the agitation cyanidation and the adsorption on activated carbon in pulp. As a final result proposed a flowsheet to improve the precious metals recovery and reduce the environment contamination. (Author)

STUDY ON PHYTO-EXTRACTION BALANCE OF ZN, CD AND PB FROM MINE-WASTE POLLUTED SOILS BY USING FESTUCA ARUNDINACEA AND LOLIUM PERENNE SPECIES

Directory of Open Access Journals (Sweden)

B. LIXANDRU

2009-05-01

Full Text Available Through the cultivation of tall fescue (Festuca arundinacea and of perennial ryegrass for two years on a chernozem type of soil, in the Banat's plain area we investigated the phyto-extraction potential of Zn, Cd and Pb. In the experimental plot it has been incorporated a quantity of 20 kg of mine-waste per square meter, in a mass ratio of 1:2,5. The mine-waste polluting "contribution" was of 1209 mg Zn / kg d.s., 4.70 mg Cd / kg d.s. and 188.2 mg Pb / kg d.s. The metals content in the soil was determined at the two moments of biomass harvesting, and through balance calculations we could establish the phyto-extraction efficiency of the two foragegrasses species. The obtained results indicate that Festuca arundinacea has an average phyto-extraction yield of 50% for Zn and Cd in the soil; in the case of an ionic excess of 3,5 to 4 times, the phyto-extraction efficiency is reduced, more obvious in the case of Pb (lead ions. The species Lolium perenne registers a yield of almost 92% in the process of phyto-extraction of Zn. The yield values for Cd si Pb are lower, but comparable with the control plot. Unlike Festuca arundinacea, the Lollium perenne species tolerates better the Cd and Pb ionic excess.

Social mobilisation and violence at the mining frontier

NARCIS (Netherlands)

Middeldorp, Nick; Morales, Carlos; Haar, van der Gemma

2016-01-01

This paper documents opposition to mining in Honduras, a country at the verge of an attempted ‘mining boom’ since the ratification of a new mining law in April 2013. It analyses how a broad movement – involving NGOs, social movements and local communities – engages in opposition to the extractive

21 Recipes for Mining Twitter

CERN Document Server

Russell, Matthew

2011-01-01

Millions of public Twitter streams harbor a wealth of data, and once you mine them, you can gain some valuable insights. This short and concise book offers a collection of recipes to help you extract nuggets of Twitter information using easy-to-learn Python tools. Each recipe offers a discussion of how and why the solution works, so you can quickly adapt it to fit your particular needs. The recipes include techniques to: Use OAuth to access Twitter dataCreate and analyze graphs of retweet relationshipsUse the streaming API to harvest tweets in realtimeHarvest and analyze friends and followers

A Survey of Text Mining in Social Media: Facebook and Twitter Perspectives

Directory of Open Access Journals (Sweden)

Said A. Salloum

2017-01-01

Full Text Available Text mining has become one of the trendy fields that has been incorporated in several research fields such as computational linguistics, Information Retrieval (IR and data mining. Natural Language Processing (NLP techniques were used to extract knowledge from the textual text that is written by human beings. Text mining reads an unstructured form of data to provide meaningful information patterns in a shortest time period. Social networking sites are a great source of communication as most of the people in today’s world use these sites in their daily lives to keep connected to each other. It becomes a common practice to not write a sentence with correct grammar and spelling. This practice may lead to different kinds of ambiguities like lexical, syntactic, and semantic and due to this type of unclear data, it is hard to find out the actual data order. Accordingly, we are conducting an investigation with the aim of looking for different text mining methods to get various textual orders on social media websites. This survey aims to describe how studies in social media have used text analytics and text mining techniques for the purpose of identifying the key themes in the data. This survey focused on analyzing the text mining studies related to Facebook and Twitter; the two dominant social media in the world. Results of this survey can serve as the baselines for future text mining research.

Geotechnical design of underground slate mines

International Nuclear Information System (INIS)

Iglesias Comesaña, C.; Taboada Castro, J.; Arzúa Touriño, J.; Giráldez Pérez, E.; Martín Suárez, J.M.

2017-01-01

Slate is one of the most important natural materials in Spain, with a potent extractive and processing industry concentrated in the autonomous communities of Galicia, Castile and León. Thanks to its resistance to external agents, its impermeability and its excellent cleavability, slate is used as for roofing and tiling. Almost all the active exploitations in our country where this resource is extracted are open pit mines, where the exploitation ratios have nearly reached their economic limit, making it necessary to look for alternatives that will allow the mining works to be continued. Underground mining is a solution that offers low exploitation ratios, with low spoil generation. The room-and-pillar method with barrier pillars is usually applied for the exploitation of slate deposits. There are several factors to be taken into account when designing a mine (economic, logistical, geotechnical, technical, environmental…), especially for an underground mine. This study focuses on the geotechnical design process of a room-and-pillar underground mine, based on the tributary area theory, the analysis of the tensions in the ground with numerical methods and the choice of an appropriate reinforcement in view of the expected instabilities. This explanation is completed with an example of a design that includes the estimate exploitation rates and production. [es

Underground mining of the lower 163 zone through groundwater drainage at the Eagle Point Mine

International Nuclear Information System (INIS)

Robson, D.M.; Bashir, R.; Thomson, J.; Klemmer, S.; Rigden, A.

2010-01-01

The Eagle Point Mine is part of the Cameco Rabbit Lake Operation. The mine produces uranium ore using the long-hole, vertical and horizontal retreat mining method. The majority of the mine workings are under Wollaston Lake and cementitious grouting is used as one of the water control measures. Historical groundwater table in the mining area was close to ground surface. The Lower 163 Zone encompasses an estimated 4.2 million pounds U_3O_8 geological resource that was not considered feasible to mine due to the expected groundwater flows in the area. Cross-hole testing was conducted to better understand the groundwater flow through various geologic units. A local depressurization test was conducted to assess the potential for lowering the water table. Following testing an active depressurization was conducted to lower the groundwater table below the planned mining areas. This resulted in safe and drier mining conditions and allowed for the successful extraction of the ore body. (author)

Geochemistry and mineralogy of arsenic in mine wastes and stream sediments in a historic metal mining area in the UK

Energy Technology Data Exchange (ETDEWEB)

Rieuwerts, J.S., E-mail: jrieuwerts@plymouth.ac.uk [School of Geography, Earth and Environmental Sciences, Plymouth University, Plymouth PL4 8AA (United Kingdom); Mighanetara, K.; Braungardt, C.B. [School of Geography, Earth and Environmental Sciences, Plymouth University, Plymouth PL4 8AA (United Kingdom); Rollinson, G.K. [Camborne School of Mines, CEMPS, University of Exeter, Tremough Campus, Penryn, Cornwall TR10 9EZ (United Kingdom); Pirrie, D. [Helford Geoscience LLP, Menallack Farm, Treverva, Penryn, Cornwall TR10 9BP (United Kingdom); Azizi, F. [School of Geography, Earth and Environmental Sciences, Plymouth University, Plymouth PL4 8AA (United Kingdom)

2014-02-01

Mining generates large amounts of waste which may contain potentially toxic elements (PTE), which, if released into the wider environment, can cause air, water and soil pollution long after mining operations have ceased. The fate and toxicological impact of PTEs are determined by their partitioning and speciation and in this study, the concentrations and mineralogy of arsenic in mine wastes and stream sediments in a former metal mining area of the UK are investigated. Pseudo-total (aqua-regia extractable) arsenic concentrations in all samples from the mining area exceeded background and guideline values by 1–5 orders of magnitude, with a maximum concentration in mine wastes of 1.8 × 10{sup 5} mg kg{sup −1} As and concentrations in stream sediments of up to 2.5 × 10{sup 4} mg kg{sup −1} As, raising concerns over potential environmental impacts. Mineralogical analysis of the wastes and sediments was undertaken by scanning electron microscopy (SEM) and automated SEM-EDS based quantitative evaluation (QEMSCAN®). The main arsenic mineral in the mine waste was scorodite and this was significantly correlated with pseudo-total As concentrations and significantly inversely correlated with potentially mobile arsenic, as estimated from the sum of exchangeable, reducible and oxidisable arsenic fractions obtained from a sequential extraction procedure; these findings correspond with the low solubility of scorodite in acidic mine wastes. The work presented shows that the study area remains grossly polluted by historical mining and processing and illustrates the value of combining mineralogical data with acid and sequential extractions to increase our understanding of potential environmental threats. - Highlights: • Stream sediments in a former mining area remain polluted with up to 25 g As per kg. • The main arsenic mineral in adjacent mine wastes appears to be scorodite. • Low solubility scorodite was inversely correlated with potentially mobile As. • Combining

Geochemistry and mineralogy of arsenic in mine wastes and stream sediments in a historic metal mining area in the UK

International Nuclear Information System (INIS)

Rieuwerts, J.S.; Mighanetara, K.; Braungardt, C.B.; Rollinson, G.K.; Pirrie, D.; Azizi, F.

2014-01-01

Mining generates large amounts of waste which may contain potentially toxic elements (PTE), which, if released into the wider environment, can cause air, water and soil pollution long after mining operations have ceased. The fate and toxicological impact of PTEs are determined by their partitioning and speciation and in this study, the concentrations and mineralogy of arsenic in mine wastes and stream sediments in a former metal mining area of the UK are investigated. Pseudo-total (aqua-regia extractable) arsenic concentrations in all samples from the mining area exceeded background and guideline values by 1–5 orders of magnitude, with a maximum concentration in mine wastes of 1.8 × 10 5 mg kg −1 As and concentrations in stream sediments of up to 2.5 × 10 4 mg kg −1 As, raising concerns over potential environmental impacts. Mineralogical analysis of the wastes and sediments was undertaken by scanning electron microscopy (SEM) and automated SEM-EDS based quantitative evaluation (QEMSCAN®). The main arsenic mineral in the mine waste was scorodite and this was significantly correlated with pseudo-total As concentrations and significantly inversely correlated with potentially mobile arsenic, as estimated from the sum of exchangeable, reducible and oxidisable arsenic fractions obtained from a sequential extraction procedure; these findings correspond with the low solubility of scorodite in acidic mine wastes. The work presented shows that the study area remains grossly polluted by historical mining and processing and illustrates the value of combining mineralogical data with acid and sequential extractions to increase our understanding of potential environmental threats. - Highlights: • Stream sediments in a former mining area remain polluted with up to 25 g As per kg. • The main arsenic mineral in adjacent mine wastes appears to be scorodite. • Low solubility scorodite was inversely correlated with potentially mobile As. • Combining mineralogical and

Data Mining Aplications in Livestock

Directory of Open Access Journals (Sweden)

Feyza ALEV ÇETİN

2016-03-01

Full Text Available Data mining provides discovering the required and applicable knowledge from very large amounts of information collected in one centre. Data mining has been used in the information industry and society. Although many methods of data mining has been used, these techniques has been remarkable in animal husbandry in recent years. For the solution of complex problems in animal husbandry many methods were discussed and developed. Brief information on data mining techniques such as k-means approach, k-nearest neighbor approach, multivariate adaptive regression function (MARS, naive Bayesian classifiers (NBC, artificial neural networks (ANN, support vector machines (SVM, decision trees are given in the study. Some data mining methods are presented and examples of the application of data mining in the field of animal husbandry in the world are provided with this study.

Using text-mining techniques in electronic patient records to identify ADRs from medicine use

DEFF Research Database (Denmark)

Warrer, Pernille; Hansen, Ebba Holme; Jensen, Lars Juhl

2012-01-01

This literature review included studies that use text-mining techniques in narrative documents stored in electronic patient records (EPRs) to investigate ADRs. We searched PubMed, Embase, Web of Science and International Pharmaceutical Abstracts without restrictions from origin until July 2011. We...... included empirically based studies on text mining of electronic patient records (EPRs) that focused on detecting ADRs, excluding those that investigated adverse events not related to medicine use. We extracted information on study populations, EPR data sources, frequencies and types of the identified ADRs......, medicines associated with ADRs, text-mining algorithms used and their performance. Seven studies, all from the United States, were eligible for inclusion in the review. Studies were published from 2001, the majority between 2009 and 2010. Text-mining techniques varied over time from simple free text...

QTLTableMiner++: semantic mining of QTL tables in scientific articles.

Science.gov (United States)

Singh, Gurnoor; Kuzniar, Arnold; van Mulligen, Erik M; Gavai, Anand; Bachem, Christian W; Visser, Richard G F; Finkers, Richard

2018-05-25

A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner ++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats.

30 CFR 75.1200-1 - Additional information on mine map.

Science.gov (United States)

2010-07-01

... SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Maps § 75.1200-1 Additional... symbols; (g) The location of railroad tracks and public highways leading to the mine, and mine buildings... permanent base line points coordinated with the underground and surface mine traverses, and the location and...

Decomposing Petri nets for process mining : a generic approach

NARCIS (Netherlands)

Aalst, van der W.M.P.

2012-01-01

The practical relevance of process mining is increasing as more and more event data become available. Process mining techniques aim to discover, monitor and improve real processes by extracting knowledge from event logs. The two most prominent process mining tasks are: (i) process discovery:

A data mining based model for selecting type of treatment for kidney stone patients

Directory of Open Access Journals (Sweden)

Sepehri MM

2009-09-01

Full Text Available "n Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Background: Data mining as a multidisciplinary field is rooted in the fields such as statistics, mathematics, computer science and artificial intelligence and has been gaining momentum in scientific, managerial, and executive applications in health care. Data mining can be defined as the automated extraction of valuable, practical and hidden knowledge and information from large data. Applying data mining in medical records and data is of utmost importance for health care givers and providers and brings vital and valuable outcomes. Data mining can help doctors come up with better recommendations and plans for treatment which actually in many respects have significant impact on patients' life and satisfaction In this paper we have proposed and utilized data mining methods to extract hidden information in medical records of pelvis stone patients with ureteral stone. We have tried to design a decision support system model to be applicable for selecting type of treatment for these groups of patients."n"nMethods: We gathered needed information from Shahid Hashemi Nejad hospital. In this research we have used decision tree as a data mining tool, for selecting suitable treatment for patients with ureteral stone. This

Possibility of uranium synthesis from radioactive waste and mine waters of uranium mine kiik-tol of Tajikistan

International Nuclear Information System (INIS)

Mirsaidov, U.M.; Hakimov, N.

2005-01-01

The article investigates the method of synthesis of U 3 O 8 from radioactive waste of Gafurov District of Republic of Tajikistan and uranium extraction from mine waters of Kiik-Tol mine. In addition, the authors showed the method of solubility of Uranium Oxide U 3 O 8

Identification of Social and Environmental Conflicts Resulting from Open-Cast Mining

Science.gov (United States)

Górniak-Zimroz, Justyna; Pactwa, Katarzyna

2016-10-01

Open-cast mining is related to interference in the natural environment. It also affects human health and quality of life. This influence is, among others, dependent on the type of extracted materials, size of deposit, methods of mining and mineral processing, as well as, equally important, sensitivity of the environment within which mining is planned. The negative effects of mining include deformations of land surface or contamination of soils, air and water. What is more, in many cases, mining for minerals leads to clearing of housing and transport infrastructures located within the mining area, a decrease in values of the properties in the immediate vicinity of a deposit, and an increase in stress levels in local residents exposed to noise. The awareness of negative consequences of taking up open-cast mining activity leads to conflicts between a mining entrepreneur and self-government authorities, society or nongovernment organisations. The article attempts to identify potential social and environmental conflicts that may occur in relation to a planned mining activity. The results of the analyses were interpreted with respect to the deposits which were or have been mined. That enabled one to determine which facilities exclude mineral mining and which allow it. The research took the non-energy mineral resources into consideration which are included in the group of solid minerals located in one of the districts of Lower Silesian Province (SW Poland). The spatial analyses used the tools available in the geographical information systems

DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW

OpenAIRE

Pragati Sharma; Dr. Sanjiv Sharma

2018-01-01

Recently, data mining is gaining more popularity among researcher. Data mining provides various techniques and methods for analysing data produced by various applications of different domain. Similarly, Educational mining is providing a way for analyzing educational data set. Educational mining concerns with developing methods for discovering knowledge from data that come from educational field and it helps to extract the hidden patterns and to discover new knowledge from large educational da...

IMPROVMENT OF THE MINING METHOD IN THE BAUXITE MINE ĆUKOVAC-GRIŽINICA

Directory of Open Access Journals (Sweden)

Borislav Perić

1992-12-01

Full Text Available Exploitation of bauxite in region of Dalmatia has tradition of more than 50 years. The biggest underground mine of this bauxite hearing area was developed in deposit Ćukovac-Grižinica with proved workable reserves of 1.2 x 106 t. Yearly output in 1990. was 100.000 t. Production in this mine started 1987, and sublevel caving method was used. Coefficient of extraction in the parts with weak rocks is low, and unsufficient security in the conditions with firm roof. Therefore investigation of improvement of mining method was carrying on to coinside characteristics of rocks, and mining methods. Following methods were selected: sublevel caving (actually retreat stoping, sublevel sloping and sublevel caving with bauxite protection layer (the paper is published in Croatian.

Textual information access statistical models

CERN Document Server

Gaussier, Eric

2013-01-01

This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access:- information extraction and retrieval;- text classification and clustering;- opinion mining;- comprehension aids (automatic summarization, machine translation, visualization).In order to give the reader as complete a description as possible, the focus is placed on the probability models used in the applications

Socioeconomic inequality of cancer mortality in the United States: a spatial data mining approach

Directory of Open Access Journals (Sweden)

Lam Nina SN

2006-02-01

Full Text Available Abstract Background The objective of this study was to demonstrate the use of an association rule mining approach to discover associations between selected socioeconomic variables and the four most leading causes of cancer mortality in the United States. An association rule mining algorithm was applied to extract associations between the 1988–1992 cancer mortality rates for colorectal, lung, breast, and prostate cancers defined at the Health Service Area level and selected socioeconomic variables from the 1990 United States census. Geographic information system technology was used to integrate these data which were defined at different spatial resolutions, and to visualize and analyze the results from the association rule mining process. Results Health Service Areas with high rates of low education, high unemployment, and low paying jobs were found to associate with higher rates of cancer mortality. Conclusion Association rule mining with geographic information technology helps reveal the spatial patterns of socioeconomic inequality in cancer mortality in the United States and identify regions that need further attention.

A diagnostic of the strategy employed for communicating nuclear related information to Brazilian communities around uranium mining areas

International Nuclear Information System (INIS)

Ferrari Dias, Fabiana; Tirollo Taddei, Maria H.

2008-01-01

This paper presents a diagnostic of the strategy used by the Brazilian uranium mining industry to communicate nuclear related information to communities around a mining area. The uranium mining industry in Brazil, which is run by the government, has been concerned with communication issues for quite some time. The need to communicate became more apparent after new mining operations started in the Northern region of Brazil. The fact that the government does not have a clear communication guideline made the operators of the uranium mining industry aware of the increasing demand for establishment of a good relationship with several types of Stake holders as well as employment of personnel with experience in dealing with them. A diagnostic of the current communication situation in Brazil and an analysis of the approaches over the past years was done through interviews with employees of the mining industry and review of institutional communication materials. The results were discussed during a Consultant's Meeting organized by the IAEA 's Seibersdorf Laboratory in October 2007. The output of the meeting included an overview of modern communication strategies used by different countries and a suggestion for new uranium mining operations in developing or under developed countries. The strategy for communicating nuclear related information to Brazilian communities varied according to the influence of different Stake holder groups. One initiative worth mentioning was the creation of a Mobile Nuclear Information Thematic Room, which was installed in several locations. This project was seen as one of the main tools to relate to community. Many Stake holders were identified during the diagnostic phase in preparation for the IAEA 's meeting on communication strategy: children, NGOs (Non Government Organizations), local churches, media and internal Stake holders, among others. An initial evaluation showed that the perception of a neighbouring community regarding an uranium

Aquifer restoration techniques for in-situ leach uranium mines

International Nuclear Information System (INIS)

Deutsch, W.J.; Bell, N.E.; Mercer, B.W.; Serne, R.J.; Shade, J.W.; Tweeton, D.R.

1984-02-01

In-situ leach uranium mines and pilot-scale test facilities are currently operating in the states of Wyoming, Texas, New Mexico and Colorado. This report summarizes the technical considerations involved in restoring a leached ore zone and its aquifer to the required level. Background information is provided on the geology and geochemistry of mineralized roll-front deposits and on the leaching techniques used to extract the uranium. 13 references, 13 figures, 4 tables

Environmental Monitoring at the Nalunaq Gold Mine, South Greenland, 2011

DEFF Research Database (Denmark)

Bach, Lis; Asmund, Gert; Søndergaard, Jens

the monitoring in 2010, the mining company Gold Angel Mining A/S is breaking new ore, but is also carrying previously broken ore with low grade back to the mine with vehicles with limited speed and load capacity. The gold is recovered by the use of chemical extraction (carbon-in-pulp) using cyanide. Due...... to the use of cyanide to extract gold from the ore, strict control with the outfl ow of cyanide from the mine to the Kirkespir Valley is performed. The described impact on the environment of the Kirkespir Valley, both terrestrial, freshwater and marine, is considered to be minor, and is generally lower than...

Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010.

Science.gov (United States)

de Bruijn, Berry; Cherry, Colin; Kiritchenko, Svetlana; Martin, Joel; Zhu, Xiaodan

2011-01-01

As clinical text mining continues to mature, its potential as an enabling technology for innovations in patient care and clinical research is becoming a reality. A critical part of that process is rigid benchmark testing of natural language processing methods on realistic clinical narrative. In this paper, the authors describe the design and performance of three state-of-the-art text-mining applications from the National Research Council of Canada on evaluations within the 2010 i2b2 challenge. The three systems perform three key steps in clinical information extraction: (1) extraction of medical problems, tests, and treatments, from discharge summaries and progress notes; (2) classification of assertions made on the medical problems; (3) classification of relations between medical concepts. Machine learning systems performed these tasks using large-dimensional bags of features, as derived from both the text itself and from external sources: UMLS, cTAKES, and Medline. Performance was measured per subtask, using micro-averaged F-scores, as calculated by comparing system annotations with ground-truth annotations on a test set. The systems ranked high among all submitted systems in the competition, with the following F-scores: concept extraction 0.8523 (ranked first); assertion detection 0.9362 (ranked first); relationship detection 0.7313 (ranked second). For all tasks, we found that the introduction of a wide range of features was crucial to success. Importantly, our choice of machine learning algorithms allowed us to be versatile in our feature design, and to introduce a large number of features without overfitting and without encountering computing-resource bottlenecks.

Cluo: Web-Scale Text Mining System For Open Source Intelligence Purposes

Directory of Open Access Journals (Sweden)

Przemyslaw Maciolek

2013-01-01

Full Text Available The amount of textual information published on the Internet is considered tobe in billions of web pages, blog posts, comments, social media updates andothers. Analyzing such quantities of data requires high level of distribution –both data and computing. This is especially true in case of complex algorithms,often used in text mining tasks.The paper presents a prototype implementation of CLUO – an Open SourceIntelligence (OSINT system, which extracts and analyzes significant quantitiesof openly available information.

Opinion mining on book review using CNN-L2-SVM algorithm

Science.gov (United States)

Rozi, M. F.; Mukhlash, I.; Soetrisno; Kimura, M.

2018-03-01

Review of a product can represent quality of a product itself. An extraction to that review can be used to know sentiment of that opinion. Process to extract useful information of user review is called Opinion Mining. Review extraction model that is enhancing nowadays is Deep Learning model. This Model has been used by many researchers to obtain excellent performance on Natural Language Processing. In this research, one of deep learning model, Convolutional Neural Network (CNN) is used for feature extraction and L2 Support Vector Machine (SVM) as classifier. These methods are implemented to know the sentiment of book review data. The result of this method shows state-of-the art performance in 83.23% for training phase and 64.6% for testing phase.

Genomic research and data-mining technology: implications for personal privacy and informed consent.

Science.gov (United States)

Tavani, Herman T

2004-01-01

This essay examines issues involving personal privacy and informed consent that arise at the intersection of information and communication technology (ICT) and population genomics research. I begin by briefly examining the ethical, legal, and social implications (ELSI) program requirements that were established to guide researchers working on the Human Genome Project (HGP). Next I consider a case illustration involving deCODE Genetics, a privately owned genetic company in Iceland, which raises some ethical concerns that are not clearly addressed in the current ELSI guidelines. The deCODE case also illustrates some ways in which an ICT technique known as data mining has both aided and posed special challenges for researchers working in the field of population genomics. On the one hand, data-mining tools have greatly assisted researchers in mapping the human genome and in identifying certain "disease genes" common in specific populations (which, in turn, has accelerated the process of finding cures for diseases tha affect those populations). On the other hand, this technology has significantly threatened the privacy of research subjects participating in population genomics studies, who may, unwittingly, contribute to the construction of new groups (based on arbitrary and non-obvious patterns and statistical correlations) that put those subjects at risk for discrimination and stigmatization. In the final section of this paper I examine some ways in which the use of data mining in the context of population genomics research poses a critical challenge for the principle of informed consent, which traditionally has played a central role in protecting the privacy interests of research subjects participating in epidemiological studies.

30 CFR 750.21 - Coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Coal extraction incidental to the extraction of... ENFORCEMENT, DEPARTMENT OF THE INTERIOR INDIAN LANDS PROGRAM REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON INDIAN LANDS § 750.21 Coal extraction incidental to the extraction of other minerals...

Hydrochemical characteristics of mine waters from abandoned mining sites in Serbia and their impact on surface water quality.

Science.gov (United States)

Atanacković, Nebojša; Dragišić, Veselin; Stojković, Jana; Papić, Petar; Zivanović, Vladimir

2013-11-01

Upon completion of exploration and extraction of mineral resources, many mining sites have been abandoned without previously putting environmental protection measures in place. As a consequence, mine waters originating from such sites are discharged freely into surface water. Regional scale analyses were conducted to determine the hydrochemical characteristics of mine waters from abandoned sites featuring metal (Cu, Pb-Zn, Au, Fe, Sb, Mo, Bi, Hg) deposits, non-metallic minerals (coal, Mg, F, B) and uranium. The study included 80 mine water samples from 59 abandoned mining sites. Their cation composition was dominated by Ca2+, while the most common anions were found to be SO4(2-) and HCO3-. Strong correlations were established between the pH level and metal (Fe, Mn, Zn, Cu) concentrations in the mine waters. Hierarchical cluster analysis was applied to parameters generally indicative of pollution, such as pH, TDS, SO4(2-), Fe total, and As total. Following this approach, mine water samples were grouped into three main clusters and six subclusters, depending on their potential environmental impact. Principal component analysis was used to group together variables that share the same variance. The extracted principal components indicated that sulfide oxidation and weathering of silicate and carbonate rocks were the primary processes, while pH buffering, adsorption and ion exchange were secondary drivers of the chemical composition of the analyzed mine waters. Surface waters, which received the mine waters, were examined. Analysis showed increases of sulfate and metal concentrations and general degradation of surface water quality.

BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language.

Science.gov (United States)

Rinaldi, Fabio; Ellendorff, Tilia Renate; Madan, Sumit; Clematide, Simon; van der Lek, Adrian; Mevissen, Theo; Fluck, Juliane

2016-01-01

Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach this complexity using fragments of large-scale manually curated biological networks, represented in Biological Expression Language (BEL), as training and test data. BEL is an advanced knowledge representation format which has been designed to be both human readable and machine processable. The specific goal of track 4 was to evaluate text mining systems capable of automatically constructing BEL statements from given evidence text, and of retrieving evidence text for given BEL statements. Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements. We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels. The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text. © The Author(s) 2016. Published by Oxford University Press.

Perception versus reality: Bridging the gap between quantitative and qualitative information relating to the risks of uranium mining

International Nuclear Information System (INIS)

Needham, S.

2002-01-01

Environmental impact of uranium mining in Australia is frequently raised as an issue of public concern. However, the level of concern both in terms of public agitation and political response has diminished over the last decade, largely as a consequence of many years of demonstrated high levels of environmental protection achieved at Australian uranium mines. Another reason is because of improved information now accessible to the public on mine environmental management systems, monitoring results, and audit outcomes. This paper describes some communication methods developed for the uranium mines of the Alligator Rivers Region of the Northern Territory. These methods have improved the effectiveness of dialogue between stakeholders, and better inform the public about the levels of environmental protection achieved and the level of risk to the environment and the community. A simple approach is described which has been developed to help build a mutual understanding between technocrats and the lay person on perceptions of risk and actual environmental impact. (author)

Electrical resistivity imaging survey to detect uncharted mine galleries in the mining district of Linares, Jaén, Spain

Science.gov (United States)

Martínez-López, J.; Rey, J.; Dueñas, J.; Hidalgo, C.; Benavente, J.

2012-02-01

The scarcity of information about the existence of old mining shafts and galleries in urban areas is an important issue for future urban development. Electrical resistivity tomography is a non-destructive geophysical technique that can detect and characterize such subsurface cavities based on differences in the behaviour of electrical current in the void and in the embedding rock. Here we present a study in which this technique was used to determine the location of old engineered structures around the city of Linares, southern Spain, and to relate these structures to the abandoned deep mines present in the area. Eight electrical resistivity imaging profiles were performed, with a total of 22 808 measurements. Correlations between geoelectrical anomalies allow detection of the depth and the direction of several galleries, as well as the voids that result from mining extraction. Given the depth at which these structures are located (in some cases less than 5 m), they pose an important risk for future construction projects in areas of urban expansion. This technique is shown to be a useful tool for locating areas that pose important urban risks and, by extension, for the decision-making process in territorial planning, especially in areas with a history of deep mining.

Electrical resistivity imaging survey to detect uncharted mine galleries in the mining district of Linares, Jaén, Spain

International Nuclear Information System (INIS)

Martínez-López, J; Rey, J; Hidalgo, C; Dueñas, J; Benavente, J

2012-01-01

The scarcity of information about the existence of old mining shafts and galleries in urban areas is an important issue for future urban development. Electrical resistivity tomography is a non-destructive geophysical technique that can detect and characterize such subsurface cavities based on differences in the behaviour of electrical current in the void and in the embedding rock. Here we present a study in which this technique was used to determine the location of old engineered structures around the city of Linares, southern Spain, and to relate these structures to the abandoned deep mines present in the area. Eight electrical resistivity imaging profiles were performed, with a total of 22 808 measurements. Correlations between geoelectrical anomalies allow detection of the depth and the direction of several galleries, as well as the voids that result from mining extraction. Given the depth at which these structures are located (in some cases less than 5 m), they pose an important risk for future construction projects in areas of urban expansion. This technique is shown to be a useful tool for locating areas that pose important urban risks and, by extension, for the decision-making process in territorial planning, especially in areas with a history of deep mining

Extracting Information from Multimedia Meeting Collections

OpenAIRE

Gatica-Perez, Daniel; Zhang, Dong; Bengio, Samy

2005-01-01

Multimedia meeting collections, composed of unedited audio and video streams, handwritten notes, slides, and electronic documents that jointly constitute a raw record of complex human interaction processes in the workplace, have attracted interest due to the increasing feasibility of recording them in large quantities, by the opportunities for information access and retrieval applications derived from the automatic extraction of relevant meeting information, and by the challenges that the ext...

Mining on the Mesa

Energy Technology Data Exchange (ETDEWEB)

Sprouls, M.W.

1994-10-01

Peabody Western Coal Co. is the owner of Black Mesa and Kayenta coal opencast mines, both sited on Hopi and Navajo lands. 93% of the employees are native American, mostly Navajo. Kayenta is the larger and extracts coal with draglines. Sulphur content is high so the coal has to be analyzed and carefully blended before use. Black Mesa also uses draglines, here quality control is not as important as it is at Kayenta. Coal is transported to power stations using slurry pipelines. Both mines are heavily involved in land reclamation, leaving a landscape that makes better grazing than it did before mining. 2 figs.

Information from geology: Implications for soil formation and rehabilitation in the post coal mining environment, Bowen Basin, Australia

International Nuclear Information System (INIS)

Spain, A.V.; Esterle, J.; McLennan, T.P.T.

1995-01-01

The coal mining industry is likely to disturb as much as 60,000 ha of the Bowen Basin up to the year 2000. While comprising only a small proportion of the approximately 32,000 km 2 of the Bowen Basin, this considerable area will eventually need to be rehabilitated by creating appropriate land forms with a stabilizing and self-sustaining cover of vegetation. The job of restoring the disturbed area will fall to the practitioners of rehabilitation science. This paper briefly outlines the actual and potential significance of geological information to rehabilitation practice in the open-cut coal mining industry of the Bowen Basin. It focuses particularly on the problems of soil formation and the consequent limitations to ecosystem development due to the nature of the overburden materials and the environment. Lastly, it describes some of the distinctive features of the mine-soils of the area. Geological information can assist in the identification, classification, description and behaviour of post-mining materials. Potential inputs are not restricted to these and there is scope for wider inputs to management of the mining environment although the interface with biology requires further development. (author). 4 figs., 31 refs

Prairie of mine(s) : cultural reclamation of the Estevan/Bienfait Coalfields

Energy Technology Data Exchange (ETDEWEB)

Baxter, S.

2010-07-01

A cultural reclamation project was launched in the Bienfait region of southern Saskatchewan where lignite mining has been ongoing since the 1800s. Evidence of 5 surface mines, 2 power stations and thousands of acres of spoil piles remain at the abandoned site. The region also comprises 140 abandoned underground mines and 4 mined-out townsites. The project introduced cultural reclamation into the role of landscape architecture, specifically in the planning and design of reclaimed mining lands. At the present time, the reclamation of post-extractive sites is limited to focusing almost exclusively on ecological factors, but failing to recognize the people and the industrial processes that actively transformed the landscape can disengage people from their past. The project concludes with a proposed master plan in addition to a few site-specific interventions that interrogate and explore the role of experiential, cultural, and historical elements in the reclamation of a site. In doing so, awareness is created about the ways in which various landscapes are manipulated every day in order for people to live in greater comfort.

Systematic Review of Data Mining Applications in Patient-Centered Mobile-Based Information Systems.

Science.gov (United States)

Fallah, Mina; Niakan Kalhori, Sharareh R

2017-10-01

Smartphones represent a promising technology for patient-centered healthcare. It is claimed that data mining techniques have improved mobile apps to address patients' needs at subgroup and individual levels. This study reviewed the current literature regarding data mining applications in patient-centered mobile-based information systems. We systematically searched PubMed, Scopus, and Web of Science for original studies reported from 2014 to 2016. After screening 226 records at the title/abstract level, the full texts of 92 relevant papers were retrieved and checked against inclusion criteria. Finally, 30 papers were included in this study and reviewed. Data mining techniques have been reported in development of mobile health apps for three main purposes: data analysis for follow-up and monitoring, early diagnosis and detection for screening purpose, classification/prediction of outcomes, and risk calculation (n = 27); data collection (n = 3); and provision of recommendations (n = 2). The most accurate and frequently applied data mining method was support vector machine; however, decision tree has shown superior performance to enhance mobile apps applied for patients' self-management. Embedded data-mining-based feature in mobile apps, such as case detection, prediction/classification, risk estimation, or collection of patient data, particularly during self-management, would save, apply, and analyze patient data during and after care. More intelligent methods, such as artificial neural networks, fuzzy logic, and genetic algorithms, and even the hybrid methods may result in more patients-centered recommendations, providing education, guidance, alerts, and awareness of personalized output.

How ISO/IEC 17799 can be used for base lining information assurance among entities using data mining for defense, homeland security, commercial, and other civilian/commercial domains

Science.gov (United States)

Perry, William G.

2006-04-01

One goal of database mining is to draw unique and valid perspectives from multiple data sources. Insights that are fashioned from closely-held data stores are likely to possess a high degree of reliability. The degree of information assurance comes into question, however, when external databases are accessed, combined and analyzed to form new perspectives. ISO/IEC 17799, Information technology-Security techniques-Code of practice for information security management, can be used to establish a higher level of information assurance among disparate entities using data mining in the defense, homeland security, commercial and other civilian/commercial domains. Organizations that meet ISO/IEC information security standards have identified and assessed risks, threats and vulnerabilities and have taken significant proactive steps to meet their unique security requirements. The ISO standards address twelve domains: risk assessment and treatment, security policy, organization of information security, asset management, human resources security, physical and environmental security, communications and operations management, access control, information systems acquisition, development and maintenance, information security incident management and business continuity management and compliance. Analysts can be relatively confident that if organizations are ISO 17799 compliant, a high degree of information assurance is likely to be a characteristic of the data sets being used. The reverse may be true. Extracting, fusing and drawing conclusions based upon databases with a low degree of information assurance may be wrought with all of the hazards that come from knowingly using bad data to make decisions. Using ISO/IEC 17799 as a baseline for information assurance can help mitigate these risks.

Effect of high-extraction coal mining on surface and ground waters

International Nuclear Information System (INIS)

Kendorski, F.S.

1993-01-01

Since first quantified around 1979, much new data have become available. In examining the sources of data and the methods and intents of the researchers of over 65 case histories, it became apparent that the strata behaviors were being confused with overlapping vertical extents reported for the fractured zones and aquiclude zones depending on whether the researcher was interested in water intrusion into the mine or in water loss from surface or ground waters. These more recent data, and critical examination of existing data, have led to the realization that the former Aquiclude Zone defined for its ability to prevent or minimize the intrusion of ground or surface waters into mines has another important character in increasing storage of surface and shallow ground waters in response to mining with no permanent loss of waters. This zone is here named the Dilated Zone. Surface and ground waters can drain into this zone, but seldom into the mine, and can eventually be recovered through closing of dilations by mine subsidence progression away from the area, or filling of the additional void space created, or both. A revised model has been developed which accommodates the available data, by modifying the zones as follows: collapse and disaggregation extending 6 to 10 times the mined thickness above the panel; continuous fracturing extending approximately 24 times the mined thickness above the panel, allowing temporary drainage of intersected surface and ground waters; development of a zone of dilated, increased storativity, and leaky strata with little enhanced vertical permeability from 24 to 60 times the mined thickness above the panel above the continuous fracturing zone, and below the constrained or surface effects zones; maintenance of a constrained but leaky zone above the dilated zone and below the surface effects zone; and limited surface fracturing in areas of extension extending up to 50 ft or so beneath the ground surface. 119 ref., 5 figs., 2 tabs

Building a glaucoma interaction network using a text mining approach.

Science.gov (United States)

Soliman, Maha; Nasraoui, Olfa; Cooper, Nigel G F

2016-01-01

The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease. A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx. This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of

A research for environmental problems in the vicinity of mining area. Investigation into the impact of metallic mining on the environment and solutions

Energy Technology Data Exchange (ETDEWEB)

Min, Jeong Sik; Cheong, Young Wook; Lee, Hyun Joo; Song, Duk Young [Korea Inst. of Geology Mining and Materials, Taejon (Korea, Republic of)

1995-12-01

This study is focused on the impacts of metalliferous mines on the environment in the vicinity of the abandoned and active mines and establishment of abatements of mining environmental problems. Total number of metalliferous mines surveyed were 40 in which samples of waters, mine wastes and soil were taken. Water parameters such as the pH, Eh, TDS, conductivity, turbidity, dissolved oxygen and temperature were measured in the field. Elements such as As, Cd, Pb, Zn, Cu, Al, Mn, sulfate and cyanide were analyzed. Significant concentrations of heavy metals, mainly Cd, Zn, Cu, Fe, Mn and Al, were found in mine waters from adit and in leachates extracted from mine wastes. The mine waters flowing out from the Dalsung and Ilgwang mines were the typical acid mine drainage(AMD) contaminated by the heavy metals. Passive biological systems(Anoxic wetland) to treat AMD for metals were designed and monitored for effluents from the reactors with 4 types of composts, cow manure and limestones, Results showed that the mushroom compost with cow manure and limestone was the best substrates in metal removing efficiencies. Results from leaching of mine wastes showed that As, Cd and Cu were extracted from some of mine wastes. AMD from the mine waste dump of the Daduk mine was found. These mean that mine wastes can contaminate the soil, surface water and ground waters in vicinity of mines. Therefore cover systems or liner system for containments of mine wastes were suggested to preserve the environment. Cu and As concentrations in soils surveyed were below the heavy metal concentrations in soils of Korean standard preventing plant of the crops. However, most of the acid mine waters are drained untreated, and mine wastes with heavy metals are distributed near soil environment. Therefore efforts to reduce possibilities of soil contamination in the vicinity of mining areas is required. (author). 33 refs.

Management of mining-related damages in abandoned underground coal mine areas using GIS

International Nuclear Information System (INIS)

Lee, U.J.; Kim, J.A.; Kim, S.S.; Kim, W.K.; Yoon, S.H.; Choi, J.K.

2005-01-01

The mining-related damages such as ground subsidence, acid mine drainage (AMD), and deforestation in the abandoned underground coal mine areas become an object of public concern. Therefore, the system to manage the mining-related damages is needed for the effective drive of rehabilitation activities. The management system for Abandoned Underground Coal Mine using GIS includes the database about mining record and information associated with the mining-related damages and application programs to support mine damage prevention business. Also, this system would support decision-making policy for rehabilitation and provide basic geological data for regional construction works in abandoned underground coal mine areas. (authors)

ParaBTM: A Parallel Processing Framework for Biomedical Text Mining on Supercomputers.

Science.gov (United States)

Xing, Yuting; Wu, Chengkun; Yang, Xi; Wang, Wei; Zhu, En; Yin, Jianping

2018-04-27

A prevailing way of extracting valuable information from biomedical literature is to apply text mining methods on unstructured texts. However, the massive amount of literature that needs to be analyzed poses a big data challenge to the processing efficiency of text mining. In this paper, we address this challenge by introducing parallel processing on a supercomputer. We developed paraBTM, a runnable framework that enables parallel text mining on the Tianhe-2 supercomputer. It employs a low-cost yet effective load balancing strategy to maximize the efficiency of parallel processing. We evaluated the performance of paraBTM on several datasets, utilizing three types of named entity recognition tasks as demonstration. Results show that, in most cases, the processing efficiency can be greatly improved with parallel processing, and the proposed load balancing strategy is simple and effective. In addition, our framework can be readily applied to other tasks of biomedical text mining besides NER.

Geological disaster survey based on Curvelet transform with borehole Ground Penetrating Radar in Tonglushan old mine site.

Science.gov (United States)

Tang, Xinjian; Sun, Tao; Tang, Zhijie; Zhou, Zenghui; Wei, Baoming

2011-06-01

Tonglushan old mine site located in Huangshi City, China, is very famous in the world. However, some of the ruins had suffered from geological disasters such as local deformation, surface cracking, in recent years. Structural abnormalities of rock-mass in deep underground were surveyed with borehole ground penetrating radar (GPR) to find out whether there were any mined galleries or mined-out areas below the ruins. With both the multiresolution analysis and sub-band directional of Curvelet transform, the feature information of targets' GPR signals were studied on Curvelet transform domain. Heterogeneity of geotechnical media and clutter jamming of complicated background of GPR signals could be conquered well, and the singularity characteristic information of typical rock mass signals could be extracted. Random noise had be removed by thresholding combined with Curvelet and the statistical characteristics of wanted signals and the noise, then direct wave suppression and the spatial distribution feature extraction could obtain a better result by making use of Curvelet transform directional. GprMax numerical modeling and analyzing of the sample data have verified the feasibility and effectiveness of our method. It is important and applicable for the analyzing of the geological structure and the disaster development about the Tonglushan old mine site. Copyright © 2011 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Statistical and Visualization Data Mining Tools for Foundry Production

Directory of Open Access Journals (Sweden)

M. Perzyk

2007-07-01

Full Text Available In recent years a rapid development of a new, interdisciplinary knowledge area, called data mining, is observed. Its main task is extracting useful information from previously collected large amount of data. The main possibilities and potential applications of data mining in manufacturing industry are characterized. The main types of data mining techniques are briefly discussed, including statistical, artificial intelligence, data base and visualization tools. The statistical methods and visualization methods are presented in more detail, showing their general possibilities, advantages as well as characteristic examples of applications in foundry production. Results of the author’s research are presented, aimed at validation of selected statistical tools which can be easily and effectively used in manufacturing industry. A performance analysis of ANOVA and contingency tables based methods, dedicated for determination of the most significant process parameters as well as for detection of possible interactions among them, has been made. Several numerical tests have been performed using simulated data sets, with assumed hidden relationships as well some real data, related to the strength of ductile cast iron, collected in a foundry. It is concluded that the statistical methods offer relatively easy and fairly reliable tools for extraction of that type of knowledge about foundry manufacturing processes. However, further research is needed, aimed at explanation of some imperfections of the investigated tools as well assessment of their validity for more complex tasks.

A Study on Environmental Research Trends Using Text-Mining Method - Focus on Spatial information and ICT -

Science.gov (United States)

Lee, M. J.; Oh, K. Y.; Joung-ho, L.

2016-12-01

Recently there are many research about analysing the interaction between entities by text-mining analysis in various fields. In this paper, we aimed to quantitatively analyse research-trends in the area of environmental research relating either spatial information or ICT (Information and Communications Technology) by Text-mining analysis. To do this, we applied low-dimensional embedding method, clustering analysis, and association rule to find meaningful associative patterns of key words frequently appeared in the articles. As the authors suppose that KCI (Korea Citation Index) articles reflect academic demands, total 1228 KCI articles that have been published from 1996 to 2015 were reviewed and analysed by Text-mining method. First, we derived KCI articles from NDSL(National Discovery for Science Leaders) site. And then we pre-processed their key-words elected from abstract and then classified those in separable sectors. We investigated the appearance rates and association rule of key-words for articles in the two fields: spatial-information and ICT. In order to detect historic trends, analysis was conducted separately for the four periods: 1996-2000, 2001-2005, 2006-2010, 2011-2015. These analysis were conducted with the usage of R-software. As a result, we conformed that environmental research relating spatial information mainly focused upon such fields as `GIS(35%)', `Remote-Sensing(25%)', `environmental theme map(15.7%)'. Next, `ICT technology(23.6%)', `ICT service(5.4%)', `mobile(24%)', `big data(10%)', `AI(7%)' are primarily emerging from environmental research relating ICT. Thus, from the analysis results, this paper asserts that research trends and academic progresses are well-structured to review recent spatial information and ICT technology and the outcomes of the analysis can be an adequate guidelines to establish environment policies and strategies. KEY WORDS: Big data, Test-mining, Environmental research, Spatial-information, ICT Acknowledgements: The

Grants Mining District

Science.gov (United States)

The Grants Mineral Belt was the focus of uranium extraction and production activities from the 1950s until the late 1990s. EPA is working with state, local, and federal partners to assess and address health risks and environmental effects of the mines

Web Mining of Hotel Customer Survey Data

Directory of Open Access Journals (Sweden)

Richard S. Segall

2008-12-01

Full Text Available This paper provides an extensive literature review and list of references on the background of web mining as applied specifically to hotel customer survey data. This research applies the techniques of web mining to actual text of written comments for hotel customers using Megaputer PolyAnalyst®. Web mining functionalities utilized include those such as clustering, link analysis, key word and phrase extraction, taxonomy, and dimension matrices. This paper provides screen shots of the web mining applications using Megaputer PolyAnalyst®. Conclusions and future directions of the research are presented.

Analysing Customer Opinions with Text Mining Algorithms

Science.gov (United States)

Consoli, Domenico

2009-08-01

Knowing what the customer thinks of a particular product/service helps top management to introduce improvements in processes and products, thus differentiating the company from their competitors and gain competitive advantages. The customers, with their preferences, determine the success or failure of a company. In order to know opinions of the customers we can use technologies available from the web 2.0 (blog, wiki, forums, chat, social networking, social commerce). From these web sites, useful information must be extracted, for strategic purposes, using techniques of sentiment analysis or opinion mining.

Semantic Information Extraction of Lanes Based on Onboard Camera Videos

Science.gov (United States)

Tang, L.; Deng, T.; Ren, C.

2018-04-01

In the field of autonomous driving, semantic information of lanes is very important. This paper proposes a method of automatic detection of lanes and extraction of semantic information from onboard camera videos. The proposed method firstly detects the edges of lanes by the grayscale gradient direction, and improves the Probabilistic Hough transform to fit them; then, it uses the vanishing point principle to calculate the lane geometrical position, and uses lane characteristics to extract lane semantic information by the classification of decision trees. In the experiment, 216 road video images captured by a camera mounted onboard a moving vehicle were used to detect lanes and extract lane semantic information. The results show that the proposed method can accurately identify lane semantics from video images.

HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

Science.gov (United States)

Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

DrugQuest - a text mining workflow for drug association discovery.

Science.gov (United States)

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Vizirianakis, Ioannis S; Iliopoulos, Ioannis

2016-06-06

Text mining and data integration methods are gaining ground in the field of health sciences due to the exponential growth of bio-medical literature and information stored in biological databases. While such methods mostly try to extract bioentity associations from PubMed, very few of them are dedicated in mining other types of repositories such as chemical databases. Herein, we apply a text mining approach on the DrugBank database in order to explore drug associations based on the DrugBank "Description", "Indication", "Pharmacodynamics" and "Mechanism of Action" text fields. We apply Name Entity Recognition (NER) techniques on these fields to identify chemicals, proteins, genes, pathways, diseases, and we utilize the TextQuest algorithm to find additional biologically significant words. Using a plethora of similarity and partitional clustering techniques, we group the DrugBank records based on their common terms and investigate possible scenarios why these records are clustered together. Different views such as clustered chemicals based on their textual information, tag clouds consisting of Significant Terms along with the terms that were used for clustering are delivered to the user through a user-friendly web interface. DrugQuest is a text mining tool for knowledge discovery: it is designed to cluster DrugBank records based on text attributes in order to find new associations between drugs. The service is freely available at http://bioinformatics.med.uoc.gr/drugquest .

Coal mine subsidence and structures

International Nuclear Information System (INIS)

Gray, R.E.

1988-01-01

Underground coal mining has occurred beneath 32 x 10 9 m 2 (8 million acres) of land in the United States and will eventually extend beneath 162 x 10 9 m 2 (40 million acres). Most of this mining has taken place and will take place in the eastern half of the United States. In areas of abandoned mines where total extraction was not achieved, roof collapse, crushing of coal pillars, or punching of coal pillars into softer mine floor or roof rock is now resulting in sinkhole or trough subsidence tens or even hundreds of years after mining. Difference in geology, in mining, and building construction practice between Europe and the United States preclude direct transfer of European subsidence engineering experience. Building damage cannot be related simply to tensile and compressive strains at the ground surface. Recognition of the subsidence damage role played by ground-structure interaction and by structural details is needed

Integrating Information Extraction Agents into a Tourism Recommender System

Science.gov (United States)

Esparcia, Sergio; Sánchez-Anguix, Víctor; Argente, Estefanía; García-Fornes, Ana; Julián, Vicente

Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.

Tanzania. A developing mining country; Tansania. Bergbauland im Aufbruch

Energy Technology Data Exchange (ETDEWEB)

Elsner, Harald [Bundesanstalt fuer Geowissenschaften und Rohstoffe (BGR), Hannover (Germany). Fachbereich Wirtschaftsgeologie der mineralischen Rohstoffe

2009-03-19

Tanzania is the rising country in East Africa, to which not least of all the booming mining sector contributes. Many large gold mines, two precious stone mines, three cement works and smaller facilities for extraction of salt, phosphates, gypsum, pozzolana, coal and coloured gemstones currently characterise the mining sector. The high mineral potential of the country combined with the mining legislation favouring investment will also lead in future to the development of further deposits in particular, nickel, gold, coal and graphite. (orig.)

African Mining, Gender and Local Employment

Science.gov (United States)

Tolonen, A.; Kotsadam, A.

2014-12-01

Access to employment improves women's lives and is listed among the top five priorities for promoting gender equality in the 2012 World Development Report. This paper addresses this issue by exploring women's labor market opportunities in Africa within one very important and growing sector: extractive industries. Africa's opportunities are being transformed by new discoveries of natural resources and their rising prices, and the mining sector is the main recipient of foreign direct investment in Sub-Saharan Africa. Whether the discovery of natural resources is a blessing or a curse to a country's citizens is a contentious issue, and natural resource dependence has been linked to negative outcomes at the national level such as environmental degradation, conflict, elite capture of rents and low female labor force participation. Natural resource extraction has been argued to be a hindrance to women's labor market participation by increasing reservation wages and by decreasing market demand for female labor. We perform the first cross-national study testing these hypotheses with micro-data. To do this we combine survey data on 500,000 women in Sub-Saharan Africa with geo-coded data on 900 large-scale mines (see Figure 1). We treat mine openings and mine closings as natural experiments to explore local labor market changes. Industrial mines generate local structural shifts. Subsistence farming becomes less important for both men and women. However, men shift to skilled manual labor, and women shift to service sector jobs. This contradicts the hypothesis that natural resource extraction is detrimental to women, by not providing them with new job opportunities. However, in support of the hypothesis, women decrease their labor market participation more than men do. A back-of-the-envelope calculation estimates that 90,000 women across Africa benefit from service sector jobs as a direct result of industrial mining in their communities, but 280,000 women leave the labor force

Occurrence of Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans in uranium mine-Caldas uranium mining and extraction plant, Brazil (CUMEP)

International Nuclear Information System (INIS)

Gomes, H.A.; Garcia, O.; Gomes, J.E.; Rabello, E.; Cannavan, F.S.; Tsai, S.M.

2005-01-01

The sulfated minerals present in mining areas may cause serious environmental problems due to the action of chemolithotrophic bacteria from genus Acithiobacillus, represented mainly by Acithiobacillus ferrooxidans and Acithiobacillus thiooxidans. These microorganisms are able to oxidize mineral sulfates, elementary sulfur and ferrous ion (A. ferrooxidans), as well are capable of mobilizing radionuclide as uranium to the environment. In this context, this study aimed at investigating the occurrence and the fluctuation of A. ferrooxidans and A. thiooxidans populations within the mine effluents, tailing dam and waste rocks of the Caldas Uranium Mining arid Extraction Plant (CUMEP) in Minas Gerais State - Brazil. Samples from 16 sites were evenly taken monthly in the CUMEP, during 28 months. The oxi-reduction potential, pH and temperature values were determined at the Radioecology Laboratory. The Most Probable Number technique was applied using a series of five tubes for selective counting of A. ferrooxidans and A. thiooxidans. Each sample was submitted to serial dilutions using Tween 80 and sterilized water (pH=2.0) and subsequently transferred into assay tubes containing T and K with ferrous ion and also elementary sulfur, as energy source, for detection of A. ferrooxidans and A. thiooxidans, respectively. Populations of A. ferrooxidans and A. thiooxidans presented seasonal quantitative fluctuations at the different studied sites. A. ferrooxidans showed higher or equal frequency to that observed for A. thiooxidans; as consequence, they were considered the predominant bacteria in this environment. In the majority of the sites, the highest values for the frequency and counting of A. ferrooxidans and A. thiooxidans were observed during the rainy period (October to March). The relative seasonal behavior when several variables are evaluated simultaneously indicated that, due to the high values of oxi-reduction potential, the low values of pH, the detection of the highest

DESIGNING AN EVENT EXTRACTION SYSTEM

Directory of Open Access Journals (Sweden)

Botond BENEDEK

2017-06-01

Full Text Available In the Internet world, the amount of information available reaches very high quotas. In order to find specific information, some tools were created that automatically scroll through the existing web pages and update their databases with the latest information on the Internet. In order to systematize the search and achieve a result in a concrete form, another step is needed for processing the information returned by the search engine and generating the response in a more organized form. Centralizing events of a certain type is useful first of all for creating a news service. Through this system we are pursuing a knowledge - events from the Internet documents - extraction system. The system will recognize events of a certain type (weather, sports, politics, text data mining, etc. depending on how it will be trained (the concept it has in the dictionary. These events can be provided to the user, or it can also extract the context in which the event occurred, to indicate the initial form in which the event was embedded.

Information and communication technology and climate change adaptation: Evidence from selected mining companies in South Africa

Directory of Open Access Journals (Sweden)

Bartholomew I. Aleke

2016-04-01

Full Text Available The mining sector is a significant contributor to the gross domestic product of many global economies. Given the increasing trends in climate-induced disasters and the growing desire to find lasting solutions, information and communication technology (ICT has been introduced into the climate change adaptation mix. Climate change-induced extreme weather events such as flooding, drought, excessive fog, and cyclones have compounded the environmental challenges faced by the mining sector. This article presents the adoption of ICT innovation as part of the adaptation strategies towards reducing the mining sector’s vulnerability and exposure to climate change disaster risks. Document analysis and systematic literature review were adopted as the methodology. Findings from the study reflect how ICT intervention orchestrated changes in communication patterns which are tailored towards the reduction in climate change vulnerability and exposure. The research concludes with a proposition that ICT intervention must be part of the bigger and ongoing climate change adaptation agenda in the mining sector. Keywords: ICT; climate change; disaster risk reduction; mining; adaptation; South Africa

Optimal Information Extraction of Laser Scanning Dataset by Scale-Adaptive Reduction

Science.gov (United States)

Zang, Y.; Yang, B.

2018-04-01

3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.

OPTIMAL INFORMATION EXTRACTION OF LASER SCANNING DATASET BY SCALE-ADAPTIVE REDUCTION

Directory of Open Access Journals (Sweden)

Y. Zang

2018-04-01

Full Text Available 3D laser technology is widely used to collocate the surface information of object. For various applications, we need to extract a good perceptual quality point cloud from the scanned points. To solve the problem, most of existing methods extract important points based on a fixed scale. However, geometric features of 3D object come from various geometric scales. We propose a multi-scale construction method based on radial basis function. For each scale, important points are extracted from the point cloud based on their importance. We apply a perception metric Just-Noticeable-Difference to measure degradation of each geometric scale. Finally, scale-adaptive optimal information extraction is realized. Experiments are undertaken to evaluate the effective of the proposed method, suggesting a reliable solution for optimal information extraction of object.

Data Mining on Distributed Medical Databases: Recent Trends and Future Directions

Science.gov (United States)

Atilgan, Yasemin; Dogan, Firat

As computerization in healthcare services increase, the amount of available digital data is growing at an unprecedented rate and as a result healthcare organizations are much more able to store data than to extract knowledge from it. Today the major challenge is to transform these data into useful information and knowledge. It is important for healthcare organizations to use stored data to improve quality while reducing cost. This paper first investigates the data mining applications on centralized medical databases, and how they are used for diagnostic and population health, then introduces distributed databases. The integration needs and issues of distributed medical databases are described. Finally the paper focuses on data mining studies on distributed medical databases.

Real world data mining applications

CERN Document Server

Abou-Nasr, Mahmoud; Stahlbock, Robert; Weiss, Gary M

2014-01-01

Data mining applications range from commercial to social domains, with novel applications appearing swiftly; for example, within the context of social networks. The expanding application sphere and social reach of advanced data mining raise pertinent issues of privacy and security. Present-day data mining is a progressive multidisciplinary endeavor. This inter- and multidisciplinary approach is well reflected within the field of information systems. The information systems research addresses software and hardware requirements for supporting computationally and data-intensive applications. Furthermore, it encompasses analyzing system and data aspects, and all manual or automated activities. In that respect, research at the interface of information systems and data mining has significant potential to produce actionable knowledge vital for corporate decision-making. The aim of the proposed volume is to provide a balanced treatment of the latest advances and developments in data mining; in particular, exploring s...

A Wireless LAN and Voice Information System for Underground Coal Mine

OpenAIRE

Yu Zhang; Wei Yang; Dongsheng Han; Young-Il Kim

2014-01-01

In this paper we constructed a wireless information system, and developed a wireless voice communication subsystem based on Wireless Local Area Networks (WLAN) for underground coal mine, which employs Voice over IP (VoIP) technology and Session Initiation Protocol (SIP) to achieve wireless voice dispatching communications. The master control voice dispatching interface and call terminal software are also developed on the WLAN ground server side to manage and implement the voice dispatching co...

Radionuclides in sheep grazing near old uranium mines

Energy Technology Data Exchange (ETDEWEB)

Carvalho, Fernando P.; Oliveira, Joao M.; Malta, M. [Instituto Superior Tecnico/Campus Tecnologico e Nuclear/ (IST/CTN), Universidade de Lisboa, Estrada Nacional 10 - ao km 139,7, - 2695-066 Bobadela LRS (Portugal); Lemos, M.E. [Servicos de Alimentacao e Veterinaria da Regiao Centro, Bairro Na Sra dos Remedios, 6300 Guarda (Portugal); Vala, H.; Esteves, F. [Escola Superior Agraria de Viseu, Quinta da Alagoa, Estrada de Nelas, Ranhados,3500-606 Viseu (Portugal)

2014-07-01

During the past century extensive uranium mining took place in Portugal for radium and uranium production. Many uranium deposits were mined as open pits and after ore extraction and transportation to milling facilities, mining wastes were left on site. One uranium ore mining site, Boco Mine, was extracted in the 1960's and 70's and mining waste and open pits were left uncovered and non-remediated since closure of uranium mining activities. During the nineties a quarry for sand extraction was operated in the same site and water from a local stream was extensively used in sand sieving. Downstream the mine areas, agriculture soils along the water course are currently used for cattle grazing. Water from this stream, and water wells, soil, pasture and sheep meat were analyzed for radionuclides of the uranium series. The U- series radionuclide {sup 226}Ra was generally the highest in concentrations especially in soil, pasture, and in internal organs of sheep. Ra-226 concentrations averaged 1093±96 Bq/kg (dry weight) in soil, 43±3 Bq/kg (dw) in pasture, and 0.76±0.41 Bq/kg (dw) in muscle tissue of sheep grown there. Other sheep internal organs displayed much higher {sup 226}Ra concentrations, such as the brain and kidneys with 7.7±2.3 Bq/kg (dw) and 28±29 Bq/kg (dw), respectively. Results of tissue sample analysis for sheep grown in a comparison area were 2 to 11 times lower, depending on the tissue. Absorbed radiation doses for internal organs of sheep were computed and may exceed 20 mSv/y in the kidney. Although elevated, this absorbed radiation dose still is below the threshold for biological effects on mammals. Nevertheless, enhanced environmental radioactive contamination mainly due to radium was observed in the area of influence of this legacy uranium mine and there is potential food chain transfer for humans (authors)

On-Board Mining in the Sensor Web

Science.gov (United States)

Tanner, S.; Conover, H.; Graves, S.; Ramachandran, R.; Rushing, J.

2004-12-01

On-board data mining can contribute to many research and engineering applications, including natural hazard detection and prediction, intelligent sensor control, and the generation of customized data products for direct distribution to users. The ability to mine sensor data in real time can also be a critical component of autonomous operations, supporting deep space missions, unmanned aerial and ground-based vehicles (UAVs, UGVs), and a wide range of sensor meshes, webs and grids. On-board processing is expected to play a significant role in the next generation of NASA, Homeland Security, Department of Defense and civilian programs, providing for greater flexibility and versatility in measurements of physical systems. In addition, the use of UAV and UGV systems is increasing in military, emergency response and industrial applications. As research into the autonomy of these vehicles progresses, especially in fleet or web configurations, the applicability of on-board data mining is expected to increase significantly. Data mining in real time on board sensor platforms presents unique challenges. Most notably, the data to be mined is a continuous stream, rather than a fixed store such as a database. This means that the data mining algorithms must be modified to make only a single pass through the data. In addition, the on-board environment requires real time processing with limited computing resources, thus the algorithms must use fixed and relatively small amounts of processing time and memory. The University of Alabama in Huntsville is developing an innovative processing framework for the on-board data and information environment. The Environment for On-Board Processing (EVE) and the Adaptive On-board Data Processing (AODP) projects serve as proofs-of-concept of advanced information systems for remote sensing platforms. The EVE real-time processing infrastructure will upload, schedule and control the execution of processing plans on board remote sensors. These plans

75 FR 51487 - Division of Coal Mine Workers' Compensation; Proposed Extension of Information Collection...

Science.gov (United States)

2010-08-20

... DEPARTMENT OF LABOR Office of Workers' Compensation Programs Division of Coal Mine Workers' Compensation; Proposed Extension of Information Collection; Comment Request ACTION: Notice. SUMMARY: The Department of Labor, as part of its continuing effort to reduce paperwork and respondent burden, conducts a...

A Review Paper On Exploring Text Link And Spacial-Temporal Information In Social Media Networks

Directory of Open Access Journals (Sweden)

Dr. Mamta Madan

2015-03-01

Full Text Available ABSTRACT The objective of this paper is to have a literature review on the various methods to mine the knowledge from the social media by taking advantage of embedded heterogeneous information. Specifically we are trying to review different types of mining framework which provides us useful information from these networks that have heterogeneous data types including text spacial-temporal and data association LINK information. Firstly we will discuss the link mining to study the link structure with respect to Social Media SM. Secondly we summarize the various text mining models thirdly we shall review spacial as well the temporal models to extract or detect the frequent related topics from SM. Fourthly we will try to figure out few improvised models that take advantage of the link textual temporal and spacial information which motivates to discover progressive principles and fresh methodologies for DM Data Mining in social media networks SMNs.

A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set

Directory of Open Access Journals (Sweden)

Abdul Wahab Muzaffar

2015-01-01

Full Text Available The information extraction from unstructured text segments is a complex task. Although manual information extraction often produces the best results, it is harder to manage biomedical data extraction manually because of the exponential increase in data size. Thus, there is a need for automatic tools and techniques for information extraction in biomedical text mining. Relation extraction is a significant area under biomedical information extraction that has gained much importance in the last two decades. A lot of work has been done on biomedical relation extraction focusing on rule-based and machine learning techniques. In the last decade, the focus has changed to hybrid approaches showing better results. This research presents a hybrid feature set for classification of relations between biomedical entities. The main contribution of this research is done in the semantic feature set where verb phrases are ranked using Unified Medical Language System (UMLS and a ranking algorithm. Support Vector Machine and Naïve Bayes, the two effective machine learning techniques, are used to classify these relations. Our approach has been validated on the standard biomedical text corpus obtained from MEDLINE 2001. Conclusively, it can be articulated that our framework outperforms all state-of-the-art approaches used for relation extraction on the same corpus.

Knowledge Dictionary for Information Extraction on the Arabic Text Data

Directory of Open Access Journals (Sweden)

Wahyu Jauharis Saputra

2013-04-01

Full Text Available Information extraction is an early stage of a process of textual data analysis. Information extraction is required to get information from textual data that can be used for process analysis, such as classification and categorization. A textual data is strongly influenced by the language. Arabic is gaining a significant attention in many studies because Arabic language is very different from others, and in contrast to other languages, tools and research on the Arabic language is still lacking. The information extracted using the knowledge dictionary is a concept of expression. A knowledge dictionary is usually constructed manually by an expert and this would take a long time and is specific to a problem only. This paper proposed a method for automatically building a knowledge dictionary. Dictionary knowledge is formed by classifying sentences having the same concept, assuming that they will have a high similarity value. The concept that has been extracted can be used as features for subsequent computational process such as classification or categorization. Dataset used in this paper was the Arabic text dataset. Extraction result was tested by using a decision tree classification engine and the highest precision value obtained was 71.0% while the highest recall value was 75.0%. 

Data mining for bioinformatics applications

CERN Document Server

Zengyou, He

2015-01-01

Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems Contains 45 bioinformatics problems that have been investigated in recent research.

Exposure pathways and biological receptors: baseline data for the canyon uranium mine, Coconino County, Arizona

Science.gov (United States)

Hinck, Jo E.; Linder, Greg L.; Darrah, Abigail J.; Drost, Charles A.; Duniway, Michael C.; Johnson, Matthew J.; Méndez-Harclerode, Francisca M.; Nowak, Erika M.; Valdez, Ernest W.; van Riper, Charles; Wolff, S.W.

2014-01-01

Recent restrictions on uranium mining within the Grand Canyon watershed have drawn attention to scientific data gaps in evaluating the possible effects of ore extraction to human populations as well as wildlife communities in the area. Tissue contaminant concentrations, one of the most basic data requirements to determine exposure, are not available for biota from any historical or active uranium mines in the region. The Canyon Uranium Mine is under development, providing a unique opportunity to characterize concentrations of uranium and other trace elements, as well as radiation levels in biota, found in the vicinity of the mine before ore extraction begins. Our study objectives were to identify contaminants of potential concern and critical contaminant exposure pathways for ecological receptors; conduct biological surveys to understand the local food web and refine the list of target species (ecological receptors) for contaminant analysis; and collect target species for contaminant analysis prior to the initiation of active mining. Contaminants of potential concern were identified as arsenic, cadmium, chromium, copper, lead, mercury, nickel, selenium, thallium, uranium, and zinc for chemical toxicity and uranium and associated radionuclides for radiation. The conceptual exposure model identified ingestion, inhalation, absorption, and dietary transfer (bioaccumulation or bioconcentration) as critical contaminant exposure pathways. The biological survey of plants, invertebrates, amphibians, reptiles, birds, and small mammals is the first to document and provide ecological information on .200 species in and around the mine site; this study also provides critical baseline information about the local food web. Most of the species documented at the mine are common to ponderosa pine Pinus ponderosa and pinyon–juniper Pinus–Juniperus spp. forests in northern Arizona and are not considered to have special conservation status by state or federal agencies; exceptions

Event-based text mining for biology and functional genomics

Science.gov (United States)

Thompson, Paul; Nawaz, Raheel; McNaught, John; Kell, Douglas B.

2015-01-01

The assessment of genome function requires a mapping between genome-derived entities and biochemical reactions, and the biomedical literature represents a rich source of information about reactions between biological components. However, the increasingly rapid growth in the volume of literature provides both a challenge and an opportunity for researchers to isolate information about reactions of interest in a timely and efficient manner. In response, recent text mining research in the biology domain has been largely focused on the identification and extraction of ‘events’, i.e. categorised, structured representations of relationships between biochemical entities, from the literature. Functional genomics analyses necessarily encompass events as so defined. Automatic event extraction systems facilitate the development of sophisticated semantic search applications, allowing researchers to formulate structured queries over extracted events, so as to specify the exact types of reactions to be retrieved. This article provides an overview of recent research into event extraction. We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems. Finally, several concrete applications of event extraction are covered, together with emerging directions of research. PMID:24907365

US uranium mining industry: background information on economics and emissions

Energy Technology Data Exchange (ETDEWEB)

Bruno, G.A.; Dirks, J.A.; Jackson, P.O.; Young, J.K.

1984-03-01

A review of the US uranium mining industry has revealed a generally depressed industry situation. The 1982 U/sub 3/O/sub 8/ production from both open-pit and underground mines declined to 3800 and 6300 tons respectively with the underground portion representing 46% of total production. US exploration and development has continued downward in 1982. Employment in the mining and milling sectors has dropped 31% and 17% respectively in 1982. Representative forecasts were developed for reactor fuel demand and U/sub 3/O/sub 8/ production for the years 1983 and 1990. Reactor fuel demand is estimated to increase from 15,900 tons to 21,300 tons U/sub 3/O/sub 8/ respectively. U/sub 3/O/sub 8/ production, however, is estimated to decrease from 10,600 tons to 9600 tons respectively. A field examination was conducted of 29 selected underground uranium mines that represent 84% of the 1982 underground production. Data was gathered regarding population, land ownership and private property valuation. An analysis of the increased cost to production resulting from the installation of 20-meter high exhaust borehole vent stacks was conducted. An assessment was made of the current and future /sup 222/Rn emission levels for a group of 27 uranium mines. It is shown that /sup 222/Rn emission rates are increasing from 10 individual operating mines through 1990 by 1.2 to 3.8 times. But for the group of 27 mines as a whole, a reduction of total /sup 222/Rn emissions is predicted due to 17 of the mines being shutdown and sealed. The estimated total /sup 222/Rn emission rate for this group of mines will be 105 Ci/yr by year end 1983 or 70% of the 1978-79 measured rate and 124 Ci/yr by year end 1990 or 83% of the 1978-79 measured rate.

US uranium mining industry: background information on economics and emissions

International Nuclear Information System (INIS)

Bruno, G.A.; Dirks, J.A.; Jackson, P.O.; Young, J.K.

1984-03-01

A review of the US uranium mining industry has revealed a generally depressed industry situation. The 1982 U 3 O 8 production from both open-pit and underground mines declined to 3800 and 6300 tons respectively with the underground portion representing 46% of total production. US exploration and development has continued downward in 1982. Employment in the mining and milling sectors has dropped 31% and 17% respectively in 1982. Representative forecasts were developed for reactor fuel demand and U 3 O 8 production for the years 1983 and 1990. Reactor fuel demand is estimated to increase from 15,900 tons to 21,300 tons U 3 O 8 respectively. U 3 O 8 production, however, is estimated to decrease from 10,600 tons to 9600 tons respectively. A field examination was conducted of 29 selected underground uranium mines that represent 84% of the 1982 underground production. Data was gathered regarding population, land ownership and private property valuation. An analysis of the increased cost to production resulting from the installation of 20-meter high exhaust borehole vent stacks was conducted. An assessment was made of the current and future 222 Rn emission levels for a group of 27 uranium mines. It is shown that 222 Rn emission rates are increasing from 10 individual operating mines through 1990 by 1.2 to 3.8 times. But for the group of 27 mines as a whole, a reduction of total 222 Rn emissions is predicted due to 17 of the mines being shutdown and sealed. The estimated total 222 Rn emission rate for this group of mines will be 105 Ci/yr by year end 1983 or 70% of the 1978-79 measured rate and 124 Ci/yr by year end 1990 or 83% of the 1978-79 measured rate

76 FR 27355 - Agency Information Collection Activities; Submission for OMB Review; Comment Request; Mine...

Science.gov (United States)

2011-05-11

... comprehensive and reliable occupational data available concerning the mining industry. This submission has been... miners. Accident, injury, and illness data, when correlated with employment and production data, provide information that allows the MSHA to improve its safety and health enforcement programs, focus its education...

DDMGD: the database of text-mined associations between genes methylated in diseases from different species

KAUST Repository

Raies, A. B.

2014-11-14

Gathering information about associations between methylated genes and diseases is important for diseases diagnosis and treatment decisions. Recent advancements in epigenetics research allow for large-scale discoveries of associations of genes methylated in diseases in different species. Searching manually for such information is not easy, as it is scattered across a large number of electronic publications and repositories. Therefore, we developed DDMGD database (http://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGD\\'s scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we developed earlier and additional post-processing, we extracted associations of genes methylated in different diseases from PubMed Central articles and PubMed abstracts. The accuracy of extracted associations is 82% as estimated on 2500 hand-curated entries. DDMGD provides a user-friendly interface facilitating retrieval of these associations ranked according to confidence scores. Submission of new associations to DDMGD is provided. A comparison analysis of DDMGD with several other databases focused on genes methylated in diseases shows that DDMGD is comprehensive and includes most of the recent information on genes methylated in diseases.

30 CFR 947.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 947.702 Section 947.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... other minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of...

30 CFR 933.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 933.702 Section 933.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... other minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of...

30 CFR 939.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 939.702 Section 939.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... other minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of...

30 CFR 903.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 903.702 Section 903.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of Other...

30 CFR 912.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 912.702 Section 912.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of Other...

30 CFR 937.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 937.702 Section 937.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of Other...

30 CFR 921.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 921.702 Section 921.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... other minerals. Part 702 of the chapter, Exemption for Coal Extraction Incidental to the Extraction of...

30 CFR 905.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 905.702 Section 905.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... other minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of...

30 CFR 942.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 942.702 Section 942.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of Other...

30 CFR 910.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 910.702 Section 910.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of Other...

30 CFR 922.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 922.702 Section 922.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of Other...

30 CFR 941.702 - Exemption for coal extraction incidental to the extraction of other minerals.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Exemption for coal extraction incidental to the extraction of other minerals. 941.702 Section 941.702 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION... other minerals. Part 702 of this chapter, Exemption for Coal Extraction Incidental to the Extraction of...

Online Analytical Processing (OLAP: A Fast and Effective Data Mining Tool for Gene Expression Databases

Directory of Open Access Journals (Sweden)

Alkharouf Nadim W.

2005-01-01

Full Text Available Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD. A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.

Online analytical processing (OLAP): a fast and effective data mining tool for gene expression databases.

Science.gov (United States)

Alkharouf, Nadim W; Jamison, D Curtis; Matthews, Benjamin F

2005-06-30

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.

Recent Advances and Emerging Applications in Text and Data Mining for Biomedical Discovery.

Science.gov (United States)

Gonzalez, Graciela H; Tahsin, Tasnia; Goodale, Britton C; Greene, Anna C; Greene, Casey S

2016-01-01

Precision medicine will revolutionize the way we treat and prevent disease. A major barrier to the implementation of precision medicine that clinicians and translational scientists face is understanding the underlying mechanisms of disease. We are starting to address this challenge through automatic approaches for information extraction, representation and analysis. Recent advances in text and data mining have been applied to a broad spectrum of key biomedical questions in genomics, pharmacogenomics and other fields. We present an overview of the fundamental methods for text and data mining, as well as recent advances and emerging applications toward precision medicine. © The Author 2015. Published by Oxford University Press.

Mapping informal small-scale mining features in a data-sparse tropical environment with a small UAS

Science.gov (United States)

Chirico, Peter G.; Dewitt, Jessica D.

2017-01-01

This study evaluates the use of a small unmanned aerial system (UAS) to collect imagery over artisanal mining sites in West Africa. The purpose of this study is to consider how very high-resolution imagery and digital surface models (DSMs) derived from structure-from-motion (SfM) photogrammetric techniques from a small UAS can fill the gap in geospatial data collection between satellite imagery and data gathered during field work to map and monitor informal mining sites in tropical environments. The study compares both wide-angle and narrow field of view camera systems in the collection and analysis of high-resolution orthoimages and DSMs of artisanal mining pits. The results of the study indicate that UAS imagery and SfM photogrammetric techniques permit DSMs to be produced with a high degree of precision and relative accuracy, but highlight the challenges of mapping small artisanal mining pits in remote and data sparse terrain.

Wastes from former mining and milling activities in Tajikistan

International Nuclear Information System (INIS)

Mirsaidov, U.M.

2012-01-01

This article is devoted to wastes from former mining and milling activities in Tajikistan. Currently, the serious radiological and ecological problems in Tajikistan are uranium mining and milling activities consequences overcoming which intensively developed during the soviet period. After the collapse of USSR, the uranic ores extraction in Tajikistan stopped due to deposit's output completion on the territory of the republic. Remediation of mining and milling activities' sites became the most urgent once all mines were closed.

Advances in research methods for information systems research data mining, data envelopment analysis, value focused thinking

CERN Document Server

Osei-Bryson, Kweku-Muata

2013-01-01

Advances in social science research methodologies and data analytic methods are changing the way research in information systems is conducted. New developments in statistical software technologies for data mining (DM) such as regression splines or decision tree induction can be used to assist researchers in systematic post-positivist theory testing and development. Established management science techniques like data envelopment analysis (DEA), and value focused thinking (VFT) can be used in combination with traditional statistical analysis and data mining techniques to more effectively explore

Research on Crowdsourcing Emergency Information Extraction of Based on Events' Frame

Science.gov (United States)

Yang, Bo; Wang, Jizhou; Ma, Weijun; Mao, Xi

2018-01-01

At present, the common information extraction method cannot extract the structured emergency event information accurately; the general information retrieval tool cannot completely identify the emergency geographic information; these ways also do not have an accurate assessment of these results of distilling. So, this paper proposes an emergency information collection technology based on event framework. This technique is to solve the problem of emergency information picking. It mainly includes emergency information extraction model (EIEM), complete address recognition method (CARM) and the accuracy evaluation model of emergency information (AEMEI). EIEM can be structured to extract emergency information and complements the lack of network data acquisition in emergency mapping. CARM uses a hierarchical model and the shortest path algorithm and allows the toponomy pieces to be joined as a full address. AEMEI analyzes the results of the emergency event and summarizes the advantages and disadvantages of the event framework. Experiments show that event frame technology can solve the problem of emergency information drawing and provides reference cases for other applications. When the emergency disaster is about to occur, the relevant departments query emergency's data that has occurred in the past. They can make arrangements ahead of schedule which defense and reducing disaster. The technology decreases the number of casualties and property damage in the country and world. This is of great significance to the state and society.

Injury experience in coal mining, 1990

Energy Technology Data Exchange (ETDEWEB)

None

1991-01-01

This Mine Safety and Health Administration (MSHA) informational report reviews in detail the occupational injury and illness experience of coal mining in the United States for 1990. Data reported by operators of mining establishments concerning work injuries are summarized by work location, accident classification, part of body injured, nature of injury, occupation, and anthracite or bituminous coal. Related information on employment, worktime, and operating activity also is presented. Data reported by independent contractors performing certain work at mining locations are depicted separately in this report. For ease of comparison between coal mining and the metal and nonmetal mineral mining industries, summary reference tabulations are included at the end of both the operator and the contractor sections of this report.

Injury experience in coal mining, 1992

Energy Technology Data Exchange (ETDEWEB)

Reich, R.B.; Hugler, E.C.

1994-05-01

This Mine Safety and Health Administration (MSHA) informational report reviews in detail the occupational injury and illness experience of coal mining in the United States for 1992. Data reported by operators of mining establishments concerning work injuries are summarized by work location, accident classification, part of body injured, nature of injury, occupation, and anthracite or bituminous coal. Related information on employment, worktime, and operating activity also is presented. Data reported by independent contractors performing certain work at mining locations are depicted separately in this report. For ease of comparison between coal mining and the metal and nonmetal mineral mining industries, summary reference tabulations are included at the end of both the operator and the contractor sections of this report.

A rapid extraction of landslide disaster information research based on GF-1 image

Science.gov (United States)

Wang, Sai; Xu, Suning; Peng, Ling; Wang, Zhiyi; Wang, Na

2015-08-01

In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 .Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.

Response of surface springs to longwall coal mining Wasatch Plateau, Utah

International Nuclear Information System (INIS)

Kadnuck, L.L.M.

1994-01-01

High-extraction longwall coal mining creates zones in the overburden where strata bend, fracture, or cave into the mine void. These physical alterations to the overburden stratigraphy have associated effects on the hydrologic regime. The US Bureau of Mines (SBM) studied impacts to the local hydrologic system caused by longwall mining in the Wasatch Plateau, Utah. Surface springs in the vicinity of two coal mines were evaluated for alterations in flow characteristics as mining progressed. Fourteen springs located above the mines were included in the study. Eight of the springs were located over longwall panels, four were located over barrier pillars and mains, and two ere located outside the area disturbed by mining. Flow hydrographs for each spring were compared to climatic data and time of undermining to assess if mining in the vicinity had influenced flow. Heights of fracturing and caving in the overburden resulting from seam extraction were calculated using common subsidence formulas, and used in conjunction with elevations of springs to assess if fracturing influenced the water-bearing zones studied. One spring over a panel exhibited a departure from a normally-shaped hydrograph after being undermined. Springs located over other mine structures, or outside the mine area did not show discernible effects from mining. The limited response of the springs was attributed to site-specific conditions that buffered mining impacts including the elevation of the springs above the mine level, and presence of massive sandstones and swelling clays in the overburden materials

Ultrasound-assisted extraction for total sulphur measurement in mine tailings

International Nuclear Information System (INIS)

Khan, Adnan Hossain; Shang, Julie Q.; Alam, Raquibul

2012-01-01

Highlights: ► We develop a total sulphur measuring procedure of mine tailings. ► Ultrasound is used in the sample pre-treatment process. ► Full factorial design is applied to identify the best level of effecting factors. - Abstract: A sample preparation method for percentage recovery of total sulphur (%S) in reactive mine tailings based on ultrasound-assisted digestion (USAD) and inductively coupled plasma-optical emission spectroscopy (ICP-OES) was developed. The influence of various methodological factors was screened by employing a two-level and three-factor (2 3 ) full factorial design and using KZK-1, a sericite schist certified reference material (CRM), to find the optimal combination of studied factors and %S. Factors such as the sonication time, temperature and acid combination were studied, with the best result identified as 20 min of sonication, 80 °C temperature and 1 ml of HNO 3 :1 ml of HCl, which can achieve 100% recovery for the selected CRM. Subsequently a fraction of the 2 3 full factorial design was applied to mine tailings. The percentage relative standard deviation (%RSD) for the ultrasound method is less than 3.0% for CRM and less than 6% for the mine tailings. The investigated method was verified by X-ray diffraction analysis. The USAD method compared favorably with existing methods such as hot plate assisted digestion method, X-ray fluorescence and LECO™-CNS method.

Syncrude's Aurora Mine : the key to future Athabasca oil sands development

International Nuclear Information System (INIS)

Kershaw, D.

1998-01-01

Syncrude's newest mine, the Aurora mine is located 35 km northeast of Syncrude's existing Mildred Lake plant, across the Athabasca River. It has a potential to produce more than 2.5 billion barrels of bitumen. Aurora will eventually consist of two surface mines, the Aurora North and Aurora South. Mining and extraction will occur at Aurora with the resulting bitumen transported as a froth by pipeline back to the existing plant for upgrading to Syncrude Sweet Blend. A total of 120 km of pipeline will be used. Syncrude has developed a new method of sending oilsand from its Athabasca deposit to the extraction plant. The company plans to phase out the dragline, bucketwheel reclaimer, and conveyor ore mining and delivery system in favour of shovel, truck, and hydrotransport technology. The advantages of hydrotransport include significant energy savings and considerably less plant infrastructure. A hydrotransport prototype is at work at Syncrude's base mine where it is responsible for 15 per cent of the production

Aspects of transport system management within mining complex using information and telecommunication systems

Science.gov (United States)

Semykina, A. S.; Zagorodniy, N. A.; Konev, A. A.; Duganova, E. V.

2018-05-01

The paper considers aspects of transport system management within the mining complex. It indicates information and telecommunication systems that are used to increase transportation efficiency. It also describes key advantages and disadvantages. It is found that software products of the Modular Company used in pits allow increasing transport performance, minimizing losses and ensuring efficient transportation of minerals.

Enriching semantic knowledge bases for opinion mining in big data applications

OpenAIRE

Weichselbraun, A.; Gindl, S.; Scharl, A.

2014-01-01

This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a doma...

Data mining: childhood injury control and beyond.

Science.gov (United States)

Tepas, Joseph J

2009-08-01

Data mining is defined as the automatic extraction of useful, often previously unknown information from large databases or data sets. It has become a major part of modern life and is extensively used in industry, banking, government, and health care delivery. The process requires a data collection system that integrates input from multiple sources containing critical elements that define outcomes of interest. Appropriately designed data mining processes identify and adjust for confounding variables. The statistical modeling used to manipulate accumulated data may involve any number of techniques. As predicted results are periodically analyzed against those observed, the model is consistently refined to optimize precision and accuracy. Whether applying integrated sources of clinical data to inferential probabilistic prediction of risk of ventilator-associated pneumonia or population surveillance for signs of bioterrorism, it is essential that modern health care providers have at least a rudimentary understanding of what the concept means, how it basically works, and what it means to current and future health care.

Information Extraction with Character-level Neural Networks and Free Noisy Supervision

OpenAIRE

Meerkamp, Philipp; Zhou, Zhengyi

2016-01-01

We present an architecture for information extraction from text that augments an existing parser with a character-level neural network. The network is trained using a measure of consistency of extracted data with existing databases as a form of noisy supervision. Our architecture combines the ability of constraint-based information extraction systems to easily incorporate domain knowledge and constraints with the ability of deep neural networks to leverage large amounts of data to learn compl...

Leachability of Arsenic and Heavy Metals from Mine Tailings of Abandoned Metal Mines

Science.gov (United States)

Lim, Mihee; Han, Gi-Chun; Ahn, Ji-Whan; You, Kwang-Suk; Kim, Hyung-Seok

2009-01-01

Mine tailings from an abandoned metal mine in Korea contained high concentrations of arsenic (As) and heavy metals [e.g., As: 67,336, Fe: 137,180, Cu: 764, Pb: 3,572, and Zn: 12,420 (mg/kg)]. US EPA method 6010 was an effective method for analyzing total arsenic and heavy metals concentrations. Arsenic in the mine tailings showed a high residual fraction of 89% by a sequential extraction. In Toxicity Characteristic Leaching Procedure (TCLP) and Korean Standard Leaching Test (KSLT), leaching concentrations of arsenic and heavy metals were very low [e.g., As (mg/L): 0.4 for TCLP and 0.2 for KSLT; cf. As criteria (mg/L): 5.0 for TCLP and 1.5 for KSLT]. PMID:20049231

BLM Colorado Mining Claims Closed

Data.gov (United States)

Department of the Interior — Shapefile Format –This data set consists of closed mining claim records extracted from BLM’s LR2000 database. These records contain case attributes as well as legal...

BLM Colorado Mining Claims Active

Data.gov (United States)

Department of the Interior — Shapefile Format –This data set consists of active mining claim records extracted from BLM’s LR2000 database. These records contain case attributes as well as legal...

Unsupervised information extraction by text segmentation

CERN Document Server

Cortez, Eli

2013-01-01

A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors' approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given domain relying on a very effective set of content-based features. The effectiveness of the content-based features is also exploited to directly learn from test data structure-based features, with no previous human-driven training, a feature unique to the presented approach. Based on the approach, a

Automated information and control complex of hydro-gas endogenous mine processes

Science.gov (United States)

Davkaev, K. S.; Lyakhovets, M. V.; Gulevich, T. M.; Zolin, K. A.

2017-09-01

The automated information and control complex designed to prevent accidents, related to aerological situation in the underground workings, accounting of the received and handed over individual devices, transmission and display of measurement data, and the formation of preemptive solutions is considered. Examples for the automated workplace of an airgas control operator by individual means are given. The statistical characteristics of field data characterizing the aerological situation in the mine are obtained. The conducted studies of statistical characteristics confirm the feasibility of creating a subsystem of controlled gas distribution with an adaptive arrangement of points for gas control. The adaptive (multivariant) algorithm for processing measuring information of continuous multidimensional quantities and influencing factors has been developed.

Uranium extraction at Rossing

International Nuclear Information System (INIS)

Kesler, S.B.; Fahrbach, D.O.E.

1982-01-01

Rossing Uranium Ltd. operates a large open pit uranium mine and extraction plant at a remote site in the Namib desert. Production started at the plant in 1978. A ferric leach process was introduced later, and the new leach plant began commissioning in October 1981. The process has proved to be reliable and easily controlled. Ferric iron is supplied through recovery from the acid plant calcine, and levels can be maintained above the design levels. Leach extractions were increased more than expected when this process was adopted, and the throughput has been considerably reduced, allowing cost savings in mining and milling

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

Science.gov (United States)

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

2016-12-01

Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.

Extraction of CT dose information from DICOM metadata: automated Matlab-based approach.

Science.gov (United States)

Dave, Jaydev K; Gingold, Eric L

2013-01-01

The purpose of this study was to extract exposure parameters and dose-relevant indexes of CT examinations from information embedded in DICOM metadata. DICOM dose report files were identified and retrieved from a PACS. An automated software program was used to extract from these files information from the structured elements in the DICOM metadata relevant to exposure. Extracting information from DICOM metadata eliminated potential errors inherent in techniques based on optical character recognition, yielding 100% accuracy.

The landscape degradation in the mining sites with suspended activity

Directory of Open Access Journals (Sweden)

Anca IONCE

2009-08-01

Full Text Available The extracting industry, through its extraction activities, of shipping the ores, of breaking the ores, of preparing the practical substances, of stowing the useless rock, of transporting the practical substances, etc. might modify the area’s relief and the quality of ground, of thesurface waters and of the air. Suceava County has an old tradition of mining, where the results of this activity are visible, especially the visual point of view, and where not taking certain measures of ecological remediation will emphasize the disappointing image of the landscape within the areas of mining activity performing.The predominant mountainous landscape, in which mining activities have been held, is being affected also by the abandoned industrial and administrative buildings, in an advanced degradation state.The hydrographic system, very rich in mining areas, has its water quality affected by the acid rock drainage- phenomenon which appeared in many mining waste deposits.

Impacts of Canada's uranium mining industry

International Nuclear Information System (INIS)

Holman, G.J.

1982-05-01

This study examines economic and environmental impacts of uranium mining in Canada and compares these impacts with those of other extractive and energy industries. The uranium industry generates taxes and royalties, income, employment, foreign exchange earnings, security of energy supply, and technological spinoffs. The indirect impacts of the industry as measured by employment and income multipliers are lower than those for other types of mining and comparable to oil and gas because of the high proportion of costs withdrawn from the economy in the form of taxes and operator margin. Social costs are primarily occupational hazards. Uranium mining probably has a lower non-health environmental impact than other mining industries due to much smaller throughputs and transportation requirements. Residents of the area surrounding the mine bear a disproportionate share of the social costs, while non-residents receive most of the benefits

Women, mercury and artisanal gold mining : Risk communication and mitigation

Science.gov (United States)

Hinton, J. J.; Veiga, M. M.; Beinhoff, C.

2003-05-01

Artisanal miners employ rudimentary techniques for minéral extraction and often operate under hazardous, labour intensive, highly disorganized and illegal conditions. Gold is the main mineral extracted by artisanal miners, and the ecological and human health impacts resulting from mercury (Hg) use in gold extraction warrant special consideration. More than 30% of world's 13 million artisanal miners are women and, as they are often perceived to be less suited for labour intensive mining methods, the majority of women work in the processing aspect of artisanal mining, including amalgamation with Hg. As women are also predominantly responsible for food preparation, they are in an excellent position to respond to health risks associated with consumption of Hg-contaminated foods in impacted areas. In addition to their influence on consumption habits, women in artisanal mining communities may be in a position to effect positive change with respect to the technologies employed. Thus, gender sensitive approaches are necessary to reduce exposure risks to women and their families, promote clean technologies and support the development of stronger, healthier artisanal mining communities. This paper describes the roles of women in artisanal gold mining, highlights their importance in reducing the Hg exposure in these communities, and provides insight into how risks from Hg pollution can effectively be communicated and mitigated.

75 FR 51488 - Division of Coal Mine Workers' Compensation; Proposed Extension of Information Collection...

Science.gov (United States)

2010-08-20

... order to carry out its responsibility to administer the Black Lung Benefits Act. Agency: Office of...). SUPPLEMENTARY INFORMATION: I. Background: The Division of Coal Mine Workers' Compensation administers the Black Lung Benefits Act (30 U.S.C. 901 et seq.), which provides benefits to coal miners totally disabled due...

Field Testing of Downgradient Uranium Mobility at an In-Situ Recovery Uranium Mine

Science.gov (United States)

Reimus, P. W.; Clay, J. T.; Rearick, M.; Perkins, G.; Brown, S. T.; Basu, A.; Chamberlain, K.

2015-12-01

In-situ recovery (ISR) mining of uranium involves the injection of O2 and CO2 (or NaHCO3) into saturated roll-front deposits to oxidize and solubilize the uranium, which is then removed by ion exchange at the surface and processed into U3O8. While ISR is economical and environmentally-friendly relative to conventional mining, one of the challenges of extracting uranium by this process is that it leaves behind a geochemically-altered aquifer that is exceedingly difficult to restore to pre-mining geochemical conditions, a regulatory objective. In this research, we evaluated the ability of the aquifer downgradient of an ISR mining area to attenuate the transport of uranium and other problem constituents that are mobilized by the mining process. Such an evaluation can help inform both regulators and the mining industry as to how much restoration of the mined ore zone is necessary to achieve regulatory compliance at various distances downgradient of the mining zone even if complete restoration of the ore zone proves to be difficult or impossible. Three single-well push-pull tests and one cross-well test were conducted in which water from an unrestored, previously-mined ore zone was injected into an unmined ore zone that served as a geochemical proxy for the downgradient aquifer. In all tests, non-reactive tracers were injected with the previously-mined ore zone water to allow the transport of uranium and other constituents to be compared to that of the nonreactive species. In the single-well tests, it was shown that the recovery of uranium relative to the nonreactive tracers ranged from 12-25%, suggesting significant attenuation capacity of the aquifer. In the cross-well test, selenate, molybdate and metavanadate were injected with the unrestored water to provide information on the transport of these potentially-problematic anionic constituents. In addition to the species-specific transport information, this test provided valuable constraints on redox conditions within

Ecotoxicological evaluation of areas polluted by mining activities

Science.gov (United States)

García-Lorenzo, M. L.; Martínez-Sánchez, M. J.; Pérez-Sirvent, C.; Molina, J.

2009-04-01

Determination of the contaminant content is not enough to evaluate the toxic effects or to characterise contaminated sites, because such a measure does not reflect the ecotoxicological danger in the environment and does not provide information on the effects of the chemical compounds. To estimate the risk of contaminants, chemical methods need to be complemented with biological methods. Therefore, ecotoxicological testing may be a useful approach for assessing the toxicity as a complement to chemical analysis. The aim of this study was to develop a battery of bioassays for the ecotoxicological screening of areas polluted by mining activities. Particularly, the toxicity of water samples, sediments and their pore-water extracts was evaluated by using three assays: bacteria, plants and ostracods. Moreover, the possible relationship between observed toxicity and results of chemical analysis was studied. The studied area, Sierra Minera, is close to the mining region of La Uni

Technology Transfer at Edgar Mine: Phase 1; October 2016

Energy Technology Data Exchange (ETDEWEB)

Augustine, Chad R. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bauer, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nakagawa, Masami [Colorado School of Mines, Golden, CO (United States); Zhou, Wendy [Colorado School of Mines, Golden, CO (United States)

2017-09-14

The objective of this project is to study the flow of fluid through the fractures and to characterize the efficiency of heat extraction (heat transfer) from the test rock mass in the Edgar Mine, managed by Colorado School of Mines in Idaho Springs, CO. The experiment consists of drilling into the wall of the mine and fracturing the rock, characterizing the size and nature of the fracture network, circulating fluid through the network, and measuring the efficiency of heat extraction from the 'reservoir' by monitoring the temperature of the 'produced' fluid with time. This is a multi-year project performed as a collaboration between the National Renewable Energy Laboratory, Colorado School of Mines and Sandia National Laboratories and carried out in phases. This report summarizes Phase 1: Selection and characterization of the location for the experiment, and outlines the steps for Phase 2: Circulation Experiments.

farmers' perceptions of mining in the Maningory watershed